Taguchi's Method Analysis of an FMS Under Review-Period-Based Operational Controls: Identification of Control Periodicity

Flexibility of flexible manufacturing systems (FMSs) has been considered as an effective tool to compete in the present manufacturing environment. Enormous research efforts have been made to harness the benefits of flexibility through superior control strategies. While modeling flexibility and control strategies, researchers have mostly assumed an information system that can provide real-time control. Literature qualitatively reports that the real-time control can be highly capital intensive and difficult to achieve. This paper focuses on FMS operating under review-period (RP)-based control and presents a combined study of routing flexibility (RF), control strategies, and information system under Taguchi's method using simulation. RP-based control for FMS has been compared with real-time control. This paper contributes an approach for the decision maker to study the performance of an FMS operating under RP control and to identify the periodicity (time interval) of RP that will not deteriorate its performance in comparison to real-time control. It also helps the decision maker to reach a tradeoff between RP-based control and real-time control. The results show that RP-based control can be effectively implemented on an FMS having lower RF level. RP-based control can outperform real-time control with a superior control strategy and smaller RP size. The results under Taguchi's method suggest that the RF and control strategy should have maximum relative percentage contributions in FMS performance, whereas contribution of the RP (information system) should be minimum. Increasing the relative percentage contribution of the information system may deteriorate the performance of FMS. The information system is needed as a catalyst to facilitate the contributions of other factors in improving the FMS performance and not its own contribution     

A parametric fuzzy logic approach to dynamic part routing under full routing flexibility

Manufacturing flexibility is a competitive weapon for surviving today’s highly variable and volatile markets. It is critical therefore, to select the appropriate type of flexibility for a given manufacturing system, and to design effective strategies for using this flexibility in a way to improve the system performance. This study focuses on full routing flexibility which includes not only alternative machines for operations but also alternative sequences of operations for producing the same work piece. Upon completion of an operation, an on-line dispatching decision called part routing is required to choose one of the alternatives as the next step. This study introduces three new approaches, including a fuzzy logic approach, for dynamic part routing. The fuzzy part routing system adapts itself to the characteristics of a given flexible manufacturing system (FMS) installation by setting the key parameters of the membership functions as well as its Takagi-Sugeno type rule base, in such a way to capture the bottlenecks in the environment. Thus, the model does not require a search or training for the parameter set. The proposed approaches are tested against several crisp and fuzzy routing algorithms taken from the literature, by means of extensive simulation experiments in hypothetical FMS environments under variable system configurations. The results show that the proposed fuzzy approach remains robust across different system configurations and flexibility levels, and performs favourably compared to the other algorithms. The results also reveal important characteristic behaviour regarding routing flexibility.     

An object-oriented model for FMS control

The flexible manufacturing system (FMS) is a distributed network of heterogeneous programmable manufacturing machinery, such as assembly lines and numerically controlled machines. Despite these interconnected, programmable hardware elements, the success of building a truly flexible manufacturing system has been limited so far, owing to the lack of flexibility in its control software layer. In integrating heterogeneous machinery, many existing FMS control software systems depend structurally on specific machinery and job-scheduling strategies, and thus it is difficult to incorporate new developments in FMS organization and operational requirements. In searching for an open architecture for the FMS control software system, this paper presents an object-oriented FMS data model. Among others, it represents each physical cluster of related machinery (called a flexible manufacturing cell) as an object. To facilitate the integration of heterogeneous physical cells, such cell objects share a common protocol of interacting with the main control process through inheritance from the abstract cell class. Other related physical and abstract entities in FMS are also modelled as objects, with their similarity and difference captured in inheritance hierarchies. To verify the proposed approach experimentally, a prototype FMS control software system named FREE (FMS Runtime Executive Environment) has been implemented on top of a commercial object-oriented database system.     

Analysis of dynamic due-date assignment models in a flexible manufacturing system

This paper investigates the effects of dynamic due-date assignment models (DDDAMs), routing flexibility levels (RFLs), sequencing flexibility levels (SFLs) and part sequencing rules (PSRs) on the performance of a flexible manufacturing system (FMS) for the situation wherein part types to be produced in the system arrive continuously in a random manner. The existing DDDAMs considered are dynamic processing plus waiting time and dynamic total work content. A new model known as dynamically estimated flow allowance (DEFA) has also been developed and investigated. The routing flexibility of the system and the sequencing flexibility of parts are both set at three levels. A discrete-event simulation model of the FMS is used as a test-bed for experimentation. The performance measures evaluated are mean flow time, mean tardiness, percentage of tardy parts and mean flow allowance. The statistical analysis of the simulation results reveals that there are significant interactions among DDDAMs, RFLs, SFLs and PSRs for all the performance measures. The proposed DEFA model provides the minimum percentage of tardy parts in all the experiments. Regression-based metamodels have been developed using the simulation results. The metamodels are found to provide a good prediction of the performance of the FMS within the domain of their definition.     

Evaluations of operational control rules in scheduling a flexible manufacturing system

In this paper, computer simulation is used to evaluate the effects of various control rules on the performance of a flexible manufacturing system (FMS) operating under different manufacturing environment. Alternative routings are available, if the operation of a part can be performed by more than one machine. Three control rules, namely, dynamic alternative routings, planned alternative routings, and no alternative routings, are proposed to control the selection of alternative routings for each part. The effects of the universal loading station and also those of the dedicated loading station are investigated. In addition, the impact of buffer existence on the system’s performance is also examined by considering machines with and without local buffers. The effects of changing production ratios of different part types on the performance of various operational control rules are also investigated. Moreover, the effects of system having machine breakdown are also discussed. The simulation results indicate that the FMS with dedicated loading stations outperforms the FMS with universal loading stations in all aspects. The dynamic alternative routings generally produces the best results in system performance if the universal loading station is provided. The planned alternative routings generally gives the best system performance when both the dedicated loading stations and local buffers are available. The no alternative routings usually remains at the bottom of the rank, occasionally with some exceptions. Problems in actual implementation are also highlighted.     

Modeling and control of workstation level information flow in FMS using modified Petri nets

A flexible manufacturing system (FMS) has a traditional structure of three levels: cell, workstation, and equipment. The workstation level plays an important role in the overall performance of the FMS. This paper focuses on modeling and control of the FMS workstation level information flow. In order to have a unified workstation level system structure, front-end interfaces are introduced as a standard communication medium between the workstation level and the equipment level. A detailed information flow analysis is then carried out on the workstation level. For modeling purposes, a modified Petri net is proposed with its increased modeling capability over an ordinary Petri net. It associates data structures with places and programs with transitions. Finally, the modified Petri net is used to model and control the FMS workstation level information flow. The designed control system has been implemented in a real manufacturing factory with satisfactory performance.     

A computer simulation model for studying the performance of coordinate measuring machines

The increasing trend toward computer-integrated manufacturing (CIM) in today's industry created a need for an effective process control. The objective of the inspection process is not only preventing shipment of defective parts but also providing a feedback to keep the manufacturing process in control. Through data processing capability, speed, and flexibility of operation, coordinate measuring machines (CMMs) play an important role for computer-integrated manufacturing (CIM). This paper introduces coordinate measuring machines and studies their performance. A computer simulation method for studying the performance of such machines working in a production line is developed. In this paper, CMM performance is measured by its speed and flexibility in performing measurements. In flexible manufacturing systems (FMS), CMMs serve as the inspection work station where arrival time of parts to be measured vary according to the flow of operations. The developed simulation model provides information about the machine, scheduled time for parts to be measured, and delay time for the measuring process.     

Evaluation and optimisation of integrated manufacturing system operations using Taguch's experiment design in computer simulation

The application of computer simulation have been proposed and implemented to solve the problems of variation in integrated manufacturing systems. However, a simulation model only acts as a tool in examining performance. It is essentially a trial and error methodology, and does not directly provide explanations for observed system behaviours. Therefore, in this paper the use of Taguchi's Experiment Design in simulation is studied to solve decision-making problems in integrated manufacturing systems. In particular, we use the case of a steel soaking-pit/rolling-mill plant to demonstrate how the approach works. The results reveal that this approach can take into account the evaluation and optimisation of operating conditions in complex systems simultaneously.     

Evaluating the impact of alternative plans on manufacturing performance

In recent years, process planners have become interested in the development of dynamic process planning systems that can interface to scheduling systems providing alternative process plans to increase flexibility in scheduling. However, deciding how many alternatives are needed has not been addressed in any previous studies. This paper presents the results of a simulation-based study aimed at characterizing the benefit provided from having alternative plans available for use in scheduling. This benefit is quantified in terms of the overall performance of a job-shop manufacturing environment. The results of this study indicate that the advantage gained by increasing the number of alternative process plans diminishes rapidly. In fact, under some conditions for the particular system studied, increasing the number of alternatives actually resulted in degraded system performance. Based on these results developers of process planning systems and methodologies need to evaluate carefully the benefit of expending time and resources on the generation of alternative plans or optimal plans.     

The effect of responsiveness of the control-decision system to the performance of FMS

In Flexible Manufacturing System (FMS), decision-making process is one of the key aspects for its performance enhancement, particularly for shop-floor control, where operation managers need to make a large number of control decisions. A term called ‘response-time’ in decision-making process has been defined in this study, which refers to a lead time in decision-making and its implementation. This paper contributes a methodology for decision-maker to study the decision-making process and identify a suitable decision-making approach, while considering critical factors such as decision automation levels, routing flexibility levels, and control strategies. Considering the complexity in modelling an FMS with routing flexibility levels, control strategies (sequencing and dispatching rules), and decision-making process with information system, computer simulation modelling has been employed to study the makespan performance. The results show that decision-making process with response-time for FMS control performs as good as with the real-time control when routing flexibility level is low. Furthermore, under some specific situations, it even outperforms the real-time control. This research gives insight to decision-maker to identify whether a decision system with response-time will be more suitable and economically justified, or real-time decision-making system is more appropriate.     

Intelligent heuristic for FMS scheduling using grouping

This paper presents an approach to scheduling production in a flexible manufacturing system (FMS) environment by employing intelligent grouping of parts which results in good schedules that are easily solvable. Scheduling production in a realistic setting represents a very hard managerial task defying exact solutions, except in very few instances. This article presents and tests a methodology which produces scheduling solutions for large problems with an average small deviation from the theoretical lower bounds. Since open-shop scheduling is the most frequently encountered scheduling discipline in FMS, we restrict the analysis to this setting. The methodology presented combines manufacturing concepts developed in the group technology context with insightful understanding of machine scheduling problems. With the increasing interest in FMS such an approach is both promising and timely.This work was conducted at the Industrial Engineering and Management Department, Ben-Gurion University of the Negev, Beer-Sheva, Israel.     

System approach to a generic software specification for flexible manufacturing system job flow management

Programmable automation is a key factor to fully exploit the potentiality of flexible manufacturing systems (FMS). In particular, the flexibility of the control software acting at the operational level, allows one to make the control activities easier to program and re-program. This characteristic needs a generic software able to control an arbitrary FMS producing an arbitrary part-mix, according to arbitrary control strategies. Turning attention to the operational job flow management, a typical FMS is modelled as a discrete-event dynamic system in a formal and unambiguous way. The system state and its transitions (i.e. logical and physical entities, their attributes and relationships and the mechanism ruling their modifications in time) are described. The discrete-event model allows one to point out the organization of a generic software for job flow management, in terms of its inputs, outputs, knowledge base and decision-making processes.     

A CONWIP model for FMS control

Production inventory control is one of the most important aspects of a flexible manufacturing system (FMS) design. CONstant Work In Process (CONWIP), which is a hybrid of push-and-pull type systems, offers an alternative to effective utilization of the expensive FMS equipment while still meeting customer requirements. In the selection of an FMS control method, material handling often becomes one of the capacity constraints which forms the basis of various research interests. In this paper, a structure-based model for a CONWIP-controlled FMS is proposed, and within it, the node type characteristics concept is used to describe the constraints in FMS. Furthermore, simulation is used to determine the card number based on the structure-based model. The simulation results demonstrate that the model is suitable for the design and operation of FMS. The model can be used as a manufacturing execution system of enterprise resources planning. An architecture for this integrated design based on Internet/Intranet systems is also proposed.     

Network-based hybrid genetic algorithm for scheduling in FMS environments

Scheduling in flexible manufacturing systems (FMS) must take account of the shorter lead-time, the multiprocessing environment, the flexibility of alternative workstations with different processing times, and the dynamically changing states. The best scheduling approach, as described here, is to minimize makespan t _M, total flow time t _F, and total tardiness penalty p _T. However, in the case of manufacturing system problems, it is difficult for those with traditional optimization techniques to cope with this. This article presents a new flow network-based hybrid genetic algorithm (hGA) approach for generating static schedules in a FMS environment. The proposed method is combined with the neighborhood search technique in a mutation operation to improve the solution of the FMS problem, and to enhance the performance of the genetic search process. We update the change in swap mutation and the local search-based mutation ration. Numerical experiments show that the proposed flow network-based hGA is both effective and efficient for FMS problems.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Expert systems: An application in flexible manufacturing

Flexible manufacturing systems (FMS) are needed to provide manufacturing operations with the capability to adjust, in real time, to changes in the manufacturing environment. Realization of the goals of flexible manufacturing is governed by the ability of the FMS to maintain adequate information on the factory to assist in generating scenarios from product planning to operations and performance. This leads to a view where the factory is represented as an integrated information system. To facilitate the analysis of information requirements and the design of information systems for flexible manufacturing, an expert support system (ESS) which can be used to model and study the various structures is described. This ESS uses the information cell model to build these information structures. Petri net representations of these structures and their interactions are then constructed. The ESS may now be used to exercise these models and study their performance using time and cost measures.     

Optimum loading of machines in a flexible manufacturing system using a mixed-integer linear mathematical programming model and genetic algorithm

Machine loading problem in a flexible manufacturing system (FMS) encompasses various types of flexibility aspects pertaining to part selection and operation assignments. The evolution of flexible manufacturing systems offers great potential for increasing flexibility by ensuring both cost-effectiveness and customized manufacturing at the same time. This paper proposes a linear mathematical programming model with both continuous and zero-one variables for job selection and operation allocation problems in an FMS to maximize profitability and utilization of system. The proposed model assigns operations to different machines considering capacity of machines, batch-sizes, processing time of operations, machine costs, tool requirements, and capacity of tool magazine. A genetic algorithm (GA) is then proposed to solve the formulated problem. Performance of the proposed GA is evaluated based on some benchmark problems adopted from the literature. A statistical test is conducted which implies that the proposed algorithm is robust in finding near-optimal solutions. Comparison of the results with those published in the literature indicates supremacy of the solutions obtained by the proposed algorithm for attempted model.     

A heuristic based on multi-stage programming approach for machine-loading problem in a flexible manufacturing system

Manufacturing industries are rapidly changing from economies of scale to economies of scope, characterized by short product life cycles and increased product varieties. This implies a need to improve the efficiency of job shops while still maintaining their flexibility. These objectives are achieved by Flexible manufacturing systems (FMS). The basic aim of FMS is to bring together the productivity of flow lines and the flexibility of job shops. This duality of objectives makes the management of an FMS complex. In this article, the loading problem in random type FMS, which is viewed as selecting a subset of jobs from the job pool and allocating them among available machines, is considered. A heuristic based on multi-stage programming approach is proposed to solve this problem. The objective considered is to minimize the system unbalance while satisfying the technological constraints such as availability of machining time and tool slots. The performance of the proposed heuristic is tested on 10 sample problems available in FMS literature and compared with existing solution methods. It has been found that the proposed heuristic gives good results.     

Dynamic routing in reentrant flexible manufacturing systems

Consider a flexible manufacturing system (FMS), with several parallel production lines. Each line is statistically balanced. Due to process time and yield variations, some workstations may be temporarily starved of parts during the FMS operation, while others may have too many. The purpose of the dynamic routing algorithm described here is to achieve real-time load balancing in a stochastic processing environment and thus to increase the performance of the system in throughput, workload balance and reduced work-in-process queues. We formulate the problem and develop an optimal stationary policy (for two lines that have a material handling transport between them) based on the input buffer state of each station.     

Heterarchical production control in manufacturing systems using the potential fields concept

This article deals with the potential field concept and its application to dynamic task allocation and dynamic routing controls of flexible manufacturing systems (FMS). This potential field approach requires increasing the interaction capabilities of the different entities, not only resources but also products themselves. In this approach, products request services from resources, sensing the fields emitted by resources and selecting the field that best satisfies the service request. Many already published approaches that are capable of modelling systems based on the interactions between the entities in manufacturing systems are presented. Then, the potential field concept and its application to FMS control are explained in detail. Next, a potential field model and its application are proposed in the real-time heterarchical control of dynamic resource allocation and dynamic product routing. Using a NetLogo simulation, the potential field model supports hard assumptions, such as dynamic transportation times, limited storage capacities and breakdown events. To validate this model, an ongoing real implementation is presented with the AIP-PRIMECA FMS.