INTELLIGENT WORKSTATION CONTROLLER FOR COMPUTER-INTEGRATED MANUFACTURING - PROBLEMS AND MODELS

A shop floor control system (SFCS), an integrated part of computer-integrated manufacturing, oversees the production required to fill orders. To effectively control these activities, it is necessary to define a control architecture and functional perspective of how a SFCS operates. In this paper, a hierarchical SFCS (shop, workstation, equipment) is adopted. The paper presents the problems and models necessary to develop an intelligent workstation controller (IWC) at the middle level of a SFCS. The IWC is responsible for selecting a specific process routing, allocating resources, scheduling and coordinating activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. The IWC fulfills this responsibility using three functions - planning, scheduling, and execution. Requirements for the development of the IWC are to create a process plan representation model, specify the evolution of a process plan from the shop down to the equipment, and define all of the functions to be integrated into an intelligent controller. A deadlock detection and resolution model is also presented to maintain the system in a deadlock-free state. Finally, the IWC software is created to demonstrate the architectural linkages with other controllers. As a result, the development of the IWC will save cost and time in developing control software for automated manufacturing systems.X1136sciescopu

A ROBUST ADAPTIVE SCHEDULER FOR AN INTELLIGENT WORKSTATION CONTROLLER

A shop floor control system (SFCS) consisting of three hierarchical control levels (shop, workstation, and equipment) is described. Each controller plans, schedules, and executes the activities necessary to process an order. An intelligent workstation controller (IWC), which is a part of the SFCS, is described in detail. The IWC receives information such as part type and quantity, part routeing specifications, and process plans from the shop level controller and coordinates production activities. The IWC performs three main functions-planning, scheduling, and execution in real-time in order to ensure completion of jobs assigned by the shop controller. The focus of this paper is to develop a robust adaptive scheduler to support the IWC which fits within the functional SFCS architecture. The objectives of this paper are: (1) to develop a neural network model that generates several part dispatching strategies based on workstation status; (2) to develop a multi-pass simulator that evaluates the generated strategies and selects the best strategy to maximize system efficiency; and (3) to compare the efficiency of the scheduling function with other single-pass strategies with respect to several performance criteria.X1163sciescopu

An intelligent workstation controller for integrated planning and scheduling of an FMS cell

This paper presents an experimental design developed to determine a combination of robust planning and scheduling rules for an intelligent workstation controller (MTC). The IWC is used as part of the control system for an automated flexible manufacturing system. A three-level hierarchical control structure (shop, workstation and equipment) is adopted in order effectively to control a shop-floor. At the top level is a shop controller which receives orders and their associated manufacturing information, and manages interactions among workstations. The IWC defines and resolves the production control activities necessary to coordinate a group of equipment controllers so as to ensure the completion of orders. Specifically, the IWC is responsible for selecting a specific process routeing for each part, allocating resources, scheduling and coordinating the activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports.X113sciescopu

GRAPH-THEORETIC DEADLOCK DETECTION AND RESOLUTION FOR FLEXIBLE MANUFACTURING SYSTEMS

Flexible manufacturing systems are capable of producing a broad variety of products and changing their characteristics quickly and frequently. This flexibility provides for more efficient use of resources, but makes control of these systems more difficult. Control problems previously unstudied now require practical resolution, like system deadlock. A system deadlock is a situation that arises due to resource sharing in manufacturing systems, when the flow of parts is permanently inhibited and/or operations on parts cannot be performed. This problem has been ignored by most scheduling and control studies, which usually assume infinite machine queue capacity and unlimited tooling resources. FMS's, however, have little or no queue capacity and Limited tooling resources. In this paper, graph-theoretic deadlock detection and resolution procedures are presented which are suitable for real-time control of manufacturing systems. These procedures determine whether part movement in the system causes system deadlock or not. To this end, a system status graph representing part routings is virtually updated for every part movement before parts move physically to the next destination. Two types of system deadlocks, part flow deadlock and impending part flow deadlock, are detected using the updated system status graph. If a deadlock detection and recovery method is used to recover from a deadlock using a storage buffer, only part flow deadlocks need to be detected. On the other hand, if no buffer is available, both types of existing as well as impending system deadlocks need to be detected to avoid a deadlock situation.X1188sciescopu

Integration framework of process planning based on resource independent operation summary to support collaborative manufacturing

In today's global manufacturing environment, manufacturing functions are distributed as never before. Design, engineering, fabrication, and assembly of new products are done routinely in many different enterprises scattered around the world. Successful business transactions require the sharing of design and engineering data on an unprecedented scale. This paper describes a framework that facilitates the collaboration of engineering tasks, particularly process planning and analysis, to support such globalized manufacturing activities. The information models of data and the software components that integrate those information models are described. The integration framework uses an Integrated Product and Process Data ( IPPD) representation called a Resource Independent Operation Summary (RIOS) to facilitate the communication of business and manufacturing requirements. Hierarchical process modelling, process planning decomposition and an augmented AND/OR directed graph are used in this representation. The Resource Specific Process Planning (RSPP) module assigns the required equipment and tools, selects process parameters, and determines manufacturing costs based on two-level hierarchical RIOS data. The shop floor knowledge ( resource and process knowledge) and a hybrid approach ( heuristic and linear programming) to linearize the AND/OR graph provide the basis for the planning. Finally, a prototype system is developed and demonstrated with an exemplary part. Java and XML ( Extensible Mark-up Language) are used to ensure software and information portability.X1114sciescopu

A STRUCTURED APPROACH TO DEADLOCK DETECTION, AVOIDANCE AND RESOLUTION IN FLEXIBLE MANUFACTURING SYSTEMS

Production scheduling models that determine part mix ratios and detailed schedules do not usually account for deadlocks that can be caused by part flow. Deadlocks must be prevented for operational control (especially in automated systems). The major thrust of this paper is in developing a structured model for deadlock detection, avoidance and resolution caused by part flow in manufacturing systems. A system status graph can be constructed for the parts currently in the system. Deadlock detection amounts to determining deadlocks in the system status graph. On the other hand, deadlock avoidance amounts to restricting parts movement so that deadlocks are completely avoided in the future. While deadlock detection is a one-step look ahead procedure, deadlock avoidance is a complete look ahead procedure. Deadlock resolution or recovery amounts to judiciously using a limited queue to recover from deadlocks. Deadlock detection and avoidance are absolutely crucial to uninterrupted operation of automated manufacturing systems. A model based in graph theory has been formulated to detect and avoid deadlocks in automated manufacturing systems.X11108sciescopu