The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Optimal scope of supply chain network & operations design

The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are significant and that has attracted considerable research attention since the late 1990s. This doctoral thesis focuses on developing manageable and realistic optimization models for solving four contemporary and interrelated supply chain network and operations design problems. Each requires an integrated decision-making approach for advancing supply chain effectiveness and efficiency. The first model formulates the strategic robust downsizing of a global supply chain network, which requires an integrated decision-making on resource allocation and network reconfiguration, given certain financial constraints. The second model also looks at the strategic supply chain downsizing problem but extends the first model to include product portfolio selection as a downsizing decision. The third model concerns the redesign of a warranty distribution network, which requires an integrated decision-making on strategic network redesign and tactical recovery process redesign. The fourth model simultaneously determines the operational-level decisions on job assignment and process sequence in order to improve the total throughput of a production facility unit

An Experimental Research on Closed Loop Supply Chain Management with Internet of Things

Abstract. Closed loop supply chain (CLSC) optimization is integration of forward and reverse logistics activities. The importance of CLSC management is increasing by legal regulations, limited energy resources and environmental- financial problems that growing in recent years. However, reverse logistics part of the CLSC is a flow type which is more difficult to made predictions, planning and controls by reason contained uncertainties. This stage, Internet of Things system reduces related uncertainties by providing all the life information of the returned product and substantially attenuates planning of reverse flow activities. In this study, a CLSC is considered that meets demands of the sales&collection center both new and remanufactured product. Manufacturer has three options (refurbishing, disassembly and disposal) to assessing returned products. A mixed integer linear programming model is proposed for a single type of product is completely modular (automobile, computer, telephone, etc.). The model meets customer's products and components demands based period, maximizes profit consist of different sales revenues and total cost (total production, purchase, transportation and disposal costs) and determines how to evaluate all returned products. The proposed model has been verified with the aid of a numerical example by solving in GAMS software and its performance reviewed with experimental studies.Keywords. Closed loop supply chain optimization, Internet of Things, Mixedinteger linear programming, Returned product management.JEL. L80, L86, Q55

Facility location decisions within integrated forward/reverse logistics under uncertainty

In this paper, a stochastic mixed integer linear programming (SMILP) model is proposed to optimize the location and size of facilities and service centres in integrated forward and reverse streams under uncertainty. The objective of the model is to minimize establishment, transportation and inventory management costs and simultaneously maximize customer satisfaction with sustainable perspective. The model incorporates different elements and features of distribution networks including inventory management, transportation and establishment of new facilities as well as existing centres. The presented model is the streamlined approach for multi-objective, multi-period, multi-commodity distribution system, and it is supported by a real case study in automobile after sales network. Genetic algorithm is implemented to solve the model in reasonable time. The performance of the model and the effects of uncertainty on provided solution are studied under different cases. Competitive result of the stochastic model compared to deterministic model ensures that the proposed approach is valid to be applied for decision making under uncertainty.Scopu

Supply chain network design models for a circular economy: a review and a case study assessment

Global supply chains are getting increasingly dispersed, and hence, more complex. This has also made them more vulnerable to disruptions and risks. As a result, there is a constant need to reconfigure/redesign them to ensure competitiveness. However, the relevant aspects/facets for doing so are fragmented and scattered across the literature. This study reviews the literature to develop a holistic understanding of the key considerations (environment, cost, efficiency, and risks) in designing/redesigning global supply chains. This understanding is then applied to assess the global supply chain network of a leading multinational tire manufacturing firm; also to provide recommendations on redesigning it. The study has significant practical and research implications for global supply chain management

A Review on the Lifecycle Strategies Enhancing Remanufacturing

Remanufacturing is a domain that has increasingly been exploited during recent years due to its numerous advantages and the increasing need for society to promote a circular economy leading to sustainability. Remanufacturing is one of the main end-of-life (EoL) options that can lead to a circular economy. There is therefore a strong need to prioritize this option over other available options at the end-of-life stage of a product because it is the only recovery option that maintains the same quality as that of a new product. This review focuses on the different lifecycle strategies that can help improve remanufacturing; in other words, the various strategies prior to, during or after the end-of-life of a product that can increase the chances of that product being remanufactured rather than being recycled or disposed of after its end-of-use. The emergence of the fourth industrial revolution, also known as industry 4.0 (I4.0), will help enhance data acquisition and sharing between different stages in the supply chain, as well boost smart remanufacturing techniques. This review examines how strategies like design for remanufacturing (DfRem), remaining useful life (RUL), product service system (PSS), closed-loop supply chain (CLSC), smart remanufacturing, EoL product collection and reverse logistics (RL) can enhance remanufacturing. We should bear in mind that not all products can be remanufactured, so other options are also considered. This review mainly focuses on products that can be remanufactured. For this review, we used 181 research papers from three databases; Science Direct, Web of Science and Scopus

Selection of return channels and recovery options for used products

Due to legal, economic and socio-environmental factors, reverse logistics practices and extended producer responsibility have developed into a necessity in many countries. The end results and expectations may differ, but the motivation remains the same. Two significant components in a reverse logistics system -product recovery options and return channels - are the focus of this thesis. The two main issues examined are allocation of the returned products to recovery options, and selection of the collection methods for product returns. The initial segment of this thesis involves the formulation of a linear programming model to determine the optimal allocation of returned products differing in quality to specific recovery options. This model paves the way for a study on the effects of flexibility on product recovery allocation. A computational example utilising experimental data was presented to demonstrate the viability of the proposed model. The results revealed that in comparison to a fixed match between product qualities and recovery options, the product recovery operation appeared to be more profitable with a flexible allocation. The second segment of this thesis addresses the methods employed for the initial collection of returned products. A mixed integer nonlinear programming model was developed to facilitate the selection of optimal collection methods for these products. This integrated model takes three different initial collection methods into consideration. The model is used to solve an illustrative example optimally. However, as the complexity of the issue renders this process ineffective in the face of larger problems, the Lagrangian relaxation method was proposed to generate feasible solutions within reasonable computational times. This method was put to the test and the results were found to be encouraging

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