Dimensioning of an automotive final assembly shop using a system of key performance indicators

All worldwide operating automobile manufacturers are on the constant search for the optimum between desirable flexibility on that one hand and required cost productivity on the other hand. In particular, the planning of a new final assembly shop of a car manufacturer is a big challenge since a huge number of influencing factors must be taken into consideration, so that in the end a best-practice final assembly shop with the desired attributes is created. To minimise the risk of bad planning, the length of time for the planning process should be shortened and at the same time the planning exactness should be improved with the help of new tools. This research project demonstrates that in the early stages of the planning process key performance indicators could be a proper instrument to achieve the the desired effects. Even if key performance indicators have been used in many areas of industry over several decades, this is the first research project which deals in this degree of accuracy with the dependencies between the different key performance indicators during the factory planning process for a new final assembly shop of a car manufacturer. Following the basic idea of 'System Thinking', numerous key performance indicators were linked to each other in an adaptable system of key performance indicators. During this research project, the developed model was successfully evaluated with four locations of the research partner BMW Group. Since the results are all between ± 20%, which is a sufficient exactness for this planning stage, there is great confidence that this general system of key performance indicators could also be important to other automobile manufacturers. The findings of this research project should serve as a basis for other researchers in this field to enhance the scarce theories about the dependencies. Besides, the software 'Powersim' and the chosen approach of 'System Thinking' doubtless can be transferred to other industrial areas with similar challenges.