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Enhancing the productivity of mould shop using continuous improvement tools and simulation

Publication Type : Journal Article

Publisher : Informa UK Limited

Source : International Journal of Systems Science: Operations & Logistics

Url : https://doi.org/10.1080/23302674.2024.2425014

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2024

Abstract : In today’s competitive manufacturing environment, enhancing productivity and operational efficiency is crucial for companies to meet the rising customer demands and expectations driven by recent technological advancements. This study presents a case of productivity enhancement in mould shop manufacturing, which was experiencing bottlenecks and non-value-added (NVA) activities, leading to inefficiencies that limit the throughput. A Discrete Event Simulation (DES) model is developed for the mould shop considering the major components such as Hub, Mainframe, and Planet Carrier. Bottleneck resources are identified from the DES model. The validation of the simulation results is carried out using Pareto analysis. Root Cause Analysis (RCA) and Five Whys (5-Why) analysis are used to brainstorm the causes that lead to lower productivity. Time-reduction strategies using the Theory of Inventive Problem Solving (TRIZ) improved the throughput. The improvements are incorporated into the DES model, and updated results are obtained. As a result, throughput for the hub improved by 60% for the hub, 40% for the mainframe, and 55.88% for the planet carrier. These results show how integrating continuous improvement tools with simulation models enables streamlining operations and substantially increases productivity. The scenario reveals that Lean principles successfully overcome real-world manufacturing problems.

Cite this Research Publication : M. Thenarasu, S. Sakthi Balaji, A. Sumesh, M.S. Narassima, K. Rameshkumar, Erfan Babaee Tirkolaee, Enhancing the productivity of mould shop using continuous improvement tools and simulation, International Journal of Systems Science: Operations & Logistics, Informa UK Limited, 2024, https://doi.org/10.1080/23302674.2024.2425014

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