Improving Flow and Resource Efficiency
to Increase Capacity and Area Utilisa-
tion
in Electronics Production

Master’s thesis in the master’s programme Production Engineering

LINA JANSSON
LINDA STRIDSBERG

Department of Technology Management and Economics
Division of Operations Management
CHALMERS UNIVERSITY OF TECHNOLOGY
Gothenburg, Sweden 2015
Master’s thesis E2015:060





Master’s thesis E2015:060

Improving Flow and Resource Efficiency to
Increase Capacity and Area Utilisation

in Electronics Production

LINA JANSSON
LINDA STRIDSBERG

Department of Technology Management and Economics
Division of Operations Management

Chalmers University of Technology
Gothenburg, Sweden 2015



Improving Flow and Resource Efficiency to Increase Capacity and Area Utilisation
in Electronics Production
LINA JANSSON
LINDA STRIDSBERG

© LINA JANSSON & LINDA STRIDSBERG, 2015.

Supervisor: Peter Almström, Department of Technology Management and Eco-
nomics
Examiner: Peter Almström, Department of Technology Management and Economics

Master’s Thesis E2015:060
Technology Management and Economics
Division of Operations Management
Chalmers University of Technology
SE-412 96 Gothenburg
Telephone +46 31 772 1000

Cover: Product passing over the soldering wave in the leaded wave soldering machine

Printed by Chalmers Reproservice
Gothenburg, Sweden 2015

iv



Improving Flow and Resource Efficiency to Increase Capacity and Area Utilisation
in Electronics Production
LINA JANSSON, LINDA STRIDSBERG
Department of Technology management and economics
Division of Operations Management
Chalmers University of Technology

Abstract
This master thesis has been conducted at Aros Electronics AB, a company produc-
ing electronic products. The thesis purpose was to increase the capacity of products
that are being processed by wave soldering machines. At the start of the project,
the production unit producing these products was highly process-oriented and this
was considered to be the cause for a lot of waste in their production. Aros therefore
wished to change their production system towards a more flow-oriented layout in
order to reduce waste and create a more efficient production system.

In order to structurally analyse and improve the production unit, Methods En-
gineering was used. There were no obtainable time data for the products to be
analysed so in order to to form a reference for the improvement work, work stan-
dards were created. The work standards were created through a time study using
both Sequential Activity and Methods analysis and stopwatch estimations. In total,
work standards for 15 products were constructed.

When creating a flow-oriented system, each products required work tasks need to be
assigned to new work stations. This is done through balancing and was in this thesis
made with the aid of a software named Avix, from Solme AB. The work standards of
the 15 products where balanced and a new layout containing three new production
lines where created. At this stage, a comparing analysis was also made in order to
quantify the impact that Aros unstable production testing equipment has. There-
fore, two balancing cases were made. One case, the ideal case, had 100 % uptime of
the testing equipment. The second case, the realistic case, had time contributions
added to the test equipment process times, based on the test equipment yields.
The realistic case was further analysed and resulted in a capacity increase of 87 %,
a productivity increase of 192 % and a reduction of the occupied area of 23 %. The
results could then act as a decision basis for Aros on how to move forward in their
production development.

Keywords: Capacity, Productivity, Area utilisation, Electronic Industry, HMLV,
Time Study, PTS, SAM, Resource balancing, Avix

v





Acknowledgements
First of all, we would like to thank Kent Johansson at Aros Electronics AB for
providing us with this opportunity. We appreciate that we have been able to wok
independently through learn-by doing but with a constant knowing that help is al-
ways close at hand. The transparency we have been given within the production
system of Aros has enabled a great understanding and knowledge of the dynamics
of production systems.

We also want to thank the helpful staff of Aros production departments. Oper-
ators, flow technicians, material handlers and service personnel and all who have
aided us in our understanding of the production processes. We especially want to
thank all the operators in the Green Production Unit for taking their time to be
filmed, patiently answering all of our questions and for being generally supportive
and showing interest in our project.

Our sincerest thanks goes to Kent Johansson, Marie Staberg-Nyqvist and Fredrik
Andersson for their support and guidance. Thanks also to Oskar Ljung and Glenn
Heiman at Solme AB, for giving us licenses to the Avix software and for helping us
when we ran into problems with it.

Finally, we would like to thank our supervisor and examinor Peter Almström for his
guidance throughout this project. His quick responses when we needed help and the
ability to concretise complex, to us, problems have been deeply appreciated.

Lina Jansson Linda Stridsberg, Gothenburg, June 2015

vii





Contents

List of Figures xii

List of Tables xiv

1 Introduction 1
1.1 Aros Electronics AB . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 Aros Production System . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Production flow through the production units . . . . . . . . . 4
1.1.3 Green production unit . . . . . . . . . . . . . . . . . . . . . . 4

1.2 Project background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Problem definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3.1 Research questions . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Methods 7
2.1 Pre-study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.1 Work Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.2 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.3 Data review . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.2 Procedure of Methods engineering . . . . . . . . . . . . . . . . . . . . 8
2.3 Step 1: Define the scope . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4 Step 2: Set the targets . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.5 Step 3: Doing the analysis . . . . . . . . . . . . . . . . . . . . . . . . 11
2.6 Step 4: Modelling the area to be improved . . . . . . . . . . . . . . . 12
2.7 Step 5: Developing the ideal Method . . . . . . . . . . . . . . . . . . 12
2.8 Step 6: Selecting the improvement plan . . . . . . . . . . . . . . . . . 13
2.9 Step 7: Implement new systems . . . . . . . . . . . . . . . . . . . . . 13
2.10 Step 8: Follow up and enforce new methods . . . . . . . . . . . . . . 13

3 Theory 15
3.1 Capacity and Productivity . . . . . . . . . . . . . . . . . . . . . . . . 15

3.1.1 Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.2 Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.2 Background of Methods engineering . . . . . . . . . . . . . . . . . . . 16
3.2.1 History Methods engineering . . . . . . . . . . . . . . . . . . . 16
3.2.2 Definition of Methods engineering . . . . . . . . . . . . . . . . 17

3.3 Time study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

ix



Contents

3.4 Work measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4.1 Estimations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4.2 Direct observation and measurement . . . . . . . . . . . . . . 18
3.4.3 Standard data systems . . . . . . . . . . . . . . . . . . . . . . 19

3.5 Predetermined Time systems . . . . . . . . . . . . . . . . . . . . . . . 19
3.5.1 MTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.5.2 Sequential Activity and Methods analysis . . . . . . . . . . . . 20

3.6 Production flow strategies . . . . . . . . . . . . . . . . . . . . . . . . 21
3.6.1 Facility layout . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.6.2 Continuous flow layout . . . . . . . . . . . . . . . . . . . . . . 22
3.6.3 Fixed position layout . . . . . . . . . . . . . . . . . . . . . . . 22
3.6.4 Product layout or Line production . . . . . . . . . . . . . . . 23
3.6.5 Process layout or Functional layout . . . . . . . . . . . . . . . 24
3.6.6 Cellular Manufacturing layout . . . . . . . . . . . . . . . . . . 25

3.7 Balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.7.1 Product families . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.7.2 Takt time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.7.3 Assembly line balancing problem . . . . . . . . . . . . . . . . 29

3.8 Lean manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.8.1 The eight wastes of Lean . . . . . . . . . . . . . . . . . . . . . 30
3.8.2 Standardised work . . . . . . . . . . . . . . . . . . . . . . . . 31
3.8.3 Just in time . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.8.4 5S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.8.5 Flow efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.9 AviX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.9.1 AviX®Method . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.9.2 AviX®Resource balance . . . . . . . . . . . . . . . . . . . . . 34

4 Current state 35
4.1 Product and area related data . . . . . . . . . . . . . . . . . . . . . . 35

4.1.1 Specified Product Mix, SPM . . . . . . . . . . . . . . . . . . . 35
4.1.2 Area utilisation . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.1.3 Process flows . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.1.4 Volume data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.2 Testings equipment data . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2.1 ICT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2.2 Functional tests . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.2.3 Testing equipment yields . . . . . . . . . . . . . . . . . . . . . 40
4.2.4 Test equipment process times . . . . . . . . . . . . . . . . . . 40

4.3 Wave soldering process . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.3.1 System description overview . . . . . . . . . . . . . . . . . . . 41

4.4 Coating Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.4.1 Processing times . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.4.2 Coating robot capacity . . . . . . . . . . . . . . . . . . . . . . 43

4.5 Measuring Process equipment capacities . . . . . . . . . . . . . . . . 43
4.5.1 Wave soldering process capacity . . . . . . . . . . . . . . . . . 44

x



Contents

4.5.2 ICT capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

5 Analysis 47
5.1 Current state analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.1.1 Cause and effect analysis . . . . . . . . . . . . . . . . . . . . . 47
5.2 Analysis of process equipment capacities . . . . . . . . . . . . . . . . 50

5.2.1 Capacity of wave soldering process . . . . . . . . . . . . . . . 50
5.2.2 Capacity ICT . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.3 Work Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.3.1 Deciding on work standards . . . . . . . . . . . . . . . . . . . 52
5.3.2 Testing equipment process times . . . . . . . . . . . . . . . . . 52
5.3.3 Construction of Work standards in Avix software . . . . . . . 53

5.4 Verification of work standards through live tests . . . . . . . . . . . . 56
5.4.1 Live test 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.4.2 Live test 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.5 Construction of ideal lead times . . . . . . . . . . . . . . . . . . . . . 59
5.6 Current production planning . . . . . . . . . . . . . . . . . . . . . . . 60

6 Solution 63
6.1 Product families . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
6.2 Balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

6.2.1 Establishing cycle times . . . . . . . . . . . . . . . . . . . . . 64
6.2.2 Testing equipment yields . . . . . . . . . . . . . . . . . . . . . 64
6.2.3 Process equipment . . . . . . . . . . . . . . . . . . . . . . . . 65
6.2.4 The iterative balancing process . . . . . . . . . . . . . . . . . 65
6.2.5 ALPHA line . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
6.2.6 BETA-line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
6.2.7 Gamma line: . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.2.8 General Conditions for balancing to succeed . . . . . . . . . . 74

6.3 Layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.3.1 Area Utilisation . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.3.2 Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.3.3 Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

7 Discussion 83
7.1 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

7.1.1 Balancing method . . . . . . . . . . . . . . . . . . . . . . . . . 83
7.1.2 Product families . . . . . . . . . . . . . . . . . . . . . . . . . . 83

7.2 Data quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
7.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

7.3.1 Live tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
7.3.2 The Performance factor of MPU . . . . . . . . . . . . . . . . . 84
7.3.3 Creating ideal lead times . . . . . . . . . . . . . . . . . . . . . 84
7.3.4 Balancing results . . . . . . . . . . . . . . . . . . . . . . . . . 84
7.3.5 Capacity and productivity increase . . . . . . . . . . . . . . . 85

7.4 Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
7.4.1 Physical work environment . . . . . . . . . . . . . . . . . . . . 85

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Contents

7.4.2 Cognitive work environment . . . . . . . . . . . . . . . . . . . 86
7.4.3 Psychosocial work environment . . . . . . . . . . . . . . . . . 86

7.5 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7.6 Project continuation . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

7.6.1 Buffer sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7.6.2 Orange unit wave soldered products . . . . . . . . . . . . . . . 87
7.6.3 Potential implementation . . . . . . . . . . . . . . . . . . . . . 88

7.7 Future project suggestions . . . . . . . . . . . . . . . . . . . . . . . . 88

8 Conclusion 89

Bibliography 89

A Appendix for Current State chapter I

B Appendix for Analysis chapter VII

C Appendix for Solutions chapter IX

xii



List of Figures

1.1 Project focus area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Overview of the production flows between production units . . . . . . 4

3.1 Correlation between volume and flexibility . . . . . . . . . . . . . . . 22
3.2 Illustration of product layout . . . . . . . . . . . . . . . . . . . . . . 24
3.3 Illustration of process layout . . . . . . . . . . . . . . . . . . . . . . . 25
3.4 Illustration of cellular manufacturing . . . . . . . . . . . . . . . . . . 27
3.5 Efficiency matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.1 Product included in the final SPM . . . . . . . . . . . . . . . . . . . 36
4.2 Production volume for products included in the SPM . . . . . . . . . 36
4.3 Current production layout . . . . . . . . . . . . . . . . . . . . . . . . 36
4.4 Product/process map illustrating each products sequential processing

steps for the SPM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.5 Overview of product flows for products included in the SPM . . . . . 37
4.6 Product volumes 2011-2014 . . . . . . . . . . . . . . . . . . . . . . . 38
4.7 ICT equipment located in Green production unit . . . . . . . . . . . 39
4.8 Common type of functional test in Green production unit . . . . . . . 39
4.9 PB-machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.10 ROHS-machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.11 Wave soldering area . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.12 Illustration of the wave soldering process including the conveyor sys-

tem and two soldering machines . . . . . . . . . . . . . . . . . . . . . 42
4.13 The Coating robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.1 Cause and effect diagram . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.2 Avix structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.3 Elements and work tasks . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.4 SAM-analysis in Avix . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.5 Process library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.6 Categorisation of work tasks when stopwatch times where used . . . . 57
5.7 Live test 1 results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.8 Live test 2 results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.9 Graph illustrating ideal lead times, in hours, based on current state

layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5.10 Graph illustrating ideal lead times, in minutes, based on current state

layout. Drying times not included. . . . . . . . . . . . . . . . . . . . 61

xiii



List of Figures

5.11 Current needed production time for SPM . . . . . . . . . . . . . . . . 61

6.1 Balance graph over the ALPHA line . . . . . . . . . . . . . . . . . . . 67
6.2 Operator and test utilisation of the ALPHA line . . . . . . . . . . . . 67
6.3 Balance graph of the ideal case BETA line . . . . . . . . . . . . . . . 69
6.4 Operator and test utilisation of the ideal case BETA line . . . . . . . 70
6.5 Operator and test utilisation of the Realistic case BETA line . . . . . 70
6.6 Balance graph of BETA realistic case . . . . . . . . . . . . . . . . . . 71
6.7 Product/station matrix . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6.8 Balancing graph of the ideal case GAMMA line,3 operators . . . . . . 73
6.9 Operator utilisation for ideal GAMMA balancing, with 3 operators . 73
6.10 Operator utilisation for ideal GAMMA balancing, with 1 operator . . 74
6.11 Balancing graph of the realistic case GAMMA line, with 1 operator . 74
6.12 Proposed layout of lines and stations . . . . . . . . . . . . . . . . . . 76
6.13 Reduction in conveyor transports . . . . . . . . . . . . . . . . . . . . 77
6.14 Product flow in the improved state suggested layout . . . . . . . . . . 78

xiv



List of Tables

3.1 Table over main advantages and disadvantages of fixed position layout 23
3.2 Table over main advantages and disadvantages of product layout . . 24
3.3 Table over main advantages and disadvantages of process layout . . . 25
3.4 Table over main advantages and disadvantages of cellular manufac-

turing layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

6.1 SPM percentage for ALPHA line . . . . . . . . . . . . . . . . . . . . 66
6.2 SPM percentage for BETA line . . . . . . . . . . . . . . . . . . . . . 68
6.3 SPM percentages for the GAMMA line . . . . . . . . . . . . . . . . . 71
6.4 Productivity estimations . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.5 Capacity estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

A.1 Split/Merge-capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . I
A.2 Process time of the wave soldering machines . . . . . . . . . . . . . . I
A.3 Conveyor transports . . . . . . . . . . . . . . . . . . . . . . . . . . . II
A.4 Coating data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II
A.5 Test units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III
A.6 Test units and Yields . . . . . . . . . . . . . . . . . . . . . . . . . . . IV
A.7 ICT Capacity data and estimation . . . . . . . . . . . . . . . . . . . V

B.1 Ideal lead times constructed in Avix based on current state layouts
transports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII

B.2 Process times used in Avix . . . . . . . . . . . . . . . . . . . . . . . . VIII

C.1 Estimated time data for conveyor transports in the Improved state . . IX

xv



List of Tables

xvi



1
Introduction

Aros Electronics AB is the provider of this thesis project. In this chapter, firstly the
company and their production systems is described. Then follows a description of
the project background, problem formulation and limitations.

1.1 Aros Electronics AB
Aros electronics AB is an Mölndal-situated company that develop, design and man-
ufacture customised electronic solutions for industry applications. They are spe-
cialised in the field of electrical motor drives, sensors and field bus technology. Aros
has since 2001 been a part of the textile industry-based Van de Wiele group. In
2012, Aros was merged with the IRO AB concern who produce and develop prod-
ucts within the textile industry.

Van de Wiele group is an international company with main focus on developing
and producing textile industry machinery, for example carpet-and velvet weaving
machines. Van de Wiele headquarters lies in Belgium but the group has 14 facil-
ities placed worldwide, which in total employs roughly 2500 people and has a net
turnover of roughly 400 M EUR. Their facilities are placed in Sweden, Belgium,
Germany, Italy and China (Aros Electronics AB, 2014) (Van de Wiele group, 2012).

IRO AB is a developer and manufacturer of textile products who specialises in
yarn feeders (IRO AB, 2014). They are located in Ulricehamn, Sweden, and in 2013
they employed 102 people and had a net turnover of 270 MSEK. (allabolag.se, 2015).

Aros Electronics AB was founded in 1970 and has in recent years seen quick and
steady growth. In 2013, Aros had 119 employees and a net turnover of 250 M SEK.
Since Aros joined the Van de Wiele group and merged with IRO AB, they have ex-
panded within Sweden and to Belgium, China and Italy. They provide customised
electronic solutions for companies in industries such as the automotive, textile, heavy
equipment and electronic. Aros has a wide range of customers but the most well
known are Volvo, ABB and Caterpillar.

In the Mölndal production site Aros has development, design and production all
under the same roof. This is one of Aros strengths since it makes for easier com-
munication between the different departments, short lead times, cost efficiency and
thorough quality control. Due to the customisations that Aros offer their customers,

1



1. Introduction

there is a great mix in products in production and a wide range in product complex-
ity. They produce everything from small circuit boards to fully integrated customer-
unique systems such as motor drives for air compression systems in buses.

1.1.1 Aros Production System
The production system of Aros consists of a variety of both automated and man-
ual processing steps. For example, they have manual assembly stations, automated
pick-and place machines, wave soldering machines, selective soldering machines and
coating machines. The production is divided into four main production units, cate-
gorised by colours, which are: Yellow unit, Orange unit, Green unit and Blue unit.
See figure 1.1 for a complete description of Aros production system.

Figure 1.1: Project focus area
,

Yellow unit
Yellow unit is run in two shifts, a day shift and a night shift. It is operated by
20 operators and one production leader, responsible for different shifts and parts
of Yellow units production. The Yellow production unit is highly automated and

2



1. Introduction

consists of a surface mounting technology (SMT) line with pick and place machines,
reflow ovens and automated optical inspection (AOI) machines. After the SMT line,
the flow of products splits up into either the selective soldering line or continues to
the other production units. The selective soldering line consist of a selective solder-
ing machine, a coating machine and testing equipment. Products from the selective
soldering line mostly go to Orange production unit but some products also go to
the Green production unit.

Orange unit
Orange unit consist of 22 operators and one production leader. This production
unit mostly make box built assemblies for integrated solutions. They also have a
few products that they through-hole mount (THM) and send to the wave soldering
machines. They also perform testing for their products and some testing equipment
is shared with Green production unit.

Green unit
Green unit consists of 18 operators and one production leader. The production unit
mostly produce products that go through the wave soldering machines, which then
need testing and board assembly. However, they also have responsibility over some
products that do not need the wave soldering machines but require manual soldering
instead. These products are then processed in the same manner as the others, with
box built assemblies and testing.

Blue unit
Blue unit consist of 8 operators and one production leader. They manufacture sel-
domproducts with high fluctuations in demand. The demand can be either from new
products that are not part of the reoccurring demand or they can be old products
that are sold in low volumes. Most of these products require the wave soldering
machines.

Material handling
Material handling are responsible for deliveries, shipping and supplying the units
with material and components. Aros has attempted to implement a scheduled Kan-
ban system. Material handling staff should make four rounds each day to fill up
material on the workstations and retrieve empty material containers. Some mate-
rial has to be replaced from its original packaging into smaller boxes before trans-
portation to stations and this responsibility belongs to Material handling. For some
products, material handling has to collect finished products on the stations but most
finished products are placed in a finished goods section in the Material handling area.

Service
The service unit looks into problems with defect products that are too complicated
for the operators to resolve and they aid in all three production units. Flow tech-
nicians
The flow technicians roles are diverse but mainly they make sure production pro-
cesses are running as they should. Also, they solve daily problems with everything

3



1. Introduction

from changing light bulbs to repairing broken equipment.

1.1.2 Production flow through the production units
Figure 1.1 shows an overview of of how production flows between the different pro-
duction units.

Figure 1.2: Overview of the production flows between production units
,

1.1.3 Green production unit
At present, Green unit is in charge of producing roughly 26 reoccurring products.
The products are similar in their required processing steps but the steps themselves
vary a lot in length and sequence.

The production is highly process oriented and each operator in Green unit fol-
lows one product from start to end and has complete assembly responsibility. The
operators in Green production unit work in cells were they are responsible for ev-
erything from visual inspections, assemblies, coating, functional testing of products
to packaging of products. The work is mostly performed in large batches and work
rotations are seldom made. An exception to this is the so-called Albany-line, where
a line flow has been attempted to be implemented. Here, five operators on five dif-
ferent workstations work on a few products, that have a high volume demand and
are very similar in the processing steps
.
Production planning:
Each new week starts with the production leader distributing the weekly workload,
the production plans, to the operators within Green unit. This distribution is based
on which products are to be produced, what volumes they come in and the available
workforce.

The production plan is a product specific document that contains the weekly vol-
ume to be produced, all processing steps required to produce the product and which
components and materials are needed. The volumes in the production plan is based
on an internal takt document called Takt-data. Takt-data is a document that is
compiled once each month by the production planning department and is based
both on forecast and actual orders from customers.

The production plans should ideally be followed but adjustment during the week
occurs. Common reasons for this are:

4



1. Introduction

• Failures in meeting delivery times. Making some products be down-prioritised
and their production is postponed.

• Lack of workforce.

• Process equipment failures.

In conclusion, production planning on weekly level is based on estimations from
the production leader. The production leader has knowledge and understanding
about the processes, the operators and the process equipment and makes production
planning based on these three aspects. Production planning on higher levels are
based on forecasts and actual demand.

1.2 Project background
Aros has gone through rapid developments from being a small-size manufacturing
company to a medium-size manufacturing company and their current production
strategy is no longer suitable. At present, they are highly space limited and need
to increase their productivity in order to raise their capacity level. Green unit
is considered to have especially high potential in increasing productivity since the
production in this unit are at present oriented towards processes rather than a
flow. Another problem are unstable processes in the system and these are especially
connected to the different testing equipment. Due to these facts, the lead times are
unnecessary high, buffer levels are necessary and take up space and it is difficult to
maintain delivery precision.

1.3 Problem definition
Aros are in need to change their production system in order to increase their capacity.
They wish to use the results of the thesis as a decision basis on how to move forward
in their production development. The purpose of this thesis is therefor to explore,
through resource balancing, different options for Green unit to go from a process-
oriented system towards a more flow-oriented system. The main goal of the proposed
suggestion is to create space on the production floor and increase productivity.

1.3.1 Research questions
This thesis aims to investigate the following research questions, where the percentage
goals have been set by the production management of Aros.

• Is it possible to increase Aros production capacity of a specified product mix
in Green production unit by 50% if going from a process layout towards a flow
oriented system? If not, which level can be reached?

• How much can the occupied area for the specified product mix in Green pro-
duction unit be decreased when creating a flow oriented system?

5



1. Introduction

1.4 Delimitations
Amain limitation of this thesis is that only the production flows linked with products
using the wave soldering machines will be analysed. Green, Blue and Orange unit
are connected to the wave soldering machine.

• The balancing of operations will be performed on all tasks related to products
manufactured within the Green unit but not the task related to Blue or Orange
unit. Products from Blue and Orange unit will be taken into consideration
if changes in the physical environment should impact them but they are not
part of the balancing.

• The analysis will start from when components arrive to the Green unit until
they are packed and ready for delivery.

• Process technology and other heavy investments for Green unit will not be
made. The analysis builds on maximising the utilisation of available resources
in operators, machines and the facility itself.

• The balancing will be focused on increasing productivity and creating more
space. Aspects such as quality, ergonomics and costs will be considered but
not be the primary focus.

6



2
Methods

This chapter will describe the methods used during the project. It will describe
the procedures used both for the more practical work on the production floor as
well as the more theoretical. Firstly, a pre-study was conducted to gain knowledge
about the topic and Aros. From this it was concluded that the general approach of
Methods engineering would provide a good foundation for this thesis method, since
it suited well with the thesis scope.

This chapter will therefore firstly present the pre-study method. It then continues
to describe the work procedure of Method engineering and finally, it will connect
each of the procedure steps in Methods engineering to the work performed during
the course of the thesis.

2.1 Pre-study
A pre-study was conducted in order to gain sufficient knowledge about the topic
of the thesis and the company, since both authors had no prior connections to the
company or the electronic industry

2.1.1 Work Practice
Since the authors, as previously stated, had no previous connection to Aros, an
introduction program was provided from the supervisor at Aros. This enabled the
authors to quickly gain knowledge about Aros and its company structure. Most
of the time during the introduction program was spent on work practice within
the Green production unit to gain sufficient understanding about the processes.
The work practice lasted seven days and the work days where split in half so two
products per day could be covered. By doing so, as many processes and products
as possible was either observed or experienced in practice. The work practice also
made the authors getting to know the operators within the Green unit, which made
communication during the project easier. It also gave a rough idea of the problems
present at the production floor.

2.1.2 Literature review
The literature study has been carried out throughout the project but with its main
focus at the beginning of the thesis. At the project start, literature connected to

7



2. Methods

each phase of the project that was considered to be of use was collected and reviewed
to gain a deeper general knowledge. Once a new phase in the project has been en-
tered, literature connected to it has been covered again to ensure nothing has been
forgotten or misinterpreted the first time. Also, additional information and topics
has been covered that was not known at the start that they would be needed.

Since the aim of the thesis is to increase Aros production capacity by changing their
production system from a process-oriented system towards a flow-oriented system,
with a main focus to create space and increase productivity, the reviewed litera-
ture has been connected to this. Keywords used when searching for literature have
been: work standards, work measurement, capacity, methods engineering, SAM,
balancing, production systems.

2.1.3 Data review
This thesis is a continuation of a time study project that a former employee at Aros
started, where the processing steps of a few products in the scope had been video
recorded. These videos were reviewed to see which products and processing steps
that had been recorded, so that the authors would be able to save time. Next, the
processing steps and work tasks of the videos had to be confirmed with the operators.
This was done to ensure that the videos contained up to date information.

2.2 Procedure of Methods engineering
When performing any change project, it is a good idea to follow a set procedure
that is set clear to everybody involved before any activity is started. This will then
result in the below following benefits from (Zandin, 2001, c. 29).

• It is possible to ahead of time get a good project understanding among all the
people involved.

• Improvement activities will be more efficient and wasted effort can be avoided.

• By concentrating on the step at hand, the quality of work done for each step
will increase.

• Monitoring of progress can be readily done.

For Methods engineering, the set procedure has already been formalised into below
eight steps(Zandin, 2001, c. 29).

Step 1: Define the scope
Consist of two sub-steps:

1. Decide what needs to be improved, select a goal
In manufacturing typical goals are to improve labour productivity, equipment
productivity, reduction in inventory, reduction of lead times, level out produc-
tion demand, improved ergonomics or balancing a system.

8



2. Methods

2. Decide area to be studied, select a study subject
Could be a department in the factory, a production line, a process in a complex
manufacturing operation etc.

Step 2: Set the targets
At this stage, the goals to be achieved are set and the project specification decided.
To do this, first a general data collection concerning the study object is completed.
Data to collect include for example past production volumes, allocated personnel,
items produced, equipment and material needed and the variety of finished products
produced.

Also at this stage, any constraints to the project needs to be clarified along with any
design specifications. Design specifications could be regarding production capacity,
products to be handled, throughput time and quality standards.

Step 3: Doing the analysis
In order to improve or redesign a system, the current conditions must be thoroughly
understood and analysed in order to find root causes for problems that must be
improved (Zandin, 2001, c. 29). In this work the following points are important to
follow(Zandin, 2001, c. 29):

• Take a quantitative approach as much as possible

• Analyse to a level of preciseness adapted to the subject being analysed (not
too coarse, not too detailed).

• Present results visually (make good use of charts, graphs, and drawings).

In doing this, the industrial engineer have many established analysis techniques to
choose from. Commonly used methods are for example process analysis, operation
analysis, motion study, time study, work sampling and flow analysis.

Step 4: Modelling the area to be improved
Many factors impact the production system and its performance varies on daily basis
due to a variety of factors. The factors could for example be related to work methods
used by operators, conditions of resources and quality of parts. In order to conduct
improvement work in an efficient manner, it is important to model a representative
model of the system. The model should be based on the most typical values and
status of the system. Improvement work should then focus on the values defined in
the model and not be distracted by daily fluctuations in the real production system
(Zandin, 2001, c. 29).

Step 5: Developing the ideal Method
Once the model has been created, the improvement plan should be made. This plan
will vary, depending on the objective set for the improvement activity in step one.
If the activity is improvement of work methods performed by the operators, the
project will take one route. HOwever, if the improvement activity is the structure of
complex multiprocess system, another route will be necessary (Zandin, 2001, c. 29).

9



2. Methods

When the change project involves changes in multiprocess system, which this thesis
project does, the first step is to study the relationships between the various processes
(Zandin, 2001, c. 29). The main task at this stage is to evaluate the suitability of
different production strategies. Consider and compare line production methods with
cell production methods or individual production methods. Also, if the production
should be in continuous flow or batch orientated. And in the case of line production,
the type of line should be considered. It could be a variety of product models on
a few lines, or a limited number of models on multiple lines(Zandin, 2001, c. 29).
Other aspects to consider, if changes to layout are considered, are how these will
affect other aspects. Aspects such as material handling methods, production control
and work in progress (WIP), who all have big impact on the production systems
output.

To aid in this analysis work, there are many different analysis tools that can be
used and below follows a list of some of them.

• Eliminate, Combine, Rearrange, Simplify (ECRS)

• Principles of Motion Economy

• Brainstorming

• The 5W1H Method
Step 6: Selecting the improvement plan
Selecting the best option, from several available ones, should be based on uniform
evaluation standards where the cost, time and technical difficulties of the improve-
ments work should be considered. Basically, all aspects considered in the objectives
for the improvement work should be included in the evaluation(Zandin, 2001, c. 29).
Parameters evaluated, both qualitative and quantitative, should to as much extent
as possible be given target numbers prior to the beginning of the evaluation. This
to more easily determine which suggestion is the best. Usually the the different
aspects are given different weights, which then helps determining the solution with
the highest impact potential. There are several standard methods to choose from
at this stage and two possible ones are the Kesselring matrix and the Pugh matrix.

Step 7: Implement new systems
In implementing the new system or method, much preparation is necessary. It in-
volves everything from ordering to installation, educating and training operators,
creating user manuals and setting maintenance procedures(Zandin, 2001, c. 29).

Step 8: Follow up and enforce new methods
Once the new system is in place, it is important to follow up and monitor the sys-
tems performance in order to ensure performance at target levels. As a mean to
achieve this written standard, operating procedures and work standards should be
made and maintained as well as standard procedures for equipment maintenance.
As a way to ensure that the new systems is performing at target, the implementation
of measurement system is necessary (Zandin, 2001, c. 29).

10



2. Methods

2.3 Step 1: Define the scope
This step has already been defined by Aros and is the reason for this thesis projects
existence.

Selected goal of study:
To improve the capacity by balancing the production system as well as reducing the
occupied area of the subject of the study.

Selected study subject:
The products of Green production unit that are being processed by the wave sol-
dering machines.

2.4 Step 2: Set the targets
The targets to be reached were decided before the data collection started. This was
done by the production management and was formulated into the research ques-
tions. Also, limitations to the project were done and these are formulated in the
delimitation in the introduction chapter.

The data collection performed was extensive and its results can be seen in the Cur-
rent state chapter. Data was gained through internal documents of the company,
own measurements, the Enterprise Resource Planning system (ERP), T-Log (inter-
nal Performance Measurement System (MPS)) and many discussions with operators.
The data was collected in the following areas:

• Product related data

• Area related data

• Test data

• Process equipment data

2.5 Step 3: Doing the analysis
In order to find the root causes to the capacity issue, a cause and effect analysis was
made. This showed that many of the problems origin from the lack of time data and
work standards. It was therefore concluded that work measurements were needed
in this project.

There where no time data available for either process equipment nor manual han-
dling. Capacity data for process equipment was collected trough stopwatch mea-
surements and the internal MPS T-log. The results from this can be seen in the
Current state chapter. The analysis of which data to use as the standard time data
is however presented in the Analysis chapter.

11



2. Methods

Due to the manual work being repetitive, a time study was chosen to be the ap-
propriate method for determining standard times for manual work activities. The
standard times were mostly done by using Sequential Activity and Methods analysis
(SAM), an easy to use Predetermined Time System (PTS). It is recommended to
start a time study through stopwatch analysis but in order to do method improve-
ment simultaneously when doing the study, a PTS system is more convenient. The
reason for this is that micro motions and moving patterns of operators and material
become more visible and easier to eliminate during this type of analysis.

Since the work tasks were a mix of short, medium and long, SAM was not al-
ways the best option. Therefore, when a task was medium to long or when the
task had motions that were difficult to analyse, stopwatch measurements were also
used. All work tasks have been video recorded in order to later judge the best work
measurement. By video recording the operator, all work tasks required to perform
a processing step was documented in an accessible way. Also, this enables any dis-
turbances to easily be subtracted when later analysing the video. Each film covered
between one to three complete work cycles to ensure that different variations are
caught on video. The Avix software was used since it provides good visual aid and
supports resource balancing, which is the final aim of the thesis. The results of the
time study can be seen in the Analysis chapter.

2.6 Step 4: Modelling the area to be improved
The time standards developed in previous step now became the foundation for a
representative model of the current systems, although work improvements have al-
ready been implemented. Each products work cycles for the processing steps could
be added to each other to form an estimated lead time per product. The lead time
for one product was verified through a live-test. The results for this can also bee
seen in the Analysis chapter.

In an attempt to model the current production systems, lead time were estimated
for the specified product mix. The team leader who is responsible for the daily plan
was asked to plan the production for Week 19, based on her own knowledge of the
process, which is the way production is normally planned. This became the time
reference to be used when later comparing the results from the improved state.

2.7 Step 5: Developing the ideal Method
As stated multiple times, the objective of the thesis was to improve the capacity
by changing the production layout to a more flow oriented layout. Product families
where therfore made, with the use of production flow analysis (PFA) of the already
created product and process map. Each product family was then balanced indi-
vidually and with the use of ECRS, work tasks were attempted to be eliminated,
work stations combined, products routing rearranged and general routing simplified.

12



2. Methods

The balancing was performed with the resource balance module in Avix. The first
step in the balancing was to define the objective. In this case, the project goal is
to increase capacity and reduce the occupied area through a flow-oriented system.
When balancing, the objective therefore was set to minimise both cycle time and
number of workstations in order to increase efficiency of both flow and resources.
The balancing results can be seen in the Solutions chapter.

Once the final balancing suggestion had been established, each work stations work
tasks where evaluated with regards to how much space they now would required.
From this, the improved layout suggestion could be made to illustrate the area re-
duction as well as the new product flows.

The Capacity of the improved state was calculated as the maximum product out-
put during a week of production and then compared to the current state Capacity.
This definition of Capacity does however not say much about the impacts of the
suggested flow-oriented system. Therefore, a Productivity increase estimation was
made in order to show the impact of methods improvement and to show the effects
of focusing on both flow and resource efficiency.

2.8 Step 6: Selecting the improvement plan
Since the aim of the thesis work was to present only a suggestion of how to increase
productivity, by changing their production strategy to a more flow oriented system,
this step lies outside of the thesis scope.

However, the presented suggestion should at this stage be weighed against the other
options that Aros has. For example, one option they have is to entirely phase out
the use of the wave soldering machines and use selective soldering instead.

2.9 Step 7: Implement new systems
This step is also left to Aros to perform by themselves, once an improvement plan has
been chosen and a production strategy finalised. The authors has however proposed
some implementations suggestions in the discussion chapter of this report, if Aros
decides to implement the suggested solution.

2.10 Step 8: Follow up and enforce new methods
Also for this step some suggestions will be aired in the discussion chapter of the
thesis.

13



2. Methods

14



3
Theory

In this chapter, the theory of the tools and methods that has been used in the
thesis will be presented. Firstly, research about capacity and productivity will be
presented. The chapter is then followed by some background information regarding
the general method applied. After that, the theories regarding production layout
and balancing and their related impact will be reviewed. Also, a chapter about lean
production has been included since Aros is influenced by this management system.
Lastly, some basic information about the software used in the thesis will be given.

3.1 Capacity and Productivity
In this section, the terms capacity and productivity will be explained and defined.

3.1.1 Capacity
According to (Olhager, 2013), capacity should be defined as the maximum work
output that a given production resource can produce during a given time period.
The work output is given as the maximum capacity of work time during a period of
for example a 40 hours week or an eight hour shift.

Capacity can also be measured as maximum product output during a given time
period but (Olhager, 2013) states that this is misleading and does not tell much
about the true capacity. This since most products in a production system differ
from each other and hence has different process flows and times that need to be
considered. Capacity can hence be measured either by equation 3.1 or 3.2.

Capacity = Maximum Work T ime output

Given T ime Period input
(3.1)

Capacity = Maximum Product output

Given T ime Period input
(3.2)

3.1.2 Productivity
Productivity is a term that can be used with many definitions but simply explained,
it is a measure that is used to show the output from a system compared to the input
of resources to a system. Equation 3.3 is one way of measuring productivity and

15



3. Theory

according to (Sakamoto, 2010), it is the measure that is most commonly used.

Productivity = Product output

Labour input
(3.3)

According to (Sakamoto, 2010), productivity can also be measured with inputs as
money, number of workers, materials, energy. So it is of high importance to define
a correct productivity measure for the system that is to be analysed.

As mentioned, output in relation to labour time input is a common measure. How-
ever, this measure can and should also be developed and used as a more complex
measure in order to reach higher productivity rates (Sakamoto, 2010). By separating
the measure into the three factors according to equation 3.4, an organisation may
receive a better perspective on what impacts the productivity and what to focus on.

Productivity = M × P × U (3.4)

M=Methods
This factor represents the planned for productivity rate or ideal cycle time.

P=Performance
The performance factor has to do with both operator speed and speed of process
equipment. It gives a percentage of how fast a resource is working in relation to the
planned production time or ideal time.

U=Utilisation
The utilisation factor also concerns both people and equipment. The utilisation
factor is denoted as the time spend on value-adding work as a proportion of the
planned production time or ideal time.

3.2 Background of Methods engineering
Since the the thesis involves performing a time study, it became apparent through
the literature study that the general method approach of Methods engineering would
be appropriate to adopt. Below follows a short introduction to Methods engineering
and its definition. It is good for the understanding of how Methods engineering and
time studies are closely related, with no clear boundaries between them.

3.2.1 History Methods engineering
Time standards and work study origins from the late 1800s when Fredrick Winslow
Taylor, a foreman at Midvale Steel company, wanted to increase productivity at
his production department. His attempts were based on systematic analyses of
operations and in time his analyses led to the principle of: "The greatest produc-
tion results when each worker is given a definite task to be performed in a definite
time and in a definite manner"(Stegemerten and Schwab, 1948, p.6). During the
same time period, Frank Gilbreth, a former building contractor, and his wife Lillian

16



3. Theory

Gilbreth was performing motions studies of work in order to improve work methods.
Franks interest of the subject started on his first day as a bricklayer apprentice when
he discovered that the simple task of laying bricks could be performed in numerous
ways. The Gilbreth’s performed detailed laboratory studies of motions and methods
and developed the micromotion study procedure that still forms the basis of the first
PTS (Stegemerten and Schwab, 1948, p.6).

Between the years 1910-1930, the two fields of study was considered to be total
opposites of each other where the time study group could not see the use of the
laboratory approach. And the motion-study followers thought of the time study
groups work as unscientific and crude(Stegemerten and Schwab, 1948, p.7). Once
the two sides became more familiar with each others work they realised that they
had been working on the same subject, just calling it by different names. The best
features of each approach where brought together to form the basis of a new, sin-
gle universal applicable approach now known as Methods engineering (Stegemerten
and Schwab, 1948, p.7). In short, Methods engineering can be described accordingly:

"Methods engineering is a systematic technique for the design and improvement of
work methods, for the introduction of those methods into the work place, and for
ensuring their solid adoption"(Zandin, 2001, c.29).

In the beginning, the objective of Methods engineering was to improve already exist-
ing work systems. This however changed and later a more design-oriented approach
has begun to evolve. The new approach can be applied in developing and designing
a completely new system, not existing before (Zandin, 2001, c. 29). A shift in the
focus on the improvement of systems have also occurred during the years. Initially,
the focus was mostly on individual work with high content of repetitive operations.
This has later changed to look at more complex systems and improve it as a whole,
involving also people and equipment(Zandin, 2001, c.29). Because of this shift, the
objective of Methods engineering has also gone through a change. From the objective
originally being limited to increasing productivity, it now contains a wider purpose of
improving work system flexibility, expandability and maintainability(Zandin, 2001,
c.29). It has today evolved so far as to involve more softer topics. Softer topics are
for example improving customer satisfaction, improving ergonomics and improving
safety and creating a more comfortable work environment(Zandin, 2001, c.29).

3.2.2 Definition of Methods engineering
During the evolution of Methods engineering, numerous definitions of the subject
has developed. The thesis will use the definition presented in (Zandin, 2001, c. 29),
which in turn is is taken from the 3rd edition of Industrial Engineering Handbook:

"The technique that subjects each operation of a given piece of work to close analysis
to eliminate every unnecessary element or operation and to approach the quickest
and best method of performing each necessary element or operation. It includes the
improvement and standardisation of methods, equipment, and working conditions:

17



3. Theory

operator training; the determination of standard time; and occasionally devising and
administering various incentive plans." (Zandin, 2001, c. 29).

The thesis will however widen the perspective compared from the definition. Instead
of just analysing the given work piece operations, the whole production department
of the Green unit will be evaluated including its equipment and people.

3.3 Time study
As stated in the methods chapter, the results of the thesis relies on work measure-
ments based on time standards. Below follows the the most important theory on
this topic.

3.4 Work measurement
In order to make manufacturing operations as efficient as possible, systematic analy-
sis of work and the establishment of work standards is required (Zandin, 2001, c. 29).
According to (Zandin, 2001, c. 29), there are three main methods for measuring work
and developing time standards.

3.4.1 Estimations
Estimations is one of the methods and can be made in two ways. Either a per-
son with knowledge about operations makes experience and knowledge-based time
estimation of them. This estimation method does not properly consider the varia-
tions in operation time and can lead to missed schedules and bottleneck creations.
The other way is to base estimations on historical production data. Historical data
over previous production times and quantities can though give cause for the Parkin-
son’s law, which states that work will expand to fill the available time (Parkinson,
1957)(Zandin, 2001, c. 29).

3.4.2 Direct observation and measurement
Direct observations can be made in three ways: Time study, Work sampling and
Psychological work measurement. Time studies are conducted by recording the
time of performing an operation, study the method, rate operator performance in
comparison with normal pace and adding allowances for Personal needs, Fatigue and
Unavoidable delays (PFD). Time studies are appropriate when tasks are repetitive
and relatively short cycled. When work cycles are long, work sampling is more
appropriate to use. Work sampling is a statistical technique that gives a prediction
of time consumption for activities through making a large number of observations at
random intervals. Psychological work measurements is used to measure physiological
costs of workers performing tasks. For example, a beginner at a certain task has a
higher physiological cost then an experienced operator, if attempting to perform at
standard rate(Zandin, 2001, c. 29).

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3. Theory

3.4.3 Standard data systems
Standard data systems are collections of motion time data that have been compiled
from previous studies of manual work. Standard data system can be divided into
two types: Macroscopic and Microscopic standard data. Macroscopic time data is
based on similarities in work elements between operations. These similarities in work
elements are developed to time standards for these activities. Microscopic standard
data, also called PTS, are used to decide on standard times through detail studies
of every single motion needed to perform a job. The time required for the motions
are found in PTS and through analysing single motions, whole sequences and their
required time can be constructed up(Zandin, 2001, c. 29).

3.5 Predetermined Time systems
There are many types of PTS but they all require the same thing: an extensive
understanding of the studied operations and a complete definitions of all single
motions involved. The time required for the single motions can be summarised into
a total operation time and the PFD-allowances can be added to create a defined
standard time(Zandin, 2001, c. 29).

3.5.1 MTM
Methods-Time Measurement (MTM) was the result of the need for being able to
measure work methods and time simultaneously, instead of separately as they were
made previously. The definition of methods engineering according to (Stegemerten
and Schwab, 1948, p. 7) states that a work method should be developed, standard-
ised and taught to the operator, in that order. The work time should be measured
only after the work method had been taught. (Stegemerten and Schwab, 1948, p. 7).
This proved to be difficult in practice since better methods are sometimes found dur-
ing time studies. Therefore, it was difficult to decide on which method is the best,
without making a time study first. MTM solves this problem since it makes it pos-
sible to analyse both method and time simultaneously (MTM-föreningen i Norden,
2015b).

The MTM system originally was one system but over the years, updates to the
system were brough and there now exists three versions of the MTM-system (MTM-
föreningen i Norden, 2015a).

• MTM-1. This is the original MTM-system and contains all original motion
and time data that the other two versions are based on.

• MTM-2. MTM-2 is a development that was presented in 1965 and this sys-
tem is used for more simple motions than those requiring MTM-1 (MTM-
föreningen i Norden, 2015a).

• MTM-3. MTM-3 came after MTM-2 and is an even more simplified version
(MTM-föreningen i Norden, 2015b).

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3. Theory

All PTS systems has a standard time unit that all motions are given in values of.
The standard time unit of the MTM systems is called TMU, Time Measurement
Unit, and one TMU is equal to 0.00001 hours (Zandin, 2001, c.126).

3.5.2 Sequential Activity and Methods analysis
SAM is a system that originates from MTM and built up on the same basis as MTM
2 and MTM 3 and it has an accuracy that lies in between MTM 2 and MTM 3. It
is created on a base of sequential thinking and during its development, the aim was
to create a system that can be used in communication with operators, designers and
processing/preparation departments (MTM-föreningen i Norden, 2015b)
.
The SAM-system is based on a time unit called a factor. One factor is equal to 5
TMU:s (IMD, International MTM Directorate, 2004).

SAM builds on the fact that manual motions involving objects, follows an activ-
ity sequence of getting an object and putting the object into a final position.

There are three type of activities in the SAM-system:

1. Basic activities

(a) Get
(b) Put

2. Supplementary activities

(a) Apply force
(b) Step
(c) Bend

3. Repetitive activities

(a) Screw
(b) Crank
(c) To and from
(d) Hammer
(e) Read
(f) Note
(g) Press button

Some of these variables in turn has variables that they depend on. Variables for put
are for example Movement distance, Weight and Degree of precision.

The variables are also divided into different levels, so called classes and cases. The
classes for the movement distance variable are three and they are defined as the

20



3. Theory

distance the hand is moved. The classes are up to 10 cm, between 10-45 cm and
45-80 cm, including a supportive step. After 80 cm, including the supportive step,
supplementary activity step needs to be added.

To conclude, the standard time for an activity sequence is then based on the three
main activities, their variables, cases and classes (IMD, International MTM Direc-
torate, 2004).

3.6 Production flow strategies
”Production flow refers to the movement of the product through a facility” (Zandin,
2001, c. 112). By effectively managing the production flow, product throughput and
quality can be increased. Also, inventory, lead times and material handling can be
reduced, which provides competitive advantages for the company. There are four
main categories that affect the production flow (Zandin, 2001, c. 112):

1. Product

2. Product environment

3. Facility layout

4. Operational strategy

The product and customer demand restricts some choices but many factors can still
be controlled by the company (Zandin, 2001, c. 112). Focus in this literature review
will lie on facility layout since that is most closely connected to the topic of the
thesis.

3.6.1 Facility layout
The facility layout is of great importance in how efficient a production plant is. The
production flow depends largely on how well its resources, equipment and employees,
are distributed around the production floor. In a properly laid out plant, the move-
ment of material from raw material to finished product is smooth and rapid. The
movement should preferably be in a forward direction with no crisscross movement
or back-and-forth transportation between operations (Aswathappa, 2011). There is
however no set pattern of how a facility layout should look like. Every facility is
different and the layout depends greatly on product size, product variety, production
volume and production flexibility (Zandin, 2001, c. 112).
Production is a living environment and an optimal layout at one point might not

be so further down the road, therefore the initial layout is almost never final or
permanent. There are five basic types of layout, which managers can choose to im-
plement: Continuous flow layout, product layout, process layout, cellular layout and
fixed layout, see figure 3.1. Each type is described in more detail below (Zandin,
2001, c. 112).

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3. Theory

Figure 3.1: Correlation between volume and flexibility

3.6.2 Continuous flow layout
Continuous flow layout is usually adopted in the processing of non-discrete materials
such as fluids or bulk material(Zandin, 2001, c. 112). Hence it is not a single work
piece being moved around but it is rather the storage container that decides the size
lot (Zandin, 2001, c. 112). All material goes through the same processes in the same
sequence.

3.6.3 Fixed position layout
Fixed position layout is, just as the name indicates, used when the products are dif-
ficult to move due to size and weight. The material, tools, machinery and workforce
are therefore brought to the fixed position of production(Kachru, 2007)(Zandin,
2001, c. 112). Highly skilled workers build the product according to detailed cus-
tomer specifications and the quantities often equal one (Zandin, 2001, c. 112). Since
there is no product flow, focus on organising workers in teams and creating zoned
areas within the production is essential in order to have a high efficiency (Zandin,
2001, c. 112). Also, good planning and focused attention on critical activities is
therefore essential in order to maximise margins (Kachru, 2007). The main advan-
tages and disadvantages can be of a fixed position layout can be found in table 3.1.

22



3. Theory

Table 3.1: Table over main advantages and disadvantages of fixed position layout

3.6.4 Product layout or Line production

Product layouts are dedicated production lines used for manufacturing one specific
product (Zandin, 2001, c.112). Traditionally it is usually adopted for products pro-
duced in big volumes, mass production, with small varieties. If there is a need for
small varieties in a dedicated line, it needs to be achieved through minimal setup
(Zandin, 2001, c.112). However, line production has more recently also gained im-
portance in low volume production with more customised products (Boysen et al.,
2008). As illustrated in figure 3.2, the product move through a sequence of stations,
containing all resource needed for one operation, and each unit is processed as it
passes through (Baudin, 2002). The stations are usually aligned in serial manner
(Boysen et al., 2008)
Assembly line systems can be very efficient if designed properly. To properly imple-
ment an assembly line system the entire production system needs to be considered
and the assembly line system adapted to suit it (Thomopoulos, 2013). Assembly
line system varies from production system to production system but there are three
main categories that can be described.
Single model line
A single-model line means that an assembly line is dedicated to one single product.
There are no variations in the product and no variations in work tasks. The mod-
ern single model assembly line is often referred to having its origins from the mass
production Henry Ford and his driven assembly line for the Ford model T.
Mixed model line
In mixed-model assembly lines, more than one product can be produced at the same
line. The line stations are balanced for all products being run at the line but it also
has to be sequenced. The products on the line is run in a sequence that is based
on customer demand and it is essential that setup times are kept low in order to
maintain a smooth flow. In order to maintaining a smooth flow at a mixed-model
lines, production processes should be similar so that the cycle times are not too
uneven (Boysen et al., 2008) (Thomopoulos, 2013).
Multi model line
As in mixed-model lines, multi model lines are also used for producing more than
one product at the same line. However, the production does dot occur in sequencing
since the production process differ too much or the set-up time are too high to be

23



3. Theory

ignored. Production therefor has to be performed in batches and the line requires
set-up time between the running of different products, in order to suit the produc-
tion of the next product. The line is treated as a single-model line but it gives more
flexibility (Boysen et al., 2008) (Thomopoulos, 2013). The main advantages and
disadvantages can be of a product layout can be found in table 3.2.

Table 3.2: Table over main advantages and disadvantages of product layout

Figure 3.2: Illustration of product layout

3.6.5 Process layout or Functional layout
Process layout, also known as functional layout, is characterised by similar machines
or operations being located at one place, grouped by their functionality. In this type
of layout, the work piece travel from one machine group to the next in a unique
sequence, see figure 3.3, and criss-cross movement and backward flow is not unusual
(Zandin, 2001, c.112). This type of production is useful when there is a wide diversity
in the product flow since each product can take its own routing. Therefore, this type
of production is useful for small orders. This is due to the unique requirements of
each order and typically the order size also defines the batch sizes (Zandin, 2001,
c.112).
Due to the irregular and unique flow patterns through the factory, detailed planning
and control is necessary (Zandin, 2001, c.112). Also, set up and work in progress
(WIP) tend to be high. Actual machining time constitutes only a small percentage
of the actual lead time and the machine utilisation is usually very varied (Zandin,
2001, c.112). The main advantages and disadvantages can be of a process layout

24



3. Theory

can be found in table 3.3.

Table 3.3: Table over main advantages and disadvantages of process layout

Figure 3.3: Illustration of
process layout

3.6.6 Cellular Manufacturing layout
Cellular layout is a combination of both process and product layout. It is suitable
when a large variety of products are needed in small volumes or batches (Kachru,

25



3. Theory

2007). It incorporates each of the above mentioned layouts best and most efficient
attributes (Kachru, 2007). By grouping into a product families, it enables parts to
be produced more economically than with traditional layouts (Kachru, 2007). When
a product family is identified its resources in the form of similar machines, labour
skills and tooling are clustered together into a machine cell (Kachru, 2007)(Zandin,
2001, c.112). In these cells, the production flow can be streamlined. Therefore in
establishing an effective cellular layout, a crucial step is to form the best product
families that tries to eliminated inter-cell transfers(Zandin, 2001, c.112)(Kachru,
2007). In other words, the traditional process layout characterised is changed into
a small and well-defined product layout, see figure 3.4. The arrangement of these
machine cells is called a Cellular layout.

As mentioned previously, the internal cell layout determines how efficient, economi-
cal and practical the cell will be be in the long-term. An efficiently designed cell will
have standard operating procedure for different throughput and production rates,
with setups and material handling being minimised (Zandin, 2001, c.112). The cell
must be flexible in its mix of capacity by being large enough so that the absence of
one operator does not force it to shut down(Kachru, 2007). However, it also needs
to be low enough for the operators to understand and identifies all the products and
operations (Kachru, 2007). As a way to achieve this, it is common to adopt the
U-shaped assembly line. The U-shaped assembly line provides the operators with
a good overview, increases teamwork and consumes less occupied space and reduce
walking distances (Kachru, 2007).

Table 3.4: Table over main advantages and disadvantages of cellular manufacturing
layout

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3. Theory

Figure 3.4: Illustration of cellular manufacturing

3.7 Balancing
For a product flow layout to perform efficiently, the assembly line needs to be bal-
anced. All manufacturing and assembly tasks can be decomposed into work ele-
ments. A work element is a discrete task required for the processing of a given
product (Zandin, 2001, c.130). Also, each work elements has set of work elements
that must precede itself (Zandin, 2001, c.130). When balancing an assembly line
all work elements needs to be distributed to different work stations while not disre-
garding any precedence rules.

3.7.1 Product families
Before balancing can be started, it is a good idea to form or evaluate already existing
product families.

A product family is a group of products that pass through similar processes or
equipment and have similar work content (Duggan, 2012). Product family forming
can be accomplished using different methods and principles of grouping technology
(Kachru, 2007). One method to use is a production flow analysis (PFA), explained
by(Olhager, 2013). PFA ends up in a product family matrix, which can either be
used as a simple visual tool or as a complex mathematical tool (Duggan, 2012).
Either way, the matrix is a grid that shows the correlation between products and
their connected processes by listing the products in rows and processes in columns
(Duggan, 2012).

The process flow might not always be continuous. In some cases, products flow
from one process to the next and back upstream to the first process again. If this

27



3. Theory

is the case, these processes should be listed again the matrix (Duggan, 2012). Also,
if a process could be performed by another process, but it is not the primary choice
because of setup or slower speed, the alternative process should be marked. To keep
the matrix simple and easy to use, it could be a good idea to place only base model
numbers in the matrix, if the derivations are non-process-related items (Duggan,
2012).

When all products have been mapped with its related processes, it can start to
be sorted visually. By moving rows and columns in the matrix, rectangles in the
diagonal is attempted to be achieved in order to find similarities in resource usage
(Olhager, 2013). From the matrix, shared resources can then be identified. The
first shared resource is the point where continuous flow ends and pull begins. Prod-
ucts with similar processing steps downstream from the shared resource should be
grouped together. Products within a now identified product family do not have to
follow the exact same process path, some process steps can be skipped or added.
However, as a rule of thumb about 80% of the downstream processing steps between
products should be should be the same, in order to create a good product family
(Duggan, 2012).

3.7.2 Takt time

Balancing means that the work tasks of a product is moved between work stations
until all workstations cycle times are lower then the takt time of the assembly line.
They should also be as even as possible. The takt time is the time that must elapse
between two finished products in order to meet customer demand. It is therefore a
function of both the demand and available time according to equation 3.5 (Baudin,
2002).

Takt time = Net Available Production T ime

CustomerDemand
(3.5)

Since demand often vary, there is usually a design takt time. The design takt time
is the minimum takt-time, or highest capacity, the line is designed to support. The
line is though usually required to operate at a higher takt time, due to fluctuations,
and the challenge is then to ensure that it runs with proportionally fewer resources
(Baudin, 2002). Changing the takt time can be a tedious task, especially in assem-
bly since it involves reassigning task among assembly station and operators (Baudin,
2002).

Not all machines are easy to run according to takt driven production. Machin-
ery that take a load of many products at a time and have long process times, such
as ovens or paint booths, can be difficult to manage. These machines must not keep
the rest of the plant further away from the ideal or takt driven production than
needed. Also, the batch sizes should be different in different parts of the production
(Baudin, 2002).

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3. Theory

3.7.3 Assembly line balancing problem
In the assembly of a product, many work elements are involved. To properly assign
these elements along the assembly line, with respect to some objective, is known as
the Assembly Line Balancing Problem (ALBP). Any type of ALBP consists of find-
ing a feasible line balance where tasks are assigned to workstations with precedence
constraints and other restrictions such as labour, facility and equipment require-
ments fulfilled (Boysen et al., 2008). There are therefore many challenges when
balancing an assembly line but the core of any ALBP is to make the work pack-
age assignments in such a way that operating costs are minimised and productivity
maximised (Zandin, 2001, c.130).

It is difficult to measure and predict the costs of operating an assembly line. There-
fore, an alternate measurement is the assembly lines efficiency (E) . This is measured
as the productive fraction of the lines total operating time according to equation
3.6, where tsum is the total sum of all task times, m is the number of works stations
and c is is the cycle time (Boysen et al., 2008).

E = tsum

mc
(3.6)

Therefore, ALBP should focus on one of the following three objectives on order to
increase the efficiency (Zandin, 2001, c.130):

1. To find a combination of cycle time and number of workstations, which results
in a minimum sum of idle time.

2. To reduce labour costs by minimising the number of workstations on the as-
sembly line. Here, the production rate is known in advance, resulting in a fixed
cycle time. An additional constraint is that the processing times at each work-
station, determined by the sum of the task times assigned to the workstation,
cannot exceed the cycle time.

3. To minimise cycle time for a given number of workstations by balancing the
line.

Balancing decisions have long–term effects and therefore the balancing objective has
to be carefully chosen considering the strategic goals of the company (Boysen et al.,
2008).

3.8 Lean manufacturing
Lean manufacturing can be viewed as a production philosophy that aims to give
an organisational culture of constantly improving every process, while eliminating
wasteful activities as much as possible. It consist of key principles and a wide range
of tools that supports the principles and the philosophy. In order for an organisation
to become Lean, it is necessary to keep a holistic view on organisational processes
and use the tools in a way that enables a lean culture. In this section, some of the

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3. Theory

principles and tools relevant for this project are described.

The term Lean origins from 1990 when the book “The machine that changed the
world” was published, written by James P. Womack, Daniel T. Jones and Daniel
Roos. The term was coined as the conceptualised form of Toyota Production Sys-
tems (TPS). The book describes the philosophy and principles of the successful pro-
duction system of Toyota and came to change they view on manufacturing within
the mass-producing manufacturing community. TPS has evolved into what it is
today over many years and it is still evolving. It was Toyotas solution to be able to
compete with companies in western countries with their expensive technologies and
mass production (Dennis, 2007).

3.8.1 The eight wastes of Lean
The idea with Lean manufacturing is to constantly focus on creating customer value
while eliminating waste. Wastes are all activities that do not add value to the cus-
tomer. According to Lean, there are eight different types of waste.

Overproduction
Overproduction is to manufacture products before there is a real customer demand
and it is considered as the worst form of waste since it contributes to all other forms
of waste. Overproducing is often the result of basing production planning on fore-
casts rather the actual customer demand. It makes companies producing too many
products, large batches than necessary and too fast or too earlier then the next
process in the production flow requires.

Inventory
Having inventory in buffers and storage is often necessary in order to be able to
deliver to customers on time. However, having excess inventory binds up capital in
materials and products, hides problems and takes up space. Lead times can become
vary long which makes it difficult to response well to fluctuations in customer orders.

Waiting
Waiting is when products are not being processed or moved and time is spent on
waiting for necessary conditions. Waiting can for example be due to lack of infor-
mation, lack of material or waiting for people that are late.

Transportation
Transportation means transportation of material between processes, internal and
external. Internal transportation is considered pure waste and can be minimise
through smarter layouts and logistic planning. The aim is to minimise the need for
transports as much as possible, not too come up with smarter solutions to transport
material (Petersson et al., 2010).

Motions
Unnecessary motions are considered waste. Walking to fetch tools or material is a

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3. Theory

waste and can be minimised through smarter workplace designs. Motions should be
made as small and easy as possible to perform, from both a waste and ergonomic
perspective .

Over processing
Over processing means performing operations that are not adding value for the
customer. Working with unsuitable techniques, oversize equipment and producing
products with a higher quality then needed are example of what may add to the
waste of over processing.

Defects
Producing defect products is a waste since producing defects requires rework. When
minimising this waste, the focus should lie on finding out why the defect occurred
and then prevent it.

Unused creativity
This waste is considered an addition to the original seven wastes and it is about not
utilising the full competence of employees.

3.8.2 Standardised work
Standardised work is about making everyone work in the same, best known, way
and allow for less individual variations and continuously improve the work method.
A good standard should describe what, how and in what time work should be done.
Having standardisation makes for high quality and efficiency and also provides a
safer workplace and good ergonomics. The purpose of standardisation must be
communicated thoroughly so that workers understand the need for it and not be
sceptical. Involving workers in creating work standards is good for this purpose but
also to ensure a good level of detail and content since the workers are the experts of
their work (Petersson et al., 2010).

3.8.3 Just in time
Production planning is often based on forecasted demand and not the real customer
demand. This type of planning is called a push system, since you push products
onto customers. This makes for expensive production with high inventory and over-
production is common. Just in time production (JIT) is about producing the right
product, at the right time, in the right quality and it is comprised by Takt, Contin-
uous flow and Pull systems (Dennis, 2007).

Takt
Takt is a principle that decides the pulse of the production flow and it is set at
a levelled rate that meets the real customer demand. The takt states how much
should be produced and at what time. As already stated, the takt time is calculated
as the planned production time divided by the customer demand (Petersson et al.,
2010).

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3. Theory

Continuous flow
Continuous flow is a principle that strives to keep products continuously moving
throughout the production system through minimising stopping points and stop-
ping times, since that only adds waste. Aim for short distances between production
processes, minimising buffers and package size and minimise transports (Dennis,
2007).

Pull systems
Pull systems is a JIT-principle that strives for controlling the production flow at a
point as close to the customer as possible. Kanban is a visual tool that can be used
for this purpose since it allows for the transfer of demand between processes. It is
used as a form of ordering system that for example can consist of simple cards being
transferred between stations to show that a process is in need of material (Dennis,
2007).

3.8.4 5S
5S is the most well-known tool of Lean and it is used to organise and improve
workplace productivity. The aim is to encourage workers to constantly reduce waste.
It is done through iterating the five steps of the 5S-methodology (Dennis, 2007).

1. Sort
Sort among the workplace items and remove unnecessary items of that are
non-value adding.

2. Straighten
Set the workplace items in order in a way that makes them easy to find, use
and put away.

3. Shine
Shine is about cleaning the workplace and the workplace items. It makes the
workplace more visual and helps workers detect malfunctions of equipment.

4. Standardise
Standardise the best practice of the previous three steps and sets a structure
that ensure that the standard is being followed.

5. Sustain
Sustain the 5S procedures and continuously maintain the standard decided in
order to improve.

3.8.5 Flow efficiency
In order to succeed with Lean, keeping a holistic view of both production resources
and flow is essential. As (Modig and Åhlström, 2012) states, most organisations
are far too focused on resource efficiency and the flow efficiency is often disregarded
from. In an attempt to clarify the goal of Lean and the importance of both resource

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3. Theory

and flow efficiency, (Modig and Åhlström, 2012) has developed a framework called
the Efficiency matrix. The efficiency matrix can be seen in figure 3.5 and it de-
scribes the different states an organisation can be in depending on how focus is put
on resources and flow efficiency.

Efficient islands

Figure 3.5: Efficiency matrix

Efficient islands is the state that organisations end up in when they have a high
resource efficiency but a low flow efficiency. The processes within an organisation
are separated from each other and are focused on individual performance, with max-
imising utilisation of resources within each process. Focusing on resource efficiency
will reduce cost of produced goods but it also causes a lot of waste in form of waiting
and high inventories, which makes for a low flow efficiency and possibly a cause for
hidden costs.

Efficient oceans
Efficient oceans is the state that is reached when an organisation has a high flow
efficiency but a low resource efficiency. In this state, the processes within an organ-
isation is not considered as individuals but as a system of processes that strives for
efficient flows in order to please customers. The state has a high customer focus
and resources are not used efficiently but are utilised only when there is a customer
need. Resource overcapacity is used in systems like theses in order to always be able
to please the customer.

Wasteland
Wasteland is the state where both resource and flow efficiency are low. Resources
are not used in way that saves cost and the flow is not creating any specific customer
value.

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3. Theory

Ideal state
The ideal state is reached when both resource and flow efficiency is high. This state
is a difficult state to reach. The difficulty lies in that every system has its variations
that can not be removed but must be considered while simultaneously focusing on
both resource and flow efficiency.

According to (Modig and Åhlström, 2012), Lean is the answer for organisation
that wish to reach the ideal state and to avoid the trap of too much focus on re-
source efficiency. The efficiency paradox, described by (Modig and Åhlström, 2012),
explains how too much focus on resource efficiency actually generates more costs.
These extra costs are found in the form of excess work and is due to the lack of flow
efficiency.

3.9 AviX
Avix is a set of software from Solme AB that are used for industrial applications.
AviX®Method is software that can be used with several modules, such as resource
balancing. The software also has modules that for example supports Failure Mode
and Effects Analysis (AviX®FMEA), Design for manufacturability (AviX®DFX)
and ergonomic analysis of the workplace (AviX®Ergo).

3.9.1 AviX®Method
AviX®Method is a software that can be used to analyse manual work in manufactur-
ing. It enables the user to build and analyse work tasks through video analysis, PTS
and work-classifications to mention a few of the functions within the software. It
is easy to store information about manufacturing processes in the software and also
very easy to interpret it. AviX®Method makes it possible to work efficiently with
increasing productivity, work with continuous improvements and creating optimal
conditions for production systems (Solme AB, 2015a)

3.9.2 AviX®Resource balance
AviX®Resource balance is a balancing module within the software. The stored data
in AviX®Method can be used and analysed to be able to balance production with
operator and machine resources (Solme AB, 2015b). The module is able to visualise
balancing losses, man-machine operations and overall efficiencies of production lines.
It is also possible to work with balancing multiple variants of a product and aiding
in creating improved layouts.

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4
Current state

In this chapter, products covered in the specified product mix, from here on denoted
SPM, will be presented. Also, an overview of Aros current production systems and
capacities of process equipment will be given.

4.1 Product and area related data
In this section, general data over the SPM, the area used by Green unit and products
flow will be presented.

4.1.1 Specified Product Mix, SPM
The project aim was to analyse the products within the Green production unit that
requires the wave soldering machine. Hence, the process flows of these products
in the unit were mapped and summarised. Many of the products are produced in
variants but with some differences. The differences can be software or hardware,
which may or may not affect the process flow and the work tasks required by the
operators. Originally, the plan was to cover all of these mapped products. However,
product changes were made during the project which affected the processes flows of
some products. Some products were planned to be phased out entirely and some
product are planned to move to the Yellow unit. The final SPM of the project
can be seen in table 4.1. It was assumed that the current way of producing the
SPM was close to max capacity. The production volumes sometimes differ but a
representative production volume, close to max capacity, are given in table 4.2.
These volumes are based on Week 19, year 2015, and the volumes were given from
an internal-document referred to as "Takt-data". Takt-data is a living document
where the production planning department tries to level out the demand, based on
both actual orders and forecast, to achieve an even takt of the production. The takt
is set in a 4 weeks period and for the SPM, Week 19 was judged to be representative
for normal production volumes. An exception to this were the articles 1399-6*
and 1379-6*. Together with the production manager, a more representative weekly
volume was decided for these products. To conclude, the weekly product capacity,
based on Week 19, was summarised to 877 products.

4.1.2 Area utilisation
Since one of the projects aims were to reduce the area occupied by Green unit, the
current occupied space was to be measured to form as a reference. The floor plan

35



4. Current state

Figure 4.1: Product included in the
final SPM

Figure 4.2: Production volume for prod-
ucts included in the SPM

of Aros entire production floor was obtained from the property and environmental
department of the company. The floor space occupied by each production unit
was then mapped in the floor plan. This was done by simplifying each production
units occupied floor space to simple geometric forms that were then added to the
floor plan. To separate which areas were used by which unit, the rectangles were
colour coded. From this mapping, the current floor space occupied by the SPM in
Green Unit could be estimated by rough calculations. The current state occupied
approximately 170 m2. This area then excludes the wave soldering machine area, the
coating room and work areas occupied by Orange production unit, Blue production
unit, service departments and other products not belonging to the scope. In figure
4.3 the current production layout and work areas of the different production units
can be seen.

Figure 4.3: Current production layout

36



4. Current state

4.1.3 Process flows
The process flows of each product in SPM were mapped. In order to know which
processes where needed for each product, work instructions for each product were
downloaded from Aros intranet. From this, a first draft of a list over each products
required processing steps and precedence was made. This list was then confirmed
with the operators to ensure that the right processing steps and its precedence had
been correctly interpreted. Each list was then finalised. From the precedence lists
of the processing steps, a product/process map was made to summarise the flows.
The first version of the product/process map contained all processing steps in a se-
quential order in an attempt to easily visualise required processes for each product.
If two products contained the same processing step but made in different orders, the
process step was added again as a different processing step in the map. This made
the the product/process map very long and difficult to overview, so a new version
was made. The second map only contained each unique processing step once. The
product routing was then visualised through sequential numbering within each cell,
see figure 4.4. This made the product/process map much easier to overview.

To make the current SPM flows more visual, all process equipment, tables, racks,
pallets, shelves and aisles where mapped and each products current flow could drawn
in the floor plan. An overview of these flows can be seen in figure 4.5.

Figure 4.4: Product/process map illustrating each products sequential processing
steps for the SPM

Figure 4.5: Overview of product flows for products included in the SPM

37



4. Current state

4.1.4 Volume data
In order to get and understanding of product fluctuations, yearly volume data for
the SPM was collected. The data was gathered through Aros purchase department
and shows the history between years 2011-2014. The fluctuations can be seen in
figure 4.6. Their help was required since the authors lacked access to Axapta, Aros
Enterprise Resource Planning system (ERP) where the data could be collected from.

Figure 4.6: Product volumes 2011-2014

4.2 Testings equipment data
All products need to go through multiple tests before being finished. The type of
testing a product requires vary but all products at least need to pass a In-Circuit-
Test (ICT) at some point. It though varies when, in the products processing steps
sequence, that the ICT occurs. Since the ICT is a shared resource, the ICT is in
the analysis distinguished from the other test, that are more product sepcific. All
product specific test are in the analysis grouped under the name "Functional test".

4.2.1 ICT
The ICT Equipment, see figure 4.7, can be used for most products, as long as there
is a jig program for that specific product. All products need to go through an ICT
and Aros in total has three of them. One is placed in the Green unit department

38



4. Current state

and two are placed in the Yellow unit department. Not all products in the SPM are
tested in the ICT placed in the Green unit. This since they have already been tested
in in the Yellow unit. The ICT in Green unit is used to test six of the products from
the SPM, three products from the Orange unit and a varying amount from Blue
unit. The ICT is currently run in two shifts a day, where the day shift is dedicated
Green units high runners: 1360-502, 1068-603 and 1068-503. The other products
requiring ICT, are placed in an buffer to the night shift. On the night shift, one
operator tests all the products from the buffer so they can continue to their next
processing step on the following day.

Figure 4.7: ICT equipment located
in Green production unit

Figure 4.8: Common type of functional
test in Green production unit

4.2.2 Functional tests
One of the limitations in the thesis was to improve the production flow using ex-
isting equipment. The amount of testing equipment at Aros is extensive and most
of their test are quite old and inflexible. This is because has a lot of long-runners
in their product range which still has their original test equipment in use. The
test equipment in Green unit has a wide range of test types. The process map felt
insufficient in providing all required data needed for the current state analysis and
therefore, a full summary of test equipment belonging to product scope was made
and can be seen in table A.5, appendix A. Test id-numbers were mainly collected
from work instructions. Some work instructions did not include this information so
these id-numbers where instead found on labels marked on the physical test equip-
ment. Some test equipment was not marked at all and these id-numbers were then
received from the flow-technicians.

A test usually consist of three components: a test unit, a computer and a test

39



4. Current state

fixture or test jig. An example of a common test type in the production is the test
that can be seen in figure 4.8. The lower part is the part referred to as a test unit
and the upper part is referred to as jig or fixture. The test unit itself is a type of
universal test. It can used for other test but as for the ICT equipment, other jigs
and other programs are then needed. It differs greatly between the functional tests
on how product specific they are. Some are dedicated to only pre-testing and can
test a few different products changing the testing program or jig. Other test can be
used for both pre-tests and final functional-test and are then usually dedicated to
only one product type.

4.2.3 Testing equipment yields
Data from most testing equipment is logged and collected in a database called T-log.
For this project, the stability of each test was required in order to provide a repre-
sentative an obtainable produc