Integration of Waste Assessment Model and Lean Automation to Improve Process Cycle Efficiency in the Automotive Industry

Setiawan Setiawan (1), Indra Setiawan (2), Choesnul Jaqin (3), Herry Agung Prabowo (4), Humiras Hardi Purba (5)
(1) Universitas Mercu Buana Jakarta, Indonesia,
(2) Universitas Mercu Buana Jakarta, Indonesia,
(3) Universitas Mercu Buana Jakarta, Indonesia,
(4) Universitas Mercu Buana Jakarta, Indonesia,
(5) Universitas Mercu Buana Jakarta, Indonesia

Abstract

Purpose: This study aims to improve Process Cycle Efficiency (PCE) by reducing waste in the assembly production line. This research is a case study conducted in a four-wheel vehicle manufacturing company to create a Lean production system.


Methodology/Approach: This study uses the Waste Assessment Model (WAM) and Lean Automation integration methods carried out by 5 expert judgements in the selected four-wheeled vehicle industry.


Findings: Based on the WAM method, this study found the biggest waste on the assembly line, namely transportation with a percentage of 20.44%. Improvements made with Lean Automation can increase the value of PCE from 56.76% to 63.62%.


Research Limitation/Implication: This research is limited to one model, namely Multi Purpose Vehicle (MPV). This research provides benefits for companies related to waste reduction. For similar companies, this research can be input for manufacturing practitioners in improving manufacturing performance to compete in the global market. This Lean production can reduce manpower which has an impact on saving production costs.


Originality/Value of paper: This paper provides added value related to the application of Lean terminology which aims to improve industrial automation-based manufacturing companies.

References

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Authors

Setiawan Setiawan
setiawan.fafa2@gmail.com (Primary Contact)
Setiawan, S., Setiawan, I. ., Jaqin, C. ., Prabowo, H. A. ., & Purba, H. H. . (2021). Integration of Waste Assessment Model and Lean Automation to Improve Process Cycle Efficiency in the Automotive Industry. Quality Innovation Prosperity, 25(3), 48–64. https://doi.org/10.12776/qip.v25i3.1613

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