Optimizing JIT production and maintenance strategies for material management in the presence of quality decline and random demand fluctuations

• Published in: Acta logistica 2024-06, Vol.11 (2), p.281-292
• Main Authors: Rivera-Gomez, Hector, Sanchez-Partida, Diana, Ortega-Reyes, Antonio, Gonzalez-Hernandez, Isidro
• Format: Article
• Language: English
• Subjects: Context; Control theory; Cost analysis; Cost control; Critical components; Defective products; Hedging; Inventory; Maintenance; Manufacturing; Materials handling; Materials management; Mathematical models; Optimal control; Optimization; Performance evaluation; Preventive maintenance; Process parameters; Product quality; Production management; Production planning; Quality control; Remanufacturing; Scheduling; Supply chains
• ISSN: 1339-5629; 1339-5629
• DOI: 10.22306/al.v11i2.511

Material management is a critical component of any organization, as it encompasses the efficient and effective handling of materials throughout the entire supply chain process. Just-in-time (JIT) strategies play a vital role in streamlining the supply chain process and minimizing waste. The paper examines the optimization of JIT production management, quality, and maintenance planning in the context of material management. An integrated model is proposed based on optimal control theory to formulate a set of innovative systems dynamics that consider quality decline in a stochastic context. The model also includes random demand fluctuations through a stochastic diffusion process. The objective of the model is to enhance company competitiveness by satisfying a service level constraint and jointly optimizing the JIT production and maintenance control parameters to minimize inventory levels and reduce the total cost. The findings reveal significant interactions between costs and control parameters of both JIT production and maintenance strategies due to their close relationship, leading to the conclusion that the development of an integrative model is more cost-efficient than managing them independently. A comparative analysis further enhances the study by highlighting the potential cost savings in implementing the suggested collaborative control strategy. Overall, the paper contributes to the literature on material management by addressing the research gap in the optimization of JIT production management, quality, and maintenance planning under a stochastic context.