Design and development of a sustainability toolkit for simulation modeling and analysis

A simulation-based sustainability toolkit is developed in this research, in order to efficiently provide the capability of modeling and evaluating the sustainability related performance measures in systems of interest. As sustainability related issues, such as energy consumption, emissions, and waste generation are becoming a more integrated part of operational and long-term planning decisions, simulation modeling is needed to analyze the system performance not only from the traditional system performance measures such as productivity and efficiency, but also taking into account the environmental impacts within the studied system in order to aid in decision-making. This research introduces the concept and general methodology to develop such a sustainability toolkit for simulation and provides a prototype implementation of the toolkit using commercially available discrete event simulation software. In particular, toolkit modules have been developed for modeling and evaluating the sustainability aspects of transportation and logistics systems, industrial and manufacturing processes, and warehouse material handling systems. Furthermore, general sustainability toolkit modules are constructed to model other systems of interest. The toolkit contains a flexible framework which enables the simulation modeling and analysis of the sustainability related performance measures as easily as traditional system performance measures. The toolkit will enable the users to efficiently simulate complex systems taking into account system sustainability in an integrated decision-making process

An effective uncertainty based framework for sustainable industrial product-service system transformation

Industrial Product-Service Systems (IPS2) can provide insights to enhance the environmental sustainability and lower environmental impact. However, its successful realisation for preventing the production of waste, while increasing efficiencies in the uses of energy and human capital remains a highly convoluted problem. This research article aims to address this issue by presenting an innovative uncertainty-based framework that can be used to assist in achieving increased sustainability within the context of IPS2. The developed framework explains the drivers for decision-making and cost to enable sustainability improvements in transforming to industrial services. This is based on academic literature, and multiple case studies of seven industrial companies with over 30 h of semi-structured interviews. The validation of the framework through two case studies demonstrates that uncertainty management can enable resource efficiency and offer sustainable transformation to service provision

Smart supply chain management in Industry 4.0

The emerging information and communication technologies (ICT) related to Industry 4.0 play a critical role to enhance supply chain performance. Employing the smart technologies has led to so-called smart supply chains. Understanding how Industry 4.0 and related ICT affect smart supply chains and how smart supply chains evolve with the support of the advanced technologies are vital to practical and academic communities. Existing review works on smart supply chains with ICT mainly rely on the academic literature alone. This paper presents an integrated approach to explore the effects of Industry 4.0 and related ICT on smart supply chains, by combining introduction of the current national strategies in North America, the research status analysis on ICT assisted supply chains from the major North American national research councils, and a systematic literature review of the subject. Besides, we introduce a smart supply chain hierarchical framework with multi-level intelligence. Furthermore, the challenges faced by supply chains under Industry 4.0 and future research directions are discussed as well

Decision theory in sustainable supply chain management: a literature review

Purpose – This study aims to aid theory building, the use of decision theory (DT) concepts in sustainable supply chain management (SSCM) research is examined. Design/methodology/approach – An abductive approach considers two DT concepts, Snowden’s Cynefin framework for sense-making and Keeney’s value-focussed decision analysis, in a systematic literature review of 160 peer-reviewed papers in English. Findings – Around 60 per cent of the papers on decision-making in SSCM come from operational research (OR), which makes explicit use of DT. These are almost all normative and rationalist and focussed on structured decision contexts. Some exceptions seek to address unstructured decision contexts via Complex Adaptive Systems or Soft Systems Methodology. Meanwhile, a second set, around 16 per cent, comes from business ethics and are empirical, behavioural decision research. Although this set does not explicitly refer to DT, the empirical evidence here supports Keeney’s value-focussed analysis. Research limitations/implications – There is potential for theory building in SSCM using DT, but the research only addresses SSCM research (including corporate responsibility and ethics) and not DT in SCM or wider sustainable development research. Practical implications – Use of particular decision analysis methods for SSCM may be improved by better understanding different decision contexts. Social implications – The research shows potential synthesis with ethical DT absent from DT and SCM research. Originality/value – Empirical behavioural decision analysis for SSCM is considered alongside normative, rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM. Originality/value – Empirical, behavioural decision analysis for SSCM is considered alongside normative rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM

Design of biomass value chains that are synergistic with the food-energy-water nexus: strategies and opportunities

Humanity’s future sustainable supply of energy, fuels and materials is aiming towards renewable sources such as biomass. Several studies on biomass value chains (BVCs) have demonstrated the feasibility of biomass in replacing fossil fuels. However, many of the activities along the chain can disrupt the food–energy–water (FEW) nexus given that these resource systems have been ever more interlinked due to increased global population and urbanisation. Essentially, the design of BVCs has to integrate the systems-thinking approach of the FEW nexus; such that, existing concerns on food, water and energy security, as well as the interactions of the BVCs with the nexus, can be incorporated in future policies. To date, there has been little to no literature that captures the synergistic opportunities between BVCs and the FEW nexus. This paper presents the first survey of process systems engineering approaches for the design of BVCs, focusing on whether and how these approaches considered synergies with the FEW nexus. Among the surveyed mathematical models, the approaches include multi-stage supply chain, temporal and spatial integration, multi-objective optimisation and uncertainty-based risk management. Although the majority of current studies are more focused on the economic impacts of BVCs, the mathematical tools can be remarkably useful in addressing critical sustainability issues in BVCs. Thus, future research directions must capture the details of food–energy–water interactions with the BVCs, together with the development of more insightful multi-scale, multi-stage, multi-objective and uncertainty-based approaches