Browsing by Subject "Computer integrated manufacturing systems"
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Item A decentralized object-oriented computer integrated manufacturing control system(Texas Tech University, 1991-12) Carroll, Dennis JamesThis dissertation presents and analyzes an object-oriented design of a fully decentralized computer-integrated manufacturing system. The intelligence of the system is dispersed among the cells of the system allowing greater ability to adapt to changes in system configuration. A necessary component of the design is a scheduling strategy for the movement of physical and logical objects through the system. This research proposes and compares two potential scheduling strategies for such a system. The system consists of a set of nodes which serve as temporary hosts for mobile "objects." Each mobile object is responsible for finding its own way through the system based on a process program contained in the object. Each mobile object contains its own copy of a process program and a full description of the path for the object through the system is contained in the process program. A resident attendant object, which serves mobile objects, commands the node to perform a required set of actions based on the mobile object's process program. The attendant object then locates and transfers the mobile object to an available node at the next level to perform the next set of functions of the process program. The potential robustness of this type of system stems from the redistribution of coordinating intelligence from a central controller to the mobile objects. Addition or removal of nodes is completely dynamic as all scheduling and negotiations take place only as needed and without the services of a central controller. Therefore, no single failure can completely and immediately halt such a system except for failures of unique nodes and global network media failures.Item Characterization and integration of control structures for hierarchical process control in production systems(Texas Tech University, 1999-08) Gherasoiu, IulianThe main objective of the research is to construct a generic framework for the design of control structures for production systems. The research deliverables are embedded in the control design framework methodology. The deliverable components of the design framework include the motivation of hierarchical control structure selection, general principles for process characterization, control element definition guidelines, formulation of control enabling principles, and definition of elementary control methods. The integration of control structures is presented from the perspective of goal and temporal coordination. Finally, procedures for conflict resolution and continuous improvement are presented in the context of control structures. The validity of the theoretical construct is based on the scientific rigor of the reference domain—control theory—and on the logical development of argumentation.Item Intelligent process quality control and tool monitoring in manufacturing systems(Texas Tech University, 1994-05) Chinnam, Ratna BabuThe work presented is best characterized as an investigation of neural networks for effective process quality control and monitoring in automated manufacturing systems. The research addresses two basic questions. The first question is whether neural networks have the potential to "identify" cause-effect relationships associated with advanced manufacturing systems to achieve real-time quality control? The second question is whether it is possible to use neural networks to develop effective reliability based real-time tool condition monitoring models for manufacturing systems? Both multilayer feedforward perceptron networks and radial basis fiinction networks are used in novel configurations to achieve real-time process parameter design. The models developed are capable of monitoring process performance characteristics of interest by building empirical based relationships to relate the process response characteristics with controllable and uncontrollable parameters, simultaneously. Using these empirical models and the levels of the uncontrollable parameters obtained through sensors, the quality controller provides levels for the controllable parameters that will lead to the desired levels ofthe quality characteristics in real-time. In general, the quality controller models were able to provide levels for the controllable variables that resulted in the desired process quality characteristics. Test results are discussed for several simulated production processes. A validity index neural network based approach was developed to automate the toolwear monitoring problem. In contrast to the contemporary approaches that basically deal with a classification problem, classifying a given tool as either fresh or worn, the model derived from radial basis function networks predicts the conditional probability of tool survival in accordance with the traditional reliability theory, given a critical performance plane, using on-line sensory data. In general, the radial basis fimction networks performed extremely well in time-series prediction, when tested on actual data collected from a drilling process. The validity index neural network is extended to arrive at the desired conditional tool reliability.Item Reactive parallel machine scheduling using hybrid-intelligence to minimize weighted tardiness, makespan, and cost of rescheduling(Texas Tech University, 2004-08) Phonganant, SupphasakNot availableItem The methodologies of system analysis and design for computer integrated manufacturing (CIM)(Texas Tech University, 1986-12) Scoggins, Shwu-yan ChangThis paper investigates the methodologies of system analysis and design for a CIM system from the software engineer's point of view. The hypotheses of this research are: 1) particular methodologies are likely to be suitable for a specific application system, 2) a combination of methodologies generally can make analysis and design more complete, and 3) analysis of their characteristics can be used to select a methodology capable of providing system specifications for software development and system implementation. To confirm the hypotheses, nine design methodologies are chosen to analyze five application systems. Each methodology and application system has its own characteristics. If the hypotheses are true, it will be possible to match the characteristics of the methodologies with corresponding characteristics of a particular system. Also, once the methodologies are used, they should yield information that provides a set of usable system specifications, and lead to a successful programming environment and implementation of the system. The nine methodologies are SD (Structured Design), MSR (Meta Stepwise Refinement), WOD (Warnier-Orr Design), TDD (Top-Down Design), MJSD (Michael Jackson Structured Design), SADT (Structured Analysis and Design Technique), PSL/PSA (Problem Statement Language/Analyzer), HOS (Higher Order Software), and HIPO (Hierarchy-Input-Process-Output). The five application systems are an overall CIM system, shop floor control subsystem, product design subsystem, production planning/scheduling subsystem, and inventory control subsystem. The characteristics of the methodologies include: system complexity, data structures, data flow, functional structures, process flow, decoupling structure clash recognition, logical control, and data flow control. The characteristics of the application systems include: system complexity, functional structures, process flow, data structures, logical control, data flow control, cohesion, and coupling. The contributions of this research include a technique for applying Information Technology to manufacturing information problems, and a set of rules for combination of different methodologies to improve the results of analysis and design efforts.