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Today's dynamic marketplace requires flexible manufacturing systems capable of cost-effective high variety - low volume production in frequently changing product demand and mix. Several new paradigms, e.g. holonic, fractal, biological and responsive manufacturing, have recently been proposed and studied in the academic literature. These 'next generation of manufacturing systems' have been especially designed to meet the requirements of an unstable and unpredictable marketplace. However, very little in-depth research of the configuration, planning and control methodologies of these new concepts has been conducted. This research aims to improve the comprehension and implementation of these 21st century manufacturing systems by developing an integrated reference architecture from the combination of their distinctive features that would enable manufacturing enterprises to handle successfully the configuration/reconfiguration, planning and control activities under the conditions of uncertainty and continuous change. In the course of the research, a detailed investigation into the fractal, biological and responsive manufacturing systems is conducted in order to identify the strengths and weaknesses of each concept. The common and distinctive features of the paradigms are then used to merge them to create an integrated reference architecture. The fractal configuration, biological scheduling and 'resource element' representation of resource capabilities and product processing requirements are selected as the major elements of the new system. A detailed study of fractal layout design resulted in seven distinctive methods for structuring and managing fractal cellular systems. A design methodology that supports three types of dynamic scheduling is developed for biological manufacturing systems. Resource elements are used with fractal layouts and biological scheduling to enhance performance and to enable an integration of the concepts. The proposed reference architecture is modelled and evaluated using object-oriented programming, computer simulation and heuristic algorithms. The research results indicate that the performance of systems that employ biological scheduling and fractal layouts can be improved by using the concept of resource elements to utilise any hidden capabilities of resources and to achieve an optimal distribution of resources on the shop floor.

The High Value Manufacturing (HVM) sector is vital for developed countries due to the creation of innovative products with advanced technology that cannot be reproduced at the same cost and time with traditional technology. The main challenge for HVM is to rapidly increase production volume from one-off products to low production volume. This requires highly flexible manufacturing systems that can produce new products at variable production volumes. Current manufacturing systems, classified as dedicated, flexible and reconfigurable systems, are limited to produce one type of product(s), within a production volume range and have fixed layouts of machines. Thus, there is a need for highly flexible systems that can rapidly adjust their production volume according to the production demand (i.e. main HVM challenge). Therefore, a novel manufacturing framework, called INTelligent REconfiguration for a raPID production change (INTREPID), is presented in this thesis. INTREPID consists of a user interface and communications platform, a job allocation system, a globally distributed network of Reconfigurable Manufacturing Centres (RMCs), consisting of interconnected factories, and Self-Reconfigurable Manufacturing Systems (S-RMSs). The highly flexible S-RMS consists of movable machines and Mobile Manufacturing Robots (MMRs). The novelty of the S-RMS is its capability of forming layouts bespoke to the current production needs. The vision of INTREPID is to offer global HVM services through the network of RMCs. The job allocation system determines the best possible RMCs or factories to perform a job by considering the complexity of the production requirements and the status of the available S-RMSs at each factory. The planning of the production with S-RMS is challenging due to its high flexibility. The main example of this flexibility is the possibility to create layouts bespoke to current production needs. Yet, this flexibility involves the challenges of determining allocations and schedules of tasks to robots and machines, positions to manufacture, and routes to reach those positions. In manufacturing systems with fixed layouts, production plans are determined by solving a sequence of problems. However, for the S-RMS, it is proposed to determine production plans with a single problem that covers the scheduling, machine layout and vehicle routing problems simultaneously. This novel problem is called the Scheduling, positions Assigning and Routing problem (SAR) problem. In order to determine the best possible production plan(s) for the S-RMS, it is necessary to use optimisation methods. Dozens of elements, characteristics and assumptions from the constituent problems might be included in the formulation of the SAR problem. Elements, characteristics and assumptions can be considered as decision variables on whether to include or not the elements and characteristics and under which assumptions in the formulation. There are two types of decision variables. Fundamental variables are natural to the SAR problem (e.g. manufacturing resources, factory design and operation), whilst auxiliary variables arise from the aim to simplify the formulation of the optimisation problem (i.e. time formulated as discrete or continuous). Due to the large number of decision variables, there might be millions of possible ways to formulate the SAR problem (i.e. the SAR problem space). Some of these variants are intractable to be solved with optimisation methods. Hence, before formulating the SAR problem, it is necessary to select a problem(s) that is realistic to industrial scenarios but solvable with optimisation methods. Existing selection methods work with pairwise comparisons of alternatives. However, for a space of millions of SAR problems, pairwise comparisons are intractable. Hence, in this thesis, a novel Decision Making Methodology (DMM) based on the controlled convergence method is presented. The DMM helps down-selecting one or a few SAR problems from millions of possible SAR problems. The DMM is demonstrated with a case study of the SAR problem and the results show a significant reduction of the reviewed SAR problems and the time to select them.

The work considered and presented in this thesis was catalysed by the potentials of the additive fabrication processes, usually referred to as Rapid Manufacturing. These fabrication methods connect its theoretical assumptions to its designs. The thesis was developed around a number of designs which were progressed in conjunction with its evolving theoretical components, the latter which entailed the formation of a bespoke taxonomy and accompanying bespoke terminology to describe the various distinct features and processes involved. The thesis questions the current detrimental schism dividing the act of computing based designing from the act of making something physical, and makes a case for a more inherent role for the material, sensory and tacit properties in the process of designing something through Rapid Manufacturing.

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The research presented in this thesis identifies the need to develop a strategy specially designed to improve the operational performance of functional layouts. The traditional approach has been to replace functional layouts with product-oriented layouts such as cellular manufacturing or flow lines. However, conditions exist in some functionally organised factories that prevent changes to the factory layout being made. In such cases, a number of tactics, operational strategies and concepts were identified which are capable of addressing the operational weaknesses of functional layouts. These include lean, agile and virtual cellular manufacturing. It was these concepts, which influenced the development of a new manufacturing strategy for functional layouts called virtual groups. Virtual groups are groups of machines with the potential to form physical manufacturing cells. This potential is limited by the difficulty of moving machines and shortages in the number of machines available to populate manufacturing cells. Virtual groups are virtual° because although they are considered as manufacturing cells, the constituent machines are physically dispersed throughout the factory. There are two key aspects of virtual groups. The first is the opportunity to replace the focus on °processes° with a focus on products'. This is achieved by replacing process managers with group managers who are responsible for the production of products rather than the management of processes, to whom all the production resources required to produce a family of parts/products are assigned. The second aspect is the assignment of the most appropriate production strategy to each virtual group. This presents the opportunity to target the production capabilities and management policies that will best address the market conditions in which the products will compete. Other benefits of virtual groups are expected to include lower WIP, improved quality, on-time delivery and reduced throughput times. Also presented in this thesis is the development of a new methodology for the formation of virtual groups called enhanced production flow analysis. Enhanced production flow analysis has been developed to identify virtual groups of machines and families of parts, which each virtual group is responsible for producing. Initially it was believed that elements of J.L Burbidge's production flow analysis could be used to form virtual groups however the first trial of the methodology showed that to identify the most appropriate virtual groups some enhancements were required, particularly to the method for forming modules. The ability of enhanced production flow analysis to form virtual groups was successfully tested through the use of two data sets collected from two different Pirelli factories. In both cases, opportunities were identified to form lean process-oriented virtual groups and agile product-oriented virtual groups. The formation of process-oriented virtual groups is not ideal, as some of the machines will continue to be managed in a functionally organised group. However, their existence signals the relevance of virtual groups over cellular manufacturing.

Assembly systems today are exposed to market trends that have become increasingly more dynamic and unpredictable, requiring product changes and adjustments which emphasise de need for more flexible systems. The requirement for increased responsiveness has led to the development of new modular concepts which provide the bases for achieving higher system adaptability through increased component/module interchangeability and reusability. The modularization of physical and control infrastructure does, however, only address one aspect of the issue and there is still a lack of appropriate tools and methods to support the rapid configuration and reconfiguration of such systems for changing sets of requirements. This work proposes a new distributed methodology for the configuration and reconfiguration of Modular Assembly Systems (MAS) through the use of agent technology. The new methodology defines a comprehensive model for the structured description of the MAS requirements, equipment modules and the configuration results. This thesis proposes a new agent architecture for the self-configuration of equipment modules into systems based on a given set of requirements, as the core of the self-configuration methodology. This architecture introduces the overall behaviour of the methodology through the definition of agent types, roles and overall interactions. Furthermore this work describes the development of the specific models and methods for the local behaviour of each agent. These enable the actual decision making method for the agents to achieve configuration solutions. This work also reports on a new methodology for the early performance simulation of MAS characteristics that can be used in conjunction with the configuration methodology.

Manufacturability analysis systems (MASs) have been developed to enable the evaluation of manufacturability aspects during the design stage. MASs have been shown to be useful for macro-manufacturing processes but less attention or effort has been put for their development in the scope of micro-manufacturing. This thesis describes the development of a MAS for a micro-machining domain (MicroMAS) with a custom-made 4-axis Miniature Machine Tool (MMT) being the scope of implementation. There are three important components in this study which are; MAS, Uncertainty Evaluation Model (UEM) and micro-milling experiments. The integration between the results from the UEM analysis and micro-machining experiments were being incorporated into the MicroMAS to provide the system with the real condition of the MMT. In MicroMAS, Primitive Feature Analysis (PFA) is introduced as a new technique in gathering information from a CAD model and analysing its manufacturability. The results from the manufacturability assessment in MicroMAS are successfully achieved through the manufacturability index which indicates the relative ease of machining the CAD model and list of related suggestions. UEM is developed to analyse the influence of the errors stemmed from the MMT construction on the geometrical accuracy of the machined micro-parts. The model has allowed a methodology for the errors in a custom-made machine tool to be predicted and to further understand the origin of the errors on the machined micro-part (either from the machine or the process itself). The abilities of the MMT are evaluated through various types of experiments where the surface quality and geometrical accuracy can be concluded to be at an acceptable range. From the experience gained from the research, the development of MicroMAS for micro-milling has been found to be practical in assisting a user to generate micro-parts using the MMT.

Automated assembly technology may be the key to sustaining manufacturing industry in more developed countries. Currently this comprises dedicated systems that can assemble single products at high volumes and flexible systems to assemble a wide variety of products in low volumes. However, competitive forces demand a compromise between the two and Reconfigurable Assembly Systems are an avenue for achieving high volume and high variety production. Although this technology is coming to the fore, there is a distinct lack of tools and methods that make the prospect attractive to key decision makers in organisations. Reconfigurable solutions, which may be profitable in the long term, are rejected in favour of short term solutions, which prove to be more expensive over time. The benefits of requirements engineering have been exploited in software engineering and this work demonstrates how these can be adapted to an assembly environment to form a new basis for communication between the system vendors, who supply assembly system solutions, and system users, who use them. Knowledge Engineering has become a key aspect in industry due to the challenges of retaining personnel and their knowledge within organisations. This is because employees take their knowledge of the organisation with them when they leave. The retention of this knowledge would help to maintain the continuity within organisations. This thesis reports on research that aims to provide a means to integrate these three aspects to form a basis for sustaining competitive manufacture in more developed countries. Moreover, Knowledge Based Requirements Specification for Reconfigurable Assembly Systems will provide a vital medium for promoting Reconfigurable Assembly Systems and encourage their implementation by providing a knowledge-based platform for the specification of Reconfigurable Assembly Systems.

Next generation manufacturing companies have to become highly responsive in order to succeed in an ever more rapidly changing global market. The ability to effectively develop and adapt their assembly facilities (systems) to changing requirements on demand plays a crucial role in achieving high responsiveness since the assembly process has to deal with the full inherent complexity of increasingly mass-customised products. This work was motivated by the current lack of a holistic assembly system design theory that would enable design environments to address the need for rapid system development and adaptation. The challenge is to create a common environment where domain experts can effectively collaborate while taking advantage of the best practices of their diverse domains. This thesis investigates how a domain ontology can help to overcome those challenges. The approach is taking advantage of the higher levels of standardisation inherent in the modular assembly system paradigm which is considered to be one of the fundamental enabling factors to achieve a high level of adaptation. A new ontology framework has been developed to support the design and adaptation of modular assembly systems (ONTOMAS). The ONTOMAS framework is based on engineering ontology principles structuring the domain using formalisms for aggregation, topology, taxonomies, and system theory principles. A number of design patterns have been identified and formalised to support key design decision-making tasks during the design of modular assembly systems. Furthermore, the function-behaviour-structure paradigm has been applied to capture the characteristics of modular assembly equipment at different levels of abstraction that reflect the specific needs of the engineering design process. The proposed ONTOMAS framework provides a sound foundation for computer based support tools to reduce the assembly system design effort and time while maintaining a high level of quality. An integrated design framework for the requirements driven specification of assembly processes and configuration of modular assembly system has been developed. The design approach applies the new formalisms of ONTOMAS to support the design decision-making activities. The developed ONTOMAS framework has been applied in several industrial and synthetic use cases to verify its applicability and appropriateness. Furthermore, the new ontology and design framework have been used as foundation for the development of a prototype collaborative design environment which allows different domain experts to participate in the design of modular assembly systems.