Multi-criteria Classification for Spare Parts Management: A Case Study

Teixeira, Catarina; Lopes, Isabel da Silva; Figueiredo, Manuel

doi:10.1016/j.promfg.2017.07.295

Cited by 24 publications

(10 citation statements)

References 22 publications

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“…Labib (2011) also investigated the power of the AHP by comparing its performance to fuzzy logic to solve the problem of selecting a spare parts supplier. In a similar application, Antosz and Chandima Ratnayake (2016) and Teixeira et al (2017) performed case studies where they produced a scoring technique for the significance of spare parts based on relevant criteria. Moreover, Chaklar et al (2016) developed a multi-criteria decision methodology, which they applied to the classification of spare parts for optimized inventory management.…”

Section: Literature Reviewmentioning

confidence: 99%

On the optimization of maintenance storage cost in industry a fuzzy logic application

Khalil

Labib

2021

IJQRM

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PurposeThe purpose of this paper is to construct a fuzzy logic model that acts as a decision support system to minimize inventory-related costs in the field of industrial maintenance. Achieving a balance between the unavailability and over-storage of spare parts is a problem with potentially significant consequences. That significance increases proportionally with the ever-increasing challenge of reducing overall cost. Either scenario can result in substantial financial losses because of the interruption of production or the costs of tied-up capital, also called the “solidification of capital.” Moreover, there is that additional problem of the expiry of parts on the shelf.Design/methodology/approachThe proposed approach relies on inputs from experts with consideration for incompleteness and inaccuracy. Two levels of decision are considered simultaneously. The first is whether a part should be stored or ordered when needed. The second involves comparing suppliers with their batch-size offers based on user-determined criteria. A mathematical model is developed in parallel for validation.FindingsThe results indicate that the fuzzy logic approach is accurate and satisfactory for this application and that it is advantageous because of its limited sensitivity to the inaccuracy and/or incompleteness of data. In addition, the approach is practical because it requires minimal user effort.Originality/valueTo the best of the authors’ knowledge, the exploitation of fuzzy-logic altogether with limited sensitivity experts' inputs were never combined for the solution of this particular problem; however, this approach's positive impact is expected to be highly significant in solving a chronic problem in industry.

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Section: Literature Reviewmentioning

confidence: 99%

On the optimization of maintenance storage cost in industry a fuzzy logic application

Khalil

Labib

2021

IJQRM

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“…Por vezes, o item defeituoso é enviado para reparo e, posteriormente, retorna tão bom quanto novo ao estoque de peças sobressalentes (Almeida, 2001. O desafio da gestão é decidir sobre a conveniência econômica na detenção e controle do estoque de um item específico, pois existe o risco de aumento de estoques e, consequentemente, custos excessivos de armazenamento. Uma prática comum para um gerenciamento de inventário eficaz é agrupar as peças de sobressalentes de acordo com algum método de classificação (Hu et al, 2018) 2.2 Criticidade de peças sobressalentes Teixeira et al (2017) consideram que a classificação de peças sobressalentes é um passo relevante para orientar todo o processo de gerenciamento, e muitas vantagens podem ser obtidas pela classificação adequada. Segundo Huiskonen ( 2001) e Molenaers et al (2012), existem dois tipos de critérios para classificar a criticidade de peças sobressalentes: a criticidade do processo -se a sua falha ou mau funcionamento resultar em graves consequências para a planta, como por exemplo, consequências relacionadas à perda de vidas, contaminação ambiental ou perda de produção -e criticidade de controle -uma peça sobressalente é considerada crítica se a possibilidade de garantir a disponibilidade imediata da peça for difícil de controlar.…”

Section: Manutenção E a Gestão De Peças Sobressalentesunclassified

Avaliação de criticidade de peças sobressalentes utilizando o método Analytic Hierarchy Process com ratings

Silva

Hernández

Brandalise

2019

S&G

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Peças sobressalentes importantes devem ser mantidas em estoque e seu inventário devidamente controlado para substituir componentes desgastados e/ou defeituosos por novos e minimizar os tempos de inatividade nas diversas atividades de manutenção. No entanto, a posse de peças sobressalentes em estoque para uma pronta disponibilidade (quando são necessárias) pode implicar, em caso de peças dispendiosas e raramente usadas, altos custos de retenção de estoques. Neste trabalho, é apresentada uma abordagem de avaliação da criticidade de peças sobressalentes utilizando o método AHP com o uso de ratings (Analytic Hierarchy Process Ratings Model). A estrutura da hierarquia de decisão elaborada relaciona-se às consequências causadas pela falha de um sobressalente no processo, no caso de uma substituição não estar prontamente disponível com atributos de demanda e suprimentos, segmentando as prioridades pelos critérios Vital, Essencial e Desejável (VED). O modelo proposto foi aplicado em peças sobressalentes de baixíssimo giro de uma organização integrante de uma empresa de capital intensivo, situada no Sul Fluminense, utilizando o procedimento de Saaty para a definição de prioridades por meio do software de livre acesso Super Decisions, permitindo a priorização das peças a serem estocadas e o estabelecimento de políticas de gestão diferenciadas para cada classe.

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“…Indonesia spare parts company used this technique for its inventory classification and as a result, increased its inventory turnover ratio and decreased its inventory cost [35]. Management of stock by accurate demand forecasting and stock classification is important for an organization to maximize profit and reduce cost [36]. The purpose of the ABC analysis in this research is:…”

Section: Introductionmentioning

confidence: 99%

Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment

et al. 2020

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This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A (Q, r) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The (Q, r) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization.

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Multi-criteria Classification for Spare Parts Management: A Case Study

Cited by 24 publications

References 22 publications

On the optimization of maintenance storage cost in industry a fuzzy logic application

On the optimization of maintenance storage cost in industry a fuzzy logic application

Avaliação de criticidade de peças sobressalentes utilizando o método Analytic Hierarchy Process com ratings

Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment

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