Evaluation of routing flexibility of a flexible manufacturing system using simulation modelling and analysis

Routing flexibility is a major contributor of the flexibility of a flexible manufacturing system (FMS). The present paper focuses on the evaluation of the routing flexibility of an FMS with the dynamic arrival of part types for processing in the system. A typical FMS configuration is chosen for detailed study and analysis. The system is set at five different levels of routing flexibility. Operations of part types can be processed on alternative machines depending upon the level of routing flexibility present in the system. Two cases have been considered with respect to the processing times of operations on alternative machines. A discrete-event simulation model has been developed to describe the operation of the chosen FMS. The performance of the system under various levels of routing flexibility is analyzed using measures such as mean flow time, mean tardiness, percentage of tardy parts, mean utilisation of machines, mean utilisation of automatic-guided vehicles, and mean queue length at machines. The routing flexibility for producing individual part types has been evaluated in terms of measures such as routing efficiency, routing versatility, routing variety and routing flexibility. The routing flexibility of the system has been evaluated using these measures. The flexibility levels are ranked based on the routing flexibility measure for the system. The ranking thus obtained has been validated with that derived using fuzzy logic approach.     

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a system's flow-time performance.     

Evaluation of the impact of information delays on flexible manufacturing systems performance in dynamic scheduling environments

The significance of the adverse effects of information delays (IDs) on flexible manufacturing system (FMS) performance is getting increasing attention from manufacturing systems managers, planners, schedulers, Enterprise Resource Planning software developers, and researchers because of their potential to disrupt production schedules. In this paper, we examine the extent of the adverse impact that IDs have on FMS performance. The FMSs are assumed to operate in a “review period” mode; i.e., the control decisions (e.g., sequencing and dispatching) are taken based on information monitored at predetermined intervals of time called “review periods”. The performance deterioration occurs due to the obsolescence of system status information. Key empirical findings based on extensive simulation experiments are: (1) IDs significantly degrade FMS performance for due date-based measures (mean tardiness and percent of jobs tardy); (2) IDs also degrade FMS performance for non-due date-based measures (mean flowtime and average machine utilization), albeit to a less severe degree; (3) routing flexibility, often regarded as a significant factor to influence FMS performance, is superseded by status review information delay.     

The measurement of flexibility in manufacturing systems

This article provides a theoretical basis for measuring the flexibility of manufacturing systems. The concept of multiple levels of measures (necessary, capability, actual, inflexibility, and optimality) for each flexibility type is introduced. Capability and actual measures are then developed for machine, routing, process, product, and volume flexibilities. For each of these flexibility types, a state defining variable is identified. A measure of flexibility is then derived by computing either, (i) the change effort expended in moving between states, (ii) the drop in system performance in moving between states, (iii) a general or physical scale of difference between two successive states, or (iv) a measure combining all three. The use of the developed measures is illustrated via a two-facility example.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available.To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived.The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

Simulation-based metamodels for the analysis of scheduling decisions in a flexible manufacturing system operating in a tool-sharing environment

This paper presents the salient aspects of developing simulation-based metamodels for scheduling a typical flexible manufacturing system (FMS) operating in a tool-sharing environment. A discrete-event simulation model of the FMS is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model for part scheduling decision. The performance measures considered for analysis are mean flow time, mean tardiness, and percentage of tardy parts. Simulation experiments have been carried out for various scenarios arising out of the settings of the mean interarrival time of parts for processing in the system and due-date factor. The simulation results are used to develop regression-based metamodels. These metamodels have been subjected to systematic analysis. The metamodels are found to offer a good prediction of the performance of FMS within the domain of their definition.     

An Evaluative Study of Operation Grouping Policies in an FMS

The increased use of flexible manufacturing systems to provide customers with diversified products efficiently has created a significant set of operational challenges for managers. This technology poses a number of decision problems that need to be solved by researchers and practitioners. In the literature, there have been a number of attempts to solve design and operational problems. Special attention has been given to machine loading problems, which involve the assignment of job operations and allocation of tools and resources to optimize specific measures of productivity. Most existing studies focus on modeling the problem and developing heuristics in order to optimize certain performance metrics rather than on understanding the problem and the interaction between the different factors in the system. The objective of this paper is to study the machine loading problem. More specifically, we compare operation aggregation and disaggregation policies in a random flexible manufacturing system (FMS) and analyze its interaction with other factors such as routing flexibility, sequencing flexibility, machine load, buffer capacity, and alternative processing-time ratio. For this purpose, a simulation study is conducted and the results are analyzed by statistical methods. The analysis of results highlights the important factors and their levels that could yield near-optimal system performance.     

Impact of operation flexibility and dispatching rules on the performance of a flexible manufacturing system

Operation flexibility is one of the eight common types of flexibility that exist in flexible manufacturing systems. Dispatching rules are commonly used in loading the machines. This paper studies the effects of different levels of operation flexibility and various dispatching rules on the performance of a flexible manufacturing system. The system performance considered is mean flow time. Simulation results indicate that the mean flow time cannot be always improved by increasing the level of operation flexibility. Altering the dispatching rules seems to have a more significant effect on the mean flow time performance than changing the level of operation flexibility.     

Real-Time Manipulation of Alternative Routeings in Flexible Manufacturing Systems: A Simulation Study

This paper presents the results of a simulation study of a typical flexible manufacturing system (FMS) that has routeing flexibility. The objective is this study is to test the effectiveness of the dissimilarity maximisation method (DMM) for real-time FMS scheduling. DMM is an alternative process plan selection method developed for routeing selection in off-line FMS sched-uling. An integrated framework that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to evaluate the effects of various operational control rules on the system performance. The hypothetical FMS employed in this study consists of seven machining centres, a loading and an unloading area, and six different part types. Owing to the existence of identical machining centres in the system, the part types have alternative routeings. For selecting an incoming part and later routeing it to a machining centre for its next operation, three control rules, namely, first-in first-out/first available (FIFO/FA), equal probability loading (EPL), and dissimilarity maximisation method/first-in first-out (DMM/ FIFO) are used. In this study, DMM is 1. Used as a real-time decision-making tool to select routeings for the parts that are in the system. 2. Tested and benchmarked against FIFO/FA and EPL. The results show that DMM/FIFO outperforms FIFO/FA and EPL on system throughput. Other measures such as average waiting time, average transportation time, and percentage utilisation rates are also investigated to provide insights for the effectiveness of the DMM rule for real-time FMS control applications.     

Comparative influence of three flexibility types on manufacturing lead-time performance

This paper presents the results of a conceptual study and simulation experimentation aimed at understanding the impact of three important types of flexibility on the lead-time performance of a manufacturing system. The three flexibility types, viz. transformation flexibility, sequencing flexibility and product flexibility have been identified based on a new conceptual model for flexibility in manufacturing systems and supply chains. The influence of these three flexibility types has been studied using simulation models. The studies indicated that among the three, product flexibility has the greatest influence followed by transformation flexibility and the sequencing flexibility. The reasons for the inferior performance of sequencing flexibility is found to be reduction of dynamic flexibility levels as compared to its static flexibility levels and the reasons for superior performance of product flexibility is found to be the lower movement of products within the manufacturing system.     

Dynamic flexible job shop scheduling with alternative process plans: an agent-based approach

This paper studies a flexible job shop problem considering dynamic events such as stochastic job arrivals, uncertain processing times, and unexpected machine breakdowns. Also, the considered job shop problem has routing flexibility and process flexibility. A multi-agent scheduling system has been developed for solution with good quality and robustness. A pheromone-based approach is proposed for coordination among agents. The proposed multi-agent approach is compared with five dispatching rules from literature via simulation experiments to statistical analysis. The simulation experiments are performed under various experimental settings such as shop utilization level, due date tightness, breakdown level, and mean time to repair. The results show that the proposed agent-based approach performs well under all problem settings.     

Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.     

Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.     

Effects of Dispatching and Routeing Decisions on the Performance of a Flexible Manufacturing System

This paper is concerned with the effects of dispatching and routeing decisions on the performance of a flexible manufacturing system (FMS). Three routeing policies, no alternative routeings, alternative routeings dynamic, and alternativerouteings planned are first considered with four dispatching rules with infinite buffer capacity. However, in real-life, the size of the local buffers in FMSs may be limited by the size of the part types. Therefore, further experiments to investigate the above three routeing policies with the four dispatching rules with finite buffer capacity are also conducted in order to study the impact of limited buffer capacity on system performance. In addition, the effect of changing part mix ratios is discussed with both infinite and finite buffer capacity. The performance measures considered are makespan, average machine utilisation, average flow-time, and average delay at local input buffers. The simulation results indicate that for infinite buffer capacity, the alternative routeings planned policy, combined with the shortest total processing time dispatching rule, gives the best results for all the above performance measures. For finite buffer capacity, the alternative routeings dynamic policy gives the best results in three performance measures, except for average delay at local input buffers. Further, the effect of changing part mix ratios is not significant. ID="A1"Correspondance and offprint requests to: Dr F. T. S. Chan, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong. E-mail: ftschan@hkucc.hku.hk     

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 % and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

An operational measure of routing flexibility in a multi-stage multi-product production system

The high degree of variety in customer demands causes mass production to become outdated and flexible production to be favored. Routing flexibility can be found in systems that implement general-purpose machines, alternative or identical machines, redundant machine tools, or the versatility of material handling systems. It is recognized that routing flexibility can be treated as a tool for enhancing system performance, such as lead time and inventory reduction. However, its implementation entails a huge cost of installation of flexible machines, automated tool changers and fixtures, and machine operators possessing multiple skills. Therefore, system managers must determine the appropriate level of routing flexibility for a specific system configuration in order to balance benefits and costs incurred. This paper presents a background to and a rational for a routing flexibility measure for a multi-stage flow shop. Instead of merely counting the number of available routes, this measure takes into account the loading balance between machines. Therefore, a manufacturing system with overloaded machines will have less routing flexibility as compared with one that is not overloaded, when both systems have the same number of available routes. An example for demonstrating the applicability of the proposed measure is also illustrated.     

A genetic algorithm approach to machine flexibility problems in an ion plating cell

For a long time, manufacturing industries have been concentrating on increasing productivity by increasing the size of the workforce, but this scenario has changed in last decade since the introduction of the term flexibility. Now, the manufacturers realize that flexibility of the machine environment can provide a better economic solution for improving productivity due to its quick response to the changing environment in the manufacturing industry. However, only very limited research on machine flexibility in the ion plating (IP) industry has been carried out and most of it has focused on product development and quality of coating. The aim of this paper is to determine the optimal level of machine flexibility in an ion plating cell (IPC) to improve the entire system performance. A machine loading sequencing (MLS) model based on a multi-objective genetic algorithm (GA) is developed and the case study of metal finishing company is discussed to validate the proposed model. Different levels of machine flexibility have been assigned to different machines to determine the optimal level to increase the overall system performance based on on-time delivery, quality of product and production cost. The results demonstrated that machine flexibility level in IPC should be zero under recent IP technology. However, when the IP technology is developed enough so that IP machine has the ability to produce different types of coating in high quality, machine flexibility should be introduced to enhance the overall system performance.     

Reliability analysis of flexible manufacturing systems

High productivity is the primary goal of flexible manufacturing systems (FMSs) in which semi-independent workstations are integrated using automated material-transport systems and hierarchical local networks. Availability of various subsystems and of the system as a whole is a prerequisite for achieving functional integration as well as high throughput. An FMS also has inherent routing and operation flexibilities that provide it with a certain degree of fault tolerance. A certain volume of production can thus be maintained in the face of subsystem (i.e., machines, robots, material handling system, etc.) failures. In this article, we propose two reliability measures, namely, part reliability (PR) and FMS reliability (FMSR) for manufacturing systems and present algorithms to evaluate them. We also consider the dynamic or time-dependent reliability analysis as a natural generalization of the static analysis. The methods outlined use an algorithm that generates process-spanning graphs (PSGs), which are used to evaluate the reliability measures.