Tool for Improving Operating Points in Multi Model Assembly Lines

Abstract

Manufacturing companies are facing highvariant diversities of their products. The degree of variant diversity increasesalongthe value chain. Hence, assembly is forced to deal with the highest diversity. These fluctuating workloads affect the utilization rate in multi model assembly lines. Thereby, constant cycle times lead to losses in time due to the model mix. Furthermore, losses can result from gaps between exact workloads and human capacities in the workstations.Optimal operating points are defined as the ideal combination of concurrent sub goals like utilization rate and throughput rate. The identification of such operating points for assembly lines with planned product sequences shows up as a task for capacity planning and line balancing. Several analytic line balancing methods were developed in the past aiming for instance at minimal cycle times. However, methods for operational decisions on cycle time and overall production capacity are still rare. Simulation methods show potential to fill this gap. They allow the modeling and simulation of specific and complex production systems. This paper describes a planning method and a simulative tool for the identification of optimal operation points. The aim of optimal operating points is a reduction of time losses due to the model mix.Based oncurrent approaches for simulative line balancing, a planning tool has been developed. Working with defined product sequences, thistool supports the variation of parameters like the cycle time. Effects on productivity and time losses can be analyzed. Optimal operating points can be identified. Furthermore, the tool can visualize specific product sequences with corresponding workloads during the shift. It supports staff decisions on improvements in production. Moreover, results can be used for decisions on staff planning and staff development. The tool has been validated by a case study in a truck assembly line.