School of Industrial and Manufacturing Sciences (SIMS)

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Browsing School of Industrial and Manufacturing Sciences (SIMS) by Supervisor "Jared, Graham"

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    Evolutionary computing techniques for handling variable interaction in engineering design optimisation
    (2001-11) Tiwari, Ashutosh; Roy, Rajkumar; Jared, Graham
    The ever-increasing market demands to produce better products, with reduced costs and lead times, has prompted the industry to look for rigorous ways of optimising its designs. However, the lack of flexibility and adequacy of existing optimisation techniques in dealing with the challenges of engineering design optimisation, has prevented the industry from using optimisation algorithms. The aim of this research is to explore the field of evolutionary computation for developing techniques that are capable of dealing with three features of engineering design optimisation problems: multiple objectives, constraints and variable interaction. An industry survey grounds the research within the industrial context. A literature survey of EC techniques for handling multiple objectives, constraints and variable interaction highlights a lack of techniques to handle variable interaction. This research, therefore, focuses on the development of techniques for handling variable interaction in the presence of multiple objectives and constraints. It attempts to fill this gap in research by formally defining and classifying variable interaction as inseparable function interaction and variable dependence. The research then proposes two new algorithms, GRGA and GAVD, that are respectively capable of handling these types of variable interaction. Since it is difficult to find a variety of real-life cases with required complexities, this research develops two test beds (RETB and RETB-II) that have the required features (multiple objectives, constraints and variable interaction), and enable controlled testing of optimisation algorithms. The performance of GRGA and GAVD is analysed and compared to the current state-of-the-art optimisation algorithm (NSGAII) using RETB, RETB-II and other ‘popular’ test problems. Finally, a set of real-life optimisation problems from literature are analysed from the point of variable interaction. The performance of GRGA and GAVD is finally validated using three appropriately chosen problems from this set. In this way, this research proposes a fully tested and validated methodology for dealing with engineering design optimisation problems with variable interaction.
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    Product complexity assessment for a Proactive-DFA implementation (Simplicity + Simplicity = Complexity)
    (2004-10) Rodriguez-Toro, Carlos A.; Jared, Graham
    This thesis presents product complexity as a criterion for the optimisation of product design in the light of an Assembly-Oriented Design and Design for Assembly implementation. It takes a holistic approach to the evaluation of the product architecture by presenting a set of indicators that help examine the product structure at two different levels: Assembly and Component complexity. Assembly complexity assessment is further sub-divided into Structural and Sequence complexity. The latter is a well-known and thoroughly studied area in assembly sequence evaluation, whereas the former gives a novel and original approach to drawing attention to those areas in the product configuration that will consume more resources (i.e. time and tooling required). Component complexity, on the other hand, is sub-divided into manufacturing and process handling/manipulation complexity. The first area has been addressed by the manufacturing analysis section of most Design for Assembly and Manufacturing methodologies, but it has been traditionally addressed as a manual and chart-based evaluation. This is a rigid approach that leaves little room for expansion and has no connection with the product structure. The metrics presented in this work embody a new approach that takes into account the component-to-component interactions and allows the analysis of component shape by extracting its geometry characteristics and comparing them with particular traits of the manufacturing processes available to the designer. Additionally, the metrics presented in this work can be used to make an assessment of the product complexity at a particular point (static complexity) in the development cycle. They can also be registered over a period of time to provide an estimate of the possible consequences of the decisions made during a part of the development cycle (dynamic complexity). By using the methods developed, designers could reduce production costs and increase the reliability of their products.