Enhancing Production Process Performance in Traditional Shipyards: An Integrated Approach for Waste Identification and Performance Optimization

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
This research introduces an innovative approach to enhance efficiency and effectiveness in traditional shipyard production. It aims to identify and categorize various production waste types and propose performance optimization strategies. The approach integrates the PDCA-CR method with the Waste Assessment Model (WAM), Value Stream Mapping (VSM), and Value Stream Analysis Tool (VALSAT) to effectively categorize waste in ship production processes. Subsequently, waste analysis and performance optimization techniques, such as lean principles and process reengineering, are applied to improve identified processes, enhancing overall performance, productivity, and profitability. The study provides valuable insights into traditional shipbuilding production processes by identifying various waste types, including transportation, excess inventory, unnecessary movement, waiting times, overprocessing, overproduction, and product defects. This analysis enables shipyards to pinpoint areas for improvement and implement optimization methods to boost performance and profitability. While primarily focused on the shipyard industry, the approach''s applicability to other sectors should be explored, along with potential implementation challenges. Practically, it offers shipyards a tool to reduce inefficiencies and improve performance, ensuring competitiveness in the maritime industry. Socially, enhanced production processes can lead to job creation, economic growth, and industry development while promoting environmentally sustainable practices. In summary, this research presents a tailored integrated approach combining waste identification and performance optimization strategies for traditional shipyards, offering a comprehensive framework to enhance production process performance.
Language:
English
Published:
Journal of Optimization in Industrial Engineering, Volume:16 Issue: 35, Summer and Autumn 2023
Pages:
221 to 241
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