Branching networks play a major role in a variety of physiological and engineering structures over a range of physical scales. However, increasingly, artificial systems are being tailored towards the nanoscale to reduce costs and improve performance and process control. In this thesis, analytical and numerical models are developed to enable the efficient design and accurate simulation of nanofluidic branching networks, where non-continuum/non-equilibrium effects prohibit the use of common solutions. A hybrid molecular-continuum method is presented for the design and simulation of general high-aspect-ratio nanofl uidic networks. This increases the scope of hybrid techniques in two main ways: 1) the method is generalised to accurately model any nanofluidic network of connected channels, regardless of its size or complexity; 2) by generalising the application of constraints, the geometry or governing pressures can be the output of the method, enabling the design of networks without the need for a costly trial-and-error process. For a variety of constraint combinations, it is shown that the hybrid method converges quickly to the solution of a full molecular dynamics simulation, with relative errors of < 4% for all variables across all cases. Network design is further advanced by the development of a generalised optimisation principle that finds the daughter-parent area ratio maximising flow conductance per unit volume in all branches. Through numerically verified analytical models, it is demonstrated that the common branching principle `Murray's law' is sub-optimal for asymmetric branching (where the local optimisation of each individual channel does not correspond to the global optimum for the network as a whole), while the generalised law presented in this thesis is valid for 1) symmetric and asymmetric branching, 2) slip and plug fl flows, which occur at very small scales, and 3) any cross-sectional shape; making it a powerful tool for nanofluidic biomimetic modelling.

Dissimilar metal welds (DMWs) are widely used in steam vessels in thermal power stations to join low-temperature alloys, such as steels, to high temperature alloys, such as nickel-based alloys. This provides a cost-effective manufacturing solution. However, there is a history of DMWs failing due to creep in service environments. Many investigations have been performed on weld systems and failures in the traditional 2.25Cr-1Mo (P22) steels, but fewer have been performed on newer 9Cr-1Mo steels, such as P91 and P92. Failures involving these newer steels continue to occur, for reasons which are not thoroughly understood. The factors involved are believed to include system stresses, differences in thermal expansion and microstructural evolution due to interdiffusion across the weld interface. The overall aim of this research was to investigate the chemical and microstructural stability of a range of DMWs involving P91 and P92 steels. Much of the work is centred on a 3-bead manual metal arc weld of nickel alloy 625 onto a P92 substrate. This was subjected to tempering (760 °C for 2 hours) and furnace ageing (625 °C for 32 and 125 days). The as-welded and aged states were characterised by a range of techniques, including SEM, TEM, EDX and microhardness testing. Site-specific TEM samples were extracted from the weld interfaces using focussed ion beam (FIB) methods. EDX measurements show iron-enrichment in the weld metal (WM) up to 30 wt%, and a partially mixed zone (PMZ) up to 50 microns from the weld. TEM analysis of the as-welded state reveals the presence of a 1 – 2 micron wide band separating the two alloys, and of different crystallographic orientation to both. Following ageing, diffusion of carbon takes place from the P92 to the WM, leading to a carbon denuded zone (CDZ) in the former and an enriched zone (CEZ) in the latter. Precipitates in the CDZ (M23C6 and MX) dissolve to supply this diffusion, while Nb-rich MX phases have formed on grain boundaries in the CEZ. Additionally, carbides are found to form along the interface between the band and the P92. EDX measurements confirm that the aged WM is enriched in carbon near the interface. Microhardness measurements reveal slight softening of the P92 in response to ageing, and pronounced hardening of the WM. The thermodynamics of the alloys were modelled using the software Thermo-Calc, while diffusion across the interface was modelled using DICTRA. The findings support the trends of the experimental results in terms of diffusion behaviour and phase changes. An industrial case study, ex-service P91 – alloy 625 pressure vessel welds exposed to c. 565 °C for c. 40,000 hours, has also been undertaken. Creep failure occurred during service near the weld interface. SEM showed that the creep crack tip was advancing through the CDZ. Microstructural changes were similar to those in the P92 – alloy 625 system, only more pronounced; the CDZ was found to be almost entirely devoid of standard M23C6 and MX precipitates, having been replaced by a band of carbonitrides (either M23X6 or M6X) of unusual chemistry, parallel to the weld interface. A second industrial case study involved a weld between P91 and P92 steels using the P87 filler metal, recently developed by EPRI, which is designed to minimise interdiffusion. This system, in contrast to those involving alloy 625, shows evidence for only minimal interdiffusion after ageing at 649 °C for 131 days, with no CDZ being observed. These observations are supported by Thermo-Calc and DICTRA calculations. Therefore, systems of this type may be resistant to creep failure in long-term service.

Intuitive use is a desirable feature in interface design. In the last decade, researchers have made considerable progress in developing approaches for design for intuitive use. Most of the current approaches, however, have been limited to qualitative exploration, in the form of providing guidelines aimed to help designers to design products that are intuitively useable. This thesis focusses on developing a quantitative approach for evaluating intuitive interaction with the help of image schemas. An image schema is a recurring structure within the human cognitive system that establishes patterns of reasoning with the physical world. Researchers have found this concept to be very useful in capturing human interaction with products; it is also suitable for analysing product features. The approach developed in this thesis measures intuitive interaction based on the degree of match (known in this study as quantification, ‘Q’) between the designer’s intent and the users’ interaction both expressed through image schemas. The value of the proposed approach is in the provision of measurable outputs for evaluating intuitive interaction. The proposed approach is evaluated through an empirical study designed to test the validity of ‘Q’ as a measure of intuitive use expressed through task completion time, errors and cognitive effort. The results reveal that participants with high ‘Q’ value were significantly quicker, made fewer errors, and expended less cognitive effort while completing all subtasks with the three products used in the study. Secondly, the thesis addresses the limitation of other studies in the applicability of the methods used for extracting image schemas. Previous approaches have predominantly relied on the expertise of the researcher conducting the study in extracting the identified image schemas from the utterances of the users. This could introduce subjective bias, thereby reducing the reliability of the method for extracting image schemas. This study addressed this limitation by developing a systematic approach based on a novel algorithm for extracting image schemas from users’ utterances. This enhanced image schema extraction method is based on the use of two ontologies: a lexical ontology and a domainspecific ontology (image schema ontology). The domain-specific ontology was purpose-built for the needs of this study. The independent evaluation study conducted to evaluate the algorithm revealed a substantial strength with an overall k of 0.67 across the 3 products used in the study. Previous studies have predominantly focussed on the cognitive aspect of intuitive use. A limited amount of work has explored the affective aspect of intuition, and integrated it into the evaluation of intuitive use. This study addressed this limitation by developing a novel approach for assessing the affective aspect of the intuitive use of products. This novel approach incorporates the enhanced algorithm for extracting image schemas that was developed for this study. In addition, a sentiment analysis on the affective words linked to the image schemas employed in the task is used as part of the evaluation process. The proposed approach is evaluated through an empirical study based on the sentiments used in describing the image schemas employed for the interaction. The results show that the approach links the image schemas used for the completion of a task to the affective experiences of the users. This has potential to lead to significant improvements in design for intuitive use because it allows experiences to be linked directly to the specific image schemas employed in the design. Overall, the study contributes significantly to the knowledge in this field by validating a new quantitative approach for evaluating intuitive interactions with physical objects. The approaches developed in this study will enable designers to evaluate intuitive usage at different phases of the design process.

Jets resulting from shaped charges which contain metal liners are able to penetrate hard or armoured targets. Their penetration performance is related to the density of the jet and target material and also the length to which the jet can elongate. Models that describe the processes involved have generally assumed hydrodynamic fluid flow and as such have been very successful in most cases. However, the break-up of jets has proved to be inconsistent with the fluid flow models and cannot be accurately described. Break-up is important since it is the final phenomenon in tensile deformation and therefore represents the limiting extent of jet elongation. Additionally, following break-up the jet fragments are particularly susceptible to lateral velocities and tumbling which dissipate the jets energy and further reduce its penetration performance. Research by Hunting Engineering Limited has indicated that mechanical properties are related to the jet break-up phenomena. However, the deformation and break-up of shaped charge jets is not well understood from a metallurgical point of view. It is essential that the jet is in the solid state for jet break-up phenomena to be related to the mechanical properties of the liner material. This has been demonstrated here by theoretical analysis and more directly by observation of in-flight and captured jet fragments. A series of experiments have been carried out in order to measure and analyse the deformation and attempt to put forward models for the break-up mechanisms in shaped charge jets. These were based upon a series of selected aluminium and aluminium alloys which were processed and heat treated to produce a range of mechanical properties. The properties under consideration are those which describe the materials strength, elongation and work hardening characteristics at intermediate strain rates under laboratory conditions. These have been used to relate metallurgical details to the nature of jet break-up. The better materials for shaped charge jets would appear to be high purity metals which exhibit large ductility through to fracture.

Modern competitive market demands frequent change in product variety, increased production volume and shorten product/process change over time. These market requirements point towards development of key enabling technologies (KETs) to shorten product and process development cycle, improved production quality and reduced time-to-launch. One of the critical prerequisite to develop the aforementioned KETs is efficient and accurate modelling of product and process dimensional errors. It is especially critical for assembly processes with compliant parts as used in automotive body, appliance or wing and fuselage assemblies. Currently, the assembly process is designed under the assumption of ideal (nominal) products and then check by using variation simulation analysis (VSA). However, the VSA simulations are oversimplified as they are unable to accurately model or predict the effects of geometric and dimensional variations of compliant parts, as well as variations of key characteristics related to fixturing and joining process. This results in product failures and/or reduced quality due to un-modelled interactions in assembly process. Therefore, modelling and prediction of the geometric shape errors of complex sheet metal parts are of tremendous importance for many industrial applications. Further, as production yield and product quality are determined for production volume of real parts, thus not only shape errors but also shape variation model is required for robust assembly system development. Currently, parts shape variation can be measured during production by using recently introduced non-contact gauges which are fast, in-line and can capture entire part surface information. However, current applications of non-contact scanners are limited to single part inspection or reverse engineering applications and cannot be used for monitoring and statistical process control of shape variation. Further, the product shape variation can be reduced through appropriate assembly fixture design. Current approaches for assembly fixture design seldom consider shape variation of production parts during assembly process which result in poor quality and yield. To address the aforementioned challenges, this thesis proposes the following two enablers focused on modelling of shape errors and shape variation of compliant parts applicable during assembly process design phase as well as production phase: (i) modelling and characterisation of shape errors of individual compliant part with capabilities to quantify fabrication errors at part level; and (ii) modelling and characterisation of shape variation of a batch of compliant parts with capabilities to quantify the shape variation at production level. The first enabler focuses on shape errors modelling and characterisation which includes developing a functional data analysis model for identification and characterisation of real part shape errors that can link design (CAD model) with manufacturing (shape errors). A new functional data analysis model, named Geometric Modal Analysis (GMA), is proposed to extract dominant shape error xixmodes from the fabricated part measurement data. This model is used to decompose shape errors of 3D sheet metal part into orthogonal shape error modes which can be used for product and process interactions. Further, the enabler can be used for statistical process control to monitor shape quality; fabrication process mapping and diagnosis; geometric dimensioning and tolerancing simulation with free form shape errors; or compact storage of shape information. The second enabler aims to model and characterise shape variation of a batch of compliant parts by extending the GMA approach. The developed functional model called Statistical Geometric Modal Analysis (SGMA) represents the statistical shape variation through modal characteristics and quantifies shape variation of a batch of sheet metal parts a single or a few composite parts. The composite part(s) represent major error modes induced by the production process. The SGMA model, further, can be utilised for assembly fixture optimisation, tolerance analysis and synthesis. Further, these two enablers can be applied for monitoring and reduction of shape variation from assembly process by developing: (a) efficient statistical process control technique (based on enabler ‘i’) to monitor part shape variation utilising the surface information captured using non-contact scanners; and (b) efficient assembly fixture layout optimisation technique (based on enabler ‘ii’) to obtain improved quality products considering shape variation of production parts. Therefore, this thesis proposes the following two applications: The first application focuses on statistical process control of part shape variation using surface data captured by in-process or off-line scanners as Cloud-of-Points (CoPs). The methodology involves obtaining reduced set of statistically uncorrelated and independent variables from CoPs (utilising GMA method) which are then used to develop integrated single bivariate T2-Q monitoring chart. The joint probability density estimation using non-parametric Kernel Density Estimator (KDE) has enhanced sensitivity to detect part shape variation. The control chart helps speedy detection of part shape errors including global or local shape defects. The second application determines optimal fixture layout considering production batch of compliant sheet metal parts. Fixtures control the position and orientation of parts in an assembly process and thus significantly contribute to process capability that determines production yield and product quality. A new approach is proposed to improve the probability of joining feasibility index by determining an N-2-1 fixture layout optimised for a production batch. The SGMA method has been utilised for fixture layout optimisation considering a batch of compliant sheet metal parts. All the above developed methodologies have been validated and verified with industrial case studies of automotive sheet metal door assembly process. Further, they are compared with state-of-the-art methodologies to highlight the boarder impact of the research work to meet the increasing market requirements such as improved in-line quality and increased productivity.

Traditional manufacturing methods like moulding or subtractive manufacturing place significant limitations on structures which could be manufactured in a single process. These limitations can now be overcome by a new manufacturing technology—Additive Manufacturing (AM), which provides the users much more freedom to design and produce structures in one piece. Additive manufacturing refers to a range of processing technologies, which fabricate 3D parts by adding successive layers. With this technology, complex 3D structures can be produced directly following the production of a geometric data. Additive manufacturing also enables production without the need of tooling, which brings the prospect of a revolution in the manufacturing industry. Material jetting is one of the additive manufacturing techniques, which generates material layers through inkjet printing. This technology also allows the user to build structures consisting of more than one material, which further expands the capability of additive manufacturing to include the production of multi-functional products. However, due to the strict requirements on the rheology of usable inks, there is a limited number of materials available for use in this technology. This research aims to develop a novel polycaprolactone based ink which is suitable for material jetting and could be potentially used for fabricating scaffolds. The bespoke nature of these devices often require a complex structures, customized design and small batch sizes, which all together make the product costly when using the traditional manufacturing methods. Additive manufacturing technology can reduce these costs, in the main due to the nil marginal cost (e.g. tooling cost, mould design etc.) when changing product design. In addition, material jetting can also incorporate multi-materials or multi-functional devices, mixing several materials at micron level, potentially enabling more advanced and intelligent functions to be incorporated into the final devices. In this project, Polycaprolactone (PCL), commonly used for its biodegradable properties, was investigated as a candidate for material jetting. Both solvent based and UV reaction based jetting techniques were attempted to build up an understanding of the aspects and parameters involved in material jetting ink development and jetting parameter optimization. For solvent based PCL ink, PCL flakes were dissolved into various solvents with different concentrations to prepare a low viscosity ink which could be printed. Volatility, viscosity and surface tension were investigated to confirm that the prepared ink was suitable for jetting. PCL with 5wt% in 1,4-dioxane was successfully jetted by using a Dimatix material printer. A range of experiments were carried out to investigate the ink’s printability under different conditions. During the study, efficiency limitation for solvent based ink was also realized. In order to meet the printing viscosity limit of the inkjet printheads, the loading level of a solute in a solvent ink as well as the efficiency of stacking precipitated layers were both restricted. This curbed the possibility of solvent based ink be applied in making large 3D parts. For UV reaction based inks, the printed ink can fully solidify to form structures after UV illumination, which overcame the processing efficiency limitation of the initial solvent based inks. Pure PCL is not UV curable and therefore chemical modifications were made to graft UV curable functional groups into the PCL structure. The rheology of synthesized UV curable PCL polymers were studied and modified to make them suitable for material jetting. Different photoinitiators were also investigated to work out the suitable composition to achieve real-time curing. Oxygen inhibition was found to be the main side effect which inhibited the curing reaction in an air environment. Type II photoinitiators can help overcome this effect and 3D structures were able to be obtained in both air and nitrogen. It was also found that a nitrogen environment can improve the properties of the printed specimens and the printed samples showed better hardness and modulus than those in printed in air. It was also noted that the increasing concentration of the photoinitiator can improve the curing speed of the ink printed in air. However the samples with higher concentration of photoinitiators manifested a reduction of hardness and modulus. A post-curing procedure, carried out using further UV illumination, was shown to help improve both the hardness and the modulus, but this improvement was limited to the directly illuminated surface.

Remanufacturing is one of the main recovery operations in Closed-Loop Supply Chains (CLSCs) that not only can contribute to a more sustainable environment, but also has significant economic and social benefits. A key factor for having an efficient remanufacturing operation is to control the heterogeneous characteristics of product returns in terms of quantity, quality and timing. Product Acquisition Management is an essential process in CLSCs, which aims to deal with these characteristics of product returns. The present study extends knowledge in Product Acquisition Management, by developing quantitative models that generate meaningful insights into the economics of proactive product acquisitioning. In addition, case studies inform the present study with the current status of product acquisition management in practice and the relevant challenges. The economic-oriented decision about operating a proactive or passive strategy is explored under quantity and quality-based incentive approaches. Closed-form solutions and quality thresholds are derived for the optimal return rate and optimal quality rate that minimises the total cost of the proactive strategy. The analysis of the infinite planning horizon models show that, the optimal acquisition strategy depends on a trade-off between the relevant remanufacturing cost advantage and the acquisition cost structure. A diseconomy of scale in the acquisition of returns leads to a decrease of the remanufacturing amount. Sensitivity analysis further highlights the differences between the quantity and the quality-based incentive approaches. This study extends its investigation on the economic viability of the proactive acquisition strategy under the finite planning horizon. Using the product life cycle as a basis for matching demand and supply, the analysis shows that delays in the processing of returns will reduce the cost advantages of a proactive acquisition strategy and that applying a dynamic acquisition policy will increase the cost improvement of the proactive strategy. Finally, the study investigates a dynamic manufacturing-remanufacturing system with a responsive buy-back policy by considering multiple quality levels and decay rates. The model is formulated using optimal control theory, and shows that the optimal acquisition strategy depends on the manufacturing-remanufacturing cost difference and price sensitivity of the return response function for high and low quality used products. The sensitivity analysis indicates that in general it is beneficial to obtain a higher rate of high quality returns in the beginning of the planning horizon, and a higher rate of low quality returns towards the end. The fluctuation in demand is mainly absorbed by manufacturing new products and much less by remanufacturing returns. Within the optimal buy-back policy, the result has indicated that it is the acquisition of high quality of returns that mirror the fluctuation in the demand, while the acquisition of low quality of returns show a relatively stable trend.

Over the past decade there has been a number of innovations in the estimation of input demand equations. In particular, ways of incorporating the hypothesis of rational expectations into empirical models of the firm have been developed and improved upon. This research agenda was perhaps inspired by the Lucas critique of econometric policy evaluation, which suggested that econometric models which did not explicitly take account of how expectations of the future affect current behaviour would give misleading results regarding the possible effects of various government policies. Lucas specifically directed part of his critique at empirical models of business investment, which had been used previously in the assessment of tax policies designed to affect investment. This thesis has a dual purpose. First, two distinct models of input demand are estimated with Canadian manufacturing data. Each of the models incorporates to some degree the hypothesis of rational expectations, but the specifications of technology differ. Neither of these models, to our knowledge, has been estimated with Canadian data. We are interested in whether either model explains well the behaviour of the Canadian manufacturing sector, and in how the results compare with the (few) U.S. applications of this type of model. The second purpose is to use the results of these models in simulations to assess the effect of changes to the after-tax rental rate of capital on investment and employment in manufacturing. While there have been studies in Canada (and elsewhere) that attempt to calculate the effects of various tax policies on investment, most studies were done prior to the innovation of techniques in estimating models with rational expectations. This thesis is able to examine the effects of a particular change while remaining immune to the Lucas critique. If the modelling of expectations is correct, this could not only improve the reliability of the estimates, but also give some indication of the empirical importance of the Lucas critique. The results can be summarized as follows. The two models give very different estimates of price elasticities of demand for capital and labour, even though they are similar in many respects and are estimated with a common data set. It is also the case that their estimates of the effects of temporary and permanent changes to the rental rate are different. Adjusting the reduced form parameters of the input demand equations to account for changes in tax policy regimes alters the results to a significant degree, suggesting that the explicit modelling of expectations matters in an empirically relevant sense. However, these effects are in opposite directions for the two models considered here. All this suggests that more research is required into the relationship between expectations of future policy and investment behaviour. / Arts, Faculty of / Vancouver School of Economics / Graduate

M.Tech. / Activities in the manufacturing sector are the bedrock of an economy and the driver of development. Within the manufacturing sector, production operations skills are deficient in a number of contexts and many times are the cause of failures in entrepreneurship development. Therefore, the purpose of this study was to investigate the relationship between the levels of production and operational skills and SMME [Small Medium and Micro Enterprises] sustainability. The gap that has been identified abides in productions operations skills development of SMME entrepreneurs. Building on previously established literature on entrepreneurial skills development, production operations management and empirical findings, a framework was then proposed. Within this framework an instrument was developed and tested for the sole purpose of assessing the level of production operations skills amongst SMME entrepreneurs. Principal literature reviews indicate that, despite South Africa’s [SA] favourable regulatory environment, a high failure rate amongst SMME’s still persists. The analysis of the data indicates that entrepreneurs with no or poor production and operation skills are most likely to be unsuccessful whilst entrepreneurs with production and operation skills are most likely to be successful. The study was limited to the manufacturing SMME’s in the Vaal Triangle Region [VTR] and the sample frame was supplied by the Gauteng Enterprise Propeller [GEP] – Vaal Branch. The implications for policymakers encouraging the development of sustainable entrepreneurs in SA, is that due consideration should be given to factors that would enhance production operations skills and, in so doing, contribute to sustainability. Entrepreneurs, educators and service providers will benefit from a better understanding of how various factors merge into the intent of creating a successful production operation environment. Training entrepreneurs to be aware of the multiple influencing factors will raise the level of skills and the ability to correctly gauge and manage opportunities. Since, thus far, a very limited study has been executed in the field of production operation management, the synthesis of the variables proposed in this framework offers an introductory roadmap to guide future research in this field.

A manufacturing company typically has the objective of maximizing the long-term value of its common stock while satisfying its customers. To achieve this, the company might increase the quantity and improve the quality of production. Since the company is operating in a dynamic environment, its policies should be dynamic also, to achieve its objective.