Application of value stream mapping in the automotive industry: A case study

• Main Authors: Shamsu Anuar, Mohamad Aqil, Mansor, M. A.
• Format: Article
• Language: English
• Published: Penerbit UMP 2022
• Subjects: TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery; TL Motor vehicles. Aeronautics. Astronautics
• Online Access: http://umpir.ump.edu.my/id/eprint/35680/1/Application%20of%20value%20stream%20mapping%20in%20the%20automotive%20industry.pdf; http://umpir.ump.edu.my/id/eprint/35680/; https://doi.org/10.15282/jmmst.v6i2.8561; https://doi.org/10.15282/jmmst.v6i2.8561
• Institution: Universiti Malaysia Pahang

Today, the automotive industry is becoming one of the essential industries in a country due to high demand from customers. This increasing demand also causes the companies in the manufacturing industry to be exposed to increasing challenges with respect to cost-effectiveness, lead time, and quality of production systems. This situation also increases the waste that occurs in the production line which is basically due to poor plant processes where excessive movement and the high processing time occur. From the previous research that the current method to detect waste is not effective where most methods do not fulfill the same framework, conditions, objectives, level, or degree of completion of detecting waste in the production line. In this paper, effort is made to detect non value added in automotive industry using VSM. VSM entails the mapping the industry current process and evaluating it for waste and bottleneck by calculating value-added and non-value-added time. The data was collected from incoming warehouse until the outgoing warehouse. The data is also taken during the observed component as it passes through the machining,painting, assembly,final assemby and final inspection processes. Based on the analysis of bottlenecks, solutions are suggested, and a future state map is created. The lead time of the process is improved by 67% where the waste is reduce to 74% based on created map.