A heuristic algorithm for cell formation problems with consideration of multiple production factors

For the design of manufacturing cells, numerous mathematical models and various algorithms have been extensively investigated in the literature. However, most of the proposed models and algorithms have more or fewer drawbacks on the issues with real-life situations. In this paper, we propose a mathematical model that incorporates multiple key real-life production factors simultaneously, namely, production volume, batch size, alternative process routings and perfect coefficient of each routing, cell size, unit cost of intercell/intracell movements, and path coefficient of material flows. Then, to solve this NP-hard model, we develop a heuristic algorithm with three stages: (1) form the temporary machine group plan according to the alternative process routings of each part, (2) select the appropriate process routing of each part with respect to the over-all material movement cost, and (3) configure the regular manufacturing cells based on the appropriate process routing. A simple numerical example and an industrial case are used to test the computational performance of the proposed algorithm. The test results imply that it is useful for manufacturing cell design in both quality and speed.     

Simultaneous manufacturing shape optimization for minimum cost of milling using interior point method

This paper presents an integrated manufacturing shape optimization method and explores the tradeoff between mass and machining cost with the application of the end-milling that used to machine a topological die. The aim is to make a simultaneous optimization method between product manufacturing and its topological shape to close the gap between theoretical work and practical needs. This innovative method depends on some manufacturing functional issues and shape constraints. The objective function is minimizing the total cost of process including the material and machining cost. The initial shape of the part is constructed by using B-splines and hole generation-based topological concept; the design variables are x- and y-coordinates of the control points that represent the B-splines. The cutting parameters of the milling process such as the cutting speed, the feed per flute, and the tool diameter are also optimized. The simultaneous manufacturing shape optimization problem will be achieved by interfacing between MATLAB2011a and ANSYS15 programs using interior point method (IPM) as a mathematical optimization solver. The comparison between the initial total cost and its optimal results for studied cases is presented, and the influence of the required batch size on the final shape is discussed. It is found that the reduction percentage in the cost function can receive 69% for small batch size (batch 50 pieces) and 54.18% for large batch size (batch 5000 pieces). The result from this simultaneous optimization is that the batch size of the required product influences the topological shape of the product.     

A mixed integer programming formulation for scheduling of virtual manufacturing cells (VMCs)

We present a multi-objective mixed integer programming formulation for job scheduling in virtual manufacturing cells (VMCs). In a VMC, machines are dedicated to a part family as in a regular cell, but machines are not physically relocated in a contiguous area. Cell configurations are therefore temporary, and assignments are made to optimize the scheduling objective under changing demand conditions. We consider the case where there are multiple jobs with different processing routes. There are multiple machine types with several identical machines in each type and are located in different locations in the shop floor. The two scheduling objectives are makespan minimization and minimizing total traveling distance. Since batch splitting is permitted in the system, scheduling decisions must tell us the (a) assignment of jobs to the machines, (b) the job starting time at each machine, and (c) the part quantity processed on different machines due to batch splitting. Under these decision variables, the objective function is to minimize the sum of the makespan and total traveling distance/cost. Illustrative examples are given to demonstrate the implementation of the model.     

多目标批量生产柔性作业车间优化调度

研究批量生产中以生产周期、最大提前/最大拖后时间、生产成本以及设备利用率指标(机床总负荷和机床最大负荷)为调度目标的柔性作业车间优化调度问题。提出批量生产优化调度策略,建立多目标优化调度模型,结合多种群粒子群搜索与遗传算法的优点提出具有倾向性粒子群搜索的多种群混合算法,以提高搜索效率和搜索质量。仿真结果表明,该模型及算法较目前国内外现有方法更为有效和合理。最后,从现实生产实际出发给出多目标批量生产柔性调度算例,结果可行,可对生产实践起到一定的指导作用。     

Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

快速扩散制造环境下制造资源选择技术研究

为解决武器装备变批量生产问题,基于信息技术和网络技术,提出了快速扩散制造问题,并对网络化制造与快速扩散制造进行了差异性比较.从制造成本、时间、质量、服务和能力等方面,将制造资源选择评价指标分为时间性指标、成本性指标、历史性指标、总体性指标、资源状态指标、制造能力指标六大类,并构建了制造资源选择综合评价体系.最后应用层次分析法与灰色关联理论相结合的制造资源选择策略和实现算法,并以某飞机关键复杂零件制造任务为例,介绍了基于灰色关联理论的制造资源快速选择过程与方法.     

生产物流跟踪的钢铁企业作业成本计算方法研究

针对目前钢铁企业多品种、小批量生产模式下成本归集和分配难以反映实际作业过程不足的问题,提出以炉号、生产批次为依据且面向作业资源管理的物料跟踪模型,并在此基础上研究生产跟踪数据向成本数据的转化方法,总结出多重资源分配方法,进而研究基于生产物流跟踪的钢铁企业作业成本计算方法.通过在某钢铁企业的应用,验证了该成本计算方法的有效件.     

基于分段线性MPCA的充液氨过程建模及监控

为深入分析晶变改性装备中反应釜充液氨工艺过程特性,同时也为了进行更精确、有效的过程监控,提出了一种分段线性多向主元分析(MPCA)方法,实现该间歇过程的建模及故障诊断。首先将三维建模数据降维展开并进行主元分析(PCA),得到采样点数据特征矩阵;然后基于间歇过程的多操作时段特性,根据特征矩阵相似度最大隶属原则,通过设定窗口长度可调的滑动聚类器,在系统运行轨迹上分别从数据变异的方向和幅值对采样点进行2次聚类划分,将间歇过程操作周期分割为一系列运行特性相同的子时段,最后利用各个子时段的线性MPCA模型逼近系统非线性运行过程,实现间歇生产过程建模及在线监测。通过反应釜充液氨工艺过程的实际应用,结果表明提出的建模方法能够对该间歇生产进行合理的、易于从过程特性角度解释的时段划分,所建模型具有可靠的监控性能,能及时准确检测出系统运行过程中的异常情况。     

Analysis of Optimum Batch Size in Multistage,Multifacility and Multiproduct Manufacturing Systems

In any type of manufacturing environment the most common configuration will be a multistage, multiproduct, manufacturing inventory system. An in-process inventory is inherent in any multistage manufacturing system, when the product is manufactured through several operations and stages. To satisfy demand requirements in multistage, multiproduct manufacturing systems, it is important to specify feasible production quantities, as batch sizes for each end product, over a finite time period at every stage. This paper deals with different methods for determining batch sizes in a multiproduct, multistage situation in the presence of decision support systems for maximum capacity. The mathematical model suggested by Gunasekaren is considered as the basis for comparison. A fuzzy logic model of the above has been developed to calculate the economic batch sizes such that machine hour and labour productivity constraints are not violated. Using Promodel, a simulation technique, the model was subjected to variable analysis and cost analysis and the results were compared. Case studies were conducted for validating the models for their ability to produce reliable output. MATLAB software package is used for developing the program to solve the problem by fuzzy approximation.     

Lot splitting scheduling procedure for makespan reduction and machine capacity increase in a hybrid flow shop with batch production

The general definition of the hybrid flow shop (HFS) environment is a set of S?≥?2 production stages where at least one of these stages includes more than one machine, which can process one job at a time. A job can be defined as several operations to be performed by none, one, or more machines at each stage. Usually, these jobs are completed in some sequence between the different production stages, and in the case of setup activities, products are grouped in batches with buffers of work in progress between different production stages. Today, flexible production systems permit in some instances to relax job precedence constrains with alternative process cycles and to group together different batches of similar products in order to reduce setup activity incidence. On the other hand, the availability of multiple parallel machines in a single production stage makes it possible to split the lot size between different resources. This paper aims to solve the HFS scheduling problem in a flexible multistage batch production system, offering a heuristic procedure, to minimize the production makespan and increase the productive capacity utilization using a batch aggregation/splitting strategy while introducing the “workload leveling function” concept. The results are compared with other important scheduling rules widely accepted in the industry and made part of an industrial application. The company used as a test sample is an Italian rotor shaft manufacturer. The final result is illustrated to validate the proposed heuristics.     

Heuristics for makespan minimization on parallel batch processing machines with unequal job ready times

This research aims at minimizing the makespan of a set of identical batch processing machines arranged in parallel. Each job is defined by its processing time, ready time, and size. Each machine can process several jobs simultaneously as long as the machine capacity is not exceeded. The batch processing and ready times depend upon the batch composition. The batch processing time is equal to the longest processing job in the batch, and the batch ready time is equal to the largest ready time among those jobs in the batch. The problem under study is NP-hard. Consequently, a constructive heuristic is proposed and its performance with respect to solution quality and computational cost is compared against other solution approaches found in the literature. The computational experiments on a set of randomly generated instances show that the performance of the proposed heuristic is competitive with respect to solution quality and requires little computational cost.     

基于混合禁忌搜索算法的供应链排序问题

分析非标准件加工企业供应链的特点,提出协同优化订单分配、生产调度和批量运输调度的多工厂多客户供应链排序问题。以工件的最长订货提前期与总成本加权之和最小化为目标,构建问题的数学模型。在分析解的最优性条件基础上,设计一种基于矢量组编码方法的混合禁忌搜索算法。算法对可行域进行分区,通过基于插入、交换两种邻域操作的禁忌搜索算法选择子区域,采用基于块结构邻域操作的禁忌搜索算法搜索子区域中的优良解。采用所提混合禁忌搜索算法对算例进行优化求解,并对采用不同编码方法、不同启发式算法的算例结果进行比较,结果表明所提出算法的有效性。     

一种新的多阶段间歇过程在线监控策略

为克服多阶段间歇过程硬划分和误分类导致漏报率和误报率高的缺陷,同时也为了实现更精确、有效地过程监控,提出一种基于模糊聚类软过渡的多PCA监控策略,实现多阶段间歇过程的在线监控.首先计算每个时刻数据矩阵的相似度指标作为聚类输入,采用模糊聚类算法实现阶段划分,根据隶属度辨识相邻阶段间的过渡过程,之后建立一系列具有时变协方差的加权PCA模型,该方法能客观地揭示各阶段及过渡过程的特征多样性,较好地解决存在过渡过程的多阶段监控问题.最后通过将所提出的方法应用于工业青霉素发酵过程的监控中,验证了该方法的可行性和有效性.     

A STEP AP224 agent-based early manufacturability assessment environment using XML

Early design assessment activities have a significant impact on reducing the cost of manufacture. The efficient utilisation of the product development time and the level of coordination of the early design activities between the major stakeholders are becoming key factors for success in manufacturing today. The paper reports on a new distributed early design manufacturability assessment methodology using collaborative autonomous agents. A product data model compliant with STEP AP224 and corresponding process and facility data models are proposed to support the decision-making process. XML was used as a medium for exchange of requests and information between design, manufacturing, and facility planning agents. A prototype Web-enabled system for rapid product manufacturability assessment in the extended enterprise has been developed using distributed multi-agent CORBA objects. The reported research is a step towards the development of a generic prototype tool for collaborative design evaluation and rapid assessment of the manufacturing feasibility and resource availability at different stages of the product development process.     

A parallel machine batch scheduling problem in a brewing company

This work introduces a scheduling problem which is motivated from a real situation faced by one of the largest brewing companies in Mexico. Several products must follow a brewing process which is composed by three main stages: coction, fermentation, and conditioning. In the coction stage, there are multiple unrelated parallel machines, and in the fermentation and conditioning stages, there are several heterogeneous tanks. Additionally, during the production process, some maintenance operations must be scheduled. The problem can be seen as a parallel machine batch scheduling problem with sequence-dependent setup times. Due to the complex structure of the problem, we propose a Greedy Randomized Adaptive Search Procedure to generate good quality solutions in a short computation time. Computational experiments are conducted with real and artificial instances. The solutions obtained for the real instances show that the proposed algorithm reaches better solutions than the current solutions generated by the decision maker at the brewery, and the computation time required by our algorithm is dramatically shorter than the one required by the company.     

基于PLC的自动钻床控制系统设计

本文给出了用可编辑控制器（PLC）将普通立式钻床改造成可批量加工的专用自动钻床的控制方法。配备的PWS1711触摸屏可实时地显示钻床的工作状态。改造后的自动钻床结构简单，成本较低，能够满足中小型企业对机械加工件批量生产的需求。     

成组技术在零件数控加工生产中的应用

多品种、小批量是某公司当前的主要生产模式。，如何提高其生产效率，甚至能达到大批量生产模式的效率，是生产型企业目前研究的课题。通过应用成组技术，按零件数控化加工的特点和订单量进行了成组工艺分类，即把原来124种零件分成了9大组，安排在11台数控机床上进行加工。经过这样的分类成组，该公司生产效率提高了26％，同时生产成本降低了20％。     

A joint GA+DP approach for single burn-in oven scheduling problems with makespan criterion

This research is motivated by the scheduling problem found in the burn-in operation of semiconductor final testing, where jobs are associated with release times, processing times, and sizes. The burn-in ovens are modeled as batch-processing machines which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity, and the processing time of a batch is equal to the longest time among all the jobs in the batch. Moreover, this paper attempts to schedule jobs on a single batch-processing machine to minimize makespan. A joint GA+DP algorithm is proposed involving two stages: (1) the formation of job sequence by genetic algorithm operators, and (2) the formation of batches by a dynamic programming algorithm. Computational experiments are given to examine the performance of the proposed algorithm. The experimental results indicate that the joint GA+DP approach has well improved on all instances with respect to solution quality and runtime.     

Genetic algorithms for minimizing makespan in a flow shop with two capacitated batch processing machines

This paper considers a flow shop with two batch processing machines. The processing times of the job and their sizes are given. The batch processing machines can process multiple jobs simultaneously in a batch as long as the total size of all the jobs in a batch does not exceed its capacity. When the jobs are grouped into batches, the processing time of the batch is defined by the longest processing job in the batch. Batch processing machines are expensive and a bottleneck. Consequently, the objective is to minimize the makespan (or maximize the machine utilization). The scheduling problem under study is NP-hard, hence, a genetic algorithm (GA) is proposed. The effectiveness (in terms of solution quality and run time) of the GA approach is compared with a simulated annealing approach, a heuristic, and a commercial solver which was used to solve a mixed-integer formulation of the problem. Experimental study indicates that the GA approach outperforms the other approaches by reporting better solution.     

成批生产计划调度的集成建模与优化

针对多品种批量生产类型,建立了调度约束的生产计划与调度集成优化模型。模型的目标函数是使总调整费用、库存费用及生产费用之和最小,约束函数包括库存平衡约束和生产能力约束,同时考虑了调度约束,即工序顺序约束和工件在单机上的加工能力约束,保证了计划可行性。该模型为两层混合整数规划模型,对其求解综合运用了遗传算法和启发式规则,提出了混合启发式求解算法。最后,针对某机床厂多品种批量生产类型车间进行了实例应用,对车间零件月份作业计划进行分解,得到各工段单元零件周作业计划,确定了零件各周生产批量与投产顺序。