Analyzing early-stage production through discrete event simulation: A Case study at Magna Electronics Developing a simulation model to analyze the performance of a production line and evaluating its ability for decision making at an early stage

Sammanfattning

The highly competitive automotive industry, characterized with varying customerdemands and requirements puts pressure on manufacturing organization’s ability todevelop flexible and efficient production systems, particularity its early stage. MagnaElectronics Vårgårda production system is currently expanding and under constantdevelopment through the implementation of new production lines. Therefore, there is aneed to understand how system parameters effect performance of the production line inits early stage of development. Hence, the aim of this study is to investigate and analyzethe newly implemented production line CHA1 through the development of a discreteevent simulation (DES) model. More specifically, understand how DES can be used asa decision-making tool, evaluate the influence of overall equipment effectiveness anddirect labor cost as well as highlighting the challenges in this context. The methodologyof the study is based on the first nine stages of Banks simulation framework, whichwere divided into three phases. Within this framework, a literature review wasconducted in combination with a mixed method approach. The qualitative datacollection provided in-depth understanding of the production line through thecombination of interviews, observations and informal conversations. Whereas thequantitative data were collected through shop floor measurement and from the companydatabase, essential for input modeling and the development of the DES model. Theexperiments conducted through the DES model and the corresponding findings showedthat DES can be a useful tool to enhance decision making and evaluate performance inan early stage of production. However, the early stage contributed to several challengesregarding input data collection and a higher degree of simplifications and estimations,effecting the ability to develop a model with the highest possible accuracy.