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Modified NEH Algorithm for Multi-Objective Sequencing in Mixed-Model Assembly Lines

机译:混合模型装配线中多目标测序的改进NEH算法

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摘要

Assembly lines are usually used for the mass production. The dawn of mass customization has forced the industries to shift to MMAL (Mixed-Model Assembly Lines). ALBP (Assembly Line Balancing Problem) and MSP (Model Sequencing Problem) are two major problems in MMAL. Sequencing of models is an important aspect of MMAL because improper sequencing can lead to the production loses. This paper dealt with the MSP in MMAL. A modified INEH (Intelligent Nawaz, Enscore, and Ham) algorithm was developed to solve multi-objective MSP. For this purpose, a MCDM (Multi-Criteria Decision Making) techniquewas integrated with NEH. A mathematical model was presented for three performance measures; Idle time, Make-span and Flow Time. A case study of pumps assembly line was conducted. Proposed INEH simultaneously optimized all performance measures (Flow Time= 123.47min, Make-Span= 156.95min and Idle Time=1.67 min) while the traditional NEH variants only optimized single performance measure and ignoring the others. Performance of the proposed algorithm was compared with traditional NEH algorithm and its variants using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), a MCDM technique. Results showed that proposed INEH outperformed rest of the NEH algorithms as TOPSIS ranked INEH first with the relative closeness of 97.3% while the NEH variant for flow time is worse algorithm with the relative closeness of 2.8%.
机译:装配线通常用于批量生产。大规模定制的曙光已迫使行业转向MMAL(混合模型装配线)。 ALBP(装配线平衡问题)和MSP(模型排序问题)是MMAL中的两个主要问题。模型的测序是MMAL的一个重要方面,因为不当测序可能导致生产损失。本文处理了MMAL中的MSP。开发了一种改进的ineh(智能Nawaz,enscore和Ham)算法来解决多目标MSP。为此目的,与NEH集成的MCDM(多标准决策)技术。提供了三种性能措施的数学模型;空闲时间,制作跨度和流量时间。进行了对泵装配线的案例研究。提出的Ineh同时优化所有性能措施(流量时间= 123.47min,Make-Span = 156.95min和空闲时间= 1.67分钟),而传统的NEH变体仅优化单个性能测量并忽略其他效果。将所提出的算法的性能与传统的NEH算法及其使用TOPSIS的变体进行比较(通过相似性与理想解决方案的顺序偏好),MCDM技术。结果表明,ineh占纳米算法的剩余效果优先于ineh排名第一,在相对近的是97.3%的情况下,纳米变型对于流动时间更差,相对近的次数为2.8%。

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