Experimental investigation of flexible manufacturing system scheduling decision rules

This paper reports the results of an experimental investigation of scheduling decision rules for a dedicated flexible manufacturing system. A simulation model of an existing flexible manufacturing system (FMS) comprised of 16 computer numerical controlled machines (CNC) was constructed using actual operation routings and machining times to evaluate the performance of various part loading and routing procedures. The results indicate that FMS performance is significantly affected by the choice of heuristic parts scheduling rules.     

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.     

Two FMS scheduling methods based on Petri nets: A global and a local approach

We are interested in the Flexible Manufacturing System (FMS) scheduling problem. Different methods have been explored to solve this problem and to master its combinatorial complexity, which is NP-hard in the general case. In this paper we will give two different scheduling methods based on Petri nets. The first one tends to solve the general scheduling problem (acyclic schedule) using the Constraint Programming method to avoid exhaustive search. The second method is a dedicated cyclic scheduling method. The aim is not to compare the methods' performances (computation time, results' quality) because they do not solve exactly the same problem, but to compare their application domains in terms of parts number.     

Flexibility trade-offs in a random flexible manufacturing system: A simulation study

Flexible manufacturing systems (FMSs) are allowing firms to take advantage of diversified, low volume production of products with short life-cycles. The flexibility provided by an FMS improves the ability of a system to respond to change. Several types of manufacturing flexibility (M F) have been identified in the literature. Ideally, it is desirable to provide an FMS with all types of flexibility. However, there is a general consensus on the discordant nature of some of the flexibilities. This makes it imperative for management to recognize which flexibilities it deems critical to the manufacturing strategy of the firm. This allows the management to trade-off some of the less important flexibilities for the more important ones, as the need arises.

This study is an attempt toward an empirical examination of the flexibility trade-offs in an FMS. By using computer simulation, we study the flexibility tradeoffs in the stochastic environment of a random FMS. Various configurations of the FMS are simulated under the influence of a variety of loading and dispatching strategies. The results show that there is a trade-off among the various flexibility types under most circumstances. However, some scenarios illustrate that an appropriate combination of the variables like scheduling environment, product variety, and system configuration, can be effective in containing these trade-offs. In other cases, it is seen that the FMS can accommodate more than one flexibility type simultaneously.     

A genetic algorithm-based approach to machine assignment problem

Over the last few decades, production scheduling problems have received much attention. Due to global competition, it is important to have a vigorous control on production costs while keeping a reasonable level of production capability and customer satisfaction. One of the most important factors that continuously impacts on production performance is machining flexibility, which can reduce the overall production lead-time, work-in-progress inventories, overall job lateness, etc. It is also vital to balance various quantitative aspects of this flexibility which is commonly regarded as a major strategic objective of many firms. However, this aspect has not been studied in a practical way related to the present manufacturing environment.

In this paper, an assignment and scheduling model is developed to study the impact of machining flexibility on production issues such as job lateness and machine utilisation. A genetic algorithm-based approach is developed to solve a generic machine assignment problem using standard benchmark problems and real industrial problems in China. Computational results suggest that machining flexibility can improve the overall production performance if the equilibrium state can be quantified between scheduling performance and capital investment. Then production planners can determine the investment plan in order to achieve a desired level of scheduling performance.     

Simulation modelling and analysis of scheduling in robotic flexible assembly cells using Taguchi method

Due to increasing competition in the developing global economy, today’s companies are facing greater challenges than ever to employ flexible manufacturing systems (FMS) capable of dealing with unexpected events and meeting customers’ requirements. One such system is robotic flexible assembly cells (RFACs). There has been relatively little work on the scheduling of RFACs, even though overall scheduling problems of FMS have attracted significant attention. This paper presents Taguchi optimisation method in conjunction with simulation modelling in a new application for dynamic scheduling problems in RFACs, in order to minimise total tardiness and number of tardy jobs (N_T). This is the first study to address these particular problems. In this study, Taguchi method has been used to reduce the minimum number of experiments required for scheduling RFACs. These experiments are based on an L9 orthogonal array with each trial implemented under different levels of scheduling factors. Four factors are considered simultaneously: sequencing rule, dispatching rule, cell utilisation and due date tightness. The experimental results are analysed using an analysis of mean to find the best combination of scheduling factors and an analysis of variance to determine the most significant factors that influence the system’s performance. The resulting analysis shows that this proposed methodology enhances the system’s scheduling policy.     

The part mix and routing mix problem in FMS: a coupling between an LP model and a closed queueing network

In the near future many companies will face the problem of the optimal use of newly installed manufacturing technology (e.g. a flexible manufacturing system or FMS). Very often this will involve decisions on what parts to produce using the new system (the part mix problem) and how to produce these parts (the routing mix problem). We show that traditional operational research tools such as linear programming and queueing network theory are well suited to tackle these problems. In particular, LP models are combined with queueing network models in an iterative procedure. As such the strengths of both techniques can be exploited in making optimal use of the part mix and routing mix flexibility of the FMS.     

Scheduling of machines and automated guided vehicles in FMS using differential evolution

This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). For solving this problem, a new meta-heuristic differential evolution (DE) algorithm is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimise the makespan will result in a FMS being able to complete all the jobs assigned to it at the earliest time possible, thus saving resources. An increase in the performance of the FMS under consideration would be expected as a result of making the scheduling of AGVs as an integral part of the overall scheduling activity. The algorithm is tested by using problems generated by various researchers and the makespan obtained by the algorithm is compared with that obtained by other researchers and analysed.     

Technology choice and capacity expansion with two product families: tradeoffs between scale and scope

Recent developments in modern technologies such as CIM, FMS and CAD provide a great degree of operational flexibility and permit production of a variety of products with little or no changeover costs. In contrast, dedicated technologies with specialized equipment are designed to produce a limited range of products more efficiently. In this paper, we examire the tradeoffs between scale and scope economies in a two-product environment with general, dynamic demand patterns. We use a discrete period, finite horizon mathematical program to determine the optimal mix of dedicated and flexible technologies. Since the problem is difficult to solve optimally, we develop a two-phased heuristic procedure to obtain good expansion plans that determine type of technologies and amount of capacity additions. These procedures are based on easily solvable subproblems derived from the planning problem. Our computational results suggest that the methods work well and provide acceptable solutions with reasonable effort.     

A constructive heuristic algorithm for concurrently selecting and sequencing jobs in an FMS environment

This paper deals with the concurrent solution of the loading and scheduling problems in a flexible manufacturing system ( FMS) environment. It is assumed that the FMS environment has production planned periodically and each job in the system has a number of operations to be processed on flexible machines. A heuristic approach using a constructive scheduling method is developed to solve the FMS loading and scheduling problems concurrently. The computational results are compared to an existing procedure that considers a hierarchical approach with a similar problem environment. The comparison study shows a significant improvement over the existing hierarchical procedure. This experiment indicates that a concurrent solution approach can solve the FMS loading and scheduling problems very effectively.     

An experimental study of human decision-making in computer-based scheduling of flexible manufacturing system

This paper describes a study which explores human decision-making abilities in scheduling and dispatching of a flexible manufacturing system (FMS) An experiment is described, using an FMS, in which subjects make scheduling and dispatching decisions using a real-time interactive computer-simulation based system. The experimental results demonstrate that human decision-making is superior to general dispatching rules. An explanation of these results and an analysis of subjects' behaviour is presented in the light of information obtained from verbal protocol data     

Distance-based fuzzy MCDM approach for evaluating flexible manufacturing system alternatives

Considering the high required capital outlay and moderate risk of a flexible manufacturing system (FMS) investment, economic justification techniques are insufficient by themselves since they cannot cope with the benefits such as flexibility and enhanced quality offered by advanced manufacturing technologies. A robust decision-making procedure for evaluating FMS requires the consideration of both economic and strategic investment measures. A distance-based fuzzy multicriteria decision-making (MCDM) framework based on the concepts of ideal and anti-ideal solutions is presented for the selection of an FMS from a set of mutually exclusive alternatives. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The multicriteria decision approach presented here enables us to incorporate data in the forms of linguistic variables, triangular fuzzy numbers and crisp numbers into the evaluation process of FMS alternatives. Linguistic variables are also used to indicate the criteria's importance weights assigned by the decisionmakers. A comprehensive example illustrates the application of the multicriteria decision analysis.     

On the feasibility of sequence-dependent economic lot scheduling problem

Most of the literature dealing with the determination of cyclic part input sequences in a flexible flow system is restricted in that it only searches for input sequences that are permutations of the minimal part set (MPS). This study is unique in that it investigates input sequences generated by integer programming (IP) formulations that balance or unbalance machine workloads to help maximize overall machine utilization (Stecke 1992). Also, this study integrates the input sequence determination decision with the part mix ratio determination, within the overall framework of a flexible approach to FMS operation over time. A simulation model of a flexible flow system was designed to study the effects on overall machine utilizations caused by utilizing alternative part mix ratios to help determine input sequences. The procedures used to determine the part mix ratios include IP formulations and those that are generated randomly, including the MPS mix ratios. Three different experimental settings are used to test these effects as well as (I) the robustness of the part input sequences that can be derived from the IP generated mix ratios, and (2) the relative importance of the part mix ratio decision in relation to the part input sequence determination. A new FMS physical design that can also be easily modelled to capture look-ahead capability proved to be simple and effective. Several significant conclusions regarding part mix ratios, pan input sequences, and look-ahead capability are revealed. These include: (1) the determination of the part mix ratios proved to be more significant in improving FMS performance than the determination of part input sequences; (2) the robust nature of the IP formulations was demonstrated; and (3) look-ahead capability provides equally high overall machine utilizations at lower levels of work-in-process. Future research areas are presented that would help validate and extend the observations found in this study.     

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.     

Investigations into the impact of flexibility on manufacturing performance

This paper provides investigative insights into the impact of routeing flexibility, machine flexibility, and product-mix flexibility on the performance of a manufacturing plant. The study employs simulation modelling as the primary tool. The facility modelled is an automobile engine assembly plant consisting of a FMS (flexible manufacturing systems), job shop, and assembly line. A variety of experiments, with the FMS exhibiting one or more of the above three flexibilities at different levels, were simulated on the model. In each experiment the manufacturing performance as given by flow time and work-in-process inventory was tracked. The experiments focused first on the FMS itself, and then on the entire plant. Measures for the three flexibilities are introduced. The simulation results are analysed in detail. The results indicate significant performance benefits in context of the FMS, but little in context of the overall plant     

A comparison of tool management strategies and part selection rules for a flexible manufacturing system

An important element in the successful operation of flexible manufacturing systems (FMS) is the management of the tooling component. This paper reports on one aspect of tool management for FMS operations. Four tool allocation and scheduling strategies are compared in the presence of three part selection rules through a simulation study of a five-machine FMS with an automated tool handling system. The tool allocation strategies are similar to those used in industry while the part selection rules are synthesized from the literature on FMS scheduling under tooling constraints. The use of different tooling strategies produces significantly different outcomes in FMS performance.     

A tabu search algorithm for simultaneous machine/AGV scheduling problem

Machines and automated guided vehicles (AGVs) scheduling problems are two essential issues that need to be addressed for the efficiency of the overall production system. The purpose of this paper is to study the simultaneous scheduling problem of machines and AGVs in a flexible manufacturing system (FMS) since the global optimum cannot be reached by considering each of them individually. In this paper, a mixed integer linear programming (MILP) model is developed with the objective of makespan minimisation. The MILP model consists of the following two constraint sets: machines and AGVs scheduling sub-problems. As both sub-problems are known to be NP-hard, a heuristic algorithm based on tabu search (TS) is proposed to get optimal or near to optimal solution for large-size problems within reasonable computation time. The proposed algorithm includes a novel two-dimensional solution representation and the generation of two neighbour solutions, which are alternately and iteratively applied to improve solutions. Moreover, an improved lower bound calculation method is introduced for the large-size problems. Computational results show the superior performance of the TS algorithm for the simultaneous scheduling problem.     

Multi-criteria optimisation-based dynamic scheduling for controlling FMS

This study deals with controlling flexible manufacturing systems (FMS) operating in volatile production environments. Most studies that address this issue use some sort of adaptive scheduling that enables the FMS to cope with the randomness and variability efficiently. The methods presented in the literature are usually based on heuristics and use simple dispatching rules. They do not consider changing the decision criteria dynamically as the system conditions change. In contrast to previous studies, the present study focuses on developing a control mechanism for dynamic scheduling that is based on incremental optimisation. This means that each time a scheduling decision is made, the local optimisation problem is solved such that the next jobs to be processed on machines are selected. The objective function (dominant decision criterion) for this optimisation problem is selected dynamically based on production order requirements, actual shop-floor status and system priorities. The proposed multi-criteria optimisation-based dynamic scheduling methodology was evaluated and compared with some known scheduling rules/policies. The results obtained demonstrate the superiority of the suggested methodology as well as its capability to cope with a multi-criteria environment.     

The effect of routing flexibility on a flexible system of integrated manufacturing

Flexible manufacturing systems (FMSs) have gained consideration due to their ability to produce customised and an increasing variety of products with shorter life cycles. A considerable amount of research has been done on manufacturing flexibility from different angles. There are many different types of manufacturing flexibility being reported in the literature, and routing flexibility is one of them. The paper focuses on the study of routing flexibility in a flexible system of integrated manufacturing (FSIM) from the view of real-time control strategies. However, flexibility incurs cost hence a judicious decision is required for implementing the right level of flexibility under a different operating environment. The paper studies the impact of routing flexibility and control strategies on the performance of FSIM. The application of discrete event simulation and Taguchi's method is applied to study the various factors contributing to FSIM performance and identifies the vital parameters for improving performance. Furthermore, the most significant factor is determined by using the analysis of variance (ANOVA). The result shows that increasing routing flexibility cannot be treated as a key role in system improvement. It is also found that there is the influence of control strategies on the performance of FSIM. Finally, it is observed that, the impact on the system performance due to the system load condition is the largest, and that of the number of pallets is the smallest.     

A financial model of flexible manufacturing systems planning under uncertainty: identification,valuation and applications of real options

Flexible manufacturing systems (FMS) have been considered to be essential for manufacturers to succeed in the uncertain market place. Flexibility typically comes at a price and is only valuable as a hedge against environmental uncertainty. It is important to determine an appropriate level of flexibility in the production system while considering the tradeoffs between its costs and benefits. This paper proposes to apply a real option theoretic approach to the modeling and analysis of various types of uncertainty involved in an FMS's operational environment. In comparison with financial options, real options in the context of an FMS, namely, production options, are identified and accordingly a pricing model for production options is proposed based on the option theory. Based on the valuation of production options, a general framework of flexibility planning is formulated. The real option approach surmounts traditional discounted cash flow analysis based valuation methods that tend to ignore the upside potentials to an investment from management flexibility. The proposed model is tested in a refrigerator company that deals with high product variety and uncertain demand.