Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 101-105). Also available in electronic version.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 141-145). Also available in electronic version.

Thesis (Ph. D.)--School of Computing and Engineering and Dept. of Mathematics. University of Missouri--Kansas City, 2005. / "A dissertation in engineering and mathematics." Advisor: Ghulam Chaudhry. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed June 26, 2006. Includes bibliographical references (leaves 341-346 ). Online version of the print edition.

Thesis (Ph. D.)--Ohio State University, 1986. / Includes bibliographical references (leaves 192-206). Available online via OhioLINK's ETD Center.

Manufacturing industries rely on automated manufacturing systems to improve the efficiency, quality and flexibility of production. Such systems typically consist of a variety of manufacturing machinery and control hardware, e.g. CNC machine tools, robots, PCs, Programmable Logic Controllers (PLCs) etc., which operate concurrently. The cost of developing and implementing an automated manufacturing system is high, and is particularly so if the control system is found to be unreliable or unsafe during operation. Distributed Control Systems are generally used to control complex concurrent systems,At present the methods used to develop DCSs tend to follow a sequence of steps, viz. a statement of the requirements of the DCS, a functional specification of the DCS, the design of the DCS, generation of the software code for the DCS, implementation of the software. This step approach is inadequate because of the dissimilarity of techniques used to represent each step, which leads to difficulties in ensuring equivalence between the final implementation of the DCS and the initial requirements, which in turn leads to errors in the final software. To overcome this, work has been conducted to unify the specification, design, and software coding phases of the DCS development procedure by ensuring formal equivalencies between them. One particular outcome of such previous work is a tool named Petri Net - Occam Methodology, developed by Dr. P. Gray, which produces dependable Occam code for DCSs. Gray's methodology produces readable designs, directly from the specification of systems, in a graphical but formal way, and results in a Petri Net graph which is equivalent to the final Occam code. However, his methodology is not for a complete DCS but only for one containing Transputers. The PLC is widely used in industry and an integral part of DCSs for Automated Manufacture. This research has developed a methodology, named PNPLC, which produces dependable PLC control programs, in a graphical but formal way, directly from a system's specification. It uses the same tool, Petri Nets, for both designing and simulating the control system, and specifies rules which ensure the correct design, simulation and encoding of PLC programs. The PN designs are a one-to-one equivalent to PLC code and can be directly translated into Ladder Diagrams. Therefore if the simulation shows the design to be correct, the final software will be correct. PNPLC works as a stand alone tool for developing dependable PLC control programs, and also unifies with Gray's methodology to produce a complete tool for developing a resilient DCS containing Transputers and PLCs. The unification of the two methodologies is also reported in this thesis. The research work presented in this thesis contributes to knowledge in the field of DCS development. Recommendations for further work regarding the applicability of the unified methodology on a wide scale industrial basis are also given.

In the competitive field of metalworking industry, the planning of manufacturing systems so as to maximise their performance is crucial. The relatively new field of Flexible Manufacturing Systems presents a new set of planning challenges to the production engineer. This is due to the integrated nature of the these systems and the resultant effects upon their performance. This thesis presents a structured approach to the planning of materials flow within these systems and develops it by the analysis of several proposed manufacturing systems. The approach is based upon the use of mathematical and discrete event simulation techniques. The thesis gives the background to the need for a structured approach, investigates the parallel development of simulation languages and related techniques as applied to manufacturing facilities planning; and of the Flexible Manufacturing Systems themselves. The approach is then detailed and some specific types of planning tool are identified as suitable for use at each project stage. The effects upon the system of the integration of separate units, especially in low work in progress environments, are discussed in some detail. The methodology developed is then used in the context of three projects, specifically developing the theme of automated tool handling and the requirements that it places upon other aspects of a manufacturing system. The projects cover the analysis of pooling strategies, a key factor in determining tool magazine sizes and handling capacity/frequency demands; an academic analysis of a system with both component and tool handling systems; and an advanced Flexible Manufacturing System, also with both automated component and tool handling, which is currently being installed. Conclusions are presented at each stage, and these are drawn together to form a foundation for the planning of materials flow within Flexible Manufacturing Systems in general. Finally, suggestions are made for future work to develop the analysis.

This thesis proposes a cost based grouping procedure for Group Technology. The procedure is a two-stage graph partitioning approach to determine machine cells. Costs of work-in-process inventory, machine depreciation, machine setup and material handling are used as a basis for grouping. The procedure begins by selecting economic lot sizes for each part type and converting these values to machine requirements. The first stage assigns parts to machines of a common type. The second stage groups individual machines to cells, with each machine cell having a number of machines between chosen lower and upper limits. An additional check is given to the final groupings to see if adding a machine of any type can result in savings on the intergroup material handling cost. The process may iterate by next obtaining updated setup times and restarting.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references.

published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

Today's manufacturers tend to use integrated manufacturing systems in order to achieve the capability to quickly respond to customer's requirements and produce high quality products in the shortest possible time and at the lowest possible cost. However, due to insufficient resources, manufacturing Small and Medium Enterprises (SMEs) are having difficulties in achieving this flexibility and competing with large companies. By integrating the manufacturing resources of many partners, which may be located in different regions, SMEs can form a global SME network to achieve the competitive edge. This need for the integration of globally distributed manufacturing resources across enterprise boundaries has been conceptualised with an integration concept of Virtual Computer Integrated Manufacturing (VCIM). / VCIM extends Computer Integrated Manufacturing (CIM) system to the next stage of virtual enterprise, and aims to provide the capability to quickly respond to customers' product orders based on working status information of distributed resources in real time. In a VCIM system, manufacturing resources may belong to different partner enterprises, or be located at different areas, but all have the intention of working together to achieve market screen. The emphasis of VCIM is to integrate many manufacturing resources and provide cohesive services for customers who may be at different locations. / Thesis (PhD)--University of South Australia, 2007.