An improved stochastic programming model for supply chain planning of MRO spare parts

Li, Ling; Shen, Weiming; Cheng, Guoqing

doi:10.1016/j.apm.2017.03.031

Cited by 23 publications

(11 citation statements)

References 32 publications

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“…49 Those studies share the similar finding that the firms are able to reduce the inventory cost with a slight loss in the service level by optimizing the maintenance and spare parts inventory policies jointly. Authors also connect the inventory level with other decisions in MRO, such as the spare parts allocation, 24 production quantity 50 and the date of parts’ order. 51 Li et al 50 develop a stochastic programming model for SC planning of MRO spare parts.…”

Section: Pssc Management Decisions and Modelling Techniquesmentioning

confidence: 99%

“…Authors also connect the inventory level with other decisions in MRO, such as the spare parts allocation, 24 production quantity 50 and the date of parts’ order. 51 Li et al 50 develop a stochastic programming model for SC planning of MRO spare parts. However, this investigation fails to incorporate the user’s benefits when minimizing the cost of the distribution, production costs and the storage.…”

Section: Pssc Management Decisions and Modelling Techniquesmentioning

confidence: 99%

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Status review and research strategies on product-service supply chain

Elomri

Zhang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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This study draws a holistic view of the supply chain with three service strategies – namely, after-sales service; maintenance, repair and operations; and the product-service system – by analysing over 71 articles in this field. In this investigation, the content analysis is used to scrutinize the research to establish the knowledge, reveal the research opportunities and propose research strategies. The supply chain for product-service system depends more heavily on the implementation of the cooperation, collaboration and integration principles in operation. However, a complete analysis reveals that those crucial principles did not embody in current literature. Current research also failed to discuss the service operation decisions by modelling the intricate relations among them in a broad product-service supply chain context. Thus, the future research directions include developing service demand forecasting models; combining the time-series methods and the causal methods; establishing service resource planning models; addressing the relations between service deliverables, service capacity and the service resource; and strengthening the quantitative evaluation of the product-service supply chain performance with a systemic view. Moreover, by addressing the principles of cooperation, collaboration and integration, the added values of this review are the proposed research strategies for integrated forecasting of product services, integrated product-service resource allocation and scheduling, and systematic performance evaluation of the product-service supply chain. The findings and the proposed research strategies develop an in-depth understanding of product-service supply chain applications and serve as a basis for future research.

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Section: Pssc Management Decisions and Modelling Techniquesmentioning

confidence: 99%

Section: Pssc Management Decisions and Modelling Techniquesmentioning

confidence: 99%

Status review and research strategies on product-service supply chain

Elomri

Zhang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

show abstract

“…Table 1 shows the previous works, searched initially by us to investigate spare parts demand forecasting in various industries. Though the applications of spare parts demand forecasting have been made in different industries such as electronics [34], automobile [35], mining [11], maintenance/repair [36,37], consumer goods [38], aviation [39][40][41], energies [42], etc., those can be grouped into three according to their demand forecasting methods as shown in Table 1. Table 1, we could confirm that the prior works on spare parts demand forecasting have applied different methods to solve their specific problems in their industries.…”

Section: Reviews On Related Workmentioning

confidence: 99%

Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea

Choi¹,

Suh²

2020

Sustainability

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In a weapon system, the accurate forecasting of the spare parts demand can help avoid the excess inventory, leading to the efficient use of budget. It can also help develop the combat readiness of the weapon system by improving weapon system utilization. Moreover, as performance-based logistics (PBL) projects have recently emerged, the accurate demand forecasting of spare parts has become an important issue for the PBL contractors as well. However, for the demand forecasting of spare parts, the time series methods, typically used in the military sector, have low prediction accuracies and the PBL contractors are mostly based on the judgment of practitioners. Meanwhile, most of the previous studies in the military sector have not considered the managerial characteristics of spare parts (e.g., reparability and the irregularity of maintenance). No previous work has considered any such features, which can indicate the reliability of spare parts (e.g., mean time between failures (MTBF)), although they can affect the spare parts demand. Therefore, to develop a more accurate forecasting of the spare parts demand of military aircraft, we designed and examined a systematic approach that uses data mining techniques. To fill up the research gaps of related works, our approach also considered the managerial characteristics of spare parts and included the new features that represent the reliability of spare parts. Consequently, given the case of South Korea and the full feature set, we found random forest gave better results than the other data mining techniques and the conventional time series methods. Using the best technique Random Forest, we identified the contribution of each managerial feature set to improving the prediction accuracy, and we found the reliability and operation environment are valuable feature sets in a significant way, so they should be collected, managed more carefully, and included for better prediction of spare parts demand of military aircraft.

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“…They introduced two new methods, i.e., deterministic mixed-integer LP models and fuzzy possibilistic-SP model to integrate CDC place and scheduling of car routing issue with various CDCs. Li et al [26] considered spare parts for maintenance, repair and operation (MRO) which are vital for machine operations and proposed an improved SP model for MRO spare parts supply chain planning. Before formulating the problem of concern, we realized that under distinct situations, all previous work was formulated for the problem of production and transportation.…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation and optimization of multi-objective capacitated stochastic transportation problem for gamma distribution

Gupta

Garg

Chaudhary

2020

Complex Intell. Syst.

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The transportation problem in real life is an uncertain problem with multi-objective decision-making. In particular, by considering the conflicting objectives/criteria such as transportation costs, transportation time, discount costs, labour costs, damage costs, decision maker searches for the best transportation setup to find out the optimum shipment quantity subject to certain capacity restrictions on each route. In this paper, capacitated stochastic transportation problem is formulated as a multi-objective optimization model along with some capacitated restrictions on the route. In the formulated problem, we assume that parameters of the supply and demand constraints' follow gamma distribution, which is handled by the chance constrained programming approach and the maximum likelihood estimation approach has been used to assess the probabilistic distributions of the unknown parameters with a specified probability level. Furthermore, some of the objective function's coefficients are consider as ambiguous in nature. The ambiguity in the formulated problem has been presented by interval type 2 fuzzy parameter and converted into the deterministic form using an expected value function approach. A case study on transportation illustrates the computational procedure.

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An improved stochastic programming model for supply chain planning of MRO spare parts

Cited by 23 publications

References 32 publications

Status review and research strategies on product-service supply chain

Status review and research strategies on product-service supply chain

Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea

Parameter estimation and optimization of multi-objective capacitated stochastic transportation problem for gamma distribution

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