Development and comparison of two new multi-period queueing reliability models using discrete-event simulation and a simulation–optimization approach

Frichi, Youness; Jawab, Fouad; Aboueljinane, Lina; Boutahari, Said

doi:10.1016/j.cie.2022.108068

Cited by 17 publications

(3 citation statements)

References 56 publications

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“…OptQuest is oriented toward optimizing a simulation model, i.e. a simulation model is established for a given system, and then, OptQuest is used to optimize the control parameters of the system (Frichi, 2022). It is an optimization add-on for Arena to optimize the control variables of the simulated systems (Borodin et al , 2019).…”

Section: Proposed Methodologymentioning

confidence: 99%

A study of the operator assignment problem in powder-coating processing using simulation optimization

Yang

Wang

Kuo

2023

RIA

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Purpose The main operations of the powder-coating process are staggered along a closed-loop conveyor. Given the volatile market demands, using a fixed level of staffing may result in significant productivity losses. The present study aims to capture stochastic behavior and optimize operator assignment problems in a practical powder-coating process. By using the proposed methodology, when demand changes, the optimal operator assignment configuration can be provided, ensuring high labor productivity. Design/methodology/approach The powder-coating process is an important industrial application and is often a labor-intensive system. The present study adopts a practical case to optimize its staffing level. Because of its operational complexity, the problem is solved by a proposed simulation-optimization approach. The results are promising, and the proposed methodology is shown to be an effective approach. Findings The proposed methodology was tested for various demand levels. The optimized operator assignment configuration always improves on the performance of other staffing levels. Given the same daily throughput, the optimized operator assignment configuration can improve performance by as much as 19%. In scenarios where there is increased demand, the resulting reduction in overtime work improves performance by between 20.33% and 56.72%. In scenarios where there is reduced demand, the optimized staffing level produces improvements between 3.13% and 50%. Compared with the fixed staffing policy of the case company, the flexible staffing policy of the proposed methodology can maintain high labor productivity across demand variations. The results are consistent with the Shojinka philosophy of the Toyota Production System. Originality/value This study proposes a solution to the operator assignment decision in a labor-intensive manufacturing system – a powder-coating processing system. Powder coating provides a solid powder coating without any solvent. Because of its excellent application performance and environmental protection, it is widely used in the field of metal coating, especially appliances for offices and homes. Most of the existing literature has solved the problem by making unrealistic assumptions. The present study proposes a simulation-optimization method to solve a practical problem in powder-coating processing. The effectiveness of the proposed methodology is illustrated by a practical application. According to the experimental results, five operators can be saved for the same daily throughput. An average of 35 and 19 min of overtimes can be saved when demand increases by 10% and 20% with one less operator; between 2 and 16 operators can be saved when demand falls by 10%–60%.

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Section: Proposed Methodologymentioning

confidence: 99%

A study of the operator assignment problem in powder-coating processing using simulation optimization

Yang

Wang

Kuo

2023

RIA

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“…DES, which is widely acknowledged for its effectiveness in analyzing complex flows that are crucial in simulations, is particularly skilled in assessing potential scenarios at critical decision points [32]. The advantages of DES contribute to its wide range of applications in various fields, including logistics, healthcare, disaster management, and manufacturing [31,32,33,34].…”

Section: Discrete Event Simulationmentioning

confidence: 99%

A Predictive Discrete Event Simulation for Predicting Operation Times in Container Terminal

Park,

Kim,

Bae

2024

IEEE Access

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Container terminals (CTs) play a crucial role within the global supply chain in the context of the global container transportation business. The primary obligation associated with these terminals involves ensuring the punctual execution of primary vessel operations, while strictly adhering to the Estimated Time of Departure (ETD) for vessels. To accomplish this goal, it is crucial to develop rigorous and exact operating strategies. Nonetheless, the accurate prediction of operation times in CT presents a significant challenge due to the concurrent involvement of various Container Handling Equipment (CHE) and the occurrence of unforeseen situations. To address this issue, this study proposes a novel approach called Predictive Discrete Event Simulation (PDES) that utilizes data collected from CT to predict the operation times. The PDES is an advanced approach that builds upon the widely used Discrete Event Simulation (DES) technique in the field of simulations. It is specifically designed to provide precise predictions of the operation times in CTs, where multiple events take place concurrently. The PDES in this paper aims to overcome the shortcomings of current simulation-based approaches for prediction in CT. These approaches often rely on predefined task sequences and assumed time for job handling time of CHE in their scenarios, which can result in reduced accuracy when predicting operation times. Through the resolution of these issues, the proposed PDES exhibits the capacity to improve predictive performance. To enhance the predictive performance of operation times in CTs through PDES, two approaches are introduced. The first approach entails the application of Support Vector Machine (SVM) algorithms for the purpose of predicting operation times. This approach is further augmented by integrating it with DES to improve the accuracy of predictive performance. The second approach involves predicting by simulating real-world operational scenarios in CTs using algorithms for CHE assignment. The predictive performance of the proposed PDES is assessed through the utilization of data gathered from Busan Port Terminal (BPT) in South Korea, demonstrating superior performance compared to alternative prediction approaches.

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“…The model developed by Frichi et al. [3] considers a variable reliability α m ranging from α 1 =1% to α 90 =90%. For this model, the number

of ambulances of type k required by demand area i during period t for α m reliable coverage ( α 1 =1%, …; α 90 =90%) is provided in Table 16 .…”

Section: Data Descriptionmentioning

confidence: 99%

Dataset on optimizing ambulance deployment and redeployment in Fez-Meknes region, Morocco

2022

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Development and comparison of two new multi-period queueing reliability models using discrete-event simulation and a simulation–optimization approach

Cited by 17 publications

References 56 publications

A study of the operator assignment problem in powder-coating processing using simulation optimization

A study of the operator assignment problem in powder-coating processing using simulation optimization

A Predictive Discrete Event Simulation for Predicting Operation Times in Container Terminal

Dataset on optimizing ambulance deployment and redeployment in Fez-Meknes region, Morocco

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