Analysis of long-term impact of maintenance policy on maintenance capacity using a time-driven activity-based life-cycle costing

• Autor(a) principal: Duran, Orlando
• Data de Publicação: 2020
• Outros Autores: Afonso, Paulo, Minatogawa, Vinicius
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/71832
• topic: Time-Driven Activity-Based Costing (TDABC); Life-Cycle Costing (LCC); Maintenance costs; Capacity analysis; Economic sustainability; Mining industry; Engenharia e Tecnologia::Outras Engenharias e Tecnologias; Science & Technology

In capital-intensive industries, physical assets and maintenance activities play a relevant and strategic role in terms of providing operational continuity and business sustainability. As a result, maintenance support structures are highly complex and sophisticated. Therefore, maintenance capacity planning must be addressed using reliable techniques to assure the adequate service levels and availabilities of critical assets at the minimum opportunity cost. There has been relatively limited research on how to determine and optimize the maintenance support structure (human resources) in such organizations. This paper proposes a novel technique for dimensioning and optimizing maintenance capacity that combines Time-Driven Activity-Based Costing and Life-Cycle Costing with the Weibull function-based reliability model. Following the main principles of the Design Science Research we propose a sophisticated but simple artifact. Through this model, it is possible to compute maintenance costs and assess both used and idle capacities, considering the behavior over time of the failure rates and the reliability of critical assets within a plant. To demonstrate how the proposed methodology addresses the problem, the model was applied in a real medium-sized Chilean comminution plant and a sensitivity analysis was performed, particularly, to evaluate the relevance of appropriate maintenance workforce planning.