Additive manufacturing (AM) techniques provide engineering design flexibility not available when manufacturing is constrained by the tool-path restrictions of conventional subtractive techniques such as turning, milling and grinding. AM techniques allow the manufacture of complex form, light weight components with optimised geometries and topographies, including internal and re-entrant features. These features may greatly enhance the components functional capability. The design flexibility may allow a reduction in assembly part count, with a corresponding reduction in assembly time. Additionally, the ability to use high performance engineering metals in the AM process, such as 316 stainless steel, titanium Ti6Al4V and cobalt chrome provide the aerospace, medical and automotive industries with a new manufacturing toolbox using familiar raw materials. These quality-driven industries are fully aware of the potential of AM and are actively engaged and invested with the AM industry and research community. The complex features and design freedom providing great potential for these industries also presents challenges for surface measurement and characterisation. Surface measurement is vital to assure compliance with designed sealing, bearing, flow and adhesion properties of the component. Parts manufactured using AM are not exempt from the stringent quality requirements applicable to other manufacturing processes and so surface texture requirements will be incorporated into drawings and design specifications, imposed by customers onto suppliers. There will need to be a common language and approved standards. Compliance verification will be mandatory. If a feature is specified on a drawing then these industries will require verification that the component complies with design requirements. Traditionally, line-of-sight measuring devices were able to follow the tool pathways to access and measure these surfaces. With the advent of additive processes, new techniques will need to be developed. X-ray computed tomography (CT) has been used successfully for dimensional and defect detection as it allows the measurement of internal and re-entrant features. Thus far, there has been little research on the application of CT for the measurement of surface texture. This thesis reports on the development of a novel technique, detailing the first extraction of areal surface texture parameters per a recognised standard (ISO 25178-2) from CT scans of AM components. Industry will require reproducibility of measurements and so an interlaboratory comparison was performed to compare CT measurement results using this technique from four laboratories. The repeatability and accuracy of surface measurements is also vital for industrial applications and so the influence on extracted surface texture parameter values of selected CT measurement and reconstruction factors has been investigated. Extraction of true 3D data from CT requires the generation of new surface characterisation parameters to take full advantage of the technique and a new parameter has been developed to enable the true surface of re-entrant surfaces to be characterised. The additive process itself is complex and verification of consistent additive machine performance is vital for production. A series of small, inexpensive, surfacespecific measurement artefacts has been developed and built to characterise the build chamber and provide production process verification. This series of inter-related experimental investigations were chosen to be industrially relevant, to be linked closely to component function and be used as practical measurement and surface characterisation techniques. This work is intended, as far as possible, to not be machine-specific, but to be applicable to all CT machines and all metal powder bed fusion (PBF) AM machines. As AM and CT machine capability improves, as it inevitably will, the techniques and applications presented here are designed to evolve with these changes.

Nowadays, New Product Development (NPD) has become a business priority in manufacturing companies due to international competition in terms of meeting higher and changing customer requirements, generating high profit at low cost, and maintaining sustainable development and growth. Through literature review and industrial investigations, it has been recognised that NPD is an information and knowledge intensive process. However, in current practice, enterprise knowledge is not properly managed or easily accessible. Many service providers have not followed the good practice of considering business objectives and end users’ requirements as main drivers of knowledge management system development and implementation. This doctoral thesis presents a methodology for the design and development of Knowledge Management (KM) systems to support NPD based on Enterprise Architecture Frameworks (EAFs). The project focuses on IT system specifications generation driven by business and knowledge users’ requirements in the automotive industry. Current EAFs have been developed by researchers and practitioners to help enterprises to design their information systems based on business objectives and user requirements. However, these frameworks are mainly proposed to manage information and data such as finances, resources, management and engineering documents, not for the increasingly important enterprise knowledge, especially tacit and unstructured knowledge. This project aims to extend the capabilities of the latest enterprise architecture frameworks so that not only data and information, but also enterprise knowledge can be managed. A guideline in the form of a flowchart has been developed, which provides a process that can be followed and used by system developers and implementation. The extended EAF has been implemented as easy-to-use folders for the development of a structured knowledge base. A case study in an automotive company proved that the methodology can be used to produce the functional specifications of their IT systems to include knowledge management capability. The system specification can then be used, either to assess a company’s existing information systems and direct its future system development and implementation; or to develop/implement a complete new information system from scratch.

Sonca is a manufacturing operation producing torches and lanterns. In order for the Company to be competitive, one of the key factors is to introduce new products to market quicker and at a lower total product cost. A system titled "concurrent integrated design and assembly planning (CIDAP)" is developed to aid this process. It is identified that methods proposed by other researchers using different algorithms are not interactive enough and need too much space to store the representation of assembly sequences and time to process the assembly operations for a complex assembly. Besides, the commercially available systems and software are not integrated and are too universal. The data used is not compatible with the company's data file. The CIDAP framework focuses on concurrent and integration, in that the different processes in the whole product development cycle are carried out concurrently and are integrated. In the framework two techniques, namely KALG (Knowledge-based Assembly Liaison Graph) and KPN (Knowledge-based Petri Net) and four expert systems for selection of assembly system, feeder, gripper, and sensing technology are developed. Commercially available software such as Boothroyd and Dewhurst's DFMA (Design For Manufacture and Assembly) software, Rapid Prototyping and Quick Tooling are also applied in the framework. The frame work and the systems are applied to an actual case in designing a series of torches within the Company. Results show that the product development cycle time is improved by 25%, rework cost reduced by 20%, and final product cost reduced by 11 %. The Company has adopted the new framework. The developed systems and data files are not only applicable to the Company, but also to other small and medium size companies in Hong Kong and China with a similar scale and nature of operation.

This thesis reports research into the specification and implementation of an Information Technology (IT) Route Map. The purpose of the Route Map is to enable rapid design and deployment of IT solutions capable of semi-automating business processes in a manufacturing enterprise. The Map helps structure transition processes involved in “identification of key business strategies and design of business processes” and “choice of enterprise systems and supporting implementation techniques”. Common limitations of current Enterprise Resource Planning (ERP) systems are observed and incorporated as Route Map implications and constraints. Scope of investigation is targeted at Small to Medium Sized Enterprises (SMEs) that employ Engineer-To-Order (ETO) and Make-To-Order (MTO) business processes. However, a feature of the Route Map is that it takes into account contemporary business concerns related to “globalisation”, “mergers and acquisitions” and “typical resource constraint problems of SMEs”. In the course of the research a “Business Strategy Driven IT System Concept” was conceived and examined. The main purpose of this concept is to promote the development of agile and innovative business activity in SMEs. The Road Map encourages strategy driven solutions to be (a) specified based on the use of emerging enterprise engineering theories and (b) implemented and changed using componentbased systems design and composition techniques. Part-evaluation of the applicability and capabilities of the Road Map has been carried out by conducting industrial survey and case study work. This assesses requirements of real industrial problems and solutions. The evaluation work has also been enabled by conducting a pilot implementation of the thesis concepts at the premises of a partner SME.

This research presents a new sensor structure, the coupled micro resonator array (CMRA) as an approach to reduce the complexity of large artificial nose sensing system. The aim is to exploit multiple resonant sensors with a simplified readout. The CMRA working principle is based on mass loading frequency response effect; the frequency response of the coupled resonators is a signature for the multiple sensors. The key research outputs are balanced effective mass of the coupled resonators for measurable response and broke the structure symmetry for unique frequency response pattern and stable structure eigenvectors to enhance the system odour discrimination. To develop the CMRA, the structure is modelled and analysed using finite element and lumped mass analysis. Using silicon-on-insulator material, the CMRA is fabricated in order to evaluate the performance. The effect of mass loading is tested by platinum mass deposition using focused ion beam technology (FIB). The inverse eigenvalue analysis was used to estimate the mass change pattern of the CMRA structure. The research also investigates effect of the manufacturing variations on the CMRA structure performance. With the finger print of the coupled frequency response, the output signal of N multiple resonant sensors is monitored by a single processor; hence, reducing the complexity of readout and signal processing system.

For the past two decades, the majority of Malaysia’s IT companies have been widely adopting a Quality Assurance (QA) approach as a basis for self-improvement and internal-assessment in IT project management. Quality Control (QC) is a comprehensive top-down observation approach used to fulfill requirements for quality outputs which focuses on the aspect of process outputs evaluation. However in the Malaysian context, QC and combination of QA and QC as a means of quality improvement approaches have not received significant attention. This research study aims to explore the possibility of integrating QC and QA+QC approaches through Six Sigma quality management standard to provide tangible and measureable business results by continuous process improvement to boost customer satisfactions. The research project adopted an exploratory case study approach on three Malaysian IT companies in the business area of IT Process, IT Service and IT Product. Semi-structured interviews, online surveys, self-administered questionnaires, job observations, document analysis and on-the-job-training are amongst the methodologies employed in these case studies. These collected data and viewpoints along with findings from an extensive literature review were used to benchmark quality improvement initiatives, best practices and to develop a Six Sigma framework for the context of the SMEs in the Malaysian IT industry. This research project contributed to both the theory and practice of implementing and integrating Six Sigma in IT products, services and processes. The newly developed framework has been proven capable of providing a general and fundamental start-up decision by demonstrating how a company with and without formal QIM can be integrated and implemented with Six Sigma practices to close the variation gap between QA and QC. This framework also takes into consideration those companies with an existing QIM for a new face-lift migration without having to drop their existing QIM. This can be achieved by integrating a new QIM which addresses most weaknesses of the current QIM while retaining most of the current business routine strengths. This framework explored how Six Sigma can be expanded and extended to include secondary external factors that are critical to successful QIM implementation. A vital segment emphasizes Six Sigma as a QA+QC approach in IT processes; and the ability to properly manage IT processes will result in overall performance improvement to IT Products and IT Services. The developed Six Sigma implementation framework can serve as a baseline for SMEs to better manage, control and track business performance and product quality; and at the same time creates clearer insights and un-biased views of Six Sigma implementation onto the IT industries to drive towards operational excellence.

In transport logistic operations, an efficient delivery plan and better utilisation of vehicles will result in fuel cost savings, reduced working hours and even reduction of carbon dioxide emissions. This thesis proposes various algorithmic approaches to generate improved performance in automated vehicle load packing and route planning. First, modifications to best-fit heuristic methodologies are proposed and then incorporated into a simple but effective “look-ahead” heuristic procedure. The results obtained are very competitive and in some cases best-known results are found for different sets of constraints on three-dimensional strip packing problems. Secondly, a review and comparison of different clustering techniques in transport route planning is presented. This study shows that the algorithmic approach performs according to the specific type of real-world transport route planning scenario under consideration. This study helps to achieve a better understanding of how to conduct the automated generation of vehicle routes that meet the specific conditions required in the operations of a transport logistics company. Finally, a new approach to measuring the quality of transportation route plans is presented showing how this procedure has a positive effect on the quality of the generated route plans. In summary, this thesis proposes new tailored and effective heuristic methodologies that have been tested and incorporated into the real-world operations of a transport logistics company. The research work presented here is a modest yet significant advance to better understanding and solving the difficult problems of vehicle loading and routing in real-world scenarios.

The work undertaken in this thesis is about the integration of two well-known methodologies: Petri net (PN) model Ii ng/analysis of industrial production processes and Artificial Intelligence (AI) optimisation search techniques. The objective of this integration is to demonstrate its potential in solving a difficult and widely studied problem, the scheduling of Flexible Manufacturing Systems (FIVIS). This work builds on existing results that clearly show the convenience of PNs as a modelling tool for FIVIS. It addresses the problem of the integration of PN and Al based search methods. Whilst this is recognised as a potentially important approach to the scheduling of FIVIS there is a lack of any clear evidence that practical systems might be built. This thesis presents a novel scheduling methodology that takes forward the current state of the art in the area by: Firstly presenting a novel modelling procedure based on a new class of PN (cb-NETS) and a language to define the essential features of basic FIVIS, demonstrating that the inclusion of high level FIVIS constraints is straight forward. Secondly, we demonstrate that PN analysis is useful in reducing search complexity and presents two main results: a novel heuristic function based on PN analysis that is more efficient than existing methods and a novel reachability scheme that avoids futile exploration of candidate schedules. Thirdly a novel scheduling algorithm that overcomes the efficiency drawbacks of previous algorithms is presented. This algorithm satisfactorily overcomes the complexity issue while achieving very promising results in terms of optimality. Finally, this thesis presents a novel hybrid scheduler that demonstrates the convenience of the use of PN as a representation paradigm to support hybridisation between traditional OR methods, Al systematic search and stochastic optimisation algorithms. Initial results show that the approach is promising.

The aim of the research is to develop a methodological analysis of problems in the area of design for manufacture in low volume high complex products found in the writer’s workplace. The majority of research in this area has been around high volume products, such as automotive products and little consideration has been given to designing complex products from industries like aircraft manufacture. This research evaluates design for manufacture (DFM) information in the design lifecycle (DLC). The author’s research introduces a unique DLC process, one which structures decisions and data transfer through the DLC. The research also looks at current academic work and introduces industrial issues present in today’s environment. It is crucial to the design of a product to select the appropriate design environment in which it operates, as it will structure the way the engineering activities are established and developed. It is also important for the organisation to decide on the environment in which the design definition should evolve. Therefore the research reviews the different design definition environments, these were carefully analysed by the author. The evaluation of a design to ensure its manufacturability is a major element in the research, a review of previous work has highlighted that within current publications there has been little work in this area. The research has developed a methodology to evaluate the robustness of a design. It not only looks at the engineering design but also evaluates its adherence to customer requirements and the effect on cost for the overall product life-cycle. It also considers industrial needs for a reduction in the length of design life-cycle, while ensuring a reduction in manufacturing costs. There are two main contributors to this, firstly the use of key characteristics and secondly, the ability to control the manufacturability of a design. The author has developed a novel software tool enabling efficient evaluation of a design. The author discusses his contribution to existing knowledge in three main areas of the research. The most significant being the introduction of a tool to evaluate a design early in the design life-cycle to ensure manufacturability. To validate the research the author introduces the reader to three experimental phases. He validates his methodology by analysing the design of various aircraft assemblies discussing his findings of how manufacturable the designs are. This leads to the conclusion that the author’s research adds substantial knowledge to the area of design for manufacture.

The research questions posed for this work were as follows: Can speech recognition and techniques for topic spotting be used to identify spoken intent in unconstrained natural speech? Can gesture recognition systems based on statistical speech recognition techniques be used to bridge the gap between physical movements and recognition of gestural intent? How can speech and gesture be combined to identify the overall communicative intent of a participant with better accuracy than recognisers built for individual modalities? In order to answer these questions a corpus collection experiment for Human-Robotic Interaction was designed to record unconstrained natural speech and 3 dimensional motion data from 17 different participants. A speech recognition system was built based on the popular Hidden Markov Model Toolkit and a topic spotting algorithm based on usefulness measures was designed. These were combined to create a speech intent recognition system capable of identifying intent given natural unconstrained speech. A gesture intent recogniser was built using the Hidden Markov Model Toolkit to identify intent directly from 3D motion data. Both the speech and gesture intent recognition systems were evaluated separately. The output from both systems were then combined and this integrated intent recogniser was shown to perform better than each recogniser separately. Both linear and non-linear methods of multimodal intent fusion were evaluated and the same techniques were applied to the output from individual intent recognisers. In all cases the non-linear combination of intent gave the highest performance for all intent recognition systems. Combination of speech and gestural intent scores gave a maximum classification performance of 76.7% of intents correctly classified using a two layer Multi-Layer Perceptron for non-linear fusion with human transcribed speech input to the speech classifier. When compared to simply picking the highest scoring single modality intent, this represents an improvement of 177.9% over gestural intent classification, 67.5% over a human transcription of speech based speech intent classifier and 204.4% over an automatically recognised speech based speech intent classifier.