An adaptive hybrid variable-large neighborhood search algorithm for profit maximization problem in designing production lines

Koyuncuoğlu, Mehmet Ulaş; Demir, Leyla

doi:10.1016/j.cie.2022.108871

Cited by 5 publications

(5 citation statements)

References 57 publications

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“…The efficiency and behavior of the approximate analytical methods proposed to calculate the performance indicators of long transfer lines and help in designing decision-making are of particular interest for long lines. The line design decision also considers the cost of the initial setup (capital) of the production line because the buffer (storage) is very expensive and can vary along the line [31,33]. This cost may even limit the desired production rate value of the production line [28].…”

Section: Additional Experimental Tests For Performance Indicators Of ...mentioning

confidence: 99%

“…Equation (17) emphasizes that the buffer value in each buffer area (Bi) is greater than or equal to 0, being also an integer. Similarly, the average inventory (𝑛 𝑖 ) for the ith buffer area is greater than or equal to 0 (Equation ( 18)) [14,33]. The C coefficient is set to 50N, and the hi cost coefficient is set to 1 for all additional tests (Massim et al [34]).…”

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

“…The mean effective service rate of Case 1 decreased from 0.9090 to 0.0909 for Case 4 and 30 lines with different reliability parameters were created with values in between (Figure 4). Considering 20 machines, 950 total buffer sizes, and C equal to 47500, the variation in performance indicators for 30 different lines with a uniform (equal), ascending, and descending order distribution of buffer values (buffer configuration) along the line [33,35] is presented. …).…”

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

“…After examining the effect of a uniformly distributed buffer configuration on system behavior, the study also examined the effects of different buffer configurations on profit. To do that, two different buffer configurations were generated [33,35]. The first one is an ascending order buffer configuration and set as [5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95].…”

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

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A Computational Analysis of Long Transfer Line Behavior

Koyuncuoğlu

2024

Gazi University Journal of Science

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Meeting customer demands for order-based production and make‐to‐stock production policies against holding and non-holding costs are fundamental functions for businesses to ensure. For these policies, finite capacity buffers between machines is of great importance. WIP, production rate, and profit values, which are the key performance indicators of the transfer line, affect the sustainable economics of companies. It is important to investigate how the production rate, one of the most important performance indicators, and its calculation time are affected by the reliability parameters of the machines, the convergence rate and the analytical methods applied. In this study, the theoretical computational analysis of Dallery-David-Xie (DDX) algorithm on unreliable transfer line with finite buffers. The results show that the performance of the DDX algorithm is very sensitive to the convergence rate. Also, initial buffer configuration allocations to maximize the profit value in the transfer line are investigated.

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Section: Additional Experimental Tests For Performance Indicators Of ...mentioning

confidence: 99%

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

Section: ∑ 𝐵 𝑖 = 𝑁mentioning

confidence: 99%

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A Computational Analysis of Long Transfer Line Behavior

Koyuncuoğlu

2024

Gazi University Journal of Science

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“…The most common optimization criteria consider maximizing the average throughput rate (Gao, 2022;Gao, Higashi, Kobayashi, Taneda, Rubrico & Ota, 2020;Gao & Liu, 2023;Kassoul, Cheikhrouhou & Zufferey, 2023;Köse, Demir, Tunal & Eliiyi, 2015;Kose & Kilincci, 2015;Koyuncuoğlu & Demir, 2021;Lin & Chiu, 2018;Nahas, Nourelfath & Gendreau, 2014;Narasimhamu, Reddy & Rao, 2014;Patchong & Kerbache, 2017;Wang, Song, Shin & Moon, 2014), minimizing the total buffer size (Li, 2013;Weiss & Stolletz, 2015), minimizing the total cost of allocation (Magnanini, Terkaj & Tolio, 2022;Nahas, 2017;Nahas & Nourelfath, 2018;Ouzineb, Mhada, Pellerin & El Hallaoui, 2018;Tiacci, 2022), among others (Alfieri, Matta & Pastore, 2020;Hernández-Vázquez, Hernández-González, Jiménez-García, Hernández-Ripalda & Hernández-Vázquez, 2019;Hernández-Vázquez, Hernández-González, Hernández-Vázquez, Figueroa-Fernández & Cancino de la Fuente, 2022b;Koyuncuoğlu & Demir, 2023;Shaaban & Romero-Silva, 2021;Shao, Moroni, Li, & Xu, 2022;Xi, Smith, Chen, Mao, Zhang & Yu, 2021;Zhou, Liu, Yu & Tao, 2018).…”

Section: Buffer Allocation Problemmentioning

confidence: 99%

Optimization of the OEE indicator through meta-models’ simulation in the buffer allocation problem

Hernández Vázquez,

Hernández González

et al. 2024

JIEM

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Purpose: The buffer allocation problem (BAP) arises in the design of production systems; it involves analyzing and defining the optimal distribution of buffers within a production line. This paper presents a BAP formulation in a parallel series line from a cup sublimation process with unreliable operating conditions. The main objective of this study is to develop a new BAP solution proposal, considering the optimization of the OEE indicator used in Lean Manufacturing.Design/methodology/approach: The BAP was analyzed under an optimization approach from two different criteria: firstly, the maximization of the OEE indicator (Overall Equipment Effectiveness) utilized in Lean Manufacturing, as well as the maximization of the average production rate (Throughput). The case study involves unreliable operating conditions. Process times, and timeframes between failures and repairs, consider normal distribution functions. The evaluation method employed in the study includes the use of simulation meta-models built from experiment designs and production line simulations; on the other hand, the nonlinear GRG algorithm is used to solve the mathematical models.Findings: In the study carried out, it is shown that the OEE indicator can be affected when more buffers are allocated than necessary, hence it is important to calculate and establish the best configuration for them through an analysis such as the one proposed in this document.Research limitations/implications: The research is limited to a case study of an unreliable production line from a cup sublimation process.Practical implications: The proposed solution established in this study can be used in other production lines with configurations different from the one analyzed, considering the optimization criterion of the OEE indicator. Originality/value: Seeking that the allocation of buffers within the production line improves the OEE indicator is something new in the literature, therefore, the results achieved in this research become even more relevant.

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Most important performance evaluation methods of production lines: A comprehensive review on historical perspective and emerging trends

Ulaş Koyuncuoğlu

2024

Computers & Industrial Engineering

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An adaptive hybrid variable-large neighborhood search algorithm for profit maximization problem in designing production lines

Cited by 5 publications

References 57 publications

A Computational Analysis of Long Transfer Line Behavior

A Computational Analysis of Long Transfer Line Behavior

Optimization of the OEE indicator through meta-models’ simulation in the buffer allocation problem

Most important performance evaluation methods of production lines: A comprehensive review on historical perspective and emerging trends

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