An intuitionistic fuzzy linear mathematical model to determine the hybrid manufacturing system’s optimal operation condition

Dinler, Esra; Atalay, Kumru Dıdem; İç, Yusuf Tansel

doi:10.1016/j.engappai.2023.106519

Cited by 3 publications

(2 citation statements)

References 29 publications

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“…Assid et al [17] Return Stochastic model Simulation and Software Giri and Masanta [21] Return Yield EOQ Simulation and Software Liu et al [23] Demand and Return Mixed-integer nonlinear model Simulation and Software Shi [32] Return Yield Stochastic dynamic programme Simulation and Software Spengler [34] Return Yield Generic system dynamic model Simulation and Software Ronzoni et al [35] Demand Dynamic programming Simulation and Software Ponte et al [36] Demand and Return Nonlinear equation Simulation and Software Dominguez et al [37] Return Yield Multiagent-based simulation Simulation and Software Wang et al [38] Demand and Return Stochastic model Simulation and Software Li et al [40] Demand Quadratic cost function Simulation and Software Dinler et al [42] Multi-uncertainties Fuzzy linear mathematical model Simulation and Software Shafiee et al [43] Multi-uncertainties Stochastic mixed-integer programming Genetic Algorithm…”

Section: References Uncertainty Type Modelling Technique Solution App...mentioning

confidence: 99%

“…They designed a stochastic dynamic programming problem with different alternatives so that the total expected costs for inventory holding, shortage and purchasing can be minimised. To show financial value and decide whether to use used parts in remanufacturing systems, an intuitionistic fuzzy linear mathematical model was created [42]. Consequently, Shafiee et al [43] explored a stochastic environment of reverse supply chain with many facilities and multiple products.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Mat Ropi,

Hishamuddin,

Wahab

et al. 2023

Mathematics

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Remanufacturing is one of the ways forward for product recovery initiatives and for maintaining sufficient production flow to satisfy customer demand by providing high-quality goods with a combination of new and return parts through a circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chains vulnerable to disruptions. One of the main disruptions that occurs in remanufacturing systems is the shortage of spare parts supply, which results in unexpected delays in the remanufacturing process and could eventually result in a possible loss of sales. In the event of such potential disruptions, remanufacturing facilities must manage their supply chains in an effective and optimal manner such that the negative impact of disruptions to their business can be minimised. In this study, a two-stage production–inventory system was analysed by developing a cost-minimisation model that focuses on the recovery schedule after the occurrence of a disruption in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch-and-bound algorithm, where the experimental results demonstrated that the model provides effective solutions. Through numerical experiments, results indicated that the optimal recovery schedule and the number of recovery cycles are considerably dependent on the disruption time, lost sales and backorder costs. A sensitivity analysis showed that the lost sales option seems to be more effective than the backorder sales option in optimising the system’s overall cost due to unmet demand, which becomes lost sales when serviceable items are reduced, thereby shortening recovery time. Furthermore, a case study revealed that a manufacturer’s response to disruption is highly influenced by the spare part costs and overall recovery costs as well as the supplier’s readiness level. The proposed model could assist managers in deciding the optimal production strategy whilst providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

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Section: References Uncertainty Type Modelling Technique Solution App...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Mat Ropi,

Hishamuddin,

Wahab

et al. 2023

Mathematics

View full text Add to dashboard Cite

show abstract

Triangular intuitionistic fuzzy number based backorder and lost sale in production, remanufacturing and inspection process

Sugapriya,

Saranyaa,

Nagarajan

et al. 2024

Expert Systems with Applications

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A multi-objective integrated scheduling of remanufacturing system considering time window constrained outsourcing option

Guo,

et al. 2024

Journal of Cleaner Production

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An intuitionistic fuzzy linear mathematical model to determine the hybrid manufacturing system’s optimal operation condition

Cited by 3 publications

References 29 publications

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Triangular intuitionistic fuzzy number based backorder and lost sale in production, remanufacturing and inspection process

A multi-objective integrated scheduling of remanufacturing system considering time window constrained outsourcing option

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