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2 Journal of Achievements in Materials and Manufacturing Engineering

2 2024

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Raw material management for rubber parts manufacturing supply chain using the LPSC model

Klaidaeng C., Butdee S., Boonmee K-o.

Journal of Achievements in Materials and Manufacturing Engineering

2024

Vol. 123, nr 1

25--32

Purpose: The paper proposes a new raw material cost management concept in the rubber parts supply chain using the Linear Programming Sharing Cost (LPSC). Rubber parts are widely used in the auto parts industry. There are a variety of product models and material types as well as produced by several subcontractors in the 2nd Tier companies. However, the whole chain controls overall cost management as the 1st Tier company. Cost-effective models are more important in the competitive era. Design/methodology/approach: The research methodology combined linear programming (LP) with sharing cost (SC) and was applied to inventory management. The LPSC model is developed to deal with Tier 1 companies linked with Tier 2 companies of the subcontractors. The LPSC is combined with the EOQ inventory management model. Findings: A new approach has been developed to reduce the cost of raw material management in the rubber part supply chain. Research limitations/implications: The limitation of the model development is that it does not yet have real-time control of the supply chain management system. Practical implications: The conceptual idea was introduced to Thailand's automotive rubber part supply chain and accepted for testing with the pilot test of actual orders. Originality/value: The paper presents the new conceptual raw material cost management model in the automotive rubber part supply chain. The LPSC combined with EOQ is effective, increases value to the supply chain, and simultaneously reduces waste and overproduction.

Prediction of the process capability for compression rubber part forming in the automotive supply chain

Butdee S., Tangchaidee K.

Journal of Achievements in Materials and Manufacturing Engineering

2024

Vol. 124, nr 2

78--85

Purpose: The paper proposes predicting production process capability for the compression rubber part in automotive supply chain management. Delivery of parts to tier 1 and OEM on time is the most important part of supply chain management, together with the delivery of on-quality and on-cost control to maintain the competitiveness of the supply chain. There are many suppliers to produce many automotive parts for tier 1. Therefore, the simulation approach properly predicts and prevents the process from getting into trouble during the actual production time. Production process quality control is critical to ensure that the good quality of the parts purchased can be delivered on time. Rubber parts are used widely in automotive, motorcycles, trucks, and other types of vehicles, with small sizes but in huge quantities to support general OEM brands and specific parts. The rubber part manufacturing process is complex and uncertain with compression moulding and rubber curing conditions. Therefore, good conditions can predict the production process's capability to commission and deliver on schedule. Design/methodology/approach: A neuro-fuzzy system is adopted and developed to deal with the uncertain process capability under multi-criteria decision-making. Findings: The methodology development can be used in the actual rubber part manufacturing supply chain environment and can predict uncertain problems that might occur in the subcontractor factories. Research limitations/implications: The prediction of the production process capability of the rubber part supply chain might be more effective on the real-time monitoring control system and can be tracking location part progress for further planning both success or rescheduling. Practical implications: The platform can be applied to audit and test the actual industrial supply chain, and problem and research questions are brought about from the real supply chain in the local country. Originality/value: The methodology development was originally created for the particular supply chain in rubber automotive parts that can replace the existing system to obtain a more efficient performance evaluation process.