Implementation of Waste Assessment Matrix for Productivity Improvement in an Automotive Industry

Jahanzaib Jamil and Syeda Marya Zaidi
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Jahanzaib Jamil: B.E in Industrial and Manufacturing from NED University of Engineering and Technology, Karachi, Master of Engineering Management (MEM) from NED University of Engineering and Technology, Karachi
Syeda Marya Zaidi: B.E in Industrial and Manufacturing from NED University of Engineering and Technology, Karachi, Master of Engineering Management (MEM) from NED University of Engineering and Technology, Karachi

Bulletin of Business and Economics (BBE), 2024, vol. 13, issue 2, 1139-1145

Abstract: Lean system is a philosophy which targets in elimination of waste so as to enhance productivity and efficiency. The automotive firms aims to streamline production to enhance efficiency. The current research address a contemporary industry problem relevant to a practice-based case study along with coming up with appropriate rationale and creative problem-solving solutions to the problems being faced by an automotive industry in Pakistan. There were numerous issues occurring in the Assembly shop of the plant such as defects, longer lead times, and excess inventory etc. delaying the overall production. Based on these industry problems, this research is conducted by adopting the methodology of Waste Assessment Model (WAM). The waste assessment matrix, which is the foundation of this study, is used in this paper to detect various waste types in the assembly shop of an automotive plant to increase industrial production. This method helps in analyzing the relative significance of different kinds of wastes. Other lean tools, such as layout improvement are then utilized as creative solutions for improving the wastes. Results demonstrate that not only lead time, inventory, transportation and wastes are reduced but the accessibility and performance of the plant are likewise enhanced.

Keywords: Emotional Intelligence; Academic Achievement; personal development; well-being (search for similar items in EconPapers)
Date: 2024
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