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

Global approaches to solving recognition problems of noisy images, 1989

An important problem in the area of pattern recognition is automatic detection of certain pre-assigned elements of an image distorted by noise. In this research, a global ap proach will be used. One such approach is to use an optimal smoothing algorithm which depends on efficient dynamic programming computational techniques. The basic purpose of this research is to make this dynamic programming process efficient in terms of storage requirement and computational effort. Our goal, using the objective function, is to find an optimal order of optimization and then design an effi cient computational technique. Two global techniques will be presented in this paper. Included is a graph-searching technique and the above men tioned technique using dynamic programming. Emphasis will be on the development of an algorithm using dynamic program ming. I wish to express ray deepest appreciation and sincere gratitude to those who have contributed their time, energy, and support to make this study possible. Thanks are especially due Dr. Warsi, Nazir A. , my thesis advisor. His instruction, suggestions, and patience were essential to the completion of this thesi s. Further thanks are also due Nasa Langley for providing financial, technical, and general support to help make this study possible. Special thanks are offered to Mr. Micheal Goode, Technical Monitor, for his technical support and to Dr. Samuel E. Massenberg, University Affairs Officer, for his general support

Evaluation Functions in General Game Playing

While in traditional computer game playing agents were designed solely for the purpose of playing one single game, General Game Playing is concerned with agents capable of playing classes of games. Given the game's rules and a few minutes time, the agent is supposed to play any game of the class and eventually win it. Since the game is unknown beforehand, previously optimized data structures or human-provided features are not applicable. Instead, the agent must derive a strategy on its own. One approach to obtain such a strategy is to analyze the game rules and create a state evaluation function that can be subsequently used to direct the agent to promising states in the match. In this thesis we will discuss existing methods and present a general approach on how to construct such an evaluation function. Each topic is discussed in a modular fashion and evaluated along the lines of quality and efficiency, resulting in a strong agent.:Introduction Game Playing Evaluation Functions I - Aggregation Evaluation Functions II - Features General Evaluation Related Work Discussio

Computer science: the hardware software and heart of IT

1st edition, 201