汽车总装车间SPS实施运行探讨

在使用流水线作业方式进行整车大批量生产的汽车总装车间,为提高生产线的利用率,主机厂一般采用多车型混线生产的形式,一条生产线通常可生产5-6种车型,甚至更多,由于车型多、配置多和准时制生产要求,导致生产线线边物料存储面积不足。SPS物料配送方式能够有效解决线边物料存储空间不足的问题,并能提高装配效率,是一种先进的物流输送方式。     

支持复杂装配线物料配送的BOM映射技术研究

在复杂装配线生产过程中,如何实现物料的按时有序配送和关键零部件的齐套控制是物料配送管理的主要难题.在分析产品装配结构、装配工艺流程以及物料配送规则的基础上,通过梳理“制造BOM—作业BOM—配送BOM”之间的转换映射关系,建立基于装配工艺流程的作业BOM生成方法和基于工位结构分解的配送BOM生成方法,实现对复杂装配生产线物料配送信息的一致性映射和完整性控制,为物料配送的精细化管理提供能够反映装配作业过程特征的数据描述模型.最后通过应用实例验证说明上述BOM转换映射技术的合理性和可行性.     

考虑转换约束的汽车混流装配线投产排序研究

讨论了有生产线线边替补人员协助完成超载工作量的情况下,汽车混流装配线投产排序的问题,并且考虑工作人员行走占用的时间。通过对某整车厂进行实地调研,将汽车装配生产中的优化问题从以往文献中只考虑的总装车间向前延伸到涂装车间,给出连续喷涂某种颜色的车辆数的上界s。在此基础上,并考虑总装线线边物料消耗速率波动均衡和子装配工负荷均衡的约束条件,建立涂装切换成本和总装车间人工成本最小化的数学模型。最后,用CPLEX对模型进行优化求解,并分析得出生产节拍和工作站长度等参数与总成本之间的变化关系。     

生产线平衡方法在水泵转子装配线改善中的应用研究

以工业工程的作业测定和方法研究为基础,用生产线平衡技术对排污泵转子装配生产线进行改善.通过制作工作流程动作时间观测表和山积图,确定改善方向;综合运用作业ECRS原则、动作分析和作业分析构建改善方案;对作业工位进行合并重组,采用U型布局的生产线,实现减少操作人员数量及提高生产线空间利用率的目的.     

工作研究在电器产品装配线平衡改善中的应用

针对粗放管理模式下温州企业普遍关注挖掘企业内部潜力,增强企业竞争力的问题,以温州某电器产品的装配生产线为研究对象,在运用程序分析方法规范产品生产工艺流程的基础上,采用秒表时间研究识别了生产线的瓶颈工位,通过工序重排、人员调整以及基于双手作业分析和动作分析的作业方法改进,使得生产线的平衡率提高了31％.     

动车组总装生产线平衡性问题研究

为了更好的适应高速列车、城际列车等多元化动车组总装需求，基于动车组结构特点，研究总装生产线台位模式，结合批量化制造组织形式，建立装配工作站与节拍之间的函数关系，分析生产线约束条件，搭建最优化生产线平衡数据库，构建一套低成本的、通用化的并具备快速反应能力的动车组总装生产线。     

飞机移动生产线作业调度问题的启发式算法

飞机移动生产线作业调度问题是一种具有特殊约束的项目调度问题。综合分析了飞机移动生产线的作业顺序关序、资源约束、空间限制的多重特点,建立了以最小装配完工时间为目标的模型。将问题分为确定作业的优先顺序和选择作业人数的两个阶段进行决策,设计了由不同规则组合成27种启发式方法。通过比较启发式方法在250个测试问题集的表现,确定最有效的解决此问题的方法。     

应用工业机器人的劳动密集型企业典型生产线的设计

提出了应用工业机器人技术升级原有自动化生产线的理念,选取电子原件装配行业为研究对象,剖析了劳动力在自动化生产线中的作用,在此基础上为劳动密集企业设计了以工业机器人为主体的装配、检测、分拣、码垛自动化生产线。该生产线通过机器人手眼系统完成典型的装配作业,能够降低劳动力成本和提高产品质量的一致性。该项研究可为长三角地区劳动密集型产业的升级——"工业机器人代替人"提供技术储备。     

某物料装配线的急停控制功能改造

对某物料装配生产线中原有的停止归零操作进行技术改进,解决生产线运行过程中急停复位需要时间过长,改造后急停可自动完成余下工序而不需要归零操作,提高生产线工作效率。     

基于整流化的生产线精益改善方法研究

针对某数字相控阵雷达的核心部件数字阵列模块生产线存在的产能不足、物流路径混乱、生产线不平衡、操作人员疲劳强度高等问题,提出了基于整流化理论的精益改善方案.通过秒表测时、工序内作业拆分、生产线布局调整、瓶颈工序改善、节拍确定和全工序流动等方法实现了在减人缩时的情况下产能提升了50％、日增值工作时间比率从73.9％提高到87.9％.生产线平衡率由原来的55.8％提高到90.3％、在制品数量从76件降低到16件.并应用元单位量份配送方式进行生产线各工位的消耗物料补充,通过带有标签的空盒回收实现对线下准备区作业的看板拉动.     

Integrated scheduling and self-reconfiguration for assembly job shop in knowledgeable manufacturing

The problems of integrated assembly job shop (AJS) scheduling and self-reconfiguration in knowledgeable manufacturing are studied with the objective of minimising the weighted sum of completion cost of products, the earliness penalty of operations and the training cost of workers. In AJS, each workstation consists of a certain number of teams of workers. A product is assumed to have a tree structure consisting of components and subassemblies. The assembly of components, subassemblies and final products are optimised with the capacity of workstations simultaneously. A heuristic algorithm is developed to solve the problem. Dominance relations of operations are derived and applied in the development of the heuristic. A backward insertion search strategy is designed to locally optimise the operation sequence. Once the optimal schedule is acquired, the teams are reconfigured by transferring them from workstations of lower utilisation to those of higher utilisation. Effectiveness of the proposed algorithm is tested by a number of numerical experiments. The results show that the proposed algorithm promises lower total cost and desirable simultaneous self-reconfiguration in accordance with scheduling.     

Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.     

Simultaneous design of a product family and its related supply chain using a Tabu Search algorithm

Product family design is currently facing a multitude of challenges, the main problem stemming from the diversity offered to consumers. To design a product family, designers have to define an efficient bill of materials which ensures product assembly within a predefined length of time in order to satisfy the synchronised delivery principle. In addition, the modules used to assemble the finished products have to be competitive in terms of logistical costs. The ability to anticipate the constraints associated with the production process and with transportation is consequently of great interest. In this paper, we focus on the process of identifying a set of modules to be used in the assembly of the finished product. The objective is to define the bill of materials for each product from the modules belonging to that set, and to assign these modules to distant facilities where they will be manufactured and then shipped to a nearby facility for final assembly within a specific time. We use a set partitioning formulations to represent the problem, and solve it by adapting a Tabu Search algorithm in which the assembly process and the supply chain design are considered at the same time.     

Composition of module stock for final assembly using an enhanced genetic algorithm

The paper focuses on modelling and solving a design problem, namely the selection of a set of modules to be manufactured at one or more distant sites and shipped to a proximity site for final assembly subject to time constraints. The problem is modelled as a mathematical one, and solved by an appropriately designed genetic algorithm enhanced with a modified crossover operation, a uniform mutation with adaptive rate and a partial reshuffling procedure. The actual design problem is solved with 17 components. Larger problems may be solved without modifying the modelling steps, although they may require variation in terms of processing time, depending on the constraints that exist between the components.     

An integrated robust replenishment/production/distribution policy under inventory inaccuracy

In this paper, a centralised production/distribution system is studied, in which the manufacturer controls the processes of raw material ordering, production and final goods distribution. The inventory records of raw materials, work-in-process, final goods in the manufacturer and the retailers are inaccurate. The objective of this research is to develop an integrated policy that can hedge against the negative impact of inventory inaccuracy at all stages of a supply chain. To achieve this aim, a backward recursive integrated robust policy is constructed. First, the time, quantity and vehicle route of the next distribution are forecasted by a distribution sub-policy; then the forecasted distribution time and quantity are used as the objective of the production process control, which is implemented by a production control sub-policy. Raw materials are ordered by a replenishment sub-policy according to the forecasted raw materials consumption in the production process. Numerical experiments are conducted to verify the feasibility and robustness of the proposed policy, which shows that besides of deploying radio frequency identification (RFID) devices in inventory management systems for raw materials, WIPs, final goods of the manufacturer and the retailers, integrated robust policies also can be employed to hedge against the impact of inventory inaccuracy.     

The economic lot and delivery scheduling problem: the common cycle case

We analyze the interface between a supplier and an assembly facility, where direct shipments are made from one to the other. The final manufacturing step at the supplier involves multiple components produced on a single machine or production line. The assembly facility uses these components at a constant rate. The supplier incurs a sequence-independent setup cost and/or setup time each time the production line is changed over from one component to another. On the other hand, setup costs and times for the assembly facility are negligible. We consider two types of delivery cost: a fixed charge for each delivery, and a fixed-charge-per-truck cost.

We develop a heuristic procedure to find a 'just-in-time' schedule in which one production run of each product and a subsequent delivery of these products to the assembly facility occur in each cycle. The objective is to find the cycle duration that minimizes the average cost per unit time of transportation, inventory at both the supplier and the assembly facility, and setup costs at the supplier. We also develop an error bound for this procedure, and use some of the insights gained from the analysis to explain how delivery schedules can influence the attractiveness of reductions in production setup costs.     

Lot size approximation based on minimising total delay in a shop with multi-assembly products

Minimising the total delay in the procurement of materials is one of the most important objectives in the production management of a manufacturing shop with multi-assembly products. This criterion is affected by the lot sizes of the materials used in the assembly of final products. Therefore, the optimum production lot size of products should be determined to minimise the total delay. In this paper, four types of delay, namely priority, processing, staging and requirements delay are formulated based on a multi-product MRP (MP-MRP) graph activity. To optimise lot sizes and minimise total delay (TD), the lead time and due date of products are considered. Artificial neural network (ANN) and regression methods are then applied to obtain the nonlinear function of TD versus the lot sizes of products. The delay-based lot size approximation (DBLSA) algorithm is proposed for obtaining the approximated lot size of products. Results obtained for a 2P-MRP case study show the effectiveness of the solutions obtained by the proposed algorithm.     

Increasing the production rate of a just-in-time production system with variable operation times

This paper examines a just-in-time (JIT) system with kanbans with three subassembly lines feeding a final assembly station. Variability in operation times exists and variability effects are reduced by increasing work in process levels or by unbalancing the subassembly lines through assignment of work content at each station. Of the several unbalancing methods that were analysed in this study, only the high-medium-low showed a consistent improvement in the output rate of the JIT production system. The output rates with unbalanced stations were always superior to the output rate of the perfectly balanced configurations used as controls. The extent of improvement over the output rate of balanced systems increased directly with the variability in operation times in final assembly and subassembly stations and inversely with the interstage buffer capacity allowed in the system.     

IE在CELL生产方式中的应用

CELL生产方式是为了适应顾客的多元化需求而在PC装配行业中诞生的一种新的(多品种小批量的)生产方式。本文从工业工程(IE)的角度出发，说明CELL生产线方式与传统流水线生产方式相比较的优点及IE在CELL生产中的应用。     

Production and inventory policies for an integrated manufacturing firm

The coordination of production and inventory decisions for raw materials, intermediate products and finished goods is important. We compare some decision rules for a ‘firm that uses a single raw material to manufacture n different parts which are then assembled into the final product. Demand for the final product is probabilistic and there are costs of holding inventory and of ordering, manufacture and assembly. These characteristics are an idealization of the problem faced by a manufacturer of scaffolds in which the major processes are the manufacture of different sheet metal parts and their assembly.

We develop production rules that use system-wide information. We use simulation to evaluate the performance of these rules and compare system behaviour to that under production rules that are derived separately for each item and use only local information about that item's status.