Scheduling and discrete event control of flexible manufacturing systems based on Petri nets

A flexible manufacturing system (FMS) is a computerized production system that can simultaneously manufacture multiple types of products using various resources such as robots and multi-purpose machines. The central problems associated with design of flexible manufacturing systems are related to process planning, scheduling, coordination control, and monitoring. Many methods exist for scheduling and control of flexible manufacturing systems, although very few methods have addressed the complexity of whole FMS operations. This thesis presents a Petri net based method for deadlock-free scheduling and discrete event control of flexible manufacturing systems. A significant advantage of Petri net based methods is their powerful modeling capability. Petri nets can explicitly and concisely model the concurrent and asynchronous activities, multi-layer resource sharing, routing flexibility, limited buffers and precedence constraints in FMSs. Petri nets can also provide an explicit way for considering deadlock situations in FMSs, and thus facilitate significantly the design of a deadlock-free scheduling and control system. The contributions of this work are multifold. First, it develops a methodology for discrete event controller synthesis for flexible manufacturing systems in a timed Petri net framework. The resulting Petri nets have the desired qualitative properties of liveness, boundedness (safeness), and reversibility, which imply freedom from deadlock, no capacity overflow, and cyclic behavior, respectively. This precludes the costly mathematical analysis for these properties and reduces on-line computation overhead to avoid deadlocks. The performance and sensitivity of resulting Petri nets, thus corresponding control systems, are evaluated. Second, it introduces a hybrid heuristic search algorithm based on Petri nets for deadlock-free scheduling of flexible manufacturing systems. The issues such as deadlock, routing flexibility, multiple lot size, limited buffer size and material handling (loading/unloading) are explored. Third, it proposes a way to employ fuzzy dispatching rules in a Petri net framework for multi-criterion scheduling. Finally, it shows the effectiveness of the developed methods through several manufacturing system examples compared with benchmark dispatching rules, integer programming and Lagrangian relaxation approaches

Modeling sequential resource allocation systems using Extended Finite Automata

Deadlock avoidance for resource allocation systems (RAS) is a well-established problem in the Discrete Event System (DES) literature. This paper is mainly concerned with modeling the class of Conjunctive / Disjunctive sequential resource allocation systems (C/D RAS) as finite automata extended with variables. The proposed modeling approach allows for modeling multiple instance execution, routing flexibility and failure handling. With an appropriate model of the system, a symbolic approach is then used to synthesize the optimal supervisor, in the least restrictive sense. Furthermore, a set of compact logical formulae can be extracted and attached to the original model, which results in a modular and comprehensible representation of the supervisor

Simulation in Automated Guided Vehicle System Design

The intense global competition that manufacturing companies face today results in an increase of product variety and shorter product life cycles. One response to this threat is agile manufacturing concepts. This requires materials handling systems that are agile and capable of reconfiguration. As competition in the world marketplace becomes increasingly customer-driven, manufacturing environments must be highly reconfigurable and responsive to accommodate product and process changes, with rigid, static automation systems giving way to more flexible types. Automated Guided Vehicle Systems (AGVS) have such capabilities and AGV functionality has been developed to improve flexibility and diminish the traditional disadvantages of AGV-systems. The AGV-system design is however a multi-faceted problem with a large number of design factors of which many are correlating and interdependent. Available methods and techniques exhibit problems in supporting the whole design process. A research review of the work reported on AGVS development in combination with simulation revealed that of 39 papers only four were industrially related. Most work was on the conceptual design phase, but little has been reported on the detailed simulation of AGVS. Semi-autonomous vehicles (SA V) are an innovative concept to overcome the problems of inflexible -systems and to improve materials handling functionality. The SA V concept introduces a higher degree of autonomy in industrial AGV -systems with the man-in-the-Ioop. The introduction of autonomy in industrial applications is approached by explicitly controlling the level of autonomy at different occasions. The SA V s are easy to program and easily reconfigurable regarding navigation systems and material handling equipment. Novel approaches to materials handling like the SA V -concept place new requirements on the AGVS development and the use of simulation as a part of the process. Traditional AGV -system simulation approaches do not fully meet these requirements and the improved functionality of AGVs is not used to its full power. There is a considerflble potential in shortening the AGV -system design-cycle, and thus the manufacturing system design-cycle, and still achieve more accurate solutions well suited for MRS tasks. Recent developments in simulation tools for manufacturing have improved production engineering development and the tools are being adopted more widely in industry. For the development of AGV -systems this has not fully been exploited. Previous research has focused on the conceptual part of the design process and many simulation approaches to AGV -system design lack in validity. In this thesis a methodology is proposed for the structured development of AGV -systems using simulation. Elements of this methodology address the development of novel functionality. The objective of the first research case of this research study was to identify factors for industrial AGV -system simulation. The second research case focuses on simulation in the design of Semi-autonomous vehicles, and the third case evaluates a simulation based design framework. This research study has advanced development by offering a framework for developing testing and evaluating AGV -systems, based on concurrent development using a virtual environment. The ability to exploit unique or novel features of AGVs based on a virtual environment improves the potential of AGV-systems considerably.University of Skovde. European Commission for funding the INCO/COPERNICUS Projec

An analysis of FMS scheduling problem: a beam search based algorithm and comparison of scheduling schemes

Ankara : Department of Industrial Engineering and Institute of Engineering and Sciences, Bilkent Univ., 1994.Thesis (Master's) -- Bilkent University, 1994.Includes bibliographical references leaves 77-80FMS scheduling procedures in the literature can be classified into on-line and off-line schemes according to the number of scheduling decisions made at a point in time. Online scheduling attempts to schedule operations one at a time when it is needed and off-line scheduling refers to scheduling operations of available jobs for the entire scheduling period. In the literature there is no unified argument for or against either of these scheduling schemes. This research has two main objectives: development of a new scheduling scheme called quasi on-line that makes a trade-off between on-line and off-line schemes and comparison of the proposed scheme with others under various experimental conditions. A new algorithm is proposed on which the quasi online scheme is based. The proposed algorithm is a heuristic and utilizes a beam search technique. It considers finite buffer capacity, routing and sequence flexibilities and generates machine and AGV schedules for a given scheduling period. A simulation model is also developed to implement and test scheduling schemes.Karabük, SüleymanM.S

Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems

The dynamic continues trend of adoption and improvement inventive automated technologies is one of the main competing strategies of many manufacturing industries. Effective integrated operations management of Automated Guided Vehicle (AGV) system in Flexible Manufacturing System (FMS) environment results in the overall system performance. Routing AGVs was proved to be NP-Complete and scheduling of jobs was also proved to be NP hard problems. The running time of any deterministic algorithms solving these types of problems increases very rapidly with the size of the problem, which can be many years with any computational resources available presently. Solving AGVs conflict free routing, dispatching and simultaneous scheduling of the jobs and AGVs in FMS in an integrated manner is identified as the only means of safeguarding the feasibility of the solution to each sub-problem. Genetic algorithm has recorded of huge success in solving NP-Complete optimization problems with similar nature to this problem. The objectives of this research are to develop an algorithm for integrated scheduling and conflict-free routing of jobs and AGVs in FMS environment using a hybrid genetic algorithm, ensure the algorithm validity and improvement on the performance of the developed algorithm. The algorithm generates an integrated scheduling and detail paths route while optimizing makespan, AGV travel time, mean flow time and penalty cost due to jobs tardiness and delay as a result of conflict avoidance. The integrated algorithms use two genetic representations for the individual solution entire sub-chromosomes. The first three sub-chromosomes use random keys to represent jobs sequencing, operations allocation on machines and AGV dispatching, while the remaining sub-chromosomes are representing particular routing paths to be used by each dispatched AGV. The multiobjective fitness function use adaptive weight approach to assign weights to each objective for every generation based on objective improvement performance. Fuzzy expert system is used to control genetic operators using the overall population performance history. The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. Parameterized uniform crossover (PUX) and migration are used as genetic operators for sub-chromosomes represented using random-key based encoding. Computational experiments were conducted on the developed algorithm coded in Matlab to test the effectiveness of the algorithm. First scenario uses static consideration, the second scenario uses dynamic consideration with machine failure recovery. Sensitivity analysis and convergence analysis was also conducted. The results show the effectiveness of the proposed algorithm in generating the integrated scheduling, AGVs dispatching and conflict-free routing. The comparison of the result of the developed integrated algorithm using two benchmark FMS scheduling algorithms datasets is conducted. The comparison shows the improvement of 1.1% and 16% in makespan of the first and the second benchmark production dataset respectively. The major novelty of the algorithm is an integrated approach to the individual sub-problems which ensures the legality, and feasibility of all solutions generated for various sub-problems which in the literature are considered separately

Analysis of multi-stage open shop processing systems

We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe system states. We show that it is easy to recognize system states that can be reached from the initial state (where the system is empty), but that in general it is hard to decide whether one given system state is reachable from another given system state. We show that the problem of identifying reachable deadlock states is hard in general open shop systems, but is easy in the special case where no job needs processing on more than two machines (by linear programming and matching theory), and in the special case where all machines have capacity one (by graph-theoretic arguments).Comment: 19 pages, no figure