Search

Chemical process manufacturing is associated with risks, which cannot be eliminated. Anyhow, controlling or minimizing of risks is possible up to a certain extent through various process safety strategies. Among these strategies, the inherent approach offers a sustainable process design. This review aims to offer an extensive survey regarding the bibliometrics and the features of the state-of-the-art inherent assessment methods. For the bibliometric part, numerous trends like publication trend, authors and geographical cooperation and prominent keywords are presented using the VOSviewer software. For the second intention, the scope and features of inherent assessments methods for sustainable process design are discussed in addition to the historical development of these methods. The techniques are categorized among seven groups based on the method adopted for inherent assessment along with the benefits and detriments of each group. It is revealed that initially, the inherent assessment has focused on the comparison of various process routes, whereas, the modern methods intend to minimize the risk. Furthermore, it is recognized that the process equipment approach is not much explored yet, which may improve the sustainable process designing via the equipment characteristics. Finally, the limitations of present schemes and future research directions for inherent assessment implications in the sustainable process design are also highlighted, such that the objectives of economic, healthier, safer and environmental-friendly process plants can be materialized. © 2019 Elsevier Ltd

Management of defectives and carbon-emissions are prominent inefficiencies identified by the environmental accounting practitioners. Minimizing these inadequacies within a supply chain through careful management strategies translates it reliably into a green system rationally. The concept of defect management is a recent trend in various industries as it aids in the better management of the products by giving them a new horizon through various operations. With such incentives, a vendor-buyer inventory strategy is formulated for an imperfect manufacturing process considering carbon-emissions and defect management. A certain proportion of defectives are produced by the vendor which undergo inspection at the buyer's domain. The secluded defectives are returned by the buyer to the vendor for which the latter incurs a warranty cost. Instead of adopting the traditional approaches of handling defectives, the vendor prefers to invest in a strong inspection which classifies the defectives into three categories viz. repairable, non-repairable, and design flawed ones. Such an approach aids in fetching profits and reducing waste thereby contributing towards a greener environment economically. The vendor also considers carbon-emission costs due to transportation and waste disposals as a step towards sustainability. The paper develops two models, the first model discusses the integrated problem-solving approach and the second one uses the Stackelberg policy. The total profit is maximized by jointly optimizing the number of shipments, order quantity and backordering quantity. Numerical analysis and sensitivity analysis is performed to establish the validity and robustness of the developed study. Findings suggest better performance of the integrated model over the Stackelberg game model. Moreover, the study highlights the significance of defect management so as to achieve sustainability goals without compromising financial objectives.

In this paper, we propose a framework to analyse the setting up of an industrial symbiosis system. The establishment of such a system entails implementation of expensive technologies by the companies so as to convert wastes into energy and other mutually beneficial materials. Much of the literature on modeling industrial symbiosis do not consider this important aspect of high conversion costs. Further, such a cooperative effort will be sustainable only if the high cost of implementing technologies is compensated by sharing of the benefits in a fair and satisfactory manner. Towards this end, first at a general level, we addres the issue of the optimal design of an industrial symbiosis network of companies in a given region. The materials processing rates depend on the choice of the new technology. We first propose an optimal control problem to determine the best choice of technology for the companies. Then, we recommend the nucleolus-based cooperative game theory approach to determine the best share of the benefits among the participating companies as this method minimizes the unhappiness of the members. A hypothetical numerical example of three companies is provided to illustrate the model. Each company has a choice of 3 technology options. The planning horizon is assumed to be 5 years. The numerical example brings out clearly the benefit of cooperation. The benefit of by-product synergy is that companies 1, 2 and 3 can realize an increase in their NPVs by 44%, 33% and 21% respectively. The nucleolus based sharing of NPVs guarantees the acceptance by companies of the distribution of the additional profits.

As the product environmental footprint (PEF) has a profound impact on the environmental sustainability, it is crucial to estimate PEF in the product life cycle. The existing researches lack the prescriptiveness and environmental footprint-specific accounting guidance to produce consistent PEF, thus most of the existing PEF models fail for product life cycle. The paper is devoted to PEF assessment for product life cycle. After the introduction of PEF, the calculation model for each of the 14 kinds of PEF is proposed. PEF assessment process is then put forward in detail, which includes 10 steps, i.e. functional unit selection, system boundary determination, impact types selection, data collection, impact types classification, impact types characterization, impact types of PEF calculation, impact types standardization, impact types grouping and weighting, PEF assessment result. PEF assessment process of an agricultural picking robot is used to demonstrate the effectiveness of the proposed methodology.

© 2019 Elsevier Ltd Improved sustainability of industrial activities and measurement of its performance are becoming prime topics of discussion among policy-makers and industrial decision-makers. The current literature proposes a number of performance measurement systems and related indicators, but mainly lacks a real capability to address all sustainability pillars and their intersections, as well as scalability to firms of different sizes, availability of internal resources, and maturity over sustainability issues, suggesting that further research is needed in this area. Building on the literature, our work develops a new framework for the evaluation of industrial sustainability performance, proposing three different Industrial Sustainability Performance Measurement Systems (ISPMSs), with a decreasing number of indicators suitable in different contexts of application. In the framework, selection mechanisms have been conceived and used to reduce the number of indicators considered, while still guaranteeing complete and adequate coverage of all sustainability pillars, as well as their intersections. The framework has been tested through semi-structured case studies in heterogeneous Northern Italian manufacturing firms. The preliminary results are sound as the different ISPMSs proved to be complete, useful, and easy to use. The proposed ISPMSs provide industrial decision-makers with a scalable framework applicable in different contexts, allowing benchmarking and development of specific implementation strategies for increased sustainability, and provide policy-makers with a framework to develop a more effective regulatory policy, better understanding how sustainability performance can be addressed in an integrated manner across industrial firms.

In design, most of recent researches focused on criteria related only to the product. These criteria do not take into account the context of the organization which is related to the enterprise's system. In sustainable design, the choice of the best product design scenario is more complex. In fact, the number of issues is importantly high, the data is imprecise and the criteria are interdependent. This situation is more critical in an advanced stage of the design process where the decisions and choices will monitor the next steps of this process. The purpose of this paper is to improve the design approaches in a critical stage from an environmental, economic and social perspective. It deals with two main challenges, the first one is the identification of product design scenarios that are coherent with the organization's context, in terms of internal and external issues along with requirements of the stakeholders. The second challenge is the selection of the optimal option from a high number of identified scenarios. To this end, a new model with two main steps is proposed to deal with both challenges. The methodology is based on two steps. The first depends on a trilogy (i.e. Strategic, tactical, and operational). It generates operational scenarios on the basis of value chain-driven sustainable design strategies using SWOT (Strengths, Weakness, Opportunity, Threats), PESTEL (Political, Economic, Social, Technological, Environmental, Legal), 7S (Structure, Strategy, Shared Values, Style, Staff, Systems, Skills) to identify a multitude of scenarios. The second step is the choice of the optimal scenario that satisfies interdependent criteria using simplified life cycle assessment tools to compute sustainability impacts' indicators, the Choquet integral to minimize the number of scenarios, and the fuzzy analytic network process to select the optimal operational scenario. The proposed model is then implemented in a Tunisian company that manufactures lead acid batteries for motorcycles. The results proved the influence of the organization's context on the choice of the optimal sustainable design scenario. The organization was able to develop strategies and tactics on the basis of its strengths, weaknesses, threats and opportunities. The number of design alternatives was reduced using relevance checks based on influence and control criteria. Environmental, economic and social indicators were computed per life cycle phase in order to be used as inputs in the Choquet integral and the analytic network process algorithms. The proposed model guided the organization to adopt a coherent design scenario that respects the sustainable development criteria.

Risk management in supply chains has emerged as one of the most attractive research topics in the supply chain management field. However, much more is still needed towards hedging against environmental risks. The recent environmental scandals and accidents bring to light the negligence of the environmental issues by supply chains. The present study analyses both external and internal factors of environmental risk and their impact on supply chain management, as well as the mitigation strategies through the literature study. Thus, by conducting a systematic literature review and after analysing 767 abstracts and 70 full papers, we identify fourteen environmental risks, three main consequences and nineteen strategies to manage these risks. As a result, we develop an Environmental Supply Chain Risk Management taxonomy, which covers the existing body of knowledge on the topic. Moreover, a framework is also proposed to synthesise and relate the environmental risks, consequences and strategies covered by the academic research. Finally, we provide a research agenda to support future works on environmental supply chain risk management, building foundations towards the formalisation and improvement of the field.

Organizations usually confront with disruptive incidents which have widespread negative effects on their performance. The ability of an organization to reduce the losses caused by these incidents is referred to economic resilience. Economic resilience is a concept that can improve the performance of an organization during crises. Petrochemical industry is a strategic industry. Any interruption in its operation can result in enormous cost and environmental hazards. Therefore, it is important to make it resilient against incidents to ensure sustainability objectives. In this research, the performance of a petrochemical plant is investigated in case of a crisis. At first, based on a comprehensive literature review, a conceptual framework for organizational economic resilience is developed. A structured questionnaire is provided and distributed among the staff of a petrochemical plant as a real case study. Then, due to the uncertain nature of incidents, three uncertain Data Envelopment Analysis (DEA) models are employed to identify the efficient units of the petrochemical plant. At the end, a sensitivity analysis is performed to examine the importance of each factor in building economic resilience in the plant. Results show that preparedness and planning, properties and resourcefulness, and collateral pathways and redundancy are the most important economic resilient factors for this specific petrochemical plant. This is the first study that presents an integrated qualitative-quantitative approach including a conceptual framework for economic resilience and a DEA model in uncertain conditions in the whole supply chain of a petrochemical plant. This proposed approach can be used for all types of industrial organizations to improve their performance during the crisis. The proposed approach can help managers to understand the situation of their organization with respect to the economic resilience factors, comprehensively. Furthermore, the results help managers to strengthen their potential economic resilience against the crisis for sustainability.

A sustainable construction ought to enhance the quality of social, economic and environmental practices by determining the current sustainability level and identifying the weak points and consequently improving them. Even though so many studies have been carried out the context of economic and environments in construction projects, less attention was always paid to the social aspect of the construction projects. In this article, a novel construction social sustainability performance evaluation is presented based on fuzzy logic to evaluate the current social sustainability status in associated construction. This study originally adds to the state-of-the-art literature on sustainable construction by articulating a proposal and applications of a new as fuzzy construction social sustainability index. Critical social sustainability attributes are collected from the literature review and expert's judgments to address main dimensions and enablers of construction projects. The proposed index is validated by both triangular fuzzy and crisp approaches, and the results showed that all approaches lead to the same conclusions. Fuzzy performance importance index is then obtained and ranked for all attributes to identify obstacles and challenges behind the social sustainable construction concept. The scientific value of the proposed model is determined by its proper contribution in computing the new index with trapezoidal fuzzy principles and identifying the obstacles of associated construction.

Life Cycle Assessment (LCA) is a widely-used methodology for estimating the potential environmental impacts of technological systems in nature. Relative maturity of this method has been achieved thanks to recent standardization efforts, although there are still several challenges, particularly in the minerals industry where LCA still needs to be strengthened and extended in use. An exhaustive review of recent LCA studies on mining and mineral processing operations was conducted to identify how these have dealt with various methodological challenges. A total of twenty-nine studies were found, most of which focusing on developed regions and in three commodities: coal (28%), aggregates (21%), and copper ores (14%). The source of data for background processes has been the Ecoinvent database in 45% of the studies analyzed, whereas the SimaPro software has been the preferred LCA tool in 66% of such studies. Although important advances have been made, significant issues remain. For instance, inconsistencies were found in the definition of the functional unit and system boundaries (temporal and technological). Further, the adoption of allocation criteria and the use of normalization and weighting in impact assessment have not been considered in most cases. While climate change was the main environmental hotspot (more than 90% of the studies addressed this impact category), the impacts associated with water use and waste management have been overlooked in most studies. Furthermore, mining and processing operations have been described as generic, averaged values or as simple functional relationships between system inputs and outputs using parameters without physical significance (“black box models”) in several production chains, making it difficult to identify opportunities for environmental sustainability enhancement within the sector. The work then discusses the opportunity of improvement in LCA in the minerals industry through the incorporation of process simulation from a bottom-up perspective. Evidence from other industries and recent advances in the computational development of such tools for the mineral sector are reviewed, which suggests that there is an opportunity for reducing the epistemic uncertainty in future LCA studies of mining and processing operations through the combination of both approaches.

This technical note discusses the synergetic attributes of four emerging technologies that have significant potentials to enhance smart and sustainable urban mobility, and ultimately improve urban sustainability. Shared mobility, wireless charging, vehicle-to-grid (V2G) integration, and vehicle automation have complementary features that rectify the practical barriers and implementation restrictions of each other. We attempt to bridge between transportation research studies and the environmental sustainability community, discuss the recent findings, and identify critical knowledge gaps to better understand the synergies and mutual benefits of these emerging technologies and avoid unintended environmental consequences.

The importance of remanufacturing has been increasing since stricter regulations on protecting the environment were enforced. Remanufacturing is considered as the main means of retaining value from used products and components in order to drive a circular economy. However, it is more complex than traditional manufacturing due to the uncertainties associated with the quality, quantities and return timing of used products and components. Over the past few years, various methods of optimising remanufacturing outcomes have been developed to make decisions such as identifying the best End-Of-Life (EOL) options, acquiring the right amounts of cores, deciding the most suitable disassembly level, applying suitable cleaning techniques, and considering product commonality across different product families. A decision being made at one remanufacturing activity will greatly affect the decisions at subsequent activities, which will affect remanufacturing outcomes, i.e. productivity, economic performance effectiveness, and the proportion of core that can be salvaged. Therefore, a holistic way of integrating different decisions over multiple remanufacturing activities is needed to improve remanufacturing outcomes, which is a major knowledge gap. This paper reviews current remanufacturing practice in order to highlight both the challenges and opportunities, and more importantly, offers useful insights on how such a knowledge gap can be bridged.

As a new cleaner man-powered product service system, bikesharing could make full use of idle bicycles, reduce traffic congestion and environmental pollution, so it contributes to develop eco-friendly urban transport system and thus has a significant increase in number and scope. However, one of the most critical issues in many Chinese bikesharing systems is the overuse, inspired by the development history of three generations of bikesharing systems worldwide, we involve various management modes to deal with the overuse problem. The paper firstly carries out the game theory analyses about three generations of bikesharing systems, and concludes that (1) the overuse will occur if adopting the management modes in the first- and second-generations (i.e. no fee with no restrictions and no fee with restrictions), or one kind in the third-generation (i.e. a low fee with few restrictions); (2) the overuse can be controlled effectively by the mode of a low fee with strict restrictions or a high fee management mode in the third-generation. Finally, under the context of Chinese bikesharing systems, these analyses results can help to design some feasible strategies to mitigate or prevent the overuse problem.

Run-of-river hydroelectric plants along Amazon River tributaries have been shown to be an ecologically viable alternative to meet Brazilian energy demand. These plants are a solution to add capacity. However, due to geographic and socioeconomic characteristics of this region, there are risks that cannot be disregarded. This study reports the application of multi-criteria analysis to identify risk events for the Santo Antonio Hydroelectric Plant under construction, related to service packs relevant to the project. The choice of the appropriate technique took into consideration the imprecision of subjective judgment. The fuzzy analytic hierarchy process (FAHP) enabled inserting a measure of inaccuracy, represented by the degree of fuzziness, assigned to each pairwise comparison. Fuzziness was incorporated into the process by means of a triangular membership function. The convergence of opinion was assessed by comparing the hierarchical order of the perceived risks identified by two distinct groups, the owner consortium, and the builder consortium. These groups have similar risk perceptions, despite having different roles and asymmetric risk sharing caused mainly by the characteristics and provisions contained in the engineering, procurement and construction (EPC) contract. The model was efficient in ranking the risk events from the perspective of the two groups, therefore constituting a rational and transparent approach for risk management in large projects.

In spite of good coverage of sustainability and sustainable development both in scientific journals and other publications, humanity is on a steady unsustainable track consuming more than is produced. Understanding of change needs, does not seem to convert into sufficient change action. Sustainability issues are often complex, interdependent and hard to comprehend, indicating that sustainable development, in addition to change willingness, requires a holistic perspective. Seeing and understanding systems - systems thinking - is important. This implies that sense-making of systems and of sustainable development is important as a prerequisite for change. Possibilities of realising synergies between quality management and sustainable development are often discussed but do often not seem to be fully realised. This paper tests two system models from Quality Management in the context of sustainability in cement manufacturing and building material production. The indicative results suggest that the proposed system models are able to describe and identify improvement opportunities that could be used to create interest for change.

Manufacturers are today striving to offer value-added Product Service System (PSS) with the purpose of achieving higher competiveness and more environmental benefits. Requirement elicitation and evaluation with sustainability concerns play a key role in a successful development of sustainable PSS. However, the previous literature rarely address the PSS requirement from the view of sustainability, while mainly focusing on the customer satisfaction. To accurately identify the requirement with respect to sustainable value from a long term perspective, it is necessary to develop effective methods for requirement elicitation for sustainable PSS. In addition, the prioritization of sustainable value requirement provides critical guidance for the later PSS design. The prioritization involves much judgement ambiguousness and diversity which may lead to inaccurate requirement analysis result. However, there are few researches on combinatory manipulation of the vagueness and diversity. Therefore, to solve these problems, an innovative methodology incorporating requirement elicitation and evaluation is developed for sustainable PSS. This study introduces the concept of value uncaptured into the identification of product value state, and offers the Product Value State Model (PVSM) method to elicit value requirements which help PSS deliver more sustainability. Moreover, a hybrid model for evaluating the sustainable value requirement is proposed by combining the fuzzy set, rough set, Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) methods. An application in an excavator PSS and the comparisons with some different methods demonstrate the feasibility and potential of the methodology. Theoretically, the proposed evaluation model provides more accurate and realistic analysis results of PSS requirements compared to traditional methods, since it supports to simultaneously manipulate judgement vagueness, group decision diversity, and complex interrelationship. In practical PSS design, the method helps PSS designers successfully recognize the most key value requirements with both respect of sustainability and customer satisfaction.

A Since construction is considered a high waste-generating industry, research and business strategies in this field are continuously expending efforts to reduce tangible material wastes and emissions. Yet, these efforts have neglected intangible resource wastes which are equally important and critical such as those produced by improper capacity planning. Capacity planning is a vital process within construction planning that aims at matching capacity (available resources) with demand (forecasted workload) to achieve planning reliability and prevent unnecessary resource waste. However, existing construction studies and practices do not emphasize capacity planning nor do they provide clear measurement frameworks for assessing its impacts on workflow and waste generation. Therefore, the purpose of this study is to highlight the importance of capacity planning by developing new metrics that help provide a holistic understanding and visualization of capacity planning performance and provide feedback for future capacity planning adjustments. The developed metrics were then empirically applied on two well managed projects in the United States. The resulting trends reveal a mismatch problem between load and capacity resulting in wasted resources due to poor allocation strategies that negatively impacted project performance. Moreover, the findings emphasize the need for dynamic evaluation and control of capacity planning performance within project teams. This research contributes novel metrics aimed towards comprehending the underlying mechanisms that shape capacity planning and aims at guiding project teams to achieve more sustainable production flows through quantitative evaluations and adjustments.

With the increased sustainable awareness and pressures from stakeholders, enterprises have realized the importance to implement sustainable supply chain management (SSCM) practices to pursue economic, environmental, and social benefits. In this paper, a novel framework is proposed, which identifies SSCM practices as the evaluation criteria for supplier evaluation. Because vague and subjective information often exists in decision-making of supplier evaluation, fuzzy-based approaches are frequently used to manipulate such vagueness and subjectivity. However, the previous fuzzy methods do not consider randomness in decision making and they require prior information. Thus, an extended TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method is developed in this paper for sustainable supplier selection, which integrates the advantage of cloud model theory in manipulating uncertainty of randomness (intrapersonal uncertainty) and the merit of rough set theory in flexibly handling interpersonal uncertainty without extra information. Additionally, an integrated weighting method considering both subjective and objective weights is proposed to determine comprehensive weights of criteria. Finally, a case study of sustainable photovoltaic modules supplier selection is conducted to show the effectiveness of the proposed method.

The discussion regarding product circularity is often framed from a production and business model perspective. In this paper, people's consumption processes are taken as a new point of departure and a re-framing of product circularity from a user perspective is proposed to complement the current narrative. This user-centred perspective emphasises the importance of product exchange, which underscores that products can be transferred in tight loops from one user to another, i.e. from Use to Use. It also highlights a number of challenges and practicalities that circular paths of consumption may entail for people in everyday life, and thus points to new opportunities for designing products and services that can create enabling preconditions that make it possible, more convenient, and more preferable for people to circulate products. These design opportunities can be categorised into four design strategies that can support the development of products and services fit for circular consumption processes. How the proposed reframing compares to the current narrative is discussed and recommendations for future research are proposed.

The European Waste Electrical and Electronic Equipment system introduced measures to encourage both the reduction of the amount of electronic waste and its separation to prepare for reuse. The aim of this study is compare the environmental performance, cost externality and job creation of the whole life cycle of new and reconditioned electrical and electronic equipment by adopting Life Cycle Assessment methodology. Five electrical and electronic equipment categories were investigated and the data collection was made on an Italian context. The refurbishing of breakdown electrical and electronic equipment was assessed by considering different sets of faulty components (Scenario A and B) and a total of 25 scenarios were studied. Moreover, both attributional and consequential life cycle inventory modelling framework were adopted to represent the investigated scenarios. The outcomes highlighted that the preparation for reuse process leads to obtaining a sustainable electronic device than the new one, depending on which set of components are replaced. Adopting Scenario B with the attributional model, the environmental damage of reconditioned electrical and electronic equipment decreases compared to the new one. Conversely, the consequential approach determines an environmental credit for all repaired electronic devices except for one category; in particular, Scenario A produced the largest environmental advantage. The analyses of external costs and social aspects confirm that the preparation for reuse activity allows to obtain a more sustainable product than a new one. For these two latter aspects, the results showed a turnaround passing from attributional model to consequential one. Noting the variability in results adopting both different life cycle inventory modelling framework and set of replaced components, the Life Cycle Assessment practitioner, that conducted the study, should help the decision-makers to determine which scenario is more sustainable accomplishing an adequate choice.

Amidst growing environmental challenges and increasing penetration of sustainable energy production, the development of efficient energy storage system (EES) is indispensable to fully benefit from the use of intermittent renewable energy sources. Although lithium-ion batteries (LIBs) have been the dominant energy storage technology for applications in consumer electronics, electrified transportation and stationary electricity storage, further technological progress is required for achieving the climate protection objectives. In this context, continuous exploration of new technological opportunities is favorable to advance the global energy transition towards sustainability to success. To facilitate such progress and to avoid potential technological lock-in situation, understanding the underlying latent knowledge construct revealed in patents may prove beneficial. However, previous studies have either focused on analyzing the technological improvements along a particular development path or emphasizing the necessity for improvements in environmental-economic dimensions. Accordingly, a novel patent-based analysis framework is proposed to obtain an inclusive view on the continuing path of technology development concerning the research of LIBs as well as to predict its future development potential based on two machine learning algorithms: Principal component analysis (PCA) and random forest classifier (RFC). In this study, PCA is firstly applied to group various knowledge areas into key technological knowledge stocks. Building upon these results, RFC is adopted to forecast the future developmental potential of technological knowledge areas. The findings show that the research landscape of LIBs is a dynamic environment where new knowledge stocks emerged overtime and the identified knowledge stocks within a defined time interval play an orchestrating role in the advancement of lithium-ion battery technology. In particular, knowledge stocks related to battery management system and hybrid capacitors have gained relevance. The proposed analysis framework can be used to track the past chronology of knowledge accumulation trajectory and can proactively enhance the knowledge management capabilities of experts, who wish to create a path towards a low-carbon economy.

Noise pollution from construction activities is a major factor jeopardizing occupational health as well as human living environments. However, previous research mainly focused on reducing noise pollution surrounding sensitive buildings off site rather than for on-site workers. Moreover, currently available noise mitigating methods tend to be passive and accompanied by significant additional expenditures. As the location of facilities is a critical factor of noise pollution, this study attempts to analyze how noise pollution for workers can be reduced by optimizing construction site layout planning in the pre-construction stage. Considering that mitigating noise by optimizing site layout may generate negative impacts on safety and cost, the desired site layout should establish a balance among noise reduction, safety improvement and cost control. Therefore, functions addressing potential safety risk and transportation cost arising from interactions between onsite facilities are designed. For solving this multi-objective optimization problem, a hybrid genetic algorithm-ant colony optimization model is applied to obtain trade-off solutions. Feasibility and effectiveness of the optimization model is verified by a case study on a residential building project. This study incorporates noise pollution reduction into site layout optimization problems in the pre-construction stage without additional expenditure and in safe manners. It aids future researchers in improving construction sustainability from as early as the planning stage. It also helps site managers enhance on-site sustainability incorporating environmental protection, economic efficiency and occupational safety together. The proposed research framework can be used as a reference to balance conflicting sustainability objectives in other industrial layout facilities as well.

The concept of green supply chain management emerged as a response to increasing public awareness of environmental protection in the past few decades. As companies tend to outsource a variety of their activities, green supplier selection as an imperative function of green supply chain management, has a crucial role in helping companies to maintain their strategic competitiveness. Despite the plethora of studies introducing supplier selection models based on economic criteria, studies that take into account the environmental issues are rather limited. In this study, a comprehensive grey-based green supplier selection model is proposed that incorporates both economic and environmental criteria. A novel weight assignment model is proposed by combining best-worst method and fuzzy grey cognitive maps to capture the interdependencies among the criteria. Improved grey relational analysis is advanced to be able to use grey weights of criteria to evaluate green suppliers which are subsequently ranked using an interval analysis approach. This study contributes to the decision-making theory by addressing the shortcomings of the available green supplier selection models. A real-world case study is also presented to show the applicability and effectiveness of the proposed model. The results of this study proved the proposed comprehensive model to be well capable of addressing the green supplier selection problem by taking in to account the interdependencies between criteria as well as the uncertainties associated with experts’ judgments.

The use of engineered nanomaterials (ENMs) in the construction sector is a newly emerging risk as there is limited knowledge about this topic. This paper studies the potential risk of nano-enabled construction products and how these are being addressed by Coordinators for safety and health matters. Firstly, a compendium of safety data sheets (SDSs) for these products and publications about the potential for nano-exposure were analysed. Secondly, a questionnaire was sent by email to a representative sample of Coordinators in Andalusia (Spain). The key findings were that practically none of the SDSs mentioned nano-specific data and the activities that involve nanomaterials in powder form or for spraying are the riskiest. From the survey, it seems that nano-enabled construction products are widely known about, but the use of nanomaterials is very limited. The nanorisks are unknown and rarely mentioned in work safety documents. It can be concluded that, a potential relationship between hazardous profile of the product and presence of ENMs is excluded. Although the use of nanotechnology in the construction site is at an early stage, workers have already been exposed to ENMs in critical activities and risk management is not being addressed.

The photovoltaic poverty alleviation project (PPAP) supplies clean power and creates considerable income for poor families, which is highly in accord with the concept of coordinated and sustainable development. Appropriate risk assessment is essential for the aversion and the disposal of potential problems, which can minimize the loss and promote the PPAP development. In this paper, a three-phase risk assessment model is proposed: firstly, through an approach combining the project life cycle theory and the Delphi method, 18 risk factors are identified and classified into 4 groups. Next, an extend Decision-Making and Trial Evaluation Laboratory (DEMATEL) method under intuitionistic fuzzy environment is employed for weight determination of indexes. Finally, the overall risk level is assessed and the priority disposal sequence of risk factors is highlighted based on the integrated results, the decision-maker preference theory and risk scenario analysis. According to the integrated results, ‘financing difficulties’, ‘no clear division of responsibilities and obligations’, ‘lack of operational experience’ and ‘material supply and installation defects’ are the riskiest factors that urgently need to be solved. Besides, the risk analysis reveals a fact that the overall risk level of China’s PPAPs is relatively high, especially in the technical aspect. Some corresponding suggestions are proposed, which may contribute to rational resource allocation and effective risk prevention.

[EN] There is a growing interest in model-based decision support systems contributing to strategic planning. The application of these in the case of urban infrastructure planning requires methods specifically aimed at addressing the relational uncertainties arising from the complex, multi-scale, nature of this field. This study presents UPSS, a comprehensive urban planning support system integrating the generation of planning alternatives, the evaluation of alternatives under a set of relevant scenarios selected dynamically in a cognitive way, and the proposal of policies to accompany the planning alternative. For this purpose, UPSS integrates two novel methods. These deal respectively with the ex post identification of relevant scenarios for the evaluation of the vulnerability and resilience of the alternatives, and with the assessment of relational uncertainty. According to the risks and opportunities borne by the system, the process makes it possible to select an infrastructure plan to alleviate the problem of urban vulnerability, as well as a set of relational contracts for its proper implementation across the different governmental scales of the infrastructure system. The whole process is tested via a case study, in which USPP first proposes optimal urban infrastructure plans that contribute to ameliorate the problem of urban vulnerability in Spain, then evaluates the risks and opportunities attached to the planning alternatives, and finally presents sets of policy measures to accompany the implementation of the alternative selected., The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R).

Traceability systems are perceived as a powerful solution to cope with food safety issues. It is important to improve the traceability for food supply chains to address potential food safety events. This paper studies the sourcing decisions in a food supply chain, in which the buyer is exposed to potential food safety events due to supplier responsibility. It is shown that the buyer may fail to source from the supplier with high-level traceability on account of information asymmetry. To address this adverse selection problem, this paper employs the certification as a screening tool, and find that the buyer could separate the two types perfectly with a pooling contract with certification, if the probability of the high type is low; otherwise, a pooling contract only separate the two types partially. This paper further considers a setting in which traceability strengthens the food safety level. It is shown that the buyer prefers the supplier with high-level traceability even the unit cost incurred by food safety events or the probability of the supplier with high-level traceability is lower.

In light of the transition towards a low-carbon economy and growing social demands for sustainable energy consumption, alternative powertrain systems, such as battery electric vehicles (BEVs), hybrid electric vehicles (HEVs) and fuel cell electric vehicles (FCEVs), have gained significance as a viable solution to revolutionize the dominant design logic of internal combustion engines (ICE) in automotive applications. By assuming that technological innovations emerge from the ability to recombine existing technologies, tracking and forecasting the technological knowledge interaction trajectory could assist experts and decision-makers in guiding their future R&D activities. To this end, a patent-based analysis framework is introduced to study the technological knowledge ecosystem of BEVs, HEVs and FCEVs in terms of technological knowledge flow (TKF). In this study, the principles of social network analysis are firstly used to quantify and visualize the connections among interacting technological knowledge areas. Secondly, link prediction technique is applied to predict the newly emerging and decaying links from a forward-looking perspective as well as the changing interrelationships among different technological knowledge areas. The findings show that the alternative powertrain systems form a cohesive technological knowledge ecosystem, pushing the underlying technological knowledge ecosystem to adopt a coopetition-based growth strategy. This study can provide valuable information for stakeholders interested in evaluating the evolving characteristics of alternative powertrain system technologies and offer an enhanced understanding on the technological competition in the automotive industry with regard to developing cleaner and more efficient mobility solutions.

Communicating the results of Life Cycle Assessment (LCA) studies is considered a challenge for researchers and practitioners, that state that one of the main issues refer to the lack of reference to position a product or service among its peers. The use of benchmarking emerges as a possible solution and is being encouraged by initiatives such as the Product Environmental Footprint. Therefore, this article aims to evaluate how benchmarking techniques have been applied in LCA. Specific keywords were investigated in relevant databases and resulted in 478 papers identified, which after refining, were reduced to 43. The techniques were classified in four categories: anchoring, creation of indicators, statistical analyses and Data Envelopment Analysis (DEA). Likewise, two perspectives were identified: a product-oriented, whenever the results are applied to one or more specific goods; and an organization-oriented, in which the data used for comparison refers to a whole production unit. DEA is mostly applied when productivity data is used, while statistical analysis were applied to establish performance classes and creation of indicators to meet specific demands. DEA is adequate for use in organizational-oriented benchmarking, but it is not possible to indicate a more appropriate technique for use in product-oriented studies. The combination of a dimensionality reduction of the LCAs, with an efficiency analysis using DEA and the establishment of performance classes can contribute to improve comparability and reporting of results. The development of LCA studies in line with Product Category Rules (PCRs), allows a greater use of DEA in product-oriented benchmarking.

© 2018 Elsevier Ltd Industrial energy efficiency has been widely recognized as a major contributor to the reduction of greenhouse gases emissions and improvement of industrial competitiveness. Nevertheless, a broad set of studies have pointed out the existence of barriers limiting the adoption of promising Energy Efficiency Measures (EEMs). Recently, scholars have shown the relevance of the so-called “non-energy benefits” (NEBs) coming from the adoption of EEMs for overcoming those barriers. Still, the existence of such benefits has been pointed out from specific studies and manuals for practitioners, but an overall framework describing them in terms of savings and benefits, as well as technical and management implications, is missing yet. Moreover, a considerable part of the scholars and of the practitioners just focuses on the identification and definition of the positive benefits deriving from these measures after they have been completely adopted, thus neglecting to describe the full set of both positive and negative effects occurring also during the implementation phase. Thus, starting from a literature review of scientific as well as practitioners’ studies, we have proposed a novel framework and characterization of the relevant items to be considered by an industrial decision-maker when deciding whether to adopt an EEM considering both the implementation and service phases. Hence, by taking this perspective, we have tested and validated the framework and the characterization in a two-step process: firstly, considering a set of EEMs well diffused and adopted in industry; secondly, investigating benefits and losses in ad-hoc selected manufacturing companies. Finally, considerations and implications are drawn from the preliminary validation and suggestion for further research are proposed, for both industrial decision-making as well as policy-making purposes.

The objective of this study is to identify and prioritize the performance outcomes (POs) due to adoption of SC remanufacturing critical success factors (CSFs). CSFs and the POs realized due do SC remanufacturing adoption, are identified based on past relevant literature analysis and subsequent discussions with the expert decision panel. This research work propose a hybrid solution methodology namely fuzzy Analytic Hierarchy Process (AHP) and fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), to prioritize the POs realized due to adoption of SC remanufacturing CSFs. Fuzzy AHP technique is used to obtain the relative weights of the CSFs by performing pair wise comparison amongst the criteria, while fuzzy TOPSIS is used to prioritize the POs due to adoption of SC remanufacturing CSFs. Further, the proposed methodological framework is applied to an Indian manufacturing organization to demonstrate its applicability, and prioritize the POs realized due to adoption of SC remanufacturing CSFs. The study presents more accurate, structured and systematic approach to the organization for improving its POs step-by-step through adoption of SC remanufacturing CSFs, thus increasing its sustenance capability. The impact of vagueness in the criterion weights on the prioritization is also investigated.

There is a lack of a clear description of the decision-making behaviors of major participants in construction and demolition (C&D) waste management. In order to achieve better and more efficient C&D waste management, this paper utilizes the evolutionary game to identify the decision-making behavior of construction contractors and government departments from theoretical perspectives. The decision-making behaviors of both participants in different circumstances are discussed in detail to clarify their roles. The results show that the supervisory intensity, supervision costs, penalties, waste disposal costs and revenues from illegal dumping are some main factors influencing the decision behaviors of contractors and government departments. Moreover, raising the penalty without maintaining the probability of supervision at a proper level is ineffective for controlling illegal-dumping while public participation in supervision could be an important supplement. Finally, a simple model based on decision behaviors is given to determine the appropriate value of penalties. A government set penalty at 66.67 yuan/ton with the probability of supervision of 22.5% could achieve the efficient control of illegal-dumping when the probability of illegal-dumping is 60%. Therefore, this study could be used as the basis for an efficient C&D waste management framework.

In recent years, several models have been proposed to inoculate Water Distribution Systems (WDS) against impacts of accidental and/or intentional compromised water quality through optimal deployment of online monitoring sensors in the network, which is referred to as Contamination Warning Systems (CWS). Translating such modeling efforts to real-world practice is, however, a challenge as different involved parties may pursue conflicting goals and modeling-based recommendations may not justify all stakeholders' criteria. It is, hence, pivotal to develop conflict resolution methodologies to support engagement of different stakeholders in securing a safe water distribution. The decision making structure for CWS design is often of top-down nature, with the upper level decision maker concerned mainly about public safety and lower level stakeholders concerned about operational costs. In this study, a decision support framework based on Leader-Follower Game is proposed, given different power levels. Leader's objectives are focused on the CWS robustness, while followers have conflicting interests that are in turn resolved via Nash Bargaining method. Lamerd WDS (Fars, Iran) is selected to assess the proposed model's performance. The results show the proposed objective and parsimonious model provides a robust solution that complies with the leader's criteria and maximizes the followers' satisfaction. The proposed decision support system helps govern WDSs in a resilient and safe manner and warrants practical implementation of modeling-based security assurance policies to provide sustainable service to the society.

Extended product life and reuse are cornerstones of the circular economy vision. Remanufacturing is one strategy that could be used to facilitate more reuse. Research on remanufacturing often addresses the use phase of a product from the perspective of the remanufacturer, not of the end-user of the product. Results are often described in terms of barriers and drivers, with end-user awareness of and trust in remanufactured products being common themes. It can be argued that such explanations are not sufficient for understanding why remanufacturing doesn't happen because they marginalize events during the use phase and the effects of end-user action. The study described here focuses on the use phase and the end-users’ role in product remanufacturing outcome. The study is based on the case of one type of mechanical component, prolific in industry and society at large, and ten of its end-users in heavy industry. The component is already remanufacturable and a functioning remanufacturing system for it is already in place, yet the bulk of used components are scrapped by end-users instead of being sent for remanufacturing. Interviews were conducted with maintenance personnel at ten paper, steel and cement factories. These personnel were asked how they determine when a component is obsolete and how they make decisions about whether to send them for remanufacturing. Responses were analyzed with the help of theories from maintenance management and decision-making. The analysis is presented as a conceptual model of the ‘End-user system’ of the component, in which complicating factors such as machine irregularities and tough work environments are mitigated by maintenance personnel with component replacement and remanufacturing protocols and where rigidities related to system-level risks and costs make it difficult for personnel to change. This study reveals the systemic nature of component remanufacturing outcomes, and specifically, how maintenance activities of both components and the machines around them influence such outcomes. Moreover, it highlights that while certain replacement protocols lend themselves to remanufacturing, convincing end-users to choose remanufactured products may be more difficult than just making them aware and confident in the remanufacturing offering.

Product lifetimes and obsolescence have been central points of discussion in the fashion field. In this context, design researchers and practitioners have proposed a variety of strategies to enable slower cycles of product replacement, leading to smaller volumes of clothing production and consumption. A previous review of these strategies, however, revealed that there is no empirical evidence of their efficacy in terms of lifetime extension or environmental sustainability. Therefore, this research takes a first step in covering this knowledge gap. It proposes methods to assess the impact of such approaches and applies them to the specific case of “product personalisation”, the strategy most frequently mentioned in literature. Clothing has characteristics that are not present in other product categories common in lifetimes studies. These characteristics enable comparative analysis of products, diachronic studies over relatively short periods of time, and estimations of the environmental benefits of lifetime extension. Taking advantage of such particularities, the article evaluates the environmental gains of personalised products by comparing their performance with ready-made garments in terms of age, usage, influence on new product demand, and waste. The research is based on a series of wardrobe studies and company interviews. The outcomes of these studies question the environmental benefits of product personalisation. When compared with ready-made garments, personalised garments were not kept for longer time, nor were they used more frequently. Moreover, no evidence of their contribution to reductions in new product demand and waste was found. These findings confirm the need for more empirical research to understand the effect of this and other design strategies aimed at delaying clothing obsolescence and reducing production volumes and waste. Such enquiries can provide relevant feedback to practitioners developing creative solutions. In that way, empirical research and creative practice can benefit from each other's input and build iterative cycles that ensure effective actions. The methods advanced in this study aim at supporting this valuable line of research, leading to a more environmentally-sound apparel sector.

s Among the potential accidents that can lead to fatal injuries in underground coal mines, gas explosion accidents have been recognized as the leading threat to miners' safety in China. Moreover, such accidents are triggered predominantly by human-related hazards, namely, the unsafe behaviours of humans. In underground coal mines, there are a considerable number of unsafe behaviours that can trigger gas explosion accidents. Consequently, how to determine scientifically the risk management priority of human unsafe behaviour is the basis of pre-controlling gas explosion accidents effectively. Therefore, the method of assessing the risk value of unsafe behaviour is proposed based on the analysis of its characteristics, and then a risk assessment model is constructed. Under this framework, the risk assessment model is composed of probability, importance degree, and loss, and the risk value is the product of the three. Furthermore, the probability and importance degree can be obtained by assessing the degree of unreliability of unsafe behaviour and analysing the degree of influence in the fault tree using the Boolean algebra algorithm, respectively. Finally, according to the risk values, the priority for controlling unsafe behaviours can be obtained to provide a theoretical basis for the effective control of gas explosion accidents.

Risk assessment is an accepted approach used worldwide to improve the sustainability of either the existing process plant or the design of a new installation. In the current practices, risk assessment is normally performed once the design has been completed. A better approach is to perform risk assessment at the initial design stages with the application of inherent safety concept to achieve the sustainable cleaner chemical process. This paper consolidates a new technique to improve the safety level of process piping from potential fire risk using the inherent safety concept. Inherently safer process piping (ISPP) technique utilizes fundamental of fluid flow to predict the potential damage from a major fire accident. A relative ranking of process streams is used to identify the critical process streams that have higher chances of damage. Risk assessment is performed to check if the potential fire exceeds the acceptance criteria or not. If the risk is not in the acceptable range, inherent safety principle is used to reduce the risk to the acceptable limit. The ISPP technique is validated using a case study of methanol process plant. This technique could be used to facilitate design practitioners to incorporate inherent safety at the early design stage.

Recycling only creates environmental benefits when it displaces other material production. Without displacement it only delays rather than prevents ultimate disposal. It is therefore critically important that we improve our understanding of the causality between recycling and other material production. This research focuses on estimation of the causal link between an increase in recycling and a reduction in primary material. We first review how structural models of supply and demand, for both the primary material and the recycled material, can be used to identify a causal link. The supply and demand approach suffers from issues of endogeneity, which require the use of advanced regression techniques. These techniques, in turn, require detailed and large datasets, which are often hard to obtain. Here, we introduce the Difference-in-Differences estimator to the industrial ecology literature, as an alternative approach to quantifying the causal effect between additional recycling and primary material production. The Difference-in-Differences estimator is based on a quasi-experimental approach, in that it classifies data into treatment and control groups. We introduce the method, analyze the data structures and assumptions needed for identification of causal effects, and discuss the advantages relative to the supply and demand framework. A hypothetical application of each method to aluminum recycling is provided, along with a simulated quantitative example of the Difference-in-Differences technique. Our proposed method will help to better understand, measure, and promote the conditions under which recycling creates environmental benefits.

In order to explain safety and environment protection from the aspects of information cognition, it is imperative to establish new safety theory by exploring accident and environmental pollution mechanism from the upstream level. In recent years, safety-related information or cognition studies have become new extension point in safety science. The researchers did not make any breakthroughs in the mechanism analysis of safety information science, because the essential process is not understood by researchers. Obviously, establishing safety information science is irreversible and critical. Therefore, it is theoretically and practically significant to establish and discuss the foundation of safety information science. Firstly, the safety systems should follow three levels: scale decomposition, dimension decomposition and research field. Then, from the perspective of spatial order, a systematic cognitive sequence of safety information and a Five Areas Four Belts spatial order model were established. Thirdly, the meaning and basic connotation of safety information are clarified. In addition, from the view of the combination between safety information dissemination and behavior cognition, the Safety Information Cognition model is constructed according to the general model of safety information cognition and Principle of system decomposition. Besides, the accident mechanism of 5-layers distortion and 4-times delay, as well as the general procedures of injury accidents were proposed. Finally, the worth of safety science model research for the future development was summarized. This paper contains a series of achievements, including system decomposition method, safety information cognition process and the cause mechanism and prevention strategies of accidents or pollution information. The conclusion shows that the information communication theory, the cognitive model and the safety information law can deepen the understanding of the safety and environment system and provide new ways for the further study of the safety and cleaner production. It can also further consolidate the essential principles of safety and environmental system and supply new preventions of accident and pollution, for example, the controls and elimination of harmful factors, Identification and analyze safety information science of dangerous and harmful factors, risk evaluation, prevention, monitoring and early warning measures et al.

The National Automotive Policy was introduced in Malaysia in 2006, which includes end-of-life vehicle (ELV) recovery policies. However, there is limited information on the current state of ELV recovery in Malaysia, which hinders the fulfillment of these new requirements. For manufacturers, the lack of information will lead to difficulties in making strategic decisions in order to fulfill the ELV policies. In order to support design strategies for ELV recovery, it is crucial to identify the issues and factors of ELV recovery, which forms the objective of this study. A survey was carried out among the key stakeholders in the aftermarket chain and the results revealed that special tooling is needed to handle ELV components as well as design that will facilitate the separation of parts according to materials. These are among the main factors that contribute toward the effectiveness of ELV recovery. The following 5 factors (pre-production, health and environment, policy and worker, manufacturing process, and end-of-life value) are the factors that will enhance ELV recovery in Malaysia and it is believed that these factors are subject to dynamic changes in the aftermarket chain. It is believed that the results presented in this paper will be useful to academics and researchers in order to establish design strategies for ELV recovery in Malaysia. Moreover, stochastic techniques are required to cater the dynamic and complex behavior of the actual ELV recovery system in Malaysia.

Selecting the supplier is a very critical part to the comprehensive performance of modern enterprises. With the large-scale development of straw biomass industry, green supplier selection has become a key decision-making task which needs to collect and process mass of information, it is necessary to make the supplier to go green. Nevertheless, it is safe to say, in fact, that so far there are a few researches on supplier selection in straw biomass industry. At the same time, some crucial problems urgently needed to be solved exist in present research, as shown below:①decision-making methods are frequently used, even though they have some serious problems, e.g. information loss.②some key index factors are ignored, green supplier selection hasn't got attracted sufficient attention.③little work has been performed on the fuzziness or the uncertainty of index weight. To solve the problems mentioned above, this paper tries to find out some ways to make improvements:①Cloud model is proposed to handle the fuzziness and randomness of evaluation information.②Index system is more comprehensive. Important issues, such as on-time delivery, pollutant emissions per unit fuel(t) and green certification, are paid more attention to.③Fuzzy AHP is applied to determine the index weight, the uncertainty of criteria and sub-criteria are considered, the vagueness of human thought is dealt with.④A decision framework based on Cloud model and possibility degree is put forward to guide the optimal selection of green supplier selection.⑤A Chinese case is carried out and related sensitivity analysis is performed. The results show that the proposed novel model not only can find the more suitable green supplier, but also reveal the big gap between alternatives clearly. The strength of the proposed new decision framework is proved.

Technical Product-Service Systems (PSS) consist of technical products that are enhanced by life cycle-oriented services. PSS enable companies to fulfill individual customer requirements and to build long-term customer relationships. Besides their economic advantages, PSS are attributed to positive effects on ecological sustainability. However, the complex structure of PSS challenges the quantification of their impact on all aspects of ecological sustainability. This leads to the demand for quantification methods with increased practical applicability compared to methods that encompass all aspects of ecological sustainability like the Life Cycle Assessment (LCA). In this context, the Cumulative Energy Demand (CED) is an elaborated method that enables the comparison of different products or services regarding their primary energy demand. Since many aspects of ecological sustainability correlate to the primary energy demand, CED is seen as a suitable estimate of the results of an LCA with reduced efforts and complexity. In consequence, the adaption of the CED method to PSS is a promising research task that could support the design and operation of PSS with increased ecological sustainability. Therefore, this paper presents an approach to systematically analyze and reduce the CED of a PSS (CEDPSS). In order to validate the feasibility of the approach, a use case from agriculture machinery is carried out. The results indicate that the technical product is responsible for a large percentage of CEDPSS, while services have a relatively low impact. Despite their low primary energy demand, specifically designed services can reduce CEDPSS. This can be described as an energetic leverage effect of services in PSS.

The product sustainability assessment is a progress to evaluate sustainability with indicators for product sustainability in the whole product life cycle. However, the current approaches could not deal with the relationships of those closed-loop indicators. This paper is devoted to a graph theory-based product sustainability assessment approach to avoid those closed loops of the evaluation indicators. The hierarchical evaluation system for mechanical product sustainability assessment with energy, environmental, resource, technical, and economic indicators is proposed. The product sustainability assessment approach is proposed with five steps: rationalization of the directed graph of the evaluation system, construction of the hierarchical structure, transformation from reachability matrix to judgment matrix, consistency check and adjustment of judgment matrix, and indicator weight determination and comprehensive assessment of evaluation system. The product sustainability assessment of an underactuated exoskeleton robot is given as an example to demonstrate the proposed methodology.

The mining activities significantly lower the sustainability in the stone mining region. Cleaner production (CP) is more likely to be proposed to achieve the sustainable development in the mining regions. Therefore, the stone mining industry has begun to implement many CP technologies and initiatives to tackle with ecological problems caused by the mining production. However, the CP practices do not solve the problems sufficiently, because of the low level of implementations by the stone mining companies, especially in the developing countries. This paper aims to establish a support framework for the stone mining industry to develop reasonable CP strategy and avoid inefficient CP practices. Our research provides a methodology for evaluating the CP level, including the principles of establishing indicator and standard system, the method of developing evaluation algorithm and the approach of data collection. A CP evaluation system is developed for the first time in the stone mining industry, which enables the methodology to be operationalization in the real evaluation process. The study also introduced the sensitivity analysis and confidence interval (ci) theory to ensure the reliability of the system and the validity of the evaluation results, respectively. A case study in Laizhou region of China illustrates how a CP strategy develops based on the CP evaluation results. The strategy has achieved collaborative optimization of various indexes of sustainability performance in the mining region.

Supplier management is one of the complex, sensitive and multifaceted measures in supply chain that has the most effect on the successful performance of a supply chain. Selection, segmentation and development of the supplier are three important parts of supplier management. With globalization and increasing disruption and vulnerability of supply chain, the resilience of all components of supply chain is necessary. For this reason, the present study was conducted with consideration of two dimensions of resilience enhancer and resilience reducer to select and segment suppliers. The Grey DEMATEL technique was used to determine the importance degree of the criteria for each of these two dimensions, and then, using Grey Simple Additive Weighting technique (GSAW), the score of each supplier was determined according to each dimension. Based on the findings, customization was known the most important enhancer criterion and the supplier's capacity limit was the most significant reducer. Finally, vulnerable, sensitive, volatile and resilient suppliers were identified in accordance with the suppliers' score in both enhancer and reducer dimensions, and strategies were also provided for supplier development.

Rigorous and fair comparison of end-of-life handling options for domestic refrigerators is much more complicated than simple policy perspectives such as the waste hierarchy might suggest. The drive towards product reuse over material recycling merits particularly close attention. This study explores the factors that might influence policy and decision-making in this area, with a view to minimising overall environmental impact. The work combines life-cycle assessments of refrigerators with models for product performance over time to give a sector-wide perspective on these issues. Generally-accepted tenets such as the preferability of product reuse are shown to be provisional, heavily dependent on factors such as the electricity mix, and non-uniform for different measures of impact. A more general and complicated picture emerges, and recommendations for existing policy and ongoing work are developed.

Environmental conservation and sustainable development have attracted considerable attention in the automotive industries. Sustainability has become one of the main items of concern in end-of-life vehicle (ELV) management. Given the toxic substances and waste materials within end-of-life vehicles (ELVs), the Chinese government has encouraged the development of ELV management firms to solve ELV problems. A proper approach for prioritising the ELV management alternatives under an uncertain, dynamic and competitive environment drives an enterprise to meet economic, environmental, societal, and technical requirements. This study presents a systematic index system in selecting criteria for sustainable ELV alternative management and then constructs a group decision-making approach that utilises picture hesitant fuzzy entropy and similarity measurements to evaluate ELV management alternatives with picture hesitant fuzzy information. An empirical case in China is proposed to illustrate the application of the proposed approach. The results can aid firms in prioritising ELV management alternatives and making the best choice.

Anthropocentrism and disciplinary research have not led to effective solutions to sustainability problems. A shift is required towards biocentric, transdisciplinarity-based solutions, to mitigate rebound effects and unintended, negative effects. In the field of Sustainable Supply Network Design, such shift implies on developing resilient solutions that maximize environmental benefits instead of minimizing environmental impacts. Recent researches have showed progress in this direction proposing more integrative approaches, but a framework to design supply networks with the purpose of environmental regeneration is yet to be proposed. This research aims to fill this gap, merging concepts from Regenerative Design, Transdisciplinary Research, Systems Thinking, Social Sciences and Design Sciences. Such framework is regarded as an artefact, and Design Science Research Methodology used for its development: a main problem is identified, objectives for a solution are drawn and the framework is designed. First, the Regenerative Supply Network Design is defined, to guide the elaboration of the Regenerative Supply Chain Design framework, consisting of six steps: (i) description of the network surroundings and identification of a regenerative purpose; (ii) redesign of outputs (iii) network conceptualization, (iv) optimize performance, (v) choose configuration, and (vi) implementation. Among the implications of this research are that (i) practitioners basing their design process in this framework are effectively shifting from anthropocentrism to biocentrism with a clear, defined purpose of environmental restoration and (ii), that the supply networks evolve in the integration with the environment, enhancing eco-systems resilience.

Construction methods in developing countries such as China are gradually industrializing due to rising labor costs, new techniques, tools, procedures and management methods. This makes it essential to develop new risk evaluation and control methods. Previous research seems to ignore the risk management of the application of new construction technologies and procedures. The identification of risk mechanisms is unclear, leading to a lack of clear guidance for risk avoidance and control. This paper describes a network model based on meta-network analysis of project objectives, risk events, risk factors and stakeholders in the construction process of building industrialization. According to ISO 31000, the main processes of risk management in the model has three parts: risk identification, risk analysis and evaluation, and risk treatment and control. Risk factors are identified from previous literature and site investigation, and the indirect impact on project objectives is analyzed and calculated with the networks in the meta-network. The order of importance is evaluated and used as the foundation of risk treatment and control. The analysis of the crucial risk factors makes it possible to identify the stakeholders who influence them, leading to suggestions for relevant control strategies. A residential building construction project in South China that uses the building industrialization construction system serves as a case study to verify the feasibility and applicability of the risk management system. Results show that critical risk factors are construction-related factors and design-related factors. The water and electricity engineers, the project manager, the project secretary, the field engineer, the project supervisor and the main contractor engineer have a significant influence on the risk factors. A stakeholder supervision system with targeted risk control strategies is proposed.

Electric vehicles (EVs) have become increasingly popular due to zero carbon emission, reduction of fossil fuel reserve, comfortable and light transport. However, EVs employing lithium-ion battery are facing difficulties in terms of predicting accurate health and remaining useful life states due to various internal and external factors. Currently, very few papers are addressed to summarize the state of health (SOH) and remaining useful life (RUL) estimation approaches. In this regard, the goal of this paper is to comprehensively review the different estimation models to predict SOH, and RUL in a comparative manner. The results identify the classifications, characteristics and evaluation processes with advantages and disadvantages for EV applications. The review also investigates the issues and challenges with possible solutions. Furthermore, the review provides some selective proposals for the further technological development of SOH, and RUL estimation for lithium-ion batteries. All the highlights insight this review will hopefully lead to the increasing efforts towards the development of the advanced SOH and RUL methods for future EV uses.