. No. of pages: 298. This book focuses on flexible manufacturing systems (FMSs) and the authors' matrix-based supervisory control design method. Their matrices are easily generated from standard manufacturing data such as the bill of materials (BOM), assembly tree, and resource requirements. An important feature of their final design is that it can be converted into an executable programmable logic controller code (PLC). The book's mathematical level makes it suitable for a graduate course. Although the mathematical rigor is high, the authors are quick to demonstrate how a practical problem has motivated their mathematical formulations. Numerous implementations on physical testbeds are described throughout the book.Chapter 1 presents the modeling and control issues for automated manufacturing systems. These systems are discrete event in their operation with numerous interacting components. These interactions lead to concurrent and asynchronous events that may also be stochastic. The interactions of the subsystems coupled with the discrete nature of the dynamics is at the core of the modeling and control problem. Hence, they are classified as a discrete-event dynamic system. A supervisory controller is essential to the successful operation of these systems, and the matrix-based methodology is an elegant solution to the design of effective controllers.The supervisory controller determines which new jobs are to be dispatched into the system and how current jobs should be routed through the production network and to which machine. These decisions are made in real time and they are based on the performance objective, e.g., minimum production time, meet the due date, maximize throughput. The control problem is further complicated by the fact that the same resource is often requested by more than one job and machines can perform more than one type of operation. This means that many paths (or routes) exist to produce the final product. The supervisory controller needs to sort out these possibilities while avoiding deadlock. It should also be possible to analyze the controller for deadlock, simulate it before implementation, and generate a code suitable for a PLC implementation. The authors demonstrate their results on a three-robot FMS at the University of Texas at Arlington.Chapter 2 describes some current ways to model manufacturing systems. Specifically, a finite state machine is used to model a one-robot, two-machine workcell. This simple example illustrates that 14 states are needed to model this system and the number of states will grow quickly as more components are added. Any changes to the system will require the designer to enumerate all possible states again. Furthermore, the model is deterministic and not very amenable to analysis.Several matrices form the building blocks for the matrix-based approach to modeling and control and they are obtained from readily available manufacturing data. Chapter 3 shows how the matrix description for a specific manufacturing system and job is generated from the BOM, Steward...
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