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.     

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.     

Agent-based FMS control

Future manufacturing systems will be integrated into the networks of distributed resources, and at the same time, such systems will be capable of processing both knowledge and material. It will probably be required that manufacturing systems be agile, flexible, and fault-tolerant. Petri nets (PN) and object-oriented design (OOD) are used together in order to develop the integrated agent-based FMS control system. The flexible manufacturing system (FMS) consists of machines, workstations, and automated material handling system, distributed buffer storage sites and computer-based supervisory control, all which can be modeled as an agent in OOD with PN. This paper introduces the design of an agent-based FMS control system through PNs and evaluates the performance using timed placed Petri nets (TPPN). In order to do so, the agent control design, FMS structure has been evaluated in detail and the agent definitions have been submitted. The system includes the sharing and distribution of tasks among agents and the mentioned structure has been simulated by TPPN. The simulation procedure has been realized through Petri Net 2.0—MATLAB Demo Program [Mahulea CF, Motcovschi MH, Pastravanu O. Department of Automatic Control Industrial Informatics, Technical University “Gh. Asachi” of Iasi, Blvd., Mangeron 53A, 6600 Iasi, Romania, 〈http://www.ac.tuiasi.ro/pntool,pntool@ac.tuiasi.ro〉, 2004.]. Each case is modeled, and then the agent's machine processing time is considered in this program. As for the evaluation of the study, the system performance is assessed through the waiting time of the parts in queue and the task distributions.     

Object-oriented design of FMS control software based on object modeling technique diagrams and Petri nets

Control software is very important to realizing the full benefits of flexible manufacturing systems. This paper highlights the difficulties in developing such software and proposes an object-oriented design (OOD) method using object modeling technique (OMT) diagrams and Petri nets (PNs). OOD is used to design reusable and easily maintainable software. OMT diagrams are used to represent explicitly different kinds of static relations, such as generalization, aggregation, and association, among the objects in an FMS. PNs are used to model the dynamic behavior of the objects and the entire FMS and to conduct performance analysis. The use of PNs also leads to a method to identify the data structures and operations of software objects. The proposed method is illustrated through an FMS example. Its capability to support reusability, extendibility, and modifiability of the resulting control software design is also demonstrated when the FMS specifications change.     

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     

Trends and perspectives in flexible and reconfigurable manufacturing systems

To better understand future needs in manufacturing and their enabling technologies, a survey of experts in manufacturing has been conducted. The survey instrument (i.e., questionnaire) tries to assess the experience to date with the use of flexible manufacturing systems (FMS) and to examine the potential roles and enabling technologies for reconfigurable manufacturing systems (RMS). The results show that two-thirds of respondents stated that FMSs are not living up to their full potential, and well over half reported purchasing FMS with excess capacity (which was eventually used) and excess features (which in many cases were not eventually used). They identified a variety of problems associated with FMS, including training, reconfigurability, reliability and maintenance, software and communications, and initial cost. However, despite these issues, nearly 75% of respondent expressed their desire to purchase additional, or expand existing FMSs. The experts agreed that RMS (which can provide exactly the capacity and functionality needed, exactly when needed) is a desirable next step in the evolution of production systems. The key enabling technologies for RMS were identified as modular machines, open-architecture controls, high-speed machining, and methods, training and education for the operation of manufacturing systems.     

PATHSIM,a modular simulator for an automatic tool handling system evaluation in FMS

The automatic movement of tools, as well as parts, within a flexible manufacturing system is now technically possible. The prospective benefits of automatic tool movement include reduced tool inventories, lower manpower requirements, and an enhanced capability for unattended operation. This report describes a tool for investigating the performance of automatic tool handling systems associated with flexible manufacturing systems.This work uses simulation to describe the prospective systems. In particular, a combined network and discrete event model, written in the SLAM simulation language, is used. The model is of a modular construction, to facilitate its use for different system configurations in the future. The trade-offs between the advantages provided by automatic tool handling and the increased system costs because of the associated hardware are outlined. An illustration of the search for a satisfactory trade-off is made by varying several factors in an example FMS and assessing their effects on system performance.     

Modeling and online scheduling of flexible manufacturing systemsusing stochastic Petri nets

The authors discuss the modeling of flexible manufacturing systems (FMSs) under uncertainty and evaluate a rule base for online scheduling. To represent uncertain events in an FMS, such as failure of machine tools, repair time, and processing time, they develop continuous-time and discrete-time stochastic Petri nets with hierarchical structures for constructing the FMS model. For obtaining an efficient schedule for the FMS with an online real-time basis, they construct a rule base and evaluate its performance using the FMS simulation system proposed     

Design and planning problems in flexible manufacturing systems: a critical review

This review paper describes the state-of-the-art research on flexible manufacturing systems (FMS) design and planning issues. The emphasis is on presenting research results coming out of the current FMS literature that help the FMS manager in setting up a highly efficient manufacturing system. In addition to that, it discusses relevant research contributions after 1986, that were not part of any of the previous survey papers on operations research models for FMSs. Also, applications of combinatorial optimization approaches to FMS planning problems are adequately exposed in the paper.     

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.     

A modeling technique for loading and scheduling problems in FMS

In recent years, due to highly competitive market conditions, it has become necessary for manufacturing systems to have quick response times and high flexibility. Flexible manufacturing systems (FMS's) have gained attention in response to this challenge. FMS has the ability to produce a variety of parts using the same system. However this flexibility comes at the price, which is the development of efficient and effective methods for integrated production planning, and control.In this paper, we analyze the production planning problem in flexible manufacturing systems. We address the problems of part loading, tool loading, and part scheduling. We assume that there is a set of tools with known life and a set of machines that can produce a variety of parts. A batch of various part types is routed through this system with the assumption that the processing time and cost vary with the assignment of parts to different machines and assignment of various tool sets to machines. We developed a mathematical model to select machines and assign operations and the required tools to machines in order to minimize the summation of maximum completion time, material handling time, and total processing time.We first integrate and formulate loading, and routing, two of the most important FMS planning problems, as a 0–1 mixed integer programming problem. We then take the output from the integrated planning model and generate a detailed operations schedule. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as production rate and utilization.     

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.     

A knowledge-based system for reactive scheduling decision-making in FMS

This paper describes research into the development of an intelligent simulation environment. The environment was used to analyze reactive scheduling scenarios in a specific flexible manufacturing systems (FMS) configuration. Using data from a real FMS, simulation models were created to study the reactive scheduling problem and this work led to the concept of capturing instantaneous FMS status data as snapshot data for analysis. Various intelligent systems were developed and tested to asses their decision-making capabilities. The concepts of History Logging and expert system learning is proposed and these ideas are implemented into the environment to provide decision-making and control across a FMS schedule lifetime. This research proposes an approach for the analysis of reactive scheduling in an FMS. The approach and system that was subsequently developed was based on the principle of automated intelligent decision-making via knowledge elicitation from FMS status data, together with knowledge base augmentation to facilitate a learning ability based on past experiences.     

Tool allocation in flexible manufacturing systems with tool alternatives

In this paper, a heuristic approach for tool selection in flexible manufacturing systems (FMS) is presented. The proposed approach utilizes the ratio of tool life over tool size (L/S) for tool selection and allocation. The proposed method selects tool types with high L/S ratios by considering tool alternatives for the operations assigned to each machine. The performance of the method is demonstrated in sample problems as static examples, as well as in a simulation study for further analysis. This study also presents a survey of several approaches related to loading and tool allocation problems in FMS, highlights the importance of tooling, and discusses the practical aspects of tool-oriented decision-making. An extended framework, which expands on the L/S concept, is also presented.     

Genetic algorithms for match-up rescheduling of the flexible manufacturing systems

Scheduling plays a vital role in ensuring the effectiveness of the production control of a flexible manufacturing system (FMS). The scheduling problem in FMS is considered to be dynamic in its nature as new orders may arrive every day. The new orders need to be integrated with the existing production schedule immediately without disturbing the performance and the stability of existing schedule. Most FMS scheduling methods reported in the literature address the static FMS scheduling problems. In this paper, rescheduling methods based on genetic algorithms are described to address arrivals of new orders. This study proposes genetic algorithms for match-up rescheduling with non-reshuffle and reshuffle strategies which accommodate new orders by manipulating the available idle times on machines and by resequencing operations, respectively. The basic idea of the match-up approach is to modify only a part of the initial schedule and to develop genetic algorithms (GAs) to generate a solution within the rescheduling horizon in such a way that both the stability and performance of the shop floor are kept. The proposed non-reshuffle and reshuffle strategies have been evaluated and the results have been compared with the total-rescheduling method.     

Establishing information requirements for supervisory controllers in a flexible manufacturing system using GTA

In this article we consider the technological change that has occurred in complex manufacturing systems within the past two decades and the implications it has had on the role of human operators in manufacturing systems control. Our examination ranges from the traditional production line manned by skilled machinists to flexible manufacturing systems (FMS) under supervisory control. On the basis of this study, we raise the question as to whether new advanced manufacturing technology interfaces are supportive of human operators in their responsibilities to manufacturing systems. We address this problem by analyzing supervisory controller information requirements for intervening in complex process control tasks as part of FMS operation. This analysis was conducted using a cognitive engineering research methodology, which has not previously been applied, in the domain of manufacturing. The method of GTA was applied to supervisory control of an FMS and produced detailed information requirements, which facilitated the formulation of general design guidelines for FMS interface design. The guidelines are aimed at supporting human operator process strategy development and decision making. © 2000 John Wiley & Sons, Inc.     

A hybrid heuristic to solve the parallel machines job-shop scheduling problem

This paper presents an advanced software system for solving the flexible manufacturing systems (FMS) scheduling in a job-shop environment with routing flexibility, where the assignment of operations to identical parallel machines has to be managed, in addition to the traditional sequencing problem. Two of the most promising heuristics from nature for a wide class of combinatorial optimization problems, genetic algorithms (GA) and ant colony optimization (ACO), share data structures and co-evolve in parallel in order to improve the performance of the constituent algorithms. A modular approach is also adopted in order to obtain an easy scalable parallel evolutionary-ant colony framework. The performance of the proposed framework on properly designed benchmark problems is compared with effective GA and ACO approaches taken as algorithm components.