Searching for the Optimum Number of Capacitated Materialistic Cars for an Automotive Manufacturing Cell Using a Shuffled Frog Leap Algorithm

Denise Barzaga, Elías Carrum
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Abstract

Due to the worldwide strengthening of the automotive sector, it presents itself as a challenge for the companies that comprise it to immerse themselves in processes of continuous improvement that contribute to increasing the satisfaction of the needs of its customers, as well as achieving a better positioning in the market. This goal is impossible to reach without proper design and management of the supply chain, consideration of issues related to logistics and inclusion of innovative techniques. In the chapter, the authors considered a manufacturing cell responsible for making the assembly of seats for the automotive industry. Waiting times and blocking of machines are incurred by not using the optimum number of vehicles to be used for the transfer of materials and the capacity with which they should count. The objective of this research is to know near-optimum quantities and capacities of the vehicles, materialistic cars, to avoid this situation. The use of mathematical formulations, simulation, and optimization techniques will be used to solve the problem.
用青蛙跳跃算法寻找汽车制造单元的最优物质汽车容量
由于全球范围内汽车行业的加强,它对组成它的公司提出了一个挑战,让他们沉浸在持续改进的过程中,从而有助于提高客户需求的满意度,并在市场中获得更好的定位。如果没有适当的供应链设计和管理,考虑到与物流相关的问题,并纳入创新技术,这一目标是不可能实现的。在本章中,作者考虑了一个制造单元,负责为汽车工业组装座椅。等待时间和机器阻塞是由于没有使用用于转移材料的最佳车辆数量和它们应该计算的容量而引起的。这项研究的目的是了解车辆的接近最佳数量和容量,物质汽车,以避免这种情况。使用数学公式,模拟和优化技术将用于解决问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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