【作者】 刘晓伟；

【导师】 芈凌云；

【作者基本信息】 中国矿业大学 ， 工业工程与管理（专业学位）， 2023， 硕士

【摘要】 在当前激烈的市场竞争环境下,越来越多的制造企业将智能化改造作为未来发展目标之一,而物流系统自动化是其中重要的步骤。MD公司电子厂车间是一个为园区内部提供电路板的生产车间。为了打造数字化车间提高生产效率,将车间内部的物料运输由人工搬运变为AGV自动搬运。在进行车间改制后,发现AGV存在运输效率低下,无法满足车间生产需求的问题。因此,本文对MD公司电子厂车间进行了车间设备布局研究。经过现场调查,发现电子厂车间存在一些问题,包括设备布局混乱、产品工序流畅性不足和AGV物流运输路线频繁交叉。通过分析发现,这些问题主要是由于布局不合理所致。为了解决这些问题,本文采用了SLP方法对电子厂车间加工区域的设备进行了物流和非物流分析,并计算了设备之间的综合相互关系。基于综合相互关系,绘制了电子厂车间设备位置相关图,并结合MD公司电子厂车间的实际限制条件,对设备进行了重排,得到了优化的电子厂车间布局方案。由于SLP方法存在一些局限性,因此,本文使用基于SLP改进遗传算法对车间布局进行再次优化。建立以总路程最小,非物流关系最大为目标的数学模型,在Matlab上使用遗传算法对其进行求解。为了提高遗传算法的准确性,使用SLP得出的结果对遗传算法的初始种群进行改进,从而得到SLP改进遗传算法。并且本文研究比较了SLP、遗传算法和SLP改进遗传算法三种方法在AGV布局优化方面的效果。结果显示,这些方法都能显著提高AGV的运输效率。具体而言,SLP方法提高了31.0%的效率,遗传算法提高了31.7%的效率。然而,使用SLP改进遗传算法效果最佳,可以提高33.4%的效率,验证了该方法的有效性。此外,为了确保项目能够顺利推进和达成预期目标,提出了成立项目组、增加激励方式和进行人员培训三个措施。本文采用了SLP改进遗传算法来优化电子厂车间设备布局,取得了显著效果。该方法有效地解决了AGV运输效率低下的问题,并为其他制造企业在面临设备布局优化问题时提供了可行的思路和方法。更多还原

【Abstract】 In the current competitive market environment,more and more manufacturing companies are taking intelligent transformation as one of their future development goals,and automation of the logistics system is one of the important steps.the electronics factory workshop of MD is a production workshop that provides circuit boards for the inner part of the park.In order to create a digital workshop to improve production efficiency,the material transport within the workshop was changed from manual handling to automatic AGV handling.After the workshop conversion was carried out,it was found that the AGVs suffered from low transport efficiency and were unable to meet the workshop’s production needs.Therefore,this thesis conducts a workshop equipment layout study of the electronics factory workshop of MD.After an on-site investigation,it was found that there were a number of problems in the electronics factory floor,including confusing equipment layouts,insufficient fluidity of product processes and frequent crossings of AGV logistics transport routes.Through analysis,it was found that these problems were mainly due to the unreasonable layout.In order to solve these problems,this thesis uses the SLP method to analyse the equipment in the processing area of the electronics factory workshop in terms of logistics and non-logistics,and calculates the integrated interrelationships between the equipment.Based on the integrated interrelationships,a correlation diagram of the equipment locations in the electronics factory workshop was drawn,and the equipment was rearranged to obtain an optimised layout plan for the electronics factory workshop,taking into account the actual constraints of MD’s electronics factory workshop.Since the SLP method has some limitations,this thesis uses an improved genetic algorithm based on SLP to optimise the workshop layout again.A mathematical model with the objective of minimising the total distance travelled and maximising the non-logistical relationships is developed and solved on Matlab using a genetic algorithm.In order to improve the accuracy of the genetic algorithm,the initial population of the genetic algorithm is improved using the results derived from the SLP,which results in the SLP improved genetic algorithm.And this study compares the effectiveness of three methods,SLP,genetic algorithm and SLP-improved genetic algorithm,in the optimisation of AGV layouts.The results show that all these methods can significantly improve the transportation efficiency of AGVs.Specifically,the SLP method improved efficiency by 31.0% and the genetic algorithm improved efficiency by 31.7%.However,the use of SLP to improve the genetic algorithm worked best,improving efficiency by 33.4%,validating the effectiveness of the method.In addition,three measures are proposed to ensure that the project can move forward smoothly and achieve the desired goals,namely the establishment of a project team,the addition of incentive methods and the training of personnel.In this thesis,an SLP improved genetic algorithm is used to optimise the equipment layout of an electronics factory floor,with significant results.The method effectively solves the problem of inefficient AGV transportation and provides feasible ideas and methods for other manufacturing companies when faced with equipment layout optimisation problems.更多还原