Computer integrated manufacturing (CIM) and the principle of business control

In response to the increasing international competitiveness, many manufacturing businesses are rethinking their management strategies and philosophies towards achieving a computer integrated environment. The explosive growth in Advanced Manufacturing Technology (AMI) has resulted in the formation of functional "Islands of Automation" such as Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), Computer Aided Process Planning (CAPP) and Manufacturing Resources Planning (MRPII). This has resulted in an environment which has focussed areas of excellence and poor overall efficiency, co-ordination and control. The main role of Computer Integrated Manufacturing (CIM) is to integrate these islands of automation and develop a totally integrated and controlled environment. However, the various perceptions of CIM, although developing, remain focussed on a very narrow integration scope and have consequently resulted in mere linked islands of automation with little improvement in overall co-ordination and control. This thesis, that is the research described within, develops and examines a more holistic view of CIM, which is based on the integration of various business elements. One particular business element, namely control, has been shown to have a multi-facetted and underpinning relationship with the CIM philosophy. This relationship impacts various CIM system design aspects including the CIM business analysis and modelling technique, the specification of systems integration requirements, the CIM system architectural form and the degree of business redesign. The research findings show that fundamental changes to CIM system design are required; these are incorporated in a generic CIM design methodology. The affect and influence of this holistic view of CIM on a manufacturing business has been evaluated through various industrial case study applications. Based on the evidence obtained, it has been concluded that this holistic, control based approach to CIM can provide a greatly improved means of achieving a totally integrated and controlled business environment. This generic CIM methodology will therefore make a significant contribution to the planning, modelling, design and development of future CIM systems.

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

CADS*: Computer-Aided Development of self-* systems

We present the prototype tool CADS* for the computer-aided development of an important class of self-* systems, namely systems whose components can be modelled as Markov chains. Given a Markov chain representation of the IT components to be included into a self-* system, CADS* automates or aids (a) the development of the artifacts necessary to build the self-* system; and (b) their integration into a fully-operational self-* solution. This is achieved through a combination of formal software development techniques including model transformation, model-driven code generation and dynamic software reconfiguration.

Computer-aided biotechnology:from immuno-informatics to reverse vaccinology

Genome sequences from many organisms, including humans, have been completed, and high-throughput analyses have produced burgeoning volumes of 'omics' data. Bioinformatics is crucial for the management and analysis of such data and is increasingly used to accelerate progress in a wide variety of large-scale and object-specific functional analyses. Refined algorithms enable biotechnologists to follow 'computer-aided strategies' based on experiments driven by high-confidence predictions. In order to address compound problems, current efforts in immuno-informatics and reverse vaccinology are aimed at developing and tuning integrative approaches and user-friendly, automated bioinformatics environments. This will herald a move to 'computer-aided biotechnology': smart projects in which time-consuming and expensive large-scale experimental approaches are progressively replaced by prediction-driven investigations.

Computer-assisted production scheduling, planning and control in foundries

The present study describes a pragmatic approach to the implementation of production planning and scheduling techniques in foundries of all types and looks at the use of `state-of-the-art' management control and information systems. Following a review of systems for the classification of manufacturing companies, a definitive statement is made which highlights the important differences between foundries (i.e. `component makers') and other manufacturing companies (i.e. `component buyers'). An investigation of the manual procedures which are used to plan and control the manufacture of components reveals the inherent problems facing foundry production management staff, which suggests the unsuitability of many manufacturing techniques which have been applied to general engineering companies. From the literature it was discovered that computer-assisted systems are required which are primarily `information-based' rather than `decision based', whilst the availability of low-cost computers and `packaged-software' has enabled foundries to `get their feet wet' without the financial penalties which characterized many of the early attempts at computer-assistance (i.e. pre-1980). Moreover, no evidence of a single methodology for foundry scheduling emerged from the review. A philosophy for the development of a CAPM system is presented, which details the essential information requirements and puts forward proposals for the subsequent interactions between types of information and the sub-system of CAPM which they support. The work developed was oriented specifically at the functions of production planning and scheduling and introduces the concept of `manual interaction' for effective scheduling. The techniques developed were designed to use the information which is readily available in foundries and were found to be practically successful following the implementation of the techniques into a wide variety of foundries. The limitations of the techniques developed are subsequently discussed within the wider issues which form a CAPM system, prior to a presentation of the conclusions which can be drawn from the study.

Computer aided process planning (CAPP) for flat rolling of copper alloys

The manufacture of copper alloy flat rolled metals involves hot and cold rolling operations, together with annealing and other secondary processes, to transform castings (mainly slabs and cakes) into such shapes as strip, plate, sheet, etc. Production is mainly to customer orders in a wide range of specifications for dimensions and properties. However, order quantities are often small and so process planning plays an important role in this industry. Much research work has been done in the past in relation to the technology of flat rolling and the details of the operations, however, there is little or no evidence of any research in the planning of processes for this type of manufacture. Practical observation in a number of rolling mills has established the type of manual process planning traditionally used in this industry. This manual approach, however, has inherent drawbacks, being particularly dependent on the individual planners who gain their knowledge over a long span of practical experience. The introduction of the retrieval CAPP approach to this industry was a first step to reduce these problems. But this could not provide a long-term answer because of the need for an experienced planner to supervise generation of any plan. It also fails to take account of the dynamic nature of the parameters involved in the planning, such as the availability of resources, operation conditions and variations in the costs. The other alternative is the use of a generative approach to planning in the rolling mill context. In this thesis, generative methods are developed for the selection of optimal routes for single orders and then for batches of orders, bearing in mind equipment restrictions, production costs and material yield. The batch order process planning involves the use of a special cluster analysis algorithm for optimal grouping of the orders. This research concentrates on cold-rolling operations. A prototype model of the proposed CAPP system, including both single order and batch order planning options, has been developed and tested on real order data in the industry. The results were satisfactory and compared very favourably with the existing manual and retrieval methods.

The development of a computer aided system for adaptive budgeting in a confectionery manufacturing firm

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

A unified classification of manufacturing strategies and design processes

This article categorises manufacturing strategy design processes and presents the characteristics of resulting strategies. This work will therefore assist practitioners to appreciate the implications of planning activities. The article presents a framework for classifying manufacturing strategy processes and the resulting strategies. Each process and respective strategy is then considered in detail. In this consideration the preferred approach is presented for formulating a world class manufacturing strategy. Finally, conclusions and recommendations for further work are given.

The handbook of engineering self-aware and self-expressive systems

When faced with the task of designing and implementing a new self-aware and self-expressive computing system, researchers and practitioners need a set of guidelines on how to use the concepts and foundations developed in the Engineering Proprioception in Computing Systems (EPiCS) project. This report provides such guidelines on how to design self-aware and self-expressive computing systems in a principled way. We have documented different categories of self-awareness and self-expression level using architectural patterns. We have also documented common architectural primitives, their possible candidate techniques and attributes for architecting self-aware and self-expressive systems. Drawing on the knowledge obtained from the previous investigations, we proposed a pattern driven methodology for engineering self-aware and self-expressive systems to assist in utilising the patterns and primitives during design. The methodology contains detailed guidance to make decisions with respect to the possible design alternatives, providing a systematic way to build self-aware and self-expressive systems. Then, we qualitatively and quantitatively evaluated the methodology using two case studies. The results reveal that our pattern driven methodology covers the main aspects of engineering self-aware and self-expressive systems, and that the resulted systems perform significantly better than the non-self-aware systems.