Risk identification model for lean manufacturing improvement

• Main Authors: Mohd Hafizuddin Syah Bangaan Abdullah,, Mohd Nizam Ab Rahman,, Yin, Ruizhe
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2023
• Online Access: http://journalarticle.ukm.my/22770/1/17.pdf; http://journalarticle.ukm.my/22770/; https://www.ukm.my/jkukm/volume-3504-2023/

Small- and medium-sized manufacturing enterprises (SMEs) were confronted with a variety of difficulties due to the increasingly complex market environment, and many of them could not make enough profits to proceed with their manufacturing tasks. The objective of this study was to develop a model of risk management by integrating several risk tools at manufacturing companies. This study was also intended to improve the decision making by providing quantitative analysis at each step of risk management and improve lean practices. Risk quantitative analysis methods such as failure modes and effects analysis (FMEA) and multi-objective optimization on the basis of ratio analysis (MOORA) were applied in this study to identify the potential risks. Moreover, the risk assessment was used to categorize risks into different severity levels. The manufacturing data obtained from a case study was utilised to calculate the risk priority number (RPN). The risk mitigation actions were formulated to reduce the original RPN and the final RPN value decreased to a normal standard in the end. Overall, this study optimised the risk management of one case study SME and improved lean manufacturing practices. By establishing the risk identification model and applying common lean manufacturing concepts in reducing wastes at actual manufacturing processes, the manufacturing enterprise could manage to optimize the operations and increase the actual manufacturing productivity. The machining and assembly processes of diesel engines were optimized and improved with the decrease of RPN and the selection of the CK6150 CNC lathe that owns the highest MOORA assessment value.