Tool planning models for flexible manufacturing systems

Although the tool loading problem for Flexible Manufacturing Systems (FMSs) has been analyzed in the past, the tool planning problem, the basis of tool management, has largely been ignored. In this paper, the interface between tool planning and the FMS loading and routing decisions is analyzed. It is shown that tool policy has a pronounced effect on the flexibility and the planned makespan of an FMS. A tool planning model is developed and integrated into an overall FMS detailed tool loading and part routing procedure. This model while considerably reducing the number of tools required (by 55%) matches the performance of a policy that equips each machine with all tools in terms makespan, routing flexibility, and tool productivity.     

A scoring model for flexible manufacturing systems project selection

This paper presents a method for identifying, evaluating, and prioritizing manufacturing modernization projects. The paper distinguishes between modernization, which contains significant uncertainty, and capital replacement which contains minimal risk. Extending classical capital budgeting analysis, which prioritizes capital replacement projects by the criterion of utility maximization, the model described herein addresses the complexities of non-economic criteria, project interdependence, and uncertainty. Exploiting results from risk-oriented R & D project selection literature, the model incorporates the scores of five additive terms: technology assessment, equipment evaluation, capacity elasticity, cost-budget analysis, and adjusted net present value. The technology and equipment scores are based on evaluative scales. The paper introduces the workload elasticity of capacity statistic for the analysis of forecasted workload and plant capacity. The model analyses expected costs and budget levels in the cost-budge ratio submodel. Finally, the model explicitly incorporates conditional probabilities into the adjustment of NPV, to address interdependency and uncertainty.     

Inspection sequencing and part scheduling for flexible manufacturing systems

An approach to the study of integrated effects of inspection sequencing rules and part scheduling policies in flexible manufacturing settings is presented. Simulation experiments were carried out to examine 5 inspection sequencing heuristics while considering 8 different part scheduling policies in a typical FMS construct. Analyses of data have shown that the inspection sequencing has a significant impact on FMS performance, and the selection of a part scheduling policy relies heavily on the inspection plan implemented in the system. The results of this study sustain the need to explore total issues of an FMS, if possible, rather than a piecemeal approach which usually falls short when pursuing a global system optimization.     

Scheduling methods for a class of flexible manufacturing systems

Scheduling methods are proposed for a class of flexible manufacturing systems consisting of machine centers served by a cyclic conveyor. The minimization of finish time is considered as the optimization criterion. An optimal algorithm is proposed for the minimum conveyor speed (S=1) for a particular system in the class under consideration. Scheduling algorithms based on a job matching principle, that are developed for the general systems, yield good results particularly for low conveyor speeds.This research is supported in part by NSERC Grant A4619 and Manufacturing Research Corporation of Ontario.     

Auxiliary tool allocation in flexible manufacturing systems

This paper analyses a new approach to the machine loading problem arising in flexible manufacturing systems (FMSs). This approach allows the operations to be assigned to machines assuming that machines have access to all the tools required for their operations. This exploits the flexibility of the FMS completely. Next an allocation of tools to machines is determined which satisfies the tool requirements for each machine and minimizes the total number of tools. Thus this approach minimizes the unnecessary tool duplications in the system and maximizes the tool utilization. The problem is modeled as an integer linear program (ILP). We notice that the main problem has a block diagonal structure which is decomposable by relaxing a set of linking constraints. Each separated sub-problem represents a problem of allocation of a single type of tools. We develop a branch-and-bound based exact solution procedure and three heuristic procedures to solve the sub-problems. Our lower bounding approach uses Lanrangean relaxation. The solutions to the Lagrangean relaxation are further used to determine the branching sequences and to develop heuristic approaches. Since finding even a feasible solution to the main problem is NP-hard, we develop only enumerative procedures to solve the main problem. Finally, these solution procedures are tested on randomly generated test problems.     

Dynamic material handling for a class of flexible manufacturing systems

A real-time hierarchical routing control scheme for a large class of material handling systems is presented. The higher level (coordinator) performs resource allocation tasks and supplies parameter values to the lower (local control) level. The lower level operates in an autonomous (without continuous supervision) and distributed fashion. If state information is made available to the coordinator, the routing strategy can furthermore be adaptively adjusted.     

A technique for on-line sensitivity analysis of flexible manufacturing systems

The recent perturbation analysis approach to discrete event systems is applied to flexible manufacturing systems (FMS). While analytic (queueing) models are useful in preliminary design of such systems, they are not accurate enough at the detailed design/operation stage. Thus, experimentation on detailed simulations or on the actual system has been the way to optimize system performance. Perturbation analysis allows us to derive the sensitivity of system performance, with respect to several design/operating parameters, by observing a single experiment (and without having to actually alter the parameters — often a costly operation). Thus, observation of one experiment can give accurate directions for the improvement of several parameter values. Here we give a simulation example illustrating how perturbation analysis could be used on-line on an FMS to improve its performance, including reducing its operating cost. Experimental results are also presented validating the estimates obtained from this technique.Work supported by U.S. Office of Naval Research Contracts N00014-75-C-0648 and N00014-79-C-0776, and NSF Grant ENG78-15231, at Harvard University.A preliminary version of this paper appeared in the Proc. 1st ORSA/TIMS Conf. on Flexible Manufacturing Systems, August 1984. This version includes two appendices, which relate to implementation of the technique described in the main body of the paper.     

Algorithms for part and machine selection in flexible manufacturing systems

Deciding whether FMS technology is viable for a given application, and if so, what machines should comprise the FMS and what parts should be produced on it, can be a difficult task. Manual methods suffice only for situations where a small number of FMS-type machines are to be considered and less than a few dozen candidate parts are to be chosen from. When both machines and parts are to be selected from a larger number of candidates, manual methods become cumbersome and time consuming, and computer-based decision aids become a necessity. This paper gives an overview of the required decision process, and then focuses on those stages for which computer-based decision aids can be used effectively. Particular decision aids are described, and case studies are cited to illustrate their motivation and use.     

Impact of flexible machines on automated manufacturing systems

Although the problem of scheduling dynamic job shops is well studied, setup and changeover times are often assumed to be negligibly small and therefore ignored. In cases where the product mix changes occur frequently, setup and changeover times are of critical importance. This paper applies some known results from the study of multi-class single-server queues with setup and changeover times to develop an approximation for evaluating the performance of job shops. It is found that the product mix, setup and changeover times, and scheduling rules affect the performance significantly, in particular at high levels of machine utilisation. This approach could be used to determine the required level of flexibility of machines and to choose an appropriate scheduling policy such that production rates remain within acceptable limits for foreseeable changes in the product mix.     

The part families problem in flexible manufacturing systems

Parts grouping into families can be performed in flexible manufacturing systems (FMSs) to simplify two classes of problems: long horizon planning and short horizon planning. In this paper the emphasis is on the part families problem applicable to the short horizon planning. Traditionally, parts grouping was based on classification and coding systems, some of which are reviewed in this paper. To overcome the drawbacks of the classical approach to parts grouping, two new methodologies are developed. The methodologies presented are very easy to implement because they take advantage of the information already stored in the CAD system. One of the basic elements of this system is the algorithm for solving the part families problem. Some of the existing clustering algorithms for solving this problem are discussed. A new clustering algorithm has been developed. The computational complexity and some of the computational results of solving the part families problem are also discussed.     

Evaluation of entropy-based dispatching in flexible manufacturing systems

Traditionally, part dispatching has been done using static rules, rules that fail to take advantage of the dynamic nature of today’s manufacturing systems. In modern manufacturing systems, machines carry multiple tools so parts have the option of being machined at more than one machine. This flexibility, termed routing flexibility in the literature, opens up new possibilities for shop floor planners for the scheduling and dispatching of parts.     

Managing production with flexible capacity deployment for serial multi-stage manufacturing systems

This paper presents a model for serial multi-stage manufacturing systems facing variability from two sources. One source is demand uncertainty; the other is manufacturing uncertainty associated with all manufacturing stages. A production control policy based on the planned lead time and the manufacturing capacity requirement is developed. It is shown that this production control policy has the effect of reducing the variance of production output for all manufacturing stages. Some specific analyses are provided to illustrate the production control policy developed. The model developed provides a vehicle for examining the interrelationships among the production output, the planned lead time and the actual manufacturing flow time. The risk-pooling value over both demand randomness and manufacturing uncertainty, which is achieved through consolidating some manufacturing capacity and deploying flexible capacity among the manufacturing stages, is analyzed. This risk-pooling value can be realized in the form of either reduced manufacturing flow time or increased effective capacity to meet more demand. It is shown that the risk-pooling value increases as the planned lead time decreases.     

A Tabu search-based approach for scheduling job-shop type flexible manufacturing systems

The problem of scheduling parts in a job-shop type flexible manufacturing system (FMS) is investigated when each part can have alternative process plans and each operation required of a part can be performed on alternative machines. The mixed-(binary) integer programming model developed for the problem is proven strongly NP-hard. A higher-level heuristic solution algorithm based on a concept known as ‘tabu search’ is developed to determine the best (near-optimal) solution for problems of industrial merit. A comparison of six different versions of tabu search-based heuristics (TSH 1-TSH 6) is performed to investigate the impact of using long-term memory and the use of fixed versus variable tabu-list sizes. A carefully constructed statistical experiment, based on randomized complete-block design, is used to test the performance on four problem structures ranging from 4–14 parts. The results show that, as the problem size increases, TSH 3 with fixed tabu-list size and long-term memory is preferred over the other heuristics. Further, the branch-and-bound technique, by failing to identify as good a solution as that determined by the heuristics (TSH 1-TSH 6), let alone an optimal solution, for a small problem reinforces the need for developing efficient heuristics for solving real problems encountered in industry practice.     

A supervisory control paradigm for real-time control of flexible manufacturing systems

Most of the current academic flexible manufacturing system (FMS) scheduling research has focused on the derivation of algorithms or knowledge-based techniques for efficient FMS real-time control. Here, the limitations of this view are outlined with respect to effective control of actual real-time FMS operation. A more realistic paradigm for real-time FMS control is presented, based on explicit engineering of human and automated control functions and system interfaces. To illustrate design principles within the conceptual model, an example of algorithmic and operator function models for a specific real-time FMS control problem are developed.Portions of this paper have appeared in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, Ann Arbor, Michigan, August 12–15, 1986, and Proc. 1986 Int. Conf. on Systems, Man, and Cybernetics, Atlanta, Georgia, October 14–17, 1986.This research was supported in part by the New Faculty Research Program of the Georgia Institute of Technology.     

Grouping of parts and components in flexible manufacturing systems

In this paper, the problem of grouping of parts and components in flexible manufacturing systems is discussed. The actual grouping is done by modelling the problem as an optimal k-decomposition of weighted networks. Algorithms which are suitable for computer implementation and large problems are developed to find an initial solution and for refining this solution. Bounds on algorithm performance are constructed to give an estimate of the quality of the generated solution. A numerical example illustrates these new techniques.