Methodology for Identifying Promising Retrofit Integrated Forest Biorefinery Strategies - Design Decision Making Under Uncertainty

Le bioraffinage forestier est de plus en plus considéré comme une activité future prometteuse pour l'industrie forestière, et comme une approche plus respectueuse de l'environnement pour répondre aux besoins de la société en matière d'énergie, de produits chimiques et de matériaux. Le bioraffinage forestier est basé en partie sur les mêmes principes que ceux de l’industrie pétrochimique et cible pratiquement le même marché de produits. L'industrie forestière possède toutefois un avantage particulier comparativement à l’industrie chimique pour cette transformation : elle possède une expérience de longue date quant à la récolte et la transformation de matières premières biologiques. D’un autre côté, la compétitivité actuelle de l’industrie des pâtes et papiers (P&P) dans les pays traditionnels de production de P&P est compromise, et ce à cause du vieillissement de ses installations, des coûts d’énergie élevés, d’une réglementation stricte et des attentes élevées du public. Dans ce contexte, la prise de décision pour un investissement dans un procédé de bioraffinage devient un défi important et donne alors lieu à des pressions supplémentaires sur la conception de procédé et sur les processus de prise de décision visant à identifier les meilleures opportunités. L’identification et la gestion des caractéristiques aux niveaux du procédé et de gestion stratégique, de même que les incertitudes reliées à l’implantation en rétro-installation du bioraffinage forestier est nécessaire pour la prise de décision concernant le choix d'investissements stratégiques. Présentement, de nombreuses méthodes sont appliquées à différentes étapes du cycle de gestion des affaires afin d’analyser l’impact des incertitudes. Au niveau du procédé, des méthodes et outils de conception de nouveaux procédés ou de procédés en rétro-installation sont appliqués pour analyser la rentabilité de projets stratégiques. Au niveau de l’entreprise ou de l’usine, des méthodes avancées de comptabilité sont utilisées pour analyser la performance au niveau des coûts des unités, et des rapports financiers sont effectués périodiquement pour caractériser la performance de l’entreprise. De plus, la prise de décision en groupe est de plus en plus utilisée pour la planification stratégique et les décisions d’investissement. L'objectif de cette thèse est de développer une méthodologie qui améliore le lien entre la conception de procédé en rétro-installation, la comptabilité analytique et les activités de prise de décision reliées à l’investissement en capital, afin d’améliorer le processus de prise de décision relié à l’investissement dans le bioraffinage forestier. Cette méthodologie est appliquée à une étude de cas considérant l’implantation en rétro-installation du bioraffinage dans une usine de P&P kraft. La méthodologie consiste en la prise de décision par étapes successives, en commençant par une présélection d’alternatives de procédés basée sur des analyses technico-économique et de risques traditionnelles. La deuxième étape du processus décisionnel utilise un nouveau cadre combinant à la fois le processus de prise de décision d'investissements stratégiques, et la conception et la simulation de procédés par le biais d’un modèle économique basé les principes de comptabilité par activités. Les modèles de coûts liés à la simulation de procédé sont d’une part en mesure de représenter avec précision les coûts de fabrication de tous les produits après l’implantation de procédés de bioraffinage. D'autre part, ces modèles sont capables de fournir des indicateurs financiers utiles pour l’évaluation des performances des projets stratégiques à court et à long terme. Par ailleurs, une analyse de risques utilisant une analyse stochastique multivariée peut être utilisée puisque toutes les mesures de performance sont explicitement quantifiées. Les résultats de l'étude de cas montrent que l'analyse systématique des incertitudes externes peut fournir des informations essentielles sur les performances d’un projet dans le pire scénario, et ce même à l’étape de présélection des alternatives de procédé. Par ailleurs, l'analyse stochastique multivariée permet une évaluation plus objective des incertitudes au lieu d'utiliser des méthodes subjectives. De plus, les résultats d'analyse des alternatives de procédés retenues en utilisant le cadre élaboré quantifient clairement les impacts économiques des projets de rétro-installation. Ces impacts varient entre les alternatives, et ce à cause des différents potentiels d'intégration et des différentes contraintes du système de production existant. Dans le cas d’un processus normal de conception de procédé et d'affectation de capitaux, cette information sur les coûts ne serait disponible que pour les projets implantés et ce, après leur mise en service. Le changement dans la compétitivité des coûts dans l’activité principale de l’entreprise peut être un facteur particulièrement important pour les producteurs de commodités papetières ayant des coûts de production élevés. En effet, lors d’un panel multicritères de décision (MCDM) où les différents calculs étaient basés sur ces données de coûts d’opération plus précises, l'intensité de différents critères de performance stratégiquement importants, tels que la performance du capital et la capacité de paiement pour les matières premières a été évaluée. Ce panel a montré que, même si certains critères de performance de projet à court terme ont été privilégiés, de bonnes performances au niveau des usines avaient également un rôle important dans le classement global. Ainsi, le classement final des alternatives obtenu lors de ce panel différait de celui obtenu lorsque seul le critère de rentabilité du projet était utilisé. De plus, les diverses importances relatives des critères de sélection de projet attribuées par les différents membres du personnel de l’entreprise ayant participé au panel ont démontré le caractère multiforme de ce problème décisionnel de choix d'investissements stratégiques. Par ailleurs, le fait d’utiliser une analyse de sensibilité lors du panel MCDM a permis d’illustrer l’impact des divergences de préférences des panélistes sur le classement des alternatives. En résumé, l’utilisation de cette méthodologie a d’abord permis de réduire un grand nombre d’alternatives de procédé pour l’usine de P&P à un premier ensemble d’alternatives potentielles, pour ensuite identifier une seule combinaison produit-procédé plus prometteuse. Cette méthodologie a donc été en mesure de lier systématiquement différentes analyses pour aider une entreprise manufacturière lors de la prise de décision pour le choix d'investissements. Les travaux futurs comprennent l'élargissement de ce cadre méthodologique au processus de décision d'investissements stratégiques au niveau corporatif, afin d’améliorer davantage la gestion des actifs et la planification stratégique. Par ailleurs, une analyse des performances au niveau des opérations pourrait être incluse dans ce cadre afin de faire la conception de procédés de bioraffinage forestier flexibles bien adaptés à la stratégie d’entreprise. ---------- Forest biorefinery is increasingly been considered as potential future business for traditional forest industry, and a more environmentally benign approach for supplying the demand of energy, chemicals and materials for the society. The forest biorefinery is partly based on the same principles, and it targets the same market sector, as traditional petro-chemical industry. However, the forest industry possesses a unique advantage over the chemical industry that is the long experience in bio-based feedstocks and their processing. The current pulp and paper (P&P) industry’s competitiveness in traditional P&P countries due to ageing assets, high energy costs, strict regulations and high environmental expectations from the public, makes however the investment decision making challenging and thus gives rise to additional pressure on the design and decision making processes to help identifying the right opportunities. Identification and management of the process and business level characteristics and uncertainties of retrofit forest biorefinery implementation is required in the strategic investment decision making. Currently, many methods are applied in different functions of the business life-cycle to analyse similar characteristics and impacts of uncertainties for varying purposes: at process level, retrofit and greenfield process design methods and tools are applied to investigate project feasibility and profitability for potential operational and strategic projects; at business or facility level, advanced cost accounting methods are used to analyse manufacturing system cost-performance, financial reporting is conducted to report business performance periodically, and group decision making is utilised in strategic planning and investment decision making. The objective of this thesis is to develop a methodology to improve the link between retrofit process design, cost accounting and capital investment decision making activities to further enhance the investment decision making process for forest biorefinery. The methodology is applied in a case study considering retrofit biorefinery implementation into a kraft P&P mill. The methodology consists of step-wise decision making starting with pre-screening of retrofit design alternatives based on traditional techno-economics and risk analysis, followed by an advanced decision making procedure. This second decision making step uses a novel framework combining process design and simulation through cost accounting models, based on activity-based costing principles, to strategic investment decision making process. The cost models linked to process simulation are able to accurately represent the manufacturing costs of all products after retrofit biorefinery implementation, and on the other hand, these models are able to provide useful financial measures of short- and long-term performance of the projects and the facility for strategic investment decision making. Moreover, risk analysis using stochastic multivariate analysis can be utilized since all performance metrics are explicitly quantified. Results of the case study application of the framework show, that systematic analysis of external uncertainties can provide critical information about the worst-case scenario project performance already in the project pre-screening stage. Moreover, multivariate stochastic analysis enables a more objective assessment of the uncertainties instead of using subjective scoring methods. Furthermore, the analysis results of the retained retrofit design alternatives using the developed framework clearly quantified the cost-impacts of the retrofit projects. These impacts vary between alternatives because of different integration potential and system constraints. In the case of normal process design and capital appropriation process, this cost information would be available only for the implemented project when it is operating. The change in the core business cost competitiveness can be especially important factor for the higher cost producers of commodity P&P products. Evaluation of the intensities of different strategically important performance criteria, such as capital performance or feedstock paying capability, based on this more accurate operating cost data showed that even though short-term project performance criteria were preferred, good facility-level performance based on the multi-criteria decision making (MCDM) panel had an important role in the overall ranking. The final ranking of the alternatives differed from that of using only a single criterion, project profitability. The attribute importance preferences of mill and company personnel from varying positions demonstrated the multi-faceted nature of this strategic investment decision making problem. Moreover, using sensitivity analysis in the MCDM was also able to illustrate the impact of the panellists’ preference differences on the ranking. In summary, the complete methodology was able to narrow down a large amount of P&P mill retrofit alternatives first to a set of potential candidates and further to a most potential process-product combination, and thus was able to systematically link the different analysis activities in a manufacturing firm to aid investment decision making. Future work includes the expansion of this framework into the strategic investment decision making at the corporate level, to further enhance the asset management and strategic planning. Furthermore, operations-performance analysis can be included in the framework to obtain flexible forest biorefinery designs with good strategic fit

A Holistic Approach to Sustainability Analysis of Industrial Networks

The aim of this thesis is to support the evaluation of sustainable development strategies for industrial networks in the context of industrial ecology (IE). Industrial networks are a group of units which carry out, or contribute to, industrial activity, and are connected by material and energy flows, but also capital and information exchanges. The components of an industrial network encompass resource extraction, processing and refining, forming and assembly, use, disposal, as well as recycling and reprocessing. The motivation behind this research is the realisation that much of the current environmental system analysis focus within IE lacks a structured approach to considering: • system environment • dynamic nature of the system and its environment • economic and social impacts • the effect of uncertainty on analysis outcomes. It is argued in this thesis that current environmental analysis approaches used in IE can be improved in their capacity to capture the complexity of industrial systems, with the objective of promoting sustainable development. While IE emphasises the benefit of a systems approach to identifying environmental strategies in industry, analysis tools have to date not engaged extensively with important aspects such as the influence of system environment and dynamics on the viability of an environmental strategy, or with the economic or social impacts of industrial system development, which are equally important for sustainable development. Nor is the assessment of the effect of uncertainty on analysis outcomes an integral part of environmental analysis tools in IE. This is particularly significant when, in fact, the degree of uncertainty in assumptions and data used increases with the scope, and therefore the abstraction, of the system under consideration. IE will have to engage with the network and contextual complexities to a greater degree if it is to evolve from a concept to the application of its principles in practice. The main contribution of this thesis is therefore the development of a structured approach to analysing industrial networks for the purpose of identifying strategies to encourage sustainable development, while accounting for the complexity of the underlying system as well as the problem context. This analysis is intended to allow the identification of preferred network development pathways and to test the effectiveness of sustainable development strategies. A top-down, prescriptive approach is adopted for this purpose. This approach is chosen as the industrial network analysis is intended to identify how a network should develop, rather than focusing on how it could develop. Industrial networks are systems which are complex in both their structure and behaviour. This thesis also delivers a characterisation of these networks, which serves two purposes – quantifying key elements of structure and behaviour; and using this information to build a foundation for subsequent industrial network analysis. The value of such an approach can be seen in the following example. With a detailed understanding of individual network characteristics, both separately and collectively, it is possible to determine the source of issues, the means available to address them, any barriers that might exist, and the consequences of implementing any strategic interventions. The analysis approach proposed in this thesis is based on multi-criteria decisions analysis (MCDA), which, as a process, combines initial problem structuring and subsequent quantitative analysis stages. The tools employed within MCDA have been employed variously around considerations of sustainable development. Their value in this thesis is their integration within a rigorous analytical framework. Rigorous problem structuring is attractive as it helps elucidate the complexities of the system and its environment and is, by definition, designed to deal with multiple environmental social and economic criteria that would have to be considered to promote sustainable development. For the quantitative analysis, the industrial network analysis draws from existing analysis tools in IE, but predominately from other systems research disciplines, such as process systems engineering (PSE) and supply chain management (SCM). These fields, due to their maturity and practical focus, have invested a lot of research into system design and strategic planning, capturing system dynamics and uncertainty to ensure, within selected system constraints, that a proposed system or changes to a system are viable, and that the system is capable of achieving the stated objectives. Both PSE and SCM rely heavily on optimisation for system design and planning, and achieve good results with it as an analytical tool. The similarity between industrial networks and process systems / supply chains, suggests that an optimisation platform, specifically multi-objective dynamic optimisation, could be employed fruitfully for the analysis of industrial networks. This is the approach taken in this thesis. It is consistent with the “top down” approach advocated previously, which is deemed preferable for the identification and implementation analysis of strategic interventions. This enables the determination of a structure (design) that is “best” able to operate under future conditions (planning) with respect to the chosen sustainable development objectives. However, an analysis is only ever as good as its underlying data and assumptions. The complexity and scope of the industrial network and the challenge of articulating sustainable development target(s) give rise to significant uncertainties. For this reason a framework is developed within this thesis that integrates uncertainty analysis into the overall approach, to obtain insight into the robustness of the analysis results. Quantifying all the uncertainties in an industrial network model can be a daunting task for a modeller, and a decision-maker can be confused by modelling results. Means are therefore suggested to reduce the set of uncertainties that have to be engaged with, by identifying those which impact critically on model outcomes. However, even if uncertainty cannot be reduced, and the implementation of any strategy retains a degree of risk, the uncertainty analysis has the benefit that it forces an analyst to engage in more detail with the network in question, and to be more critical of the underlying assumptions. The analysis approach is applied to two case studies in this thesis: one deals with waste avoidance in an existing wood-products network in a large urban metropolis; the other with the potential for renewable energy generation in a developing economy. Together, these case studies provide a rich tableau within which to demonstrate the full features of the industrial network analysis. These case studies highlight how the context within which the relevant industrial network functions influences greatly the evolution of the network over time; how uncertainty is managed; and what strategies are preferred in each case in order to enhance the contribution of each network to sustainable development. This thesis makes an intellectual contribution in the following areas: • the characterisation of industrial networks to highlight sources of environmental issues, role the characteristics (could) play in the identification of (preferred) sustainable development strategies, and the need to explicitly consider these in a systems analysis. • the synthesis, adaptation and application of existing tools to fulfil the need for analysis tools in IE that can handle both contextual and system complexity, and address the above mentioned issues of lacking consideration of o system environment o dynamic nature of the system and its environment o economic and social impacts o the effect of uncertainty on analysis outcomes. • the development and demonstration of an industrial network analysis approach that o is flexible enough to model any industrial network at the inter-firm level, regardless of form and configuration of materials and products circulated, and depending on the existing network and the proposed strategies. o is able to encompass a wide range of environmental strategies, either individually or in combination depending on what best suits the situation, rather than focusing on any strategy in particular. o ensures long term viability of strategies, rather than short term solutions delivering incremental improvement. • the development of a comprehensive approach to capturing and assessing the effect of uncertainty on solution robustness for industrial network analysis, including the screening to determine the most important parameters, considering valuation and technical uncertainties, including future uncertainty. The industrial network analysis approach presented in this thesis looks more to how a network should develop (according to a set of sustainable development objectives), rather than how it may in actual fact develop. Consequently, the influence of agent interests and behaviour is not considered explicitly. This may be construed as a limitation of the industrial analysis approach. However, it is argued that the “top down” modelling approach favoured here is useful at a policy-making level. Here, for example, government instrumentalities, trade organisations and industry groupings, non-government organisations and community-based organisations are likely to be interested more in the performance of the network as a whole, rather than (necessarily) following the behaviour of individual agents within the network. Future work could well entertain the prospect of a mixed approach, in which the top-down approach of this thesis is complemented by a “bottom-up”, agent-based analysis. In this manner, it would be possible to give an indication of how attainable the identified industrial network development pathways are. Furthermore, the use of government incentives can be explored to assess if network development could approach the preferred development pathway which is identified using the methodology and results articulated in this thesis

A Holistic Approach to Sustainability Analysis of Industrial Networks

The aim of this thesis is to support the evaluation of sustainable development strategies for industrial networks in the context of industrial ecology (IE). Industrial networks are a group of units which carry out, or contribute to, industrial activity, and are connected by material and energy flows, but also capital and information exchanges. The components of an industrial network encompass resource extraction, processing and refining, forming and assembly, use, disposal, as well as recycling and reprocessing. The motivation behind this research is the realisation that much of the current environmental system analysis focus within IE lacks a structured approach to considering: • system environment • dynamic nature of the system and its environment • economic and social impacts • the effect of uncertainty on analysis outcomes. It is argued in this thesis that current environmental analysis approaches used in IE can be improved in their capacity to capture the complexity of industrial systems, with the objective of promoting sustainable development. While IE emphasises the benefit of a systems approach to identifying environmental strategies in industry, analysis tools have to date not engaged extensively with important aspects such as the influence of system environment and dynamics on the viability of an environmental strategy, or with the economic or social impacts of industrial system development, which are equally important for sustainable development. Nor is the assessment of the effect of uncertainty on analysis outcomes an integral part of environmental analysis tools in IE. This is particularly significant when, in fact, the degree of uncertainty in assumptions and data used increases with the scope, and therefore the abstraction, of the system under consideration. IE will have to engage with the network and contextual complexities to a greater degree if it is to evolve from a concept to the application of its principles in practice. The main contribution of this thesis is therefore the development of a structured approach to analysing industrial networks for the purpose of identifying strategies to encourage sustainable development, while accounting for the complexity of the underlying system as well as the problem context. This analysis is intended to allow the identification of preferred network development pathways and to test the effectiveness of sustainable development strategies. A top-down, prescriptive approach is adopted for this purpose. This approach is chosen as the industrial network analysis is intended to identify how a network should develop, rather than focusing on how it could develop. Industrial networks are systems which are complex in both their structure and behaviour. This thesis also delivers a characterisation of these networks, which serves two purposes – quantifying key elements of structure and behaviour; and using this information to build a foundation for subsequent industrial network analysis. The value of such an approach can be seen in the following example. With a detailed understanding of individual network characteristics, both separately and collectively, it is possible to determine the source of issues, the means available to address them, any barriers that might exist, and the consequences of implementing any strategic interventions. The analysis approach proposed in this thesis is based on multi-criteria decisions analysis (MCDA), which, as a process, combines initial problem structuring and subsequent quantitative analysis stages. The tools employed within MCDA have been employed variously around considerations of sustainable development. Their value in this thesis is their integration within a rigorous analytical framework. Rigorous problem structuring is attractive as it helps elucidate the complexities of the system and its environment and is, by definition, designed to deal with multiple environmental social and economic criteria that would have to be considered to promote sustainable development. For the quantitative analysis, the industrial network analysis draws from existing analysis tools in IE, but predominately from other systems research disciplines, such as process systems engineering (PSE) and supply chain management (SCM). These fields, due to their maturity and practical focus, have invested a lot of research into system design and strategic planning, capturing system dynamics and uncertainty to ensure, within selected system constraints, that a proposed system or changes to a system are viable, and that the system is capable of achieving the stated objectives. Both PSE and SCM rely heavily on optimisation for system design and planning, and achieve good results with it as an analytical tool. The similarity between industrial networks and process systems / supply chains, suggests that an optimisation platform, specifically multi-objective dynamic optimisation, could be employed fruitfully for the analysis of industrial networks. This is the approach taken in this thesis. It is consistent with the “top down” approach advocated previously, which is deemed preferable for the identification and implementation analysis of strategic interventions. This enables the determination of a structure (design) that is “best” able to operate under future conditions (planning) with respect to the chosen sustainable development objectives. However, an analysis is only ever as good as its underlying data and assumptions. The complexity and scope of the industrial network and the challenge of articulating sustainable development target(s) give rise to significant uncertainties. For this reason a framework is developed within this thesis that integrates uncertainty analysis into the overall approach, to obtain insight into the robustness of the analysis results. Quantifying all the uncertainties in an industrial network model can be a daunting task for a modeller, and a decision-maker can be confused by modelling results. Means are therefore suggested to reduce the set of uncertainties that have to be engaged with, by identifying those which impact critically on model outcomes. However, even if uncertainty cannot be reduced, and the implementation of any strategy retains a degree of risk, the uncertainty analysis has the benefit that it forces an analyst to engage in more detail with the network in question, and to be more critical of the underlying assumptions. The analysis approach is applied to two case studies in this thesis: one deals with waste avoidance in an existing wood-products network in a large urban metropolis; the other with the potential for renewable energy generation in a developing economy. Together, these case studies provide a rich tableau within which to demonstrate the full features of the industrial network analysis. These case studies highlight how the context within which the relevant industrial network functions influences greatly the evolution of the network over time; how uncertainty is managed; and what strategies are preferred in each case in order to enhance the contribution of each network to sustainable development. This thesis makes an intellectual contribution in the following areas: • the characterisation of industrial networks to highlight sources of environmental issues, role the characteristics (could) play in the identification of (preferred) sustainable development strategies, and the need to explicitly consider these in a systems analysis. • the synthesis, adaptation and application of existing tools to fulfil the need for analysis tools in IE that can handle both contextual and system complexity, and address the above mentioned issues of lacking consideration of o system environment o dynamic nature of the system and its environment o economic and social impacts o the effect of uncertainty on analysis outcomes. • the development and demonstration of an industrial network analysis approach that o is flexible enough to model any industrial network at the inter-firm level, regardless of form and configuration of materials and products circulated, and depending on the existing network and the proposed strategies. o is able to encompass a wide range of environmental strategies, either individually or in combination depending on what best suits the situation, rather than focusing on any strategy in particular. o ensures long term viability of strategies, rather than short term solutions delivering incremental improvement. • the development of a comprehensive approach to capturing and assessing the effect of uncertainty on solution robustness for industrial network analysis, including the screening to determine the most important parameters, considering valuation and technical uncertainties, including future uncertainty. The industrial network analysis approach presented in this thesis looks more to how a network should develop (according to a set of sustainable development objectives), rather than how it may in actual fact develop. Consequently, the influence of agent interests and behaviour is not considered explicitly. This may be construed as a limitation of the industrial analysis approach. However, it is argued that the “top down” modelling approach favoured here is useful at a policy-making level. Here, for example, government instrumentalities, trade organisations and industry groupings, non-government organisations and community-based organisations are likely to be interested more in the performance of the network as a whole, rather than (necessarily) following the behaviour of individual agents within the network. Future work could well entertain the prospect of a mixed approach, in which the top-down approach of this thesis is complemented by a “bottom-up”, agent-based analysis. In this manner, it would be possible to give an indication of how attainable the identified industrial network development pathways are. Furthermore, the use of government incentives can be explored to assess if network development could approach the preferred development pathway which is identified using the methodology and results articulated in this thesis

The effects of waste management on profitability in a flexible packaging company

A research report submitted to the Faculty of Engineering and Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering, 2017Waste results in material loss and cascades to production processes, affecting a company’s profitability. This research sought to answer to what extent the implementation of a solid waste management protocol in a flexible packaging company (FPC) improves profitability. The research focused on reducing waste from the gravure printing process, which was analysed using a Lean Six Sigma tool, DMAIC, that has been shown to increase productivity, reduce cost, reduce defects and standardise operations. Processes were implemented to ensure that quality substrate was input at the correct levels and transformed efficiently into sellable product. Additionally, new protocols were employed to control and manage waste, further increasing the FPC’s savings. These modifications reduced waiting down time by 78%, rework by 53%, and job-specific waste by 6%, which translated into a 17% improvement in profit on average. Thus, the research effectively demonstrates that a waste management protocol increases the profitability of a FPC.XL201

Quantification of uncertainty of geometallurgical variables for mine planning optimisation

Interest in geometallurgy has increased significantly over the past 15 years or so because of the benefits it brings to mine planning and operation. Its use and integration into design, planning and operation is becoming increasingly critical especially in the context of declining ore grades and increasing mining and processing costs. This thesis, comprising four papers, offers methodologies and methods to quantify geometallurgical uncertainty and enrich the block model with geometallurgical variables, which contribute to improved optimisation of mining operations. This enhanced block model is termed a geometallurgical block model. Bootstrapped non-linear regression models by projection pursuit were built to predict grindability indices and recovery, and quantify model uncertainty. These models are useful for populating the geometallurgical block model with response attributes. New multi-objective optimisation formulations for block caving mining were formulated and solved by a meta-heuristics solver focussing on maximising the project revenue and, at the same time, minimising several risk measures. A novel clustering method, which is able to use both continuous and categorical attributes and incorporate expert knowledge, was also developed for geometallurgical domaining which characterises the deposit according to its metallurgical response. The concept of geometallurgical dilution was formulated and used for optimising production scheduling in an open-pit case study.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201

Simulation and optimisation of the controls of the stock preparation area of a paper machine.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2004.At Mondi Paper Ltd, Merebank, South of Durban, Paper Machine 2 has recently been transferred onto a Distributed Control System (DCS). This was seen as a good opportunity to enhance the control of the pulp feed to the machine. A prime concern in operating a paper machine is to ensure consistent set-point paper properties in the Cross-Direction (CD: ie. across the paper width) and in the Machine-Direction (MD: ie. along the paper length). Sophisticated adjustments are available to ensure an even feed of the stock (consistencies around 2% m/m wood fibres in water) from the head-box across the receiving width of the paper machine. The properties of prime interest as the pulp is pumped through the head-box distributor onto the receiving belt of the machine are the basis weight (fibre mass per unit area) and moisture content (per unit area). However, the distribution system is highly dependent on the properties of the stock as it arrives at the head-box. Variations in upstream chest levels, the supplied pressure, flow-rate and fibre/water ratio, all cause MD and even CD variations. The problems of maintaining steady conditions at the head-box are well known, and are understood to arise from sub-optimal control in the preceding section involving a blend chest and machine chest, amongst other items, where several pulp streams and dilution water are combined. A number of control loops are involved, but appear to require different tuning for different paper grades. Often individual loops are taken off-line. In this study, an understanding of the controller interactions in the stock preparation section has been developed by detailed dynamic modelling, including all of the existing control loops. The model is built up in a modular fashion using a basic element, having one input (which can collect multiple streams originating elsewhere) and four outputs, linked through a vessel of variable volume. Several basic elements are linked together to form the overall system. All of the necessary properties can be defined so that the model allows the simulation of all features of the network: vessels, pipes, junctions, valves, levels and consistencies. A set of first order differential equations is solved which includes total water balance, species mass balances, derivatives of flow controller action, and derivatives of supervisory controller action. Supervisory controllers for consistency or level cascade onto flow controllers. Flow controllers manipulate valves which give a first-order dynamic response of actual flow. Where valves are manipulated directly by the supervisory level, the flow controller is effectively bypassed. This study involves a constraint problem around the blend chest, resulting in a loss of specification at the paper machine. This was solved by the implementation of a static optimiser. Its objective function penalizes deviations from setpoint of five parameters (ratios, consistency and level) using respective weight factors. Both the model and its optimiser were included in a simulator designed with the graphical user interface (GUI) of Matlab. The simulator has then been used to explore control performance over the operating range, by means of a set of scenarios

Techno-economic evaluation of battery storage systems in industry

In the context of a changing energy system towards one dominated by renewable energy sources, the demand for flexible energy generation and consumption will increase. Battery storage systems can provide a significant share of this energy flexibility, especially when combined with an industrial manufacturing plant to shift the industrial electricity demand over time. This paper contributes to a better understanding of the business decision when investing in a battery storage system and when marketing energy flexibility. For this purpose, the work considers the techno-economic and regulatory framework for flexibility measures and examines the optimal investment and dispatch planning for a battery storage system in an industrial company. The studies in this thesis focus on three central aspects. As a first aspect, the various revenue streams for the stored electricity are analysed and how these influence the profitability of a battery storage system. In particular, the provision of frequency containment reserve power, peak load shifting or peak shaving, arbitrage trading on the energy markets and the increase in self-consumption through photovoltaic self-generation are addressed. For this purpose, an optimisation model is formulated as a discrete, linear programme that maps the economic framework of the flexibility markets and integrates the technological constraints of the battery storage system. As a second aspect, uncertainties about market prices, load and generation behaviour are integrated into the optimisation model and the influence on the investment decision is investigated. This is done on the one hand by a two-stage robust optimisation model, which represents the uncertainty about the market success on the intraday market. On the other hand, the significance of the sequence of uncertain market decisions is illuminated through a multi-stage stochastic optimisation model. As a third aspect, the trade-off between the economic and ecological use of a battery storage system is analysed. For this purpose, an ecological, CO₂-minimal dispatch is calculated by deriving national CO₂-emission factors and compared with an economically optimal dispatch. The case studies are analysed based on real industrial load data from small, medium and large enterprises. The thesis discusses the technical and economic framework conditions, with the main focus on Germany. However, a comparison between the countries Germany, Denmark, and Croatia is also presented. The results show that peak shaving and the provision of frequency containment reserve are complementary and make the investment in a battery storage system economically viable. Self-generation through a photovoltaic system can reduce the risk arising from uncertain energy market prices. However, the sequence of uncertain decisions has a significant impact on the design of the battery storage system. Economically feasible operation through arbitrage trading, on the other hand, is not possible due to the small price differences in the markets and limitations due to battery ageing and efficiency. These battery characteristics also influence the use of a battery storage system for CO₂-reduction. Due to the limited number of cycles and relatively high charging losses, battery technology is currently unsuitable for CO₂-minimal storage use. Nevertheless, the economic and ecological potential of battery storage systems strongly depends on individual factors such as local grid charges, the selected battery technology and the individual industrial load profile. Advances in battery technology, such as increased lifetime, and possible new flexibility markets, such as dynamic grid charges, offer new application and marketing opportunities that could increase the economic viability of a battery storage system

Systems Analysis in Forestry and Forest Industries

The purpose of this book is to present a variety of articles revealing the state of the art of applications of systems analysis techniques to problems of the forest sector. Such applications cover a vast range of issues in forestry and the forest industry. They include the dynamics of the forest ecosystem, optimal forest management, the roundwood market, forest industrial strategy, regional and national forest sector policy as well as international trade in forest products. Forest industrial applications at mill level, such as optimal paper trimming, cutting, and production scheduling, are however, excluded