Typical Flexible Manufacturing System Research Articles

A Two-Phase Iterative Mathematical Programming-Based Heuristic for a Flexible Job Shop Scheduling Problem with Transportation

In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of automated transporters in Industry 4.0. In this article, a two-phase iterative mathematical programming-based heuristic is proposed to minimize makespan using a machine-operation assignment centric decomposition scheme. The first phase approximates the FJSPT through an augmented flexible job shop scheduling problem (FJSP + T) that reduces the solution space while serving as a heuristic in locating good machine-operation assignments. In the second phase, a job shop scheduling problem with transportation (JSPT) network is constructed from these assignments and solved for the makespan. Compared to prior JSPT implementations, the proposed JSPT model considers job pre-emption, which is instrumental in enabling this FJSPT implementation to outperform certain established benchmarks, confirming the importance of considering job pre-emption. Results indicate that the proposed approach is effective, robust, and competitive.

Modeling and Analysis for Minimization of Mean Flow Time in FMS Simulation

The aim of this paper is to deal with a simulation study on effect of part launching, part sequencing at central buffer and tool selection rules on a flexible manufacturing system (FMS) involving tool movement along with part movement policy. A typical FMS is selected for a study of discrete event simulation model. Simulation experiments are conducted on various combinations of decision rules and it is found to be good in evaluated performance measures.

Impacts of Scheduling Decisions Based On PSO Algorithm and Dispatching Rules on FMS Performances

This paper investigates the scheduling problem in a typical flexible manufacturing system (FMS) with routing flexibility. The scheduling decisions have been established in terms of how the parts are launched into the system, how these parts are routed through various machines and how parts are sequenced for processing on a machine. The first decision is taken using one of the two dynamic dispatching rules (least work remaining (LWR) and most work remaining (MWR)) or first in first out (FIFO). Concerning the second decision, an algorithm based on particle swarm optimization (PSO) is used for real time alternative routing selection of each part whereas shortest processing time (SPT), longest processing time (LPT) and FIFO are used as sequencing rules for working centres (third decision). The simulation results evaluated in terms of the productivity and the utilisation of the system show that the proposed PSO algorithm performs the best when it is combined with LWR as part launching rule and SPT as machine sequencing rule.

Real-time rescheduling metaheuristic algorithms applied to FMS with routing flexibility

This paper presents the results of a simulation study of a typical flexible manufacturing system that consists of seven machining centres, a loading and an unloading area, and six different part types. Owing to the existence of identical machining centres, the part types have alternative routings (their number varies between two and eight). One of the objectives of this work is to show how the following metaheuristics: ant colony optimisation, genetic algorithms, simulated annealing, tabu search, particle swarm optimisation and electromagnetism-like method, are adapted for solving the alternative routing selection problem in real time in order to reduce the congestion in the system by selecting a routing for each part among its alternative routings. The other goal is to highlight the impact of the real-time rescheduling of parts contained in the loading station on system performances when these metaheuristics are applied. The simulation results jugged by the production rate, machines and material handling utilisation rate show that for an overloaded system, the real-time rescheduling outperforms the case without rescheduling, but it has a negative impact on the work in process.

Combined buffer pre-allocation and siphon control for deadlock prevention in Petri nets

We study the design of deadlock prevention for a special class of flexible manufacturing systems (FMSs). In such FMSs, each machine has its own input and output buffers and multiple resources can be used in one step. As proved in this paper, by pre-allocating and partitioning all buffers in an FMS, deadlocks can be prevented. To demonstrate this policy, two subclasses of Petri nets, denoted by MRSNB and MRSANB, are defined. Furthermore, on combining buffer pre-allocation and siphon control, two deadlock prevention approaches for such FMSs are proposed. Compared with other reported methods, the two proposed approaches can achieve a satisfactory trade-off among permissiveness, structural simplicity and computational complexity. Several typical FMS examples are used to illustrate the proposed concepts and policies, and to show the advantages over other methods.

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.

Effects of routing flexibility, sequencing flexibility and scheduling decision rules on the performance of a flexible manufacturing system

This paper focuses on a simulation-based experimental study of the interaction among routing flexibility, sequencing flexibility and part sequencing rules in a typical flexible manufacturing system (FMS). Two scenarios are considered for experimentation. Three routing flexibility levels, five sequencing flexibility levels and four scheduling rules for part sequencing decision are considered for detailed investigation. 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. The analysis of results reveals that deterioration in system performance can be minimized substantially by incorporating either routing flexibility or sequencing flexibility or both. However, the benefits of either of these flexibilities diminish at higher flexibility levels. Part sequencing rules such as earliest due date and earliest operation due date provide better performance for all the measures at higher flexibility levels.

Development of simulation-based metamodels for the analysis of routing flexibility, sequencing flexibility and scheduling decision rules on the performance of an FMS

This paper focuses on the development of simulation-based metamodels for analysing the effects of routing flexibility, sequencing flexibility and part sequencing rules (PSRs) on the performance of a typical flexible manufacturing system (FMS). Three routing flexibility levels, five sequencing flexibility levels and four scheduling rules for part sequencing decision are considered for detailed investigation. The performance of the FMS is evaluated using measures related to flow time and tardiness of parts. Multiple regression-based metamodels have been developed using the simulation results. The analysis of results reveals 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, PSRs, such as earliest due date and earliest operation due date, provide better performance for all the measures.

Ranking of scheduling rule combinations in a flexible manufacturing system using preference selection index method

This paper focuses on scheduling decision problems of a flexible manufacturing system (FMS) using simulation modelling and analysis. A typical FMS configuration is considered for the study. A discrete-event simulation model is developed for the purpose of experimentation. In this study, various scheduling rules are used for the decisions such as part launching, part routing and part sequencing. The performance of the system is evaluated using the measures such as mean flow time, mean tardiness, percentage of tardy parts, mean utilisation of machines and mean work-in-process. Based on the overall performance score, the combinations of scheduling rules for part launching, part routing and part sequencing decisions are ranked using the preference selection index method.

Simulation modelling and analysis of routing flexibility of a flexible manufacturing system

Routing flexibility is a major contributor of the flexibility of a flexible manufacturing system (FMS). This 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 FMS. The routing flexibility of the system has been evaluated using the measures such as routing efficiency, routing versatility and routing variety. The flexibility levels are ranked based on the routing flexibility measure for the system.

Evaluating the Effect of Part-mix and Routing Flexibility on FMS Performance

The flexibility in manufacturing environment is implemented to respond proactively and cost effectively towards dynamic production requirements. Previous literature has explored eight common types of flexibility in manufacturing. This paper presents a simulation study based on Part-mix and Routing Flexibility and their impact on system performance of a typical Flexible Manufacturing System (FMS). ARENA based computer simulation models have been developed to investigate the effect of flexibility on the performance under various control strategies (sequencing and dispatching rules). The performance measure used in this paper is make-span time. Unbalanced type job shop FMS consist of four CNC general purpose machining centers and one loading/ unloading station is considered for the illustration of simulation models. These demo simulation models are intended for deterministic environment, and the use of discrete event simulation approach is adopted to offer a focus on dynamic behavior of FMS operating under different manufacturing strategies and flexibility types. This simulation study, under dynamic environment, may be very useful for practitioners. Management can obtain better insight and guidelines for determining various decisions relating to process and operations improvement and investment in new facility.

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.

Study of Flexible Scheduling System of the Hull Job Shop Based on OOCPN

The hull job shop in a shipyard is a typical flexible manufacturing system (FMS), the flexibility and efficiency of which largely depends on the level of FMS scheduling. In this paper, the Object-Oriented Colored Petri Net (OOCPN) is used to build the FMS model for the hull job shop. A four-step modeling method of FMS has been developed to successfully simulate the scheduling of the hull job shop.

Performance Analysis of a Flexible Manufacturing System

A typical Flexible Manufacturing System (FMS) has been studied under Planning Design and Control (PDC) strategies. The chief objective is to test the impact of design strategy (routing flexibility) on system performance under planning strategy (alternate system load condition) with control strategies (sequencing and dispatching rules). A computer simulation model is developed to evaluate the effects of aforementioned strategies on the make-span time, which is taken as the system performance measure. Shortest Processing Time (SPT), Maximum Balance Processing Time (MBPT) are the sequencing rules for selecting the part from the input buffer whereas for machine selection the dispatching rules are Minimum Number of parts in the Queue (MINQ), and Minimum queue with Minimum Waiting Time of all parts in the Queue (MQMWT). In this paper, the same manufacturing system is modeled under four different system load conditions. These load conditions are Full Balanced Load (FBL), Balanced Machine Load and Unbalanced Processing Time (BMLUPT), Unbalanced Machine Load and Balanced Processing Time (UMLBPT) and Unbalanced Load (UBL) with respect to machine load and processing time. The result of the simulation shows that there is continuous reduction in make-span with increase in routing flexibility when both machine load and processing times are unbalanced i.e., under UBL system condition.

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 scheduling. 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.

Failure rate distributions for flexible manufacturing systems: An empirical study

To aid researchers in the simulation and testing of maintenance policies for complex, computer controlled technological equipment this paper presents a description of failure and repair rate characteristics as well as distribution data for a typical flexible manufacturing system (FMS) that is in use in a mid-western (USA) manufacturing plant. Separate data are included for mechanical, hydraulic, electrical, electronic, software and human failures as well as repairs. The data are also fit with appropriate theoretical distributions.

An object-oriented rule-based framework for the specification of flexible manufacturing systems

The design of flexible manufacturing systems (FMSs) requires an effective system specification method, which is flexible to cope with redesigns as a result of requirement changes. In order to facilitate the design of such systems, object-oriented methods are increasingly adopted. However, they only provide limited support to system integration and the explicit specification of operational policies. In this connection, an object-oriented rule-based specification framework is proposed to incorporate a rule model into an object-oriented specification, to analyze and design the global processes and operational policies of FMSs. The application of this framework is illustrated via the specification of a typical vehicle-based FMS.

Multi-level scheduling decisions in a class of FMS using simulation based metamodels

This paper pertains to a detailed simulation study conducted on a typical Flexible Manufacturing System (FMS). Initially, the configurations of the FMS under study have been established. Two types of FMSs have been evolved: one is failure free and the other is failure prone. For each of these cases, simulation models have been developed using SLAMSYSTEM. Orders arriving randomly at the FMS are subjected to three levels of scheduling decisions namely, launching of parts into the system, routing of parts through machines and sequencing of parts on AGVs at a central buffer. The simulation results have been used to develop metamodels for the two types of FMSs. These metamodels have been subjected to statistical analysis to ascertain their adequacy to represent the simulation models. These metamodels have been found to be useful for simulating the FMSs under study so as to evaluate various multi-level scheduling decisions in the FMS.

Using an unsupervized neural network and decision tree as knowledge acquisition tools for FMS scheduling

This paper applies neural network learning techniques and a decision tree method to obtain scheduling knowledge for flexible manufacturing systems. A search is made for the reverse relationship between the FMS system performance and its corresponding decision parameters. More specifically, the learning function is to acquire the scheduling knowledge which determines the decision-mix to control adequately the system in fulfilling a specified system performance. This paper first configures a typical flexible manufacturing system and defines a set of decision parameters along with a set of system performance evaluation criteria. The learning procedure initiates accumulating simulated data through the system. Next, the ART2 ( adaptive resonance theory) neural model takes the system performance data as inputs and forms performance classes according to their similarities. Finally, the decision tree construction method is applied to extract the definition of each class, The definitions are converted into rule-type knowledge associated with certainty factors, and used as the scheduling knowledge.

Quantitative Analysis of AGV System in FMS Cell Layout

Material handling is a specialised activity for a modern manufacturing concern. Automated guided vehicles (AGVs) are invariably used for material handling in flexible manufacturing Systems (FMSs) due to their flexibility. The quantitative analysis of an AGV system is useful for determining the material flow rates, operation times, length of delivery, length of empty move of AGV and the number of AGVs required for a typical FMS cell layout. The efficiency of the material handling system, such as AGV can be improved by reducing the length of empty move. The length of empty move of AGV depends upon despatching and scheduling methods. If these methods of AGVs are not properly planned, the length of empty move of AGV is greater than the length of delivery .This results in increase in material handling time which in turn increases the number of AGVs required in FMS cell. This paper presents a method for optimising the length of empty travel of AGV in a typical FMS cell layout.