Flexible Parts Routing in Manufacturing Systems*

We study dynamic parts routing in flexible manufacturing systems. To quantify flexibility, we develop an entropy type of measure that incorporates all the job and machine characteristics that contribute to routing flexibility. Based on this measure and the principle of “least reduction in entropy” (LRE), two operating rules, the part selection rule and the machine selection rule, are established. These rules are then applied to drive some simulated systems and compared with the “shortest processing time” (SPT) rule. It is found that LRE either outperforms or is as good as SPT in terms of makespan and machine utilization.     

Material handling considerations in the FMS loading problem with full routing flexibility

This study exploits machining and routing flexibility to effectively deal with the material handling requirements resulting from a frequently changing demand mix in a manufacturing system where material handling is a bottleneck. For this purpose, the objective function of the operation and tool loading problem is selected as the minimisation of the total distance traveled by parts during their production. Versatile machines and the flexible process plans offer full routing flexibility that enable the same workpiece to be processed using alternative sequences of operations on alternative machines. Three mathematical programming (MP) models and a genetic algorithm (GA) are proposed to solve this problem. The proposed MP formulations include a mixed-integer nonlinear programming (MINLP) model and two mixed-integer programming (MIP) models, which offer different representations for the flexible process plans. The GA is integrated with linear programming for fitness evaluation and incorporates several adaptive strategies for diversification. The performances of these solution methods are tested through extensive numerical experiments. The MP models are evaluated on the basis of the exact solutions they yield as well as how they lend themselves for GA fitness evaluation. The GA–LP integration works successfully for this hard-to-solve problem.     

MOCACEF 1.0: Multiple objective capability based approach to form part-machine groups for cellular manufacturing applications

A pre-emptive goal programming formulation is developed for concurrently forming independent part/machine cells. Machine independent capability units, which are known as Resource Elements (RE), are used to define processing requirements of parts and processing capabilities of machine tools. Representation of unique and shared capability boundaries of machine tools is possible via RE, which increases the opportunity to form independent manufacturing cells and efficient utilization of them. RE-based operation sequences, processing times, capacities, demand, cell sizes, cell flexibility, load balance between cells, cell interaction, copies of each machine type in the job shop are all considered in the problem formulation. The model is solved by a specially developed tabu search algorithm.     

Manufacturing cells' design in consideration of various production factors

A cell formation problem is introduced that incorporates various real-life production factors such as the alternative process routing, operation sequence, operation time, production volume of parts, machine capacity, machine investment cost, machine overload, multiple machines available for machine types and part process routing redesigning cost. None of the cell formation models in the literature has considered these factors simultaneously. A similarity coefficient is developed that incorporates alternative process routing, operation sequence, operation time and production volume factors. Although very few studies have considered the machine capacity violated issue under the alternative process routing environment, owing to the difficulties of the issue discussed here, these studies fail to deal with the issue because they depend on some unrealistic assumptions. Five solutions have been proposed here and are used to cope with this difficulty. A heuristic algorithm that consists of two stages is developed. The developed similarity coefficient is used in stage 1 to obtain basic machine cells. Stage 2 solves the machine-capacity violated issue, assigns parts to cells, selects process routing for each part and refines the final cell formation solution. Some numerical examples are used to compare with other related approaches in the literature and two large size problems are also solved to test the computational performance of the developed algorithm. The computational results suggest that the approach is reliable and efficient in either the quality or the speed for solving cell formation problems.     

Design and scheduling of hybridmulti-cell flexible manufacturing systems

The objective of this paper is to minimize machine duplication by increasing its utilization, minimize intercell moves, simplify the scheduling problem and increase the flexibility of the manufacturing system. An integrated approach of design and scheduling alternative hybrid multi-cell flexible manufacturing systems (MCFMSs) in four steps will be presented in this paper. The first step is the implementation of branch and bound techniques which provide tools to design group technology (GT) cells. The second step is balancing the inter-cell workload of GT cells which leads to a hybrid MCFMS with better utilization of the machines. The problem of the exception machines and their utilization and workload balance will be solved within the MCFMScentre. Thus the performance of GT cells can be improved by transferring workloads from a congested (bottleneck) machine in one cell to an alternative one, a less congested (exception) machine in another cell within a group of GT cells forming a MCFMS centre. The third step is the group scheduling; a proposed heuristic method will be used for the scheduling of a family of parts with the objective of minimizing the maximum completion time of each part. The problem of scheduling under MCFMS can be reduced by considering the scheduling of each family of parts. Finally, the flexibility of the system will be enhanced by selecting appropriate machine tools and flexible material handling equipments. This approach is both effective and efficient-it has generated a hybrid MCFMS centre which includes several alternatives, for some benchmark problems in much shorter time than algorithms previously reported in the literature. In addition, the method is conceptually simple and easy to implement.     

Linguistic-based meta-heuristic optimization model for flexible job shop scheduling

In this paper, a linguistic based meta-heuristic modelling and solution approach for solving the Flexible Job Shop Scheduling Problem (FJSSP) is presented. FJSSP is an extension of the classical job-shop scheduling problem. The present problem definition is to assign each operation to a machine out of a set of capable machines ( the routing problem ) and to order the operations on the machines ( the sequencing problem ), such that a predefined performance measure is optimized. The scope of the problem is widened by taking into account the alternative process plans for each part ( process plan selection problem ) in the present study. Moreover, instead of using operations to represent product processing requirements and machine processing capabilities, machine independent capability units, which are known as Resource Elements (RE), are used. Representation of unique and shared capability boundaries of machine tools and part processing requirements is possible via RE. Using REs in scheduling can also reduce the problem size. The FJSSP is presented as a grammar and the productions in the grammar are defined as controls. Using these controls and the Giffler and Thompson (1960) priority rule-based heuristic, a simulated annealing algorithm is developed to solve FJSSP. This novel approach simplifies the modelling process of the FJSSP and enables usage of existing job shop scheduling algorithms for its solution. The results obtained from the computational study have shown that the proposed algorithm can solve this complex problem effectively within reasonable time. The results have also given some insights on the effect of the selection of dispatching rules and the flexibility level on the job shop performance. It is observed that the effect of dispatching rule selection on the job shop performance diminishes by increasing the job shop flexibility.     

Intelligent dispatching for flexible manufacturing

A decision rule for real-time dispatching of parts, each of which may have alternative processing possibilities, has been developed and tested in a simulated flexible manufacturing system. A part, upon completion of an operation, is not routed to a specific machine, but is, in effect, sent to a general queue. Thus, a machine has a global option for choosing parts which in turn may be processed on alternative machines. For effective use of the system's routeing flexibility under these circumstances, the machine needs an intelligent part-selection strategy (rather than shallow heuristics represented by the conventional dispatching rules) that takes into account the current state and trends of the system. The proposed intelligent reasoning procedure has been found to achieve better shop performance than some of the popular dispatching rules, the improved performance being due to the ability to respond to changing circumstances.     

复合进给电解加工机床控制系统设计与测试

为解决航空制造领域复杂零件的加工难题，针对研制的复合进给电解加工机床，开发了基于PC（ personal computer，个人计算机）和PMAC（programmable multi-axles controller，可编程多轴控制器）运动控制卡的开放式数控系统。基于虚拟仪器技术及其开发环境LabVIEW平台，遵循模块化设计思路，采用ActiveX自动化技术和CLF (call library function，调用库函数)节点设计了复合进给电解加工机床控制系统的人机交互界面，通过调用PMAC运动控制卡中的服务程序PmacServer，实现上位机与PMAC运动控制卡之间的功能交互。为了验证该控制系统的可靠性和运行稳定性，使用激光干涉仪进行了实验测试。实验结果显示，该控制系统响应迅速，运行稳定，人机交互界面易于操作；机床运动误差控制在-5~5 μm内，重复定位误差小于2.3 μm，能够满足航空发动机叶片的电解加工精度要求。研究结果在电解加工领域具有重要工程应用价值，可以为新一代高性能电解加工机床的设计提供参考。     

Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing

This paper deals with the design and loading of Cellular Reconfigurable Manufacturing Systems in the presence of alternative routing and multiple time periods. These systems consist of multiple reconfigurable machining cells, each of which has Reconfigurable Machine Tools and Computer Numerical Control (CNC) machines. Each reconfigurable machine has a library of feasible auxiliary machine modules for achieving particular operational capabilities, while each CNC machine has an automatic tool changer and a tool magazine of a limited capacity. The proposed approach consists of two phases: the machine cell design phase which involves the grouping of machines into machine cells, and the cell loading phase that determines the routing mix and the tool and module allocation. In this paper, the cell design problem is modelled as an Integer Linear Programming formulation, considering the multiple process plans of each part type as if they were separate part types. Once the manufacturing cells are formed, a Mixed Integer Linear Programming model is developed for the cell loading problem, considering multi-period demands for the part types, and minimising transportation and holding costs while keeping the machine and cell utilisations in each period, and the system utilisation across periods, approximately balanced. An illustrative problem and experimental results are presented.     

Production planning for flexible flow systems with limited machine flexibility

A flexible manufacturing system (FMS) is highly capital-intensive and FMS users are concerned with achieving high system utilization. The production planning function for setting up an FMS prior to production should be developed in order to make the most of the potential benefits of FMSs. We consider two production planning problems of grouping and loading a flexible flow system, which is an important subset of FMSs where the routing of parts is unidirectional. We show that considering this routing restriction as well as limited machine flexibility strongly affects both the solution techniques and the quality of the solutions. Because of the complexity of the problem, we present a heuristic approach that decomposes the original problem into three interrelated subproblems. We show that the proposed approach usually finds a near-optimum solution and is superior to an approach that exists in the literature of FMS production planning. We also introduce effective heuristic methods for two new subproblems that arise because of the unidirectional flow precedence and flexibility constraints. Computational results are reported and future research issues are discussed.     

Compensation of systematic errors in five-axis high-speed machining

A method is described for the compensation of errors associated with tool path generation, particularly during five-axis high-speed machining (HSM). Information on machine tool performance and its dynamic features is used to calculate possible errors and convenient modifications of the NC program, thereby avoiding errors when parts are actually being machined. This 'preprocess method' by means of postprocessing with NC software is presented. The errors dealt with are mainly servo lag errors, but the explored approach can support most systematic errors associated with machine tool performance. These are briefly summarized. Research so far has largely been aimed at the implementation of compensation routines in the CNC controller and at corrections in real time. The problem is that most applications are only available for three-axis milling. The presented approach (compensation before machining by using software routines in a specially designed postprocessor) is based on a fuzzy logic expert system. The benefits can be summarized as data reduction, data improvement, precontrol of feed, and improved component accuracy. The applied procedure is also convenient for implementation in an industrial environment by retrofitting existing equipment. The suggested method provides improved control over machine dynamics, permitting high-speed machining centres to maintain a maximum or near-maximum feed rate despite axis reversals and tool path changes, even at corners. Two categories of results are presented, namely the management of NC data related to expected performance of the machine tool and improvements of the machine tool performance in terms of productivity and accuracy of the machined test components.     

A methodology for designing flexible cellular manufacturing systems

Cell formation in cellular manufacturing deals with the identification of machines that can be grouped to create manufacturing cells and the identification of part families to be processed within each cell. Dynamic and random variations in part demands can negatively impact cell performance by creating unstable machine utilizations. The purpose of this paper is to introduce and illustrate an interactive cell formation method that can be used to design 'flexible' cells. Flexibility in this context refers to routing flexibility (i.e., the ability for the cellular system to process parts within multiple cells) and demand flexibility (i.e., the ability of the cell system to respond quickly to changes in part demand and part mix). Through an experimental analysis using multiple data sets, we also validate the procedure and provide guidelines for parameter settings depending upon the type of flexibility of interest to the user. Finally, trade-offs and interdependences between alternative types of flexibility in the context of cellular systems are illustrated.     

Adaptive scheduling and tool flow control in flexible job shops

The recent manufacturing environment is characterized as having diverse products due to mass customization, short production lead-time, and ever-changing customer demand. Today, the need for flexibility, quick responsiveness, and robustness to system uncertainties in production scheduling decisions has dramatically increased. In traditional job shops, tooling is usually assumed as a fixed resource. However, when a tooling resource is shared among different machines, a greater product variety, routing flexibility with a smaller tool inventory can be realized. Such a strategy is usually enabled by an automatic tool changing mechanism and tool delivery system to reduce the time for tooling set-up, hence it allows parts to be processed in small batches. In this paper, a dynamic scheduling problem under flexible tooling resource constraints is studied and presented. An integrated approach is proposed to allow two levels of hierarchical, dynamic decision making for job scheduling and tool flow control in flexible job shops. It decomposes the overall problem into a series of static sub-problems for each scheduling horizon, handles random disruptions by updating job ready time, completion time, and machine status on a rolling horizon basis, and considers the machine availability explicitly in generating schedules. The effectiveness of the proposed dynamic scheduling approach is tested in simulation studies under a flexible job shop environment, where parts have alternative routings. The study results show that the proposed scheduling approach significantly outperforms other dispatching heuristics, including cost over time (COVERT), apparent tardiness cost (ATC), and bottleneck dynamics (BD), on due-date related performance measures. It is also found that the performance difference between the proposed scheduling approach and other heuristics tend to become more significant when the number of machines is increased. The more operation steps a system has, the better the proposed method performs, relative to the other heuristics.     

Effects of flexibility and scheduling decisions on the performance of an FMS: simulation modelling and analysis

This paper focuses on a simulation-based experimental study of the effects of routing flexibility, sequencing flexibility, and part sequencing rules on the performance of a typical FMS. Three routing flexibility levels, five sequencing flexibility levels, and four scheduling rules for part sequencing decision are considered for detailed investigation. The system work load characterised by the mean interarrival time of parts has been set at different levels. The performance of the FMS is evaluated using various measures related to flow time and tardiness of parts. The simulation results are subjected to statistical analysis. Multiple regression-based metamodels have been developed using the simulation results. The analyses of results reveal that deterioration in system performance can be minimised substantially by incorporating either routing flexibility or sequencing flexibility or both. However, the benefits of either of these flexibilities diminish at higher flexibility levels. When flexibility exists, part sequencing rules such as the earliest due date and earliest operation due date provide a better performance for all the measures.     

On the performance of hybrid multi-cell flexible manufacturing systems

Industrial experience has shown that it is virtually impossible to implement a large-scale flexible manufacturing system (FMS) without using the group technology manufacturing concept. However, grouping machines into product cells can limit the FMS flexibility. Thus when the production cells are not completely disjoint, problems under multi-cell flexible manufacturing systems (MCFMS) can be caused by changes in job mix and demand which lead to a workload imbalance both between cells and between machine centres within the same cell. The problems can be mitigated and shop performance improved by transferring workloads from a congested machine centre in one cell to an alternative, less congested machine centre in another cell. Such inter-cell workload transfer results in a hybrid MCFMS which is a cross between a parts similarity-based MCFMS and a process similarity-based MCFMS. Results of a simulation study carried out by the author show that inter-cell workload transfer is very effective in improving shop performance. This paper briefly describes the simulation study and discusses the implications of its results for the design and operation of FMSs. The operational viability, and economic feasibility of hybrid MCFMSs are also discussed in the paper.     

Bicriteria robotic cell scheduling with controllable processing times

The current study deals with a bicriteria scheduling problem arising in an m-machine robotic cell consisting of CNC machines producing identical parts. Such machines by nature possess the process flexibility of altering processing times by modifying the machining conditions at differing manufacturing costs. Furthermore, they possess the operational flexibility of being capable of processing all the operations of these identical parts. This latter flexibility in turn introduced a new class of robot move cycles, called pure cycles, to the literature. Within the restricted class of pure cycles, our task is to find the processing times on machines so as to minimise the cycle time and the manufacturing cost simultaneously. We characterise the set of all non-dominated solutions for two specific pure cycles that have emerged as prominent ones in the literature. We prove that either of these pure cycles is non-dominated for the majority of attainable cycle time values. For the remaining regions, we provide the worst case performance of one of these two cycles.     

Three-dimensional profile curve machining on three-axis machines

Presented in this paper is a tool path generation procedure for three-dimensional profile curve machining on three-axis machines, which is essential for making dies of automotive press panels. While sculptured surface machining has received a significant amount of attention, there has been very little work on profile curve machining. The most distinctive feature of profile curve machining is that the machine operator determines the exact cutter radius at the stage of numerical control (NC) machining. For this reason, profile curve machining usually makes use of the cutter radius compensation functionality of an NC controller. In this paper, four technological requirements for the profile curve machining are identified: (1) maintaining a constant machining width; (2) avoiding controller alarms; (3) avoiding unbalanced cutter wear; and (4) retaining down-milling. To satisfy these requirements, a tool path generation procedure is proposed, implemented and tested.     

基于有限元分析的薄壁圆环零件加工工艺研究

目的 针对薄壁圆环零件刚性差、强度弱、加工过程中易发生受力变形的难题,基于薄壁圆环零件加工成形工艺,优化零件的加工工艺和装夹方式。方法 考虑到工艺对零件加工质量的影响,对零件的加工方法和装夹方式进行研究,提出一种新的加工工装,运用ANSYS软件对零件装夹受力情况和振动变形进行有限元模拟仿真分析。结果 该工装不仅能够防止零件发生应力集中,还提升了零件加工精度和表面质量,工装设计为一夹一顶方式,只需调整顶尖压紧力便可确保圆环件在加工中不会发生变形,同时拆装方便,提高了生产效率。结论 对于薄壁圆环件的数控加工,可通过科学设计零件加工工艺流程和装夹工装,解决零件受力变形问题,保证薄壁圆环零件的尺寸、形位公差和表面粗糙度符合要求,提高了生产加工效率,满足产品批量生产使用要求,为类似薄壁件的加工提供了参考。     

Machining Parameter Optimization with Lot Size Considerations

The research literature on metal cutting contains numerous papers on optimizing machining parameters for maximum production rate or minimum production cost. Analyses presented in the literature, however, have been limited to conditions of “steady-state” manufacture (i.e., a large number of parts were to be produced). In today's metal cutting industry, over ninety percent of all parts are produced in lots of thirty or less. This implies that steady-state manufacturing may never be reached. This paper introduces lot size information into the selection of machine operating rates. A solution procedure is presented for the single decision variable (machine speed) case. An example problem is also presented to illustrate the gains that can be attained using lot size information.     

An Artificial Intelligence Approach to the Scheduling of Flexible Manufacturing Systems

Scheduling in a flexible manufacturing system (FMS)must take into account the shorter lead-time, the multiprocessing environment, the flexibility of machine tools, and the dynamically changing states. The scheduling approach described in this paper employs a knowledge-based system to carry out the nonlinear planning method developed in artificial intelligence. The state-space process for plan-generation, by either forward- or backward-chaining, can handle scheduling requirements unique to the FMS environment. A prototype of this scheduling system has been implemented on a LISP machine and is applied to solve the scheduling problem in flexible manufacturing cells. This scheduling method is characterized by its knowledge-based organization, symbolic representation, state-space inferencing, and its ability for dynamic scheduling and plan revision. It provides a foundation for integrating intelligent planning, scheduling, and machine learning in FMSs.