Lean Approach to Spare Parts Management in a Food Production Company: A Case Study

In a world increasingly driven by competition between companies, where profit constitutes the ultimate determinant of an organisation’s survival, it becomes essential to optimise production processes to reduce waste and inefficiencies. Within this context, Lean methodologies emerge as indispensable instruments to enhance the overall productivity of organisations. A critical domain where Lean principles can be effectively applied is equipment maintenance, whose primary objective is to ensure system reliability and prevent production downtime. Within maintenance management, the optimisation of spare parts management plays a fundamental role in sustaining operational continuity and efficiency. This study addresses this specific aspect, focusing on the application of Lean tools to improve spare parts management in an industrial pasta production line. The implemented approach involved the development and integration of a Kanban-based cataloguing system for the existing spare parts inventory. This system facilitated the elimination of obsolete components and significantly improved the speed and accuracy with which workers could identify and retrieve spare parts. Furthermore, the collected data supported a detailed risk analysis of each spare part, enabling the prioritisation of critical components and the optimisation of stock levels. The applied methodology demonstrated tangible results, achieving a total cost saving of €45,445. In subsequent stages of improvement, a software tool was developed to centralise and manage information related to each spare part and its corresponding equipment. This digital integration represented a significant advancement, as it provided warehouse personnel with real-time access to inventory status and allowed maintenance teams to quickly identify and allocate the correct spare parts during equipment failures. Collectively, these developments contributed to enhanced maintenance responsiveness, reduced downtime, and improved overall equipment reliability. Overall, this study contributes to the literature by proposing and validating an integrated Lean-based framework for spare parts management that goes beyond traditional qualitative applications. Unlike existing studies that address isolated Lean tools, the proposed approach combines Kanban-based cataloguing, quantitative risk assessment, Failure Mode and Effects Analysis (FMEA), and digital integration between spare parts and equipment. The proposed methodology is also structured to be replicable and adaptable to other industrial contexts facing high capital immobilization in spare parts.

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Journal
Journal of Mechanical Engineering and Manufacturing
Published
2026-04-23
DOI
https://doi.org/10.53941/jmem.2026.100017
Primary Topic
Forecasting Techniques and Applications
Type
article
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article

Lean Approach to Spare Parts Management in a Food Production Company: A Case Study

Ana Júlia Viamonte, Isabel Figueiredo, Isabel Mendes Pinto, Alexandra Gavina et al.
Journal of Mechanical Engineering and Manufacturing
Forecasting Techniques and Applications
article

Lean Approach to Spare Parts Management in a Food Production Company: A Case Study

Ana Júlia Viamonte, Isabel Figueiredo, Isabel Mendes Pinto, Alexandra Gavina, Marlene Ferreira Brito, Raul D. S. G. Campilho, David Almeida
article en

Abstract

In a world increasingly driven by competition between companies, where profit constitutes the ultimate determinant of an organisation’s survival, it becomes essential to optimise production processes to reduce waste and inefficiencies. Within this context, Lean methodologies emerge as indispensable instruments to enhance the overall productivity of organisations. A critical domain where Lean principles can be effectively applied is equipment maintenance, whose primary objective is to ensure system reliability and prevent production downtime. Within maintenance management, the optimisation of spare parts management plays a fundamental role in sustaining operational continuity and efficiency. This study addresses this specific aspect, focusing on the application of Lean tools to improve spare parts management in an industrial pasta production line. The implemented approach involved the development and integration of a Kanban-based cataloguing system for the existing spare parts inventory. This system facilitated the elimination of obsolete components and significantly improved the speed and accuracy with which workers could identify and retrieve spare parts. Furthermore, the collected data supported a detailed risk analysis of each spare part, enabling the prioritisation of critical components and the optimisation of stock levels. The applied methodology demonstrated tangible results, achieving a total cost saving of €45,445. In subsequent stages of improvement, a software tool was developed to centralise and manage information related to each spare part and its corresponding equipment. This digital integration represented a significant advancement, as it provided warehouse personnel with real-time access to inventory status and allowed maintenance teams to quickly identify and allocate the correct spare parts during equipment failures. Collectively, these developments contributed to enhanced maintenance responsiveness, reduced downtime, and improved overall equipment reliability. Overall, this study contributes to the literature by proposing and validating an integrated Lean-based framework for spare parts management that goes beyond traditional qualitative applications. Unlike existing studies that address isolated Lean tools, the proposed approach combines Kanban-based cataloguing, quantitative risk assessment, Failure Mode and Effects Analysis (FMEA), and digital integration between spare parts and equipment. The proposed methodology is also structured to be replicable and adaptable to other industrial contexts facing high capital immobilization in spare parts.

Journal of Mechanical Engineering and Manufacturing
Institute of Mechanical Engineering and Industrial Mangement (PT), Laboratório Associado de Energia, Transportes e Aeronáutica (PT), Polytechnic Institute of Porto (PT)
Openalex Percentile: Top 10%
Forecasting Techniques and Applications
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