Variation Risk Management and Decision Making

dc.contributor.authorAndréasson, Isabelle
dc.contributor.authorCatalano, Gabriele
dc.contributor.departmentChalmers tekniska högskola / Institutionen för material- och tillverkningstekniksv
dc.contributor.departmentChalmers University of Technology / Department of Materials and Manufacturing Technologyen
dc.description.abstractVariations are always present in processes and depending on how organisations manage these variations, targets risk not to be reached. The performance of a modern company strictly depends on the ability of combining interfaces between different processes, increasing the value added to the customer and optimizing utilization of the assets and resources; reducing the variation affecting the process. Variation Mode and Effect Analysis (VMEA) is a commonly known tool within product development for robust product design. The purpose of this study is to investigate if VMEA is applicable to processes in order to manage process variation and to build robust processes. The goal is to fulfil the purpose and to make generalizable conclusions. This work rises after a successful Six Sigma project, where the authors applied the VMEA methodology to a process in an improvement project. With the intention to achieve the purpose, a qualitative research strategy was selected. Qualitative data were collected through semi-structured interviews and a Kano survey. The main research was done at Volvo Group Trucks Technology (Volvo GTT). Furthermore, for increasing the validity of the study, a benchmark was performed at Volvo Group Trucks Operations, Ericsson AB and Tetra Pak. In addition, VMEA researchers and experiences Six Sigma black belts supervised this thesis work. A case study was performed at Powertrain Engineering within Volvo GTT for analysing the In-Service Conformity test process. The results of this thesis show that VMEA is applicable to processes. A new developed Process-VMEA (P-VMEA) framework is provided for identifying, assessing, mitigating and managing variations in a process. The deliveries of the framework are mainly directed towards decision makers and aim to strengthen fact based decisions. The reader is guided step by step in the P-VMEA methodology by using artificial organisation examples and real application cases. The P-VMEA framework is divided in four phases with review gates in the end of each phase to ensure that the goals are achieved.
dc.relation.ispartofseriesDiploma work - Department of Materials and Manufacturing Technology, Chalmers University of Technology
dc.subjectHållbar utveckling
dc.subjectSustainable Development
dc.subjectManufacturing engineering
dc.titleVariation Risk Management and Decision Making
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
local.programmeQuality and operations management (MPQOM), MSc
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