DEPRO - Departamento de Engenharia de Produção

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Browsing DEPRO - Departamento de Engenharia de Produção by Subject "Analytic hierarchy process"

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    A new combined spare parts classification method and acriticality analysis : an iron ore mining company study case.
    (2021) Muniz, Leandro Reis; Conceição, Samuel Vieira; Rodrigues, Lásara Fabrícia; Reis, Allexandre Fortes da Silva; Sousa Junior, Wilson Trigueiro de
    Spare parts are important to maintain mining operations, which made necessary the development of consolidated classification methods, to help in the decision-making process. The management of spare parts aims to reduce the unnecessary inactivity time arising from the component failures and represent a significant part of the total operational cost. A way to manage the inventory of these materials is its classification. This work presents a new spare parts categorization method based on multi-criteria classification for managing the spare parts inventory using the approaches cut-off point, XYZ, ABCD, Kraljič matrix, Analytical Hierarchical Process (AHP), and Bottom- up to categorize in the sectors of production, maintenance, and supply. The study was realized with real data from a mining company composed of 40,002 stored materials, and the results showed an abridgment of the management models. This new categorization contributes to the literature of spare parts inventory management, once there are few studies of practical applications in mining industries besides conducting a literature review regarding relevant criteria and methods used to classify spare parts.
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    Spare parts inventory management : a new hybrid approach.
    (2021) Muniz, Leandro Reis; Conceição, Samuel Vieira; Rodrigues, Lásara Fabrícia; Almeida, João Flávio de Freitas; Affonso, Tássia Bolotari
    Purpose – The purpose of this paper is to present a new hybrid approach based on criticality analysis and optimisation to deal with spare parts inventory management in the initial provisioning phase in the mining industry. Spare parts represent a significant part of mining companies’ expenditures, so it is important to develop new approaches to reduce the total inventory value of these items. Design/methodology/approach – This hybrid approach combines qualitative and quantitative methods based on VED (vital, essential and desirable) analysis, analytical hierarchical process (AHP), and e-constraint optimisation method to obtain the spare parts to be stocked. The study was applied to a large mining company. The mineral sector was chosen due to the great importance to the emerging Brazilian economy and the lack of researches in this sector. In addition, the spare parts have a relevant weight on the total inventory cost. Findings – Present a novel approach combining multi-objective optimisation and multi-criteria evaluation approaches to tackle the inventory decision in spare parts management. This work also defines and classifies relevant criteria for spare parts management in the mineral sector validated by specialists. The proposed approach achieves an average increase of 20.2% in the criticality and 16.6% in the number of items to be stocked compared to the historical data of the surveyed company. Research limitations/implications – This paper applies the proposed approach to a mining company in Brazil. Future research in other companies or regions should analyse the adequacy of the criticality criteria, hierarchy and weights adopted in this paper. Practical implications – The proposed approach is useful for mining industries that deal with a large variety of resource constraints as it helps in formulating appropriate spare part strategies to rationalise financial resources at both tactical and strategic levels. Originality/value – The paper presents a new hybrid method combining the AHP a multi-criteria decision making (MCDM) approach coupled with e-constraint optimisation to deal with spare parts inventory management allowing for a better spare parts inventory analysis in the initial provisioning phase and providing managers with a systematic tool to analyse the trade-off between spare parts criticality and total inventory value.