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The increase in the world population and resource scarcity has led to the introduction of environmental concepts such as sustainability and sustainable supply chain design (SSCD). However, there is a lack of consensus among researchers on how to measure sustainability in SSCD. Therefore, the authors propose a novel approach to measuring sustainability in the context of SSCD by developing an integrated, tractable, and representative metrics framework. The methodology corresponds to a quantitative approach involving bibliographic examination and statistical techniques. First, the authors conducted a systematic literature review by formulating research questions and a search protocol, searched for relevant articles, and conducted a quality assessment on full-text reviews to obtain metrics for measuring sustainability in SSCD from the literature. Then, they defined aggregation criteria representing their inclusion relationship by merging associated metrics. The authors then used Cluster Analysis (CA), a multivariate statistical technique, for grouping the metrics. Consequently, twelve clusters were distinguished from 541 research articles, grouping 51 metrics from different sustainability dimensions. It shows the strong connection among the sustainability dimensions, i.e., they must be assessed holistically. Then, we proposed reducing the 51 metrics to 5 to evaluate sustainability in the SSCD, allowing us to focus on a reduced number of indicators.

Mass customized and mass personalized production has become facilitated by the fourth industrial revolution. The resulting industrial environments require the development of information systems able to take the specifications of customers and convey them to the production system in such a way as to contribute to the coordination of all the stakeholders and activities required to fulfill the orders of the customers. This is beyond the capabilities of traditional systems based on MRP and ERP, since the information should be managed in a flexible and decentralized way to exploit the Smart Manufacturing facilities of Industry 4.0. Blockchain, instead, is a technology that provides those features constituting a sound information supporting basis for mass customized/personalized production. Consequently, we explore the potential of blockchain as an information technology able to support industries that base their business models on mass customized/personalized production processes. This survey allows us to identify important challenges for further developments, highlighting three issues in the production setting: (i) to deepen the interoperability of systems, (ii) to generate more implementations, and (iii) to develop efficient consensus protocols. As a response to these insights we provide a conceptual design of how blockchain contributes to managing efficiently mass customized production systems. In our design the information of customer specifications can be fused with data from the production process to generate a plan to fulfill the demand. This design arises as a solution approach to three stated problem, which are faced by mass customized production systems.

Over the past fifty years the population of the world has doubled, while resources as water have become increasingly scarce. In particular, water consumption has far exceeded the available of this resource in some regions of the world. In order to address the above problem, the possibility of reusing grey water by installing wastewater treatment plants could be a suitable alternative for several developing countries. This paper seeks to find the best configuration for these facilities in Chile by considering the economic and environmental aspects conjoint to the social dimension. The problem is modeled as a multi-objective optimization including: minimizing costs, minimizing environmental impact, maximizing phosphorus extraction from wastewater and maximizing the number of workers to be required with the goal of analyzing the sustainability of the system. To find the Pareto frontiers of multi-objective problem, a resolution framework based on an adaptation of elitist non-dominated sorting genetic algorithm (NSGA-II) is provided for the problem. From the obtained results, the non-dominated solutions and a compromise solution are computed, reporting configuration alternatives that integrate the three sustainability dimensions, the economic, the environmental and the social as objectives for the design for a sustainable system of wastewater treatment plants.

International audience; Bioeconomy has gained importance during the last decade as a frame of reference for the design and implementation of policies to foster sustainable development and innovation. Considering the need for society to move to forms of production in which generation of wastes and the use of fossil fuels must be minimized or eliminated, Phase III biorefineries (mix feedstock and multiple products) have emerged as a promising and central element in bioeconomy. However, its industrial development has been slower than expected, especially due to investors’ poor perception of technological risk and large investment required. Among the current climate change challenges, the need of methodologies and tools to develop an optimal supply chain for a biorefinery, including all the aspects of sustainability and considering the territorial context of the project is fundamental. The present work proposes a comprehensive decision-making approach for a Phase III biorefinery project, by integrating all the sustainability dimensions. This approach is formalized and solved thanks to a multiobjective optimization model, where sustainability criteria are included in the formulation of objective functions, decision variables and constraints. To illustrate the proposed approach, a case study was developed for the Colombian context. The resulting Pareto fronts shown that biorefineries integrating different types of raw materials, even non-food crops, are economical feasible in North Colombia.

In this paper, we introduce the problem of minimizing total implementation cost of a 2-D indoor localization system for underground mine tunnels, guaranteeing a constant accuracy. To address this problem, we propose a system based on Cell-ID technique and visible light communication (VLC) technology with square panels of light-emitting diode (LED) lights, which fixes the maximum position error in each cell by considering the distribution of overlapping and non-overlapping cells. Formally, our system is mainly defined by an easy-to-implement algorithm based on a simple order rule. In order to illustrate the usefulness of the proposal, an example is provided. Finally, potential applications in the industrial environments are discussed and future research is proposed.

Municipal solid waste (MSW) management is an important challenge in developing and emerging countries, where two realities co-exist. On the one hand, their metropolitan cities exhibit an integrated MSW system with a specialized fleet for the collection and landfills for the final disposal, concentrating on environmental initiatives such as municipal recycling programs. On the other hand, their regional cities show an MSW system based on adapted transports for collection and open dumps for final disposal. Besides, they face other environmental problems due to local conditions. This research proposes a life cycle assessment (LCA) approach to close the gap between these two realities. In particular, we study the city of Valdivia (Chile), one of the main regional capitals of South America, which shares similarities with other southern regional cities in the Global South. This city disposes 95% of its MSW in open dumps and presents one of the highest environmental pollution rates in Latin America. We analyze the greenhouse gas (GHG) emissions and energy performance of six scenarios, seeking a solution for these problems. The results obtained show that a waste-to-energy scenario would generate savings of GHG emission and particulate matter, reaching 11.3% and 21.8%, respectively. Using our LCA approach, we can provide environmental evidence to highlight the importance of improving MSW management in regional cities, closing the gap with MSW management in metropolitan cities, and contributing to national targets such as United Nations Sustainable Development Goals and Nationally-Determined Contributions.

The growing global population and its effects on world food security, as well as the urgency for climate change mitigation, are issues that foster technological, social, and political innovations to increase the efficiency of use of natural resources, such as biomass among others. While significant research efforts have been devoted to biomass conversion processes, their associated supply chains and their implication for complete process efficiency have only been studied more recently. However, most of the recent investigations into the design and optimization of biomass supply chains have focused on an economic point of view, sidelining other dimensions of sustainability, which represents a serious drawback for this kind of work. This article surveys the recent research on design and management optimization of biorefinery supply chains from a sustainability perspective. 72 published research articles from 2006 to 2015 have been analyzed to highlight the sustainability dimensions considered, as well as the inclusion of uncertainties. A typology of decision-making at three levels of analysis (strategic, tactical and operational), and the specific set of tools used to model and optimize the biorefinery supply chain have also been studied. The conclusion underlines the contributions and shortcomings of current research and suggests possible future directions.