Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems

[EN] The urgent need for sustainable development is imposing radical changes in the way manufacturing systems are designed and implemented. The overall sustainability in industrial activities of manufacturing companies must be achieved at the same time that they face unprecedented levels of global competition. Therefore, there is a well-known need for tools and methods that can support the design and implementation of these systems in an effective way. This paper proposes an engineering method that helps researchers to design sustainable intelligent manufacturing systems. The approach is focused on the identification of the manufacturing components and the design and integration of sustainability-oriented mechanisms in the system specification, providing specific development guidelines and tools with built-in support for sustainable features. Besides, a set of case studies is presented in order to assess the proposed method.This research was supported by research projects TIN2015-65515-C4-1-R and TIN2016-80856-R from the Spanish government. The authors would like to acknowledge T. Bonte for her contribution to the NetLogo simulator of the AIP PRIMECA cell.Giret Boggino, AS.; Trentesaux, D.; Salido Gregorio, MÁ.; Garcia, E.; Adam, E. (2017). A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems. Journal of Cleaner Production. 167(1):1370-1386. https://doi.org/10.1016/j.jclepro.2017.03.079S13701386167

A Dual Scheduling Model for Optimizing Robustness and Energy Consumption in Manufacturing Systems

[EN] Manufacturing systems involve a huge number of combinatorial problems that must be optimized in an efficient way. One of these problems is related to task scheduling problems. These problems are NP-hard, so most of the complete techniques are not able to obtain an optimal solution in an efficient way. Furthermore, most of real manufacturing problems are dynamic, so the main objective is not only to obtain an optimized solution in terms of makespan, tardiness, and so on but also to obtain a solution able to absorb minor incidences/disruptions presented in any daily process. Most of these industries are also focused on improving the energy efficiency of their industrial processes. In this article, we propose a knowledge-based model to analyse previous incidences occurred in the machines with the aim of modelling the problem to obtain robust and energy-aware solutions. The resultant model (called dual model) will protect the more dynamic and disrupted tasks by assigning buffer times. These buffers will be used to absorb incidences during execution and to reduce the machine rate to minimize energy consumption. This model is solved by a memetic algorithm which combines a genetic algorithm with a local search to obtain robust and energy-aware solutions able to absorb further disruptions. The proposed dual model has been proven to be efficient in terms of energy consumption, robustness and stability in different and well-known benchmarks.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been supported by the Spanish Government under research project TIN2013-46511-C2-1 for the Spanish government and the TETRACOM EU project FP7-ICT-2013-10-No 609491.Escamilla Fuster, J.; Salido Gregorio, MA. (2016). A Dual Scheduling Model for Optimizing Robustness and Energy Consumption in Manufacturing Systems. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 1(1):1-12. https://doi.org/10.1177/0954405415625915S1121

Energy Efficient Manufacturing Scheduling: A Systematic Literature Review

The social context in relation to energy policies, energy supply, and sustainability concerns as well as advances in more energy-efficient technologies is driving a need for a change in the manufacturing sector. The main purpose of this work is to provide a research framework for energy-efficient scheduling (EES) which is a very active research area with more than 500 papers published in the last 10 years. The reason for this interest is mostly due to the economic and environmental impact of considering energy in production scheduling. In this paper, we present a systematic literature review of recent papers in this area, provide a classification of the problems studied, and present an overview of the main aspects and methodologies considered as well as open research challenges

A Dynamic Hybrid Control Architecture for Sustainable Manufacturing Control

Manufacturing systems face the challenge of accomplishing the productive effectiveness and sustainable efficiency goals at operational level. For this, manufacturing control systems must incorporate a mechanism that balances the trade-off between effectiveness and efficiency in perturbed scenarios. This paper proposes a framework of a dynamic hybrid control that manages and balances the trade-off between effectiveness and efficiency objectives. Our proposal integrates this trade-off in three different locations: the predictive-offline scheduling component, the reactive-online control component, and the switching mechanism that changes dynamic architecture. To show the contribution of our approach and the progress of our research, a case study dealing with energy-aware manufacturing control is presented.Jimenez, JF.; Bekrar, A.; Giret Boggino, AS.; Leitão, P.; Trentesaux, D. (2016). A Dynamic Hybrid Control Architecture for Sustainable Manufacturing Control. IFAC-PapersOnLine. 49(31):114-119. doi:10.1016/j.ifacol.2016.12.171S114119493

Federated Embedded Systems – a review of the literature in related fields

This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways

Background, Systematic Review, Challenges and Outlook

Publisher Copyright: © 2013 IEEE. This research is supported by the Digital Manufacturing and Design Training Network (DiManD) project funded by the European Union through the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) under grant agreement no. 814078The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.publishersversionpublishe