Frequent product model changes have become a characteristic feature in new product development and modern manufacturing. This has triggered a number of requirements such as shortening new product development time and production ramp-up time with simultaneous reduction of avoidable engineering changes and overall vehicle development cost. One of the most significant challenges when reducing new model development lead time is the large number of engineering changes, that are triggered by failures during production ramp-up stage but are unseen during design. In order to reduce engineering changes during ramp-up stage and also increase Right-First-Time development rate, there is a critical demand for improving quality of integrated product and production system design solutions. Currently, this is obtained by carrying out design synthesis which focuses on design optimization driven by computer simulation and/or physical experimentation. The design synthesis depends on the quality of the used surrogate models, which integrate critical product variables, (also known as Key Product Characteristics (KPCs)), with key process variables (Key Control Characteristics (KCCs)). However, a major limitation of currently existing surrogate models, used in design synthesis, is that these simply approximate underlying KPC-KCC relations with any deviation between the actual and predicted KPC assumed to be a simple random error with constant variance. Such an assumption raises major challenges in obtaining accurate design solutions for a number of manufacturing processes when: (1) KPCs are deterministic and non-linearity is due to interactions between process variables (KCCs) as is frequently the case in fixture design for assembly processes with compliant parts; (2) KPC stochasticity is either independent of (homo-skedastic) or dependent on (hetero-skedastic) on process variables (KCCs) and there is lack of physics-based models to confirm these behaviour; as can be commonly observed in case of laser joining processes used for automotive sheet metal parts; and, (3) there are large number of KCCs potentially affecting a KPC and dimensionality reduction is required to identify few critical KCCs as commonly required for diagnosis and design adjustment for unwanted dimensional variations of the KPC. This thesis proposes a generic Scalable Design Synthesis framework which involves the development of novel surrogate models which can address a varying scale of the KPC-KCC interrelations as indicated in the aforementioned three challenges. The proposed Scalable Design Synthesis framework is developed through three interlinked approaches addressing each aforementioned challenge, respectively: i. Scalable surrogate model development for deterministic non-linearity of KPCs characterized by varying number of local maximas and minimas. Application: Fixture layout optimization for assembly processes with compliant parts. This is accomplished in this thesis via (1) Greedy Polynomial Kriging (GPK), a novel approach for developing Kriging-based surrogate models for deterministic KPCs focusing on maximization of predictive accuracy on unseen test samples; and, (2) Optimal Multi Response Adaptive Sampling (OMRAS) a novel method of accelerating the convergence of multiple surrogate models to desired accuracy levels using the same training sample of KCCs. GPK surrogate models are then used for fixture layout optimization for assembly with multiple sheet metal parts. ii. Scalable surrogate model development for stochasticity characterized by unknown homo-skedastic or hetero-skedastic behaviour of KPCs. Application: In-process laser joining processes monitoring and in-process joint quality evaluation. Scalable surrogate model-driven joining process parameters selection, addressing stochasticity in KPC-KCC relations, is developed. A generic surrogate modelling methodology is proposed to identify and characterize underlying homo- and hetero-skedastic behaviour in KPCs from experimental data. This is achieved by (1) identifying a Polynomial Feature Selection (PFS) driven best-fitting linear model of the KPC; (2) detection of hetero-skedasticity in the linear model; and, (3) enhancement of the linear model upon identification of hetero-skedasticity. The proposed surrogate models estimate the joining KPCs such as weld penetration, weld seam width etc. in Remote Laser Welding (RLW) and their variance as a function of KCCs such as gap between welded parts, welding speed etc. in RLW. This information is then used to identify process window in KCC design space and compute joining process acceptance rate. iii. Scalable surrogate model development for high dimensionality of KCCs. Application: Corrective action of product failures triggered by dimensional variations in KPCs. Scalable surrogate model-driven corrective action is proposed to address efficient diagnosis and design adjustment of unwanted dimensional variations in KPCs. This is realized via (1) PFS to address high dimensionality of KCCs and identify a few critical ones closely related to the KPC of interest; and (2) surrogate modelling of the KPC in terms of the few critical KCCs identified by PFS; and, (3) two-step design adjustment of KCCs which applies the surrogate models to determine optimal nominal adjustment and tolerance reallocation of the critical KCCs to minimize production of faulty dimensions. All the aforementioned methodologies are demonstrated through the use of industrial case studies. Comparison of the proposed methods with design synthesis existing for the applications discussed in this thesis, indicate that scalable surrogate models can be utilized as key enablers to conduct accurate design optimization with minimal understanding of the underlying complex KPC-KCC relations by the user. The proposed surrogate model-based Scalable Design Synthesis framework is expected to leverage and complement existing computer simulation/physical experimentation methods to develop fast and accurate solutions for integrated product and production system design.

The Grain Silos and Flour Mills Organisation (GSFMO) is the responsible authority monopolising the Kingdom's milling industry. However, the organisation has recently been facing financial problems. The aim of this study is to estimate the technical, cost and allocative efficiency (TE, CE and AE) of the flour mills of the GSFMO (1988-2011), using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) approaches. In addition, it seeks to explain variation in efficiency levels between the mills and conduct further analysis through the second stage regression to estimate the effect of managerial variables. Productivity growth over time was also estimated in this study using DEA (2008-2011) and SFA (1988-2011) approaches. Both primary data and secondary data (1988-2011) to cover the nine milling branches were utilised. Using DEA under constant return to scale (CRS), average TE ranged from 91.72% in Khamis branch to 97.63% in Almadinah. Average TE under input-orientated variable return to scale (VRS) was lower than TE estimated under output-orientated VRS. The older branches had the lowest TE compared to newer branches. Under VRS, TE was greater than TE for the same branches under CRS. TE results using SFA were quite analogous to the results using DEA. Regarding productivity growth, using DEA for the 2008-2011 data, no consistent patterns were found across the GSFMO branches in the mean total factor productivity growth (TFPG), technical change (TC), and efficiency change (EC). When using SFA to estimate productivity growth over the period 1988 to 2011, there was a decrease in productivity growth for most branches. With regards to the results of the second stage regression, branch managers’ age, local temperature and 'bad' infrastructure have a significant negative relationship with TE, while manager's experience did not seem to have any significant relationship with TE. However, new and mix machine conditions and number of mills in each branch have a significant positive relationship with TE. In terms of CE and AE using the DEA approach, the results show that major losses incurred by the organisation were partly due to the significant decrease in CE and AE and that there is a significant scope to reduce inputs costs in the production process.

At 2009 rates of disposal, there are only 8 years of remaining landfill capacity at permitted sites in England and Wales. Industry – encouraged by financial penalties from the Government – faces the challenges of cleaner and more sustainable production whilst trying to remain competitive in the market place. This thesis presents development of several theoretical propositions: a ‘fit thinking’ design framework, the ‘All Seeing Eye of Business’ (All-SEB) and the ‘waste alchemist’ industrial role. The ALL-SEB is a model to understand the impact and potential uses of manufacturing waste. The insights provided by the All-SEB model, resulted in a general waste elimination framework developed to serve as a guiding strategy for waste elimination. The main objective of this study was to investigate a major hypothesis derived from the All-SEB: unavoidable waste could be transmuted into profitable co-products as a measure to divert waste from landfill. The ATM (analyse, transform and market) methodology was developed as a way to help companies transmute waste into ‘co-products’. A tool for idea generation (the wheel of waste) was developed to be used in the Analysis phase of the ATM methodology. Case study research was undertaken in order to test the ATM methodology and the way in which unavoidable waste could be transmuted into a profitable co-product in a real world manufacturing setting. The case study results revealed the generative mechanisms that enable waste transmutation into profitable co-products; based on these findings a refined ATM methodology for waste transmutation was proposed. The implementation of the theoretical propositions in industrial settings shed light into strategic aspects of resource efficiency: from waste prevention through ‘fit thinking’, to manufacturing process innovation all the way to a better company integration into the industrial ecosystem. Companies looking to achieve zero waste to landfill status would benefit from using the refined ATM methodology. It was found that the ATM methodology and the wheel of waste are useful to several other actors in the industrial ecosystem: waste management companies looking to transform themselves into ‘resource and energy providers’, to external consultants and to third party companies dubbed ‘waste alchemists’ that could offer waste transmutation services to manufacturers.

In this thesis we study the chemical reactions and transport phenomena which occur in a microwave power assisted chemical vapour deposition (MPA-CVD) reactor which facilitates diamond growth. First we introduce a model of an underlying binary gas flow and its chemistry for a hydrogen gas mixture. This system is heated by incorporating a microwave frequency electric field, operating in a resonant mode in the CVD chamber. This heating facilitates the dissociation of hydrogen and the generation of a gas discharge plasma, a key component of carbon deposition in industrial diamond manufacture. We then proceed to summarise the discontinuous Galerkin (DG) finite element discretisation of the standard hyperbolic and elliptic partial differential operators which typically occur in conservation laws of continuum models. Additionally, we summarise the non-stabilised discontinuous Galerkin formulation of the time harmonic Maxwell operator. These schemes are then used as the basis for the discretisation method employed for the numerical approximation of the MPA-CVD model equations. The practical implementation of the resulting DG MPA-CVD model is an extremely challenging task, which is prone to human error. Thereby, we introduce a mathematical approach for the symbolic formulation and computation of the underlying finite element method, based on automatic code generation. We extend this idea further such that the DG finite element formulation is automatically computed following the user's specification of the convective and viscous flux terms of the underlying PDE system in this symbolic framework. We then devise a method for writing a library of automatically generated DG finite element formulations for a hierarchy of partial differential equations with automatic treatment of prescribed boundary conditions. This toolbox for automatically computing DG finite element solutions is then applied to the DG MPA-CVD model. In particular, we consider reactor designs inspired by the AIXTRON and LIMHP reactors which are analysed extensively in the literature.

The aim of the work presented in this thesis was to investigate the impact of different mechanical treatments on the structure and physical properties of microfibrillar cellulose (MFC) and examine further changes upon drying of these MFC suspensions. It has been demonstrated that depending on the type of homogeniser and number of passes through the homogeniser results in a different variety of MFC with a distinct degree of fibrillation. An entangled network structure of MFC plays an important role in maintaining the rheological properties as well as water mobility in the system. Spin-spin relaxation time (T2) of the highly entangled microfibrils network indicates that the water mobility was higher in suspensions with a high degree of fibrillation, as compared to the low degree of fibrillation. It is now well established that during the drying stage MFC fibril-aggregates are formed due to strong intermolecular hydrogen bonds within the network structure. Due to a lack of redispersibility in water and the presence of fibril-aggregates, a non-homogenous distribution throughout the system was observed and the aqueous suspension of redispersed MFC shows a noticeable reduction in complex and shear viscosities. Hence, the next stage of the study focused on to stabilise the fibril-networks of microfibrils upon the drying, where the impact of different polymeric additives i.e. carboxyl methylcellulose (CMC), locust bean gum (LBG) and a blend of CMC/LBG was investigated. The addition of polymeric additives significantly improves the redispersibility of dried MFC in water with reduced fibrils aggregates. The interaction between microfibrils and additives are driven by surface OH-group-mediated hydrogen bonds; however the extents of these interactions are highly dependent on the type of additive used to stabilise the microfibrils. The point of the addition of polymeric additives plays an important role in terms of interaction between the polymeric additive and MFC. Co-processing of MFC and polymeric additives has a noticeable impact on the degree of fibrillation (visualised through light microscopy and degree of transparency) of the final MFC product. The presence of a charged polymeric additive such as carboxyl methyl cellulose (CMC) results in strong synergistic interaction with MFC, whereas weak synergistic interaction is reported with Locust bean gum (LBG). The addition of a CMC/LBG blend also showed strong synergistic interaction with MFC when added in a small amount. The amounts of additive present in the system have a noticeable impact on the viscoelastic properties of the suspensions. At ambient temperature, the MFC/additives suspensions formed a weak gel-like network. It was found that a polymeric additive forms a surface coating on MFC fibrils which protects the fibrils, to form strong intermolecular hydrogen bonds during the drying process, resulting in improved redispersibility of the dry product in an aqueous medium. The interaction between MFC and polymeric additives leads to an increase in moisture uptake even after drying process. Increase in water accessibility within the microfibril network was evident with Dynamic Vapour sorption analysis and low-temperature thermal transitions measured by Differential Scanning Calorimetry. This research also features a preliminary study on the potential application of MFC produced from softwood spruce as a dietary fibre for food application. This includes a comparison between the microstructure and different physical properties of softwood MFC (flakes and powder) with food grade commercial dietary fibres e.g. citrus fibres. Softwood MFC (both flakes and powder form) showed similar rheological properties to other cellulosic dietary fibres such as citrus fibres. Due to a highly entangled network structure softwood MFC showed the highest water retention values (also known as water holding capacity) as compared to other cellulosic fibres. A comparison of the rate of taste i.e. salt perception was also carried out, and the structural features of MFC affect this and appear to be more similar to soluble hydrocolloid solutions than the particulate systems such as citrus fibres. In summary, this thesis describes the mechanistic understanding of the interaction between MFC and different polymeric additives such as CMC and LBG. This research highlights the these interactions results in different microstructures affecting the functional properties of MFC such as redispersing behaviour, water mobility, low-temperature polymer-water interactions and rheological properties. Microfibrillar cellulose (MFC) are not only fundamentally interesting but most importantly they are practical, and certainly offers a more environmentally friendly, and cost-effective ingredient for various traditional commercial applications such as paints, composites and adhesives. This work also proves, for the first time, that the MFC from softwood can also be used as an ingredient for food applications as a bulking agent, stabilising agent, texture and viscosity enhancer.

Natural rubber from the para rubber tree Hevea brasiliensis is one of world’s most important natural resources. Despite its use in the manufacture of a wide range of essential items the mechanisms by which natural rubber is synthesised is poorly understood. Natural rubber is a long chain cis-polyisoprene, composed of units of isopentenyl pyrophosphate (IPP) which is contained within rubber particles. Rubber particles consist of a hydrophobic polyisoprene interior surrounded by a monolayer membrane. Due to the insoluble nature of rubber the only place that polymerisation could occur is on this membrane by a hypothetical membrane bound rubber transferase. Whether this is a single enzyme or complex is currently unknown. Cis-prenyltransferases (CPTs) are a group of enzymes responsible for the polymerisation of cis-polyisoprene. The first plant CPTs were identified in Arabidopsis which paved the way for the identification of two Hevea CPTs, HRT1 and HRT2. HRT2 is able catalyse the formation of long chain polyisoprene products in the presence of rubber particles and is the focus of this thesis. Hevea takes at least 4 years to reach maturity. Its long life cycle coupled with the difficulty of genetic transformation meant that direct study on Hevea was not feasible for this project. Instead transient expression in N. benthamiana as well as some preliminary work in L. sativa was used to characterise rubber associated proteins. HRT2 was found to be a cytosolic protein and in theory incapable of polymerising natural rubber on the surface of rubber particles. The scope of the project was therefore widened to include possible interactors that could act to bring it to a membrane. These interactors were identified and cloned based on existing literature and included small rubber particle protein (SRPP), rubber elongation factor (REF), rubber biosynthesis stimulator protein (RBSP) and a newly characterised cis-prenyltransferase like (CPTL) protein, HevNogo. Whilst HRT2 on its own was unable to associate with a membrane, expression with HevNogo induced its subsequent localisation to the plasma membrane. This interaction initially took place on the endoplasmic reticulum. The HRT2/HevNogo complex may be part of a rubber transferase complex, however it is likely that additional components are required.

Manufacturing is a vital and significant element of the British economy. The sector has made a transition towards the production of higher value-added products and services to remain competitive in increasingly international markets. A highly skilled and competitive supply base is central to the viability of the sector as tasks once undertaken by end-manufacturers are increasingly being absorbed into the portfolio of functions undertaken by the supplier. This thesis examines how one supply industry, intermediate metal processing (IMP), is adjusting to international competition in the context of increasingly complex dependencies in the supply chain. An intensive study of IMP manufacturers in the West Midlands (UK) was undertaken through qualitative interviews and desk based research to understand the current challenges and opportunities the industry faced. The analysis is focused on the transition to higher value manufacturing and the complexity of buyer-supplier relationships. This is developed through a case study analysis of the industry’s adjustment to rising industrial energy costs and a detailed examination of customer agreement structures in shaping transactional governance structures. The research makes a contribution to current conceptions of the spatial organisation of production and the nature of production relationships. Mature industries, such as metal component manufacture, are successfully undertaking complex and varied forms of adaptation to remain competitive. Despite transitions to value-added products, costs continue to be an important element to both competitiveness and viability. Production relationships, and specifically the nature of the inter-firm agreement, are a significant aspect of adjustment and the capacity to capture value through governance mechanisms. Contracts are a relatively under represented factor of inter-firm relationships but are found to be central to the adaptability of firms, the attainment of value and stability of the business.

Aluminium Lost Foam castings were made using gravity and counter-gravity filling techniques. Tensile strength was found to be most uniform in those castings which had been filled slowly from the bottom and where the metal front had remained stable throughout filling sequence. Pores containing carbon deposits were found on the fracture surfaces of all the castings made and this suggested that the defect was caused by polymer entrapment. A Saffman-Taylor instability was observed at the interface between Hg and a viscous glucose syrup which were contained in an analogue, that was used simulate the casting of Lost Foam moulds at room temperature. The liquid degradation products of the polystyrene patterns were also found to be viscous, although this was reduced by treatment with Br. Under the same conditions of temperature and velocity, the interface observed during the filling of a Br-treated pattern was planar whereas that of an untreated pattern was unstable. This demonstrated not only that the interfacial instability entrapped polymer degradation products, which adversely affected casting quality, but was probably of the Saffman-Taylor type.

Core and shell deformation during the firing stage of the investment casting process was investigated. Relevant thermo-mechanical and thermal properties were characterised for a commercial core and shell system. A finite-element model was created using the experimentally obtained data. Four major mechanisms were shown to contribute to ceramic mould deformation; general thermal expansion, sintering, phase transformations and creep. The shell system experienced little deformation form phase transformation, the core system exhibited minor deformation from sintering. The sintering behaviour of shell material was observed to be highly dependent on the temperature-time profile of the firing cycle, with lower heating rates resulting in more sintering. The crystallisation of amorphous silica to β-cristobalite in core materials was also seen to follow this trend. A rule of mixtures approach showed that inter-layer interaction in shell materials was minimal. An Avrami-based kinetic modelling approach was applied to pressed silica pellets, showing very good prediction of similar heating rates, but an interaction effect between crystallisation and sintering behaviour needs to be established to predict a wider range of heating cycles. A master sintering curve approach was adapted to incorporate crystallisation to predict the displacement of pellets mimicking core materials. Due to silica crystallisation inhibiting sintering, lower heating rates produced less displacement. In order to validate the finite-element model, an experimental test was developed capturing the deformation of a shell test bar in a three-point bend rig at high temperature using photography. Images were then analysed in ImageJ® to measure the bending of the shell material, this was validated using a transducer attached to a three-point bend knife. Comparison of the finite-element model with the validation test showing good agreement. The creep exponents which were the main proponent of shell bending were optimized to be used in future models.

Job shop scheduling, especially in machine intensive manufacturing is heavily reliant upon job assignment systems for the management of machines on the shop-floor. Considering the machines as the elements of a network in the shop-floor, similar approach could be extended to the elements of supply chain of the manufacturing enterprise. This approach, combined with relevant concepts of the agent-based and holonic systems, has caused motivation to this research, whose primary aim is proposing new job allocation models in multi-level manufacturing operations. That aim has been achieved by bringing the concept of topology of distributed systems into the current agent-based and holonic manufacturing systems. After presenting a conceptual holonic model of multi-level manufacturing operations for fulfillment of an external customer order, the work has focused on shop-floor level. Interaction protocol in multi-agent systems and its relation with the architecture of the agents’ network were studied and new models for task allocation were proposed in the context of a machine-intensive shop-floor. Having examined the models in the shop-floor, the best performing models were further customized and extended to manufacturing supply network (top-floor level). At the both levels, the research uses information and data from case studies of real-world manufacturing. The results obtained were very promising for a ring-like job allocation model, to improve the key performance indicators of operations at the both levels. Although the research seeks practical solutions in Manufacturing Systems, its developed concept on the platform of MAS topology might be utilized within other engineering fields that benefit from the agent technology.