Research of Dynamic Material Handling in an Automobile General Assembly Line Based on Real-time Information

The status of material delivery of an automobile general assembly line is analyzed, and the technique to achieve the real-time tracking of assembly status information is proposed based on RFID（ Radio Frequency Identification）. Thus the consumption of line-side buffer is obtained dynamically, then the type and quantity of needed material are fed back to the subsystem of material handling; the algorithm for determining the best time departure time of delivery driver based on minimizing of total time penalty function is proposed. This approach makes the material amount of a single delivery trip maximized and improves the efficiency of delivery drivers significantly in the case of does not affect the assembly line normal throughput. Additionally, although this dynamic material handling method is developed for the automobile assembly plant, it should be pointed out that this method is also applicable to other mixed model assembly plants such as electronics, semiconductor and aerospace industry.

Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models

The growing global competition compels manufacturing organizations to engage themselves in all productivity improvement activities. In this direction, the consideration of mixed-model assembly line balancing problem and implementing in industries plays a major role in improving organizational productivity. In this paper, the mixed model assembly line balancing problem with deterministic task times is considered. The authors made an attempt to develop a genetic algorithm for realistic design of the mixed-model assembly line balancing problem. The design is made using the originnal task times of the models, which is a realistic approach. Then, it is compared with the generally perceived design of the mixed-model assembly line balancing problem.

Mixed-Model U-Shaped Assembly Line Balancing Problems with Coincidence Memetic Algorithm

Mixed-model U-shaped assembly line balancing problems (MMUALBP) is known to be NP-hard resulting in it being nearly impossible to obtain an optimal solution for practical problems with deterministic algorithms. This paper pre-sents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of MMUALBP in a just-in-time production system. Three objectives are simultaneously considered;minimum number workstations, minimum work relatedness, and minimum workload smoothness. The variances of COIN are also proposed, i.e. CNSGA II, and COIN-MA. COIN and its variances are tested against a well-known algo-rithm namely non-dominated sorting genetic algorithm II (NSGA II) and MNSGA II (a memetic version of NSGA II). Experimental results showed that COIN outperformed NSGA II. In addition, although COIN-MA uses a marginal CPU time than CNSGA II, its other performances are dominated.

Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing

The growing global competition compels organizations to use many productivity improvement techniques. In this direction, assembly line balancing helps an organization to design its assembly line such that its balancing efficiency is maximized. If the organization assembles more than one model in the same line, then the objective is to maximize the average balancing efficiency of the models of the mixed model assembly line balancing problem. Maximization of average balancing efficiency of the models along with minimization of makespan of sequencing models forms a multi-objective function. This is a realistic objective function which combines the balancing efficiency and makespan. This assembly line balancing problem with multi-objective comes under combinatorial category. Hence, development of meta-heuristic is inevitable. In this paper, an attempt has been made to develop three genetic algorithms for the mixed model assembly line balancing problem such that the average balancing efficiency of the model is maximized and the makespan of sequencing the models is minimized. Finally, these three algorithms and another algorithm in literature modified to solve the mixed-model assembly line balancing problem are compared in terms of the stated multi-objective function using a randomly generated set of problems through a complete factorial experiment.

汽车总装生产线自动化改造与实施

在当今竞争激烈的汽车制造业中,提升生产效率和质量已成为企业持续发展的关键。汽车总装生产线的自动化改造,作为提升生产效率和应对市场需求变化的重要手段,日益受到广泛关注。本文旨在探讨汽车总装生产线自动化改造的技术基础、实施方法及其对企业管理与运营的影响。通过案例分析和实证研究,本文将深入探讨自动化技术在提升生产效率、优化资源利用和改善产品质量方面的实际效果。最后,对未来汽车制造业在智能制造和工业4.0趋势下的发展方向进行展望,以期为相关领域的研究和实践提供理论支持和实际指导。

某乘用车白车身总拼试制生产线分析

目前,中国已经成为世界上最大的单一汽车产销市场。中国市场上的乘用车白车身主流方案是以碳钢冲焊成型为主,每一款乘用车型从研发到正式批产都会先进行白车身试制生产验证,以确保白车身方案的结构及性能满足设计要求。白车身试制过程的总拼集成工序是其关键工序之一,常规量产的总拼生产线由于车型生产固定,如果调整生产车型需要投入大量的时间和人力,则不能适应白车身总拼试制柔性化、快速切换生产的需求。因此,对乘用车白车身总拼试制生产线研究对中国乘用车的试制生产开发能力提升具有重要意义。文章以某碳钢白车身总拼试制生产线为例,对该类型的总拼试制生产线布局及应用方案作详细的分析研究。

基于物联网的汽车变速箱装配产线系统设计

目前,新能源汽车和智能汽车已经成为全球汽车产业发展的战略方向,对经济发展起到重要的带动作用。汽车变速箱部件装配作为汽车生产的重要环节,其智能化程度越来越重要。但是,目前大多数汽车变速箱部件装配生产线仍采用传统的人工上下物料方式,存在效率低、生产安全性低的弊端。近年来,国内外学者对汽车变速箱自动化装配产线进行了研究,但仍然存在自动化产线控制协同度不高、制造成本过高等问题。为全面贯彻落实“中国制造2025”,进一步推进人工智能技术在工业自动化中的应用,联合某汽车企业,设计一种基于物联网的变速箱部件装配产线系统。该系统以工业机器人代替工人进行上下物料,通过可编程逻辑控制器(Programmable Logic Controller,PLC)控制系统调度,采用模块化结构,具有安装、拆卸简单、成本低的优点,可以用于大规模工业生产,以提高生产效率,也可以作为示范教学项目进行推广,具有较高的经济价值。

Part Supply Method for Mixed-Model Assembly Lines with Decentralized Supermarkets

In-house part supply affects the efficiency of mixed-model assembly lines considerably. Hence, we propose a reliable Just-In-Time part supply strategy with the use of decentralized supermarkets. For a given production sequence and line layout, the proposed strategy schedules tow train routing and delivery problems jointly to minimize the number of employed town trains and the traveling time, while ensuring that stations never run out of parts. To solve this problem, a mathematical formulation is proposed for each sub-problem aiming at minimizing supply cost. Then, a dynamic programming algorithm for routing and a greedy algorithm for delivery are developed, both of which are of polynomial runtime. Finally, a computational study is implemented to validate the effectiveness of the strategy, and to investigate the effects of the delivery capacity of tow trains and storage capacity of stations on supply cost.

Hybrid genetic algorithm for a type-Ⅱ robust mixed-model assembly line balancing problem with interval task times

The typemixed-model assembly line balancing problem with uncertain task times is a critical problem. This paper addresses this issue of practical significance to production efficiency. Herein, a robust optimization model for this problem is formulated to hedge against uncertainty. Moreover, the counterpart of the robust optimization model is developed by duality. A hybrid genetic algorithm (HGA) is proposed to solve this problem. In this algorithm, a heuristic method is utilized to seed the initial population. In addition, an adaptive local search procedure and a discrete Levy flight are hybridized with the genetic algorithm (GA) to enhance the performance of the algorithm. The effectiveness of the HGA is tested on a set of benchmark instances. Furthermore, the effect of uncertainty parameters on production efficiency is also investigated.

AN OPTIMAL KANBAN SYSTEM IN A MULTI-STAGE,MIXED-MODEL ASSEMBLY LINE

This paper studies the parameter design and the performance optimization of a Kanban system without stockouts in a multi-stage, mixed-model assembly line. The model of a Kanban system based on production processes is established by examining the relationship among the set-up time, the amount of work in process （WIP）, the capacity indicated by a Kanban, and the takt-time ratio. A novel method for optimizing performance on the premise of no stockouts is proposed. Empirical results show that the amount of WIP is reduced remarkably after optimization.

Sequencing Mixed-Model Flexible Assembly Lines with Variable Launching Intervals

To solve the sequencing problem in mixed-model flexible assembly lines (MMFALs) with variable launching intervals, a mathematical model aiming to minimize the cost of utility and idle times is developed. To obtain high-quality sequences, an advanced scatter search (ASS) algorithm is proposed. A heuristic approach, i.e. launching intervals between products algorithm (LIBPA), is incorporated into the ASS algorithm to solve the launching interval problem for each sequence. Numerical experiments with different scales are conducted to compare the performance of ASS with genetic algorithm (GA). In addition, we compare the cost of variable launching intervals approach with fixed launching intervals approach. The results indicate that the ASS is efficient and effective, and considering variable launching intervals in mixed-model assembly lines (MMALs) sequencing problem can improve the performance of the line.

A dynamic delivery strategy for material handling in mixed-model assembly lines using decentralized supermarkets

Material handling has become one of the major challenges in modern production management.Consequently,this paper intends to investigate the part delivery of mixedmodel assembly lines with decentralized supermarkets and tow trains.Besides,uncertain exception disturbances,including tow train failures and adjustments of the production sequence,are also considered.To solve this problem,a heuristic-based dynamic delivery strategy is proposed,which dynamically schedules the route,departure time,quantities and types of loaded parts for each tour.To evaluate the performance of this strategy,it is used to solve an instance in comparison with the periodic delivery strategy,experimental results are reported and their performances are compared under different metrics.Moreover,a multi-scenario analysis is employed to determinate the long-term decisions,including the number of tow trains and the route layout.Finally,the critical storage is suggested to be set for each station to avoid part starvation resulting from disturbances,and its effect on the delivery performance is investigated.

Minimizing Products Rates Variation in Just-in-Time Mixed-Model Manufacturing

Mixed-Model assembly lines are often used in manufacturing based on just-in-time techniques. The effective utilization of these lines requires a schedule for assembling the different models be determined. The objective is to minimize the total deviation of actual production rates from the desired production rates. Mathematical method with the optimization algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the proposed algorithm is an efficient and effective algorithm which gives better results with the large problem sizes. This paper presents a practical procedure to minimize total product variation rates, and easy to use by practitioner.

改进遗传算法支持下汽车中控混流装配生产线优化数学模型构建

针对当下对混流装配生产线现存方法不足的问题,实验提出一种结合GA算法和模拟退火算法的IGA模型,用以求解汽车混流装配线的平衡问题。模型对IGA所有步骤进行了充分的解释说明,并引入模拟退火算法中的采样规则来选择操作。最终实验结果显示,优化前后,生产线平衡率提高了4.77%,生产线负荷均衡提高了3.56,平衡损耗系数降低了0.047,生产节拍降低了6.21 s。该模型能够实现装配工艺的最优分配策略,同时提升整体生产线的工作效率。

面向智能制造的商用汽车发动机装配线平衡优化实验研究

发动机装配线平衡优化时的平衡损失率较高,导致优化效果较差,为此,应研究面向智能制造的商用汽车发动机装配线平衡优化。首先,设置商用汽车发动机装配件,并建立装配线模型,提出实验中的装配步骤;其次,根据装配线平衡优化指标,分别构建拆解重排与并行作业两种优化目标函数;最后,采用蚂蚁算法求解优化后的目标函数,实现装配线的平衡优化。实验结果可知,并行作业方案的优化指标较优,发动机平衡损失率在6%~9%左右,说明本文方案具有一定的应用水平。

乘用车底盘合装生产线

介绍了乘用车底盘合装工艺及底盘合装自动导引车的特点,在此基础上设计了乘用车底盘合装生产线。论述了设计原则,分析了工艺流程,并给出了自动导引车运行路线、充电方式、导航方式、通信系统等。

汽车装配工艺规划及相关技术的探讨

针对现代制造业中汽车设计制造流水线总装工艺的发展趋势，提出了具有高适应性和高柔度性的集成化虚拟汽车装配工艺规划系统，并对规划系统中的技术要点进行了探讨，希望能够起到抛砖引玉的作用。

基于RFID的混流装配汽车生产线物料动态配送研究

针对混流装配的汽车自动化生产线提出了基于RFID的车辆追踪和基于条码的无线物料库存管理实现方法。在此基础上,设计了装配生产线的物料动态配送调度业务流程,给出了物料动态配送的规划依据,并进行了实例计算。

带时间窗的汽车总装线物料配送路径规划

分析了现阶段汽车总装线物料配送中存在的问题,建立了适用于汽车总装线物料配送路径规划的混合时间窗模型,提出了解决带时间窗的汽车总装线物料配送路径优化问题的改进遗传算法,使用了一种新的染色体编码方式和与之对应的交叉算子。针对传统轮盘赌随机操作选择误差比较大的弊端,提出改进的轮盘赌选择算子,加大随机数的产生次数并加入排序选择的思想,融合了最佳个体保存选择策略,提高算子的选优性能。实验表明该算法用于求解带时间窗的汽车总装线物料配送路径问题的有效性。

汽车发动机装配线MES中的订单管理系统

通过对某汽车发动机制造企业的生产订单管理制度和业务流程的分析和研究,开发了一套生产订单管理软件。在基于ERP/MES/PCS三层体系结构的制造企业信息系统中,位于制造执行系统内部顶层的生产订单管理系统负责ERP和MES之间的信息交互,在ERP和MES中起着信息桥梁的关键作用。采用Oracle透明网关技术,使Oracle数据库访问SQL Server2008数据库,基于SQL Server2008中的CLR集成技术、UDP协议的网络通信等关键技术实现了SQL Server 2008数据库主动与订单管理系统通讯。运行结果表明该系统性能稳定,满足生产需要。