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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.