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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.

In recent years interest has grown in the use of composite components within the automotive industry. Fibre reinforced plastic (FRP) components are of particular interest to the industry, since lower tooling costs and part consolidation can be utilised, whilst lighter, stiffer components can be produced. Several methods are available to produce FRP components at high volumes, including compression moulding (using dough and sheet moulding compounds), reinforced reaction injection moulding (RRIM) and liquid moulding processes (resin transfer moulding (RTM) and structural reaction injection moulding (SRIM)). RTM is a closed mould process, which is widely used to produce components economically in low volumes using matched moulds to produce two good surfaces. The absence of a high volume manufacturing technology, however, has impeded the acceptance and advance of RTM within the automotive industry. A research programme was established at the University of Nottingham to address the problems associated with the use of RTM for high volume manufacture. This programme has considered the topics of process technology, processing characteristics of polyester resin systems and fibre preforms, fibre wet-out and interfacial bonding, mould design, microwave pre-heating of reactive resin systems and process modelling. This thesis concerns the research which was undertaken to identify the causes of void formation during the impregnation and polymerisation stages of RTM, and methods of reducing the final void content within the component. The impregnation phase of the RTM process was identified as being the stage where the majority of voids were formed. A study of oil impregnation (having a similar viscosity to that of resin) into reinforcement was undertaken to determine the reasons for uneven flow and air entrapment. The dry reinforcements were studied to assess the microstructure of the preforms in order to determine reasons for obstruction of the resin flow. Fabric stitching, thermoplastic binder and size deposits were identified as potential causes of flow impediment. Fibre orientation and preform stacking were also assumed to assist in the development of uneven flow, leading to air entrapment. A major factor determining the formation of microvoids within fibre bundles was identified as the transverse impregnation of resin into high Tex fibre bundles. The major moulding process variables of injection pressure, vent pressure, fibre volume fraction, mould temperature and resin pre-heating have been assessed, to determine their effect on the void content within unidirectional and CFRM reinforced polyester laminates. It was observed that vacuum assistance during impregnation reduced void formation, although higher exotherm pressures and the possibility of monomer boiling arise from its use. A simple impregnation model was developed to assess the microscopic impregnation rates between fibre bundles, in the capillary between fibres and transversely into fibre bundles. The results from this model were compared with actual moulding histories. The findings of the overall work are discussed and suggestions proposed for the reduction of void content in RTM automotive components.

Several techniques are applicable to the modelling of production and inventory control systems. In this thesis discrete linear control theory is examined as a method of modelling multi-product, multi-level systems. These systems are categorised and a general discrete linear control model is used to determine system stability and to predict system responses to specific patterns of input information. The response of the system to random variability in input or other system variable is also shown to be predictable. A library of sub-system models is provided and the method is illustrated by examples and a case study. Alternative modelling techniques rely upon sequential simulation, either directly or in solving equations representing the system. The need to include forecasting, inventory and production decision-making procedures makes such models large and their sequential nature imposes the need for complete remodelling for each system modification and for each input pattern. Where random effects are modelled, protracted runs are necessary to achieve statistically acceptable results. In contrast, discrete linear control theory provides a nonsequential model, thereby alleviating these problems. Thus it is possible both to reduce computing expense and increase the range of systems susceptible to manual analysis. The method is limited by the restriction of linearity, but, in many practical situations this restriction poses no insuperable difficulty in the interpretation of results.

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This thesis proposes a new simulated annealing approach to solve multiple objective sequencing problems in mixed-model assembly lines. Mixed-model assembly lines are a type of production line where a variety of product models similar in product characteristics are assembled. Such an assembly line is increasingly accepted in industry to cope with the recently observed trend of diversification of customer demands. Sequencing problems are important for an efficient use of mixed-model assembly lines. There is a rich of criteria on which to judge sequences of product models in terms of line utilization. We consider three practically important objectives: the goal of minimizing the variation of the actual production from the desired production, which is minimizing usage variation, workload smoothing in order to reduce the chance of production delays and line stoppages and minimizing total set-ups cost. A considerate line manager would like to take into account all these factors. These are important for an efficient operation of mixed-model assembly lines. They work efficiently and find good solution in a very short time, even when the size of the problem is too large. The multiple objective sequencing problems is described and its mathematical formulation is provided. Simulated annealing algorithms are designed for near or optimal solutions and find an efficiency frontier of all efficient design configurations for the problem. This approach combines the SA methodology with a specific neighborhood search, which in the case of this study is a "swapping two sequence". Two annealing methods are proposed based on this approach, which differ only in cooling and freezing schedules. This research used correlation to describe the degree of relationship between results obtained by method B and other heuristics method and also for quality of our algorithm ANOVA's of output is constructed to analyse and evaluate the accuracy of the CPU time taken to determine near or optimal solution.