Among many issues involved within the field of manufacturing systems, the design of facilities layout is an ongoing and interesting research field, where new solutions and approaches are sought to determine the appropriate location and physical organisation of the resources in manufacturing systems. Issues such as space, material handling, machine placement and orientation, utilities location, and environmental factors are important features that may be considered when establishing the requirements of a facility layout design. The facility layout design can be thought of in terms of interconnecting work centres that can be represented by a set of interrelated vertices in a graph. Directed graphs can be used to characterise each product operation sequence, which combined into a single directed graph, be used to represent appropriately a layout design. Doing this together with the material handling system requirements, will allow better facilities planning and may improve process sequences that should be reflected in better designs. The Strong Component Based Methodology proposed here, obtains a graphical structure from the integration of various products and using their operation sequences to produce a relationship diagram. The attributes of the resultant structure are used to create this diagram. The objective is to obtain layouts that minimise material handling, that is, as close as possible to that which can be obtained with dedicated facilities for each product family but without the capital costs involved in the case of the latter. Encouraging results have been obtained by considering strong components, a feature of directed graphs, because less computational resources than in the case of many previous methods, which use Quadratic Assignment Problem approaches, are required to formulate and produce a relationship diagram. Moreover, this approach produces faster designs than other graph theoretic approaches because it avoids using planar and dual graphs. These characteristics allow the Strong Components approach to address more complex situations and obtain comparable or better solutions than previous approaches. The proposed Strong Component approach is a robust and versatile tool to support layout designs. It is a robust methodology because it provides efficient relationship diagrams even in cases when the resultant structure has relatively few strong component relationships. It is a versatile approach, because it can address various situations and can use different criteria to create layouts. Thus, the proposed approach offers effective-economical relationship diagrams to produce the same set of products as when producing them in dedicated facilities.

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Assembly plays a vital role in the quality of a final product and has a great impact on the manufacturing cost. The mechanical assemblies consist of parts that inevitably have variations from their ideal dimensions. These variations propagate and accumulate as parts are assembled together. Excessive amount of variations in an assembly may cause improper functionality of the product being assembled. Improving assembly quality and reducing the assembly time and cost are the main objectives of this thesis. The quality of an assembly is determined in terms of variations in critical assembly dimensions, also known as Key Characteristics (KCs). Key Characteristics are designated to indicate where excess variation will affect product quality and what product features and tolerances require special attention. In order to improve assembly quality and reduce assembly time and cost, it is necessary to: (1) model non-ideal parts based on tolerances defined in design standards or current industrial practice of component inspection, (2) model assemblies and their associated assembly processes to analyse tolerance stack-up in the assembly, (3) develop probabilistic model to predict assembly variation after product assembly, and (4) implement control strategies for minimising assembly variation propagations to find optimum configuration of the assembly. Two assembly models have been developed, a linear model and a fully non-linear model for calculating assembly variation propagations. The assembly models presented in this thesis also allows for inclusion of geometric feature variation of each assembly component. Methods of incorporating geometric feature variations into an assembly variation model are described and analysis techniques are explained. The assembly variation model and the geometric variation models have been developed for 20 and 3D assemblies. Modelling techniques for incorporating process and measurement noise are also developed and described for the nonlinear assembly model and results are given to demonstrate the calculation of assembly variations while considering part, process and measurement errors. Two assembly case studies originating in sub-assemblies of aero-engines have been studied: Case Study 1, representing the rotating part (rotor) of an aero-engine, and Case Study 2, representing non-rotating part (stator) of an aero-engine. A probabilistic method based on the linear model is presented as a general analytical method for analysis of 3D mechanical assemblies. Probability density functions are derived for assembly position errors to analyse a general mechanical assembly, and separate probability functions are derived for the Key Characteristics (KCs) for assembly in Case Studies 1 and 2. The derived probability functions are validated by using the Monte Carlo simulation method based on the exact (full non-linear) model. Results showed that the proposed probabilistic method of estimating tolerance accumulation in mechanical assemblies is very efficient and accurate when compared to the Monte Carlo simulation method, particularly if large variations at the tails of the distributions are considered. Separate control strategies have been implemented for each case study. Four methods are proposed to minimise assembly variations for Case Study 1, and one error minimisation method is suggested for assemblies of Case Study 2. Based on the developed methods to optimise assembly quality, the two case studies were investigated, and it was found that the proposed optimisation methods can significantly improve assembly quality. The developed optimisation methods do not require any special tooling (such as fixtures) and can easily be implemented in practice.

There is no abstract available for this thesis.

The Stereolithography (SL) process has developed into an accurate method of replicating 3D CAD images into tactile objects used for functions such as product evaluation, preproduction testing or as patterns around which tool cavities can be formed. One of the main limitations with the SL process is the surface roughness of parts resulting from the layer manufacturing process. To-date surface roughness has only been reduced using techniques such as additive coating or abrasive finishing. Research has shown however, that these techniques are both detrimental to the accuracy of parts and can prove to increase the cost of SL parts to the end user. The object of this research is to assess the fundamental cause of surface roughness in layer manufacturing and develop techniques that can be used during the build process to produce SL parts with lower surface deviation. To do this a comparison of the most common commercial RP systems was undertaken to identify the attributes causing surface deviation. From these attributes a mathematical model of layer manufactured surface roughness was developed. Parts manufactured using different SL machines were compared to the mathematical model showing a variety of causes in surface deviation not considered in earlier research, such as layer composition, layer profile and the affects of over curing or print-through on surface deviation. The layer edge profile caused by the shape of the scanning laser also has a significant effect on roughness deviation. However, by using a combination of part orientation and optimal shaped meniscus smoothing, the surface deviation of SL parts was found to be reduced by up to 400% on at least 90- degrees of continuous surfaces. A better understanding of layer manufactured surface roughness has now been achieved and a new smooth build algorithm has been developed.

The potential advantages of Cellular Manufacturing Systems (CMS) are very well known in industry. However it is also shown that their performance is very sensitive to changing production requirements. The detrimental effects of changing production requirements on the performance of CMS can be alleviated by "implementing better manufacturing cell designs", "employing effective part loading strategies" and "reconfiguration". This thesis proposes a decision support framework that provides solution strategies for manufacturing cell design, cell loading and reconfiguration problems. There are three main modules in the proposed framework, named as cell formation, loading and reconfiguration. Each module can handle multiple objectives and integrates several planning and design functions, by considering the capabilities of manufacturing resources. Reconfiguration decisions are made explicitly in the proposed framework by answering the questions "when to reconfigure?" and "how to reconfigure?”. In order to answer these questions, the modules of the proposed framework are interconnected. The cell formation module creates the initial set of cells. The loading module makes the 'part to cell assignment' and the scheduling in each production period. The reconfiguration module regenerates manufacturing cells, if the loading module can not find a satisfactory solution. The cell formation module solves the part-machine cell formation problem by simultaneously considering multiple objectives and constraints. Overlapping machine capabilities and generic part process plans are taken into account in the model formulation. A new approach for the evaluation of machine capacities is also presented. Results of the comparative study show that the proposed cell formation method gives better results than several other cell-formation procedures. The manufacturing cells are formed with improved capacity utilisation levels and reduced extra machine requirements. The method is also more likely to produce independent manufacturing cells with higher flexibility. The loading module solves the 'part to cell assignment' and 'cell scheduling' problems simultaneously for cellular manufacturing applications. Alternative parts to cell and machine assignments are considered by making use of generic part process plans in the model formulation. A parametric simulation model is developed to determine cell schedules for a given part assignment scenario. The proposed loading system can assess performance of the CMS in each production period. Therefore a decision can be made about its reconfiguration. It is also shown that the efficiency of CMSs facing changing production requirements can be improved and/or sustained by using the proposed loading strategy. The reconfiguration module takes the existing cell configuration as the current solution and generates a new solution from it, to enhance its performance. The model is objective driven and considers multiple objectives and constraints within a goal programming framework. The virtual cell concept is applied as the reconfiguration strategy. In the virtual cell approach the physical locations of machines are not changed, only cell memberships of machines are updated after reconfiguration. The results of the test studies showed that it is possible to improve the performance of CMS by reconfiguring it using virtual cells. The cell formation, loading and reconfiguration problems issues discussed in this thesis are combinatorially complex multiple objective optimisation problems. Additionally simulation is used to evaluate several of the objective functions used in the modelling of loading and reconfiguration problems. Classical optimisation algorithms have various limitations in solving such problems. Therefore Tabu Search (TS) based multiple objective optimisation algorithms are developed. The proposed TS algorithms are general-purpose and can also be used to solve other multiple objective optimisation problems. The results obtained from several test problems show the proposed TS algorithms to be very effective in solving multiple objective optimisation problems. More than 500/0 improvement in solution quality is obtained in some test problems.

In today's business environment, firms increasingly think in the context of a supply chain rather than a single factory and operate globally rather than in a single nation. At the same time, we have also witnessed increasing breadth in product ranges and accelerating rates of new product introduction in the marketplace. While there are potentially strong interrelationships between product variety and international supply chain management, the issues have been addressed separately in the research literature. Owing to this shortfall, this study investigates the issue of product variety in the context of international supply networks. More specifically, the study seeks to gain insights on different types of co-ordination and configuration of international supply network and to more deeply understand the impact of, and the interrelationships between, product variety, supply lead-time and demand uncertainty on the performance of an international supply chain. Empirical and simulation studies have been conducted to fulfil the above objectives. The empirical study involves eleven manufacturing companies in Indonesia, belonging to both Multinational Corporations (MNC) and contract manufacturers, and one company in the UK operating internationally that owns manufacturing units as well as contracting out. The empirical study generated findings on configuration structures, co-ordination policies, and product variety impact and management. Based on their configuration and coordination strategies, MNC supply networks involved in the empirical study can be classified as supply networks that have regional autonomous subsidiaries, regional clusters of subsidiaries and purely global supply network. Contract manufacturers' configurations may change from one selling period to another. More co-ordination efforts are found to be necessary in MNC supply networks compared to contract manufacturer supply networks. Although companies face different challenges with respect to product variety and uncertainties in demand and supply, the evidence shows that product variety principally affects the procurement of materials, as various products require different materials and parts. Product variety also affects production due to the need to conduct set-up activities. To obtain a deeper understanding of the impacts of product variety, supply lead time and demand uncertainty on supply chain performance, a simulation study has been conducted. A simulation model was developed based on the insights obtained from the empirical study. The model represents a three-stage MNC supply network producing consumer goods in discrete manufacturing processes. Product variety is represented in the model by the use of different types of material required at different stages of the production process. An extensive set of simulation experiments concentrated on flow time and inventory performance. Results from the simulation experiments show that increases in product variety extend the average flow time due to the need to conduct set-up activities. The impact of product variety on flow time depends on the severity of set-up and the stage at which variety occurs in the production processes. Variety occurring early in the production process and generating long set-up times has a more pernicious impact on average flow time compared to variety occurring later and requiring shorter set-ups. Supply and demand uncertainty may affect the supply chain performance as it may delay the manufacturing processes. When supply lead-time is subject to uncertainty, materials may not be available at the right time for production. Similarly, demand uncertainty may lead to a situation where the available materials may not be adequate to meet the production requirements. The simulation results show that producing high variety when material delivery time is subject to uncertainty has a damaging impact on the two supply chain performance metrics - flow time and inventory level. The supply chain performance worsens with increasing level of supply uncertainty. Producing high variety when either aggregate-level or product-level demand is subject to uncertainty results in a higher level of inventory and longer average flow time. The worst performance in terms of average flow time and average inventory is evident when the supply chain produces maximum variety and both supply and demand are subject to uncertainty. The simulation study provides a guide to the magnitude of the impact in each case. Findings from the empirical and simulation study are synthesised into a framework for understanding and managing product variety in international supply chains. The framework can be used to understand interrelationships between key factors in managing product variety in international supply networks and to identify potential strategies to mitigate the negative impact of those factors on performance.

An experimental study has been made of the behaviour of "very thin" torispherical ends subjected to internal pressure. The seventeen ends tested were full-size production ends made from stainless steel, with thickness to diameter ratios (te/Di) varying from 0.002 to 0.001. At each value of te/Di the knuckle radius (ri) and crown radius (Ri) were varied to cover the range of ends frequently used. Each end was stain gauged on both inner and outer surfaces and then pressurised until buckling occurred in the knuckle region. The strain gauges were monitored throughout each test thus giving a detailed coverage of the strain distribution. High compressive hoop strains, shown to exist on both surfaces of the knuckle, are responsible for the buckling mode of failure. A shape/thickness survey was performed on each end prior to pressure testing. The effects of thickness reductions and deviations of curvature from the nominal are discussed. Residual strain measurements were made on three ends and were shown to be significantly large in the pressed and spun manufactured ends. A study of the effect of work hardening on the properties of the material from which the ends were made is also presented. It is shown that the proof stress and Vickers hardness number increases rapidly when the material is work hardened. The dependence of the elastic stress indices, limit pressures and first buckling pressures on wall thickness, knuckle radius and crown radius has been examined. The design implications of the study are discussed and a method for predicting the first buckling pressure of production ends given.

Effectively managing and measuring the product development process is widely seen as a means of ensuring business survival through reduced time to market, increased quality and reduced costs. This thesis explores the research question of "How do companies know that they are making effective use of their product design and development function?". A review of the literature in this area revealed that there is a distinct lack of detail available on how measurement of product development should be approached. Where articles do exist, it was found that most report on isolated projects or jump from problem solving straight through to results, without explaining the methodology used. Additionally, both in the literature and in practice, many applications of performance measures to date have been incomplete - without due consideration being given to monitoring and controlling the whole design and development process. For example one tool or technique has been introduced in isolation or schemes have been introduced without evidence of the benefits gained. This thesis documents the development of an implementation framework and a tool (usable in the form of a workbook) to enable a Project Manager, Concurrent Engineering or Process Improvement Champion to use performance measures to improve decision-making during the product development process. The investigative part of the research was carried out by following a longitudinal case study approach with sustained participation in the organisation. This was supplemented by a series of follow-up cases, together with results from surveys to academics and industrialists both in the UK and overseas. Through interpreting the literature and triangulating the results from the data collection and analysis, a number of principles surrounding performance measurement in this area were identified. These were then grouped into system-related and metrics-related principles. Opinions of European managers were gained throughout to ensure direct applicability. The resulting Performance Measurement for Product Development (PMPD) Methodology, consisting of an implementation framework and accompanying practical paper-based workbook (with software extensions), was tested in two companies to determine its usability. These testbeds yielded encouraging results and provided opportunities for further refinement and improvement. The next step will be further testing and refinement in a wider range of applications. It is believed that the research outputs of the international survey results, generic PMPD Implementation Framework, Workbook and Training Guidelines have together made a positive contribution to understanding and measuring the product development process in manufacturing organisations.