Improving the performance of assembly line: Review with case study

Abstract

Context: Continuous Improvement in manufacturing to attain manufacturing excellence is today's requirement. It gives cutting edge over the competitors. This has developed lot of interest for the researchers during the last few years. Vehicle Assembly Line being the most complex Assembly line has been active area of research over years and has attracted many researchers. Objective: This paper systematically identifies and unfolds the important parameters by systematic review. Goal of this Research is to develop a novel classification of literature on Assembly Line and to improve the performance of vehicle assembly line using Lean implementation and Simulation approach. Methodology: Total of 116 referred journal articles in the domain of Vehicle assembly are reviewed here. Data is sourced from 40 publications, majority of which includes Elsevier, IEEE, and Springer. Further a mathematical model is developed considering the effect of number of resources, Break time, Downtime of machines and Absenteeism. A real world case study is done for a period of one year in a reputed vehicle assembly manufacturing plant. Results: Analysis of research on Assembly Line Balancing and optimization within many different industrial scenarios has been done her. This paper contributes to existing domain by classifying and comparing the means for input data, constraints and methodology used. It has been classified into five heads. A real world case study is done in reputed Company. Cycle time was reduced from 110 seconds to 100 seconds. Conclusion: It is difficult to perform the experiments like Design of Experiments (DOE) in complex manufacturing systems. Simulation allows us to test different concepts, various options without having to build prototypes. A case study done in Vehicle assembly shows the importance of Simulations to improve its performance measures. Limitations of the Research: The research does not completely optimize the production parameters. It improves the production system performance significantly.