An optimization model to improve the production process: A case of a tag manufacturer in Sweden

Abstract

In recent years, the constant improvements in production planning has become increasingly important for manufacturing enterprises seeking to maximize their market value in a volatile industrial environment. This thesis is entitled towards providing an optimized production planning model. Mark Bric is a manufacturer of size marker hangers which are mainly used in the clothing industry. Size hangers are of different varieties which differ in size and color. When there are many varieties of products to be produced in manufacturing line it requires time for change-overs between each variant change. The aim of this thesis is to develop the resources needed for Mark Bric to become more efficient in their sequencing of these variation. This thesis illustrates how an investment decision was analyzed by constructing an objective function, constraints, variables, and solving it using a mixed integer function created in Python. The authors of this thesis has researched the optimal number of machines needed to be procured to satisfy the future demand. Throughout this thesis 4 different numbers of machines (4-5-6-7 machines) are going to be analyzed over 4 different production demands, this will create 16 different scenarios of data which will be analyzed to make a the investment decision. The comparison shows that using 6 machines allows for an advantage in terms of total machine run-time when compared to other scenarios. The majority of scenarios shows that there is a decline of around 50% compared to 4 machines and 68% compared to 5 machines. also, the overall change-over time during 6 machines is reduced. Therefore, it demonstrates that production alignment is well-organized while using 6 machines. Hence, purchasing 6 machines will be beneficial because it would allow Mark Bric to achieve a more efficient output.