Towards a business model for sustainable supply chain management

Designers make decisions that ultimately impact on both the economic, environmental and social performance of the products and process, and many of these costs and impacts occur across the supply chain. This paper aims to show initials elements of a research which aims to develop an integrated business model for sustainable supply chain management in order to facilitate the business management process in terms of assessment of suppliers and collaboration addressed to the sustainable improvements across supply chain. It is noteworthy that it is an imperative in the current competitive market that companies must be able to manage their entire production chain taking into account sustainable issues as an important factor in their decision processes. Therefore, it is believed that this model can integrate and strengthen a company’s functions and assist its decision processes as well as implement improvements within its supply chain

Contributions to smart grids based on renewable energy sources with hydrogen as backup system. Energy management system: design, modeling and physical implementation based on model predictive control theory

Atendiendo al concepto de Smart Grid (Red Inteligente), estos sistemas están íntimamente relacionados con el uso de los sistemas de generación renovable. A pesar de los beneficios de esta tecnología, su dependencia de los recursos ambientales hace imposible garantizar el balance de energía entre generación y demanda en todo momento. Para ello, la hibridación de sistemas, así como el uso de sistemas basados en hidrógeno, se muestra como una solución técnica viable para resolver o mitigar los problemas asociados a este tipo de tecnologías. El empleo de este tipo de sistemas híbridos plantea una mayor complejidad en materia de gestión debido a la elevada cantidad de parámetros y factores a tener en cuenta de cara a garantizar un óptimo reparto energético en función de la aplicación y el estado energético del sistema. En este sentido, han de considerarse ciertos aspectos asociados a la operación real de los sistemas, tales como la topología del sistema, costes de operación y mantenimiento, la necesidad de un control de tensión de carga para baterías, la degradación de los equipos, la dinámica de cada sistema, las pérdidas asociadas al punto de trabajo, o parámetros relacionados con la calidad del suministro eléctrico. A tenor de lo anterior, es necesario el empleo de estrategias de gestión de la energía que permitan determinar el reparto energético entre dispositivos, con el objetivo de optimizar la respuesta del sistema desde el punto de vista técnico y económico, planteándose por lo tanto un problema de optimización multiobjetivo. Para dar respuesta al problema de optimización multiobjetivo propuesto, en la presente Tesis, se hace uso de una arquitectura de control distribuida, compuesta en un primer nivel por controladores locales, y en el nivel superior, se propone el uso de un controlador supervisor basado en técnicas de control predictivo (MPC). La función principal del controlador propuesto es determinar la consigna de operación de cada uno de los equipos que componen la Smart Grid, dando respuesta a la función objetivo propuesta de acuerdo a los criterios de diseño del sistema. Las ventajas de la utilización de técnicas de control predictivo respecto a otro tipo de técnicas son claras; permite el empleo de técnicas de control multivariable, permitiendo plantear problemas de optimización multiobjetivo con restricciones; así como implementar una estrategia de control basado en un horizonte de predicción, lo que permite al sistema adaptar la respuesta del controlador en base a acontecimientos futuros, mejorando la respuesta del sistema frente a técnicas de control meramente pasivas. Como base de conocimientos del controlador propuesto, en esta tesis se presenta un modelo lineal discreto generalista de la planta, calculado en cada periodo de muestreo, en base a una linealización recursiva, lo que permite aument ar la calidad del modelo respecto a soluciones basadas en torno a un único punto de linealización. El modelo incluye todos los parámetros necesarios para el control de una planta real, incluyendo los términos asociados al estado energético del sistema, tensión de operación de baterías, así como los parámetros técnicos y económicos. tales como degradación. oérdidas o coste de operación con el obietivo de definir una función de coste del sistema que permita su generalidad para cualquier tipo de aplicación u objetivo de diseño. Atendiendo al diseño del controlador propuesto, y con el objetivo de garantizar la generalidad requerida en todo el proceso, en la presente tesis se propone una metodología de diseño basado en el modelo propuesto y una función de coste que incluye todos los parámetros técnicos y económicos necesarios para resolver el problema de optimización multiobjetivo propuesto, independientemente de la aplicación y topología del sistema. Esta función objetivo permite establecer un problema de tracking de acuerdo al balance de potencia instantáneo del sistema, a la vez que son considerados los parámetros técnicos y económicos asociados a la respuesta del sistema, véase degradación y rendimiento de equipos, límites y dinámica de operación, costes de operación y mantenimiento, criterios de carga de baterías, etc. Para garantizar la generalidad del controlador propuesto, fomentando así su uso, independientemente de la aplicación y topología del sistema, en la presente tesis se propone una metodología de diseño y tuning de los parámetros del controlador, de acuerdo a la función objetivo propuesta y los criterios de diseño en materia de prioridad de uso y distribución de energía entre equipos. La propuesta metodológica está basada en las relaciones causa-efecto entre los distintos parámetros, las cuales permiten definir el comportamiento del sistema de acuerdo a la estrategia de gestión de la energía y objetivos de diseño propuestos. De forma similar, con el objetivo de considerar la optimización a corto y largo plazo del sistema, limitada por el concepto de horizonte deslizante propio de las técnicas de control predictivo, se hace uso de técnicas de control adicionales, las cuales actúan directamente sobre el proceso de ajuste de los parámetros del controlador. En este sentido, en base a la historia del sistema, se recalculan los parámetros del controlador, en caso de que sea necesario, actuándose directamente sobre los parámetros de ponderación, de tal forma que permita adaptar la respuesta dinámica o reparto energético de acuerdo a los criterios de diseño del controlador. Finalmente, la metodología de diseño y el controlador propuesto fueron validados sobre la micro red experimental del grupo de investigación TEP-192. Para ello, fue necesario el diseño, desarrollo e implementación de toda la electrónica de control, adquisición y electrónica de potencia para la correcta operación e integración de los equipos.Attending to the concept of Smart Grid, these systems are closely related to the use of renewable generation systems. Despite the benefits of this technology, its dependence on environmental resources makes it impo ssible to guarantee the balance of energy between generation and demand at all times. Far this, the hybridization of systems, as well as the use of hydrogen-basedsystems, is shown as a viable technical solution to salve or mitigate the probel ms associated with this type of technologies. The use of this type of hybrid systems poses a greater compel xity in terms of managementdue to the high number of parameters and factors to be taken into account in arder to guarantee an optimal energy distribution dependingon the application and the energy status of the system. In this sense, certain aspects associated with the actual operation of the systems, such as the topology, the operating and maintenance costs, the need far a charge voltage control far batterie s, the degradation of equipment, dynamics of each system, the lossesassociated with the working point, or parameters related to the quality of the electricity supply.In the light of the above, it is necessary to use energy management strategies to determine the energy distribution between devices, in arder to optimize the response of the system from a technicaland economic point of view, thereforeposing a multi-objective optimization problem. In arder to respond to the proposed multiobjective optimization problem, in this Thesis, a distributed control architecture is used, composed of local controllers at th e first level, and at the top level, the use of a supervisory controlel r based on predictive control techniques (MPC). The main function of the proposed controlel r is to det ermine the operating setpoint of each of the equipment that makes up the Smart Grid, responding to the proposed objective function accordingto the system design criteria. The advantages of using predictive control techniques over other types of techniques are clear; allows the use of multivariable control techniques, allowing multiobjective optimization in constrained problems; as well as implementing a control strategy based on a prediction horizon, which allows the system to adapt the response of the controller based on future events, improvingthe response of the system against merely passive control techniques. As a knowledge base of the proposed controller, this Thesis presents a general discrete linear model of the plant, calculated in each sampling period, based on a recursive linearization, which allows to increase the quality of the model with respectto solutions based on lathe to a singlepoint of linearization. The model includes all the necessary parameters far the control of a real plant, including the terms associated with the energy status of the system, battery operating voltage, as well as technical and economic parameters, such as degradation, losses or operating cost, with the objective of defining a system cost function that allows its generality far any type of application or design objective. Based on the design of the proposed controller, and with the objective of guaranteeing the generality required throuqhout the orocess. in this Thesis a desian methodoloav basedon the orooosed model and a cost function that includes ali the necessary technical and economic parameters are proposed to solve the proposed multiobjective optimization problem, regardless of the application and system topology. This objective function allows to establish a tracking problem according to the instantaneous power balance of the system, while the technical and economic parameters associated with the system response are considered, see equipment degradation and performance, limits and operating dynamics, operation and maintenance costs, battery charging criteria, etc. To guarantee the generality of the proposed controller, thus promoting its use, regardless of the application and topology of the system, this Thesis proposes a design and tuning methodology of the controller parameters, according to the proposed objective function and the design criteria in terms of priority of use and energy distribution. The methodological proposal is based on the cause-effect relationships between the different parameters, which allow defining the behavior of the system according to the energy management strategy and proposed design objectives. Similarly, in order to consider the short and long-term optimization of the system, limited by the concept of the sliding horizon typical of predictive control techniques, additional control techniques are used, which act directly on the process of adjustment of the parameters of the controller. In this sense, based on the history of the system, the parameters of the controller are recalculated, if necessary, acting directly on the weighting parameters, in such a way that it allows adapting the dynamic response or energy distribution according to the controller design criteria. Finally, the design methodology and the proposed controller were validated on the experimental micro grid of the TEP-192 research group. For this, it was necessary to design, develop and implement ali the control, acquisition and power electronics for the correct operation and integration of the equipment

Partner selection in green supply chains using PSO – a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer

The potential of additive manufacturing in the smart factory industrial 4.0: A review

Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations

A systematic mapping of the advancing use of machine learning techniques for predictive maintenance in the manufacturing sector

The increasing availability of data, gathered by sensors and intelligent machines, is chang-ing the way decisions are made in the manufacturing sector. In particular, based on predictive approach and facilitated by the nowadays growing capabilities of hardware, cloud-based solutions, and new learning approaches, maintenance can be scheduled—over cell engagement and resource monitoring—when required, for minimizing (or managing) unexpected equipment failures, improving uptime through less aggressive maintenance schedules, shortening unplanned downtime, reducing excess (direct and indirect) cost, reducing long-term damage to machines and processes, and improve safety plans. With access to increased levels of data (and over learning mechanisms), companies have the capability to conduct statistical tests using machine learning algorithms, in order to uncover root causes of problems previously unknown. This study analyses the maturity level and contributions of machine learning methods for predictive maintenance. An upward trend in publications for predictive maintenance using machine learning techniques was identified with the USA and China leading. A mapping study—steady set until early 2019 data—was employed as a formal and well-structured method to synthesize material and to report on pervasive areas of research. Type of equipment, sensors, and data are mapped to properly assist new researchers in positioning new research activities in the domain of smart maintenance. Hence, in this paper, we focus on data-driven methods for predictive maintenance (PdM) with a comprehensive survey on applications and methods until, for the sake of commenting on stable proposal, 2019 (early included). An equal repartition between evaluation and validation studies was identified, this being a symptom of an immature but growing research area. In addition, the type of contribution is mainly in the form of models and methodologies. Vibrational signal was marked as the most used data set for diagnosis in manufacturing machinery monitoring; furthermore, supervised learning is reported as the most used predictive approach (ensemble learning is growing fast). Neural networks, followed by random forests and support vector machines, were identified as the most applied methods encompassing 40% of publications, of which 67% related to deep neural network with long short-term memory predominance. Notwithstanding, there is no robust approach (no one reported optimal performance over different case tests) that works best for every problem. We finally conclude the research in this area is moving fast to gather a separate focused analysis over the last two years (whenever stable implementations will appear)

Performance-Based Specifications: Exploring When They Work and Why

There is extensive research and attention on innovation and sustainable public procurement (SPP) in the European Union at present, with the 2014 revision of the Procurement Directives, the Innovation Union strategy and other European Union policy initiatives. This report seeks to contribute to this discussion through the investigation of the use of performance based specifications (PBSs) in public procurement in the European Union and the United States. The report outlines the benefits and limitations of the use of PBSs, even in the most "progressive" public procurement environments, such as the Netherlands, particularly around their ability to support sustainable development goals and deliver environmental benefits for a procuring authority, such as energy and resource efficiency. Additionally, this report aims to identify the sectors in which the enabling conditions for the successful use of PBSs in public procurement are in place and to understand what policies and regulations are needed to promote the use of PBSs in public tenders and public procurement framework agreements

Advancing the Frontier of Extended Producer Responsibility: The management of waste electrical and electronic equipment in non-OECD countries

Waste electrical and electronic equipment (WEEE) has become a salient issue in non-OECD countries. With a growing awareness about serious damages to the environment and human health from a lack of safe treatment and recycling of WEEE, there has been a search for policy responses in several of these countries. This research finds that extended producer responsibility (EPR), a policy principle that underpins WEEE programmes in many OECD countries, can help solve the WEEE problem in non-OECD countries by putting the onus on the producers to ensure environmentally sound management of their end-of-life products and make improvements in their product systems, including change in product design. Although there are challenges to the implementation of EPR in emerging and developing economies, notably the problem of free riders and the competition for materials from the polluting recycling sector, they are manageable. In addition, opportunities exist that can facilitate the development of EPR-based solutions, such as the relatively small stock of historical WEEE and manufacturers that have the commitment and experiences with the principle. What is needed to realise this potential is for the policy-makers to create a policy framework that allows and encourages product and system innovations from the producers

The consolidation process of the EU regulatory framework on nanotechnologies: within and beyond the EU case-by-case approach

The field of nanotechnologies has been the subject of a process of wide-ranging regulation, which covers two different trends. From the 2000s the European Commission and Parliament agreed on a type of adaptive, experimental and flexible approach, which had its apex with the Commission code of conduct on responsible nano-research developed through a set of consultations. In 2009 this initial agreement subsequently broke down and the EU started to develop a set of regulatory initiatives of a sectoral nature in several fields (cosmetics, food, biocides). Thus, the current arrangement of governance in the field of nanotechnologies appears to be a hybrid, which mixes forms belonging to the new governance method (consultations, self-regulation, agency, comitology committees, networking), working like a lung in the framework of EU policy, with more traditional tools belonging to the classic governance method (regulations, directives). This model of governance based on a case-by-case approach runs the risk of lacking coherence since it is exposed to sudden changes of direction when risks emerge and it has a weak anticipatory dimension due to both its excessive dependency on data collection and its insufficient use of upstream criteria, such as human rights, which should be used earlier, to allow anticipated intervention with a less intense use of hard law solutions

Transition UGent: a bottom-up initiative towards a more sustainable university

The vibrant think-tank ‘Transition UGent’ engaged over 250 academics, students and people from the university management in suggesting objectives and actions for the Sustainability Policy of Ghent University (Belgium). Founded in 2012, this bottom-up initiative succeeded to place sustainability high on the policy agenda of our university. Through discussions within 9 working groups and using the transition management method, Transition UGent developed system analyses, sustainability visions and transition paths on 9 fields of Ghent University: mobility, energy, food, waste, nature and green, water, art, education and research. At the moment, many visions and ideas find their way into concrete actions and policies. In our presentation we focused on the broad participative process, on the most remarkable structural results (e.g. a formal and ambitious Sustainability Vision and a student-led Sustainability Office) and on recent actions and experiments (e.g. a sustainability assessment on food supply in student restaurants, artistic COP21 activities, ambitious mobility plans, food leftovers projects, an education network on sustainability controversies, a transdisciplinary platform on Sustainable Cities). We concluded with some recommendations and reflections on this transition approach, on the important role of ‘policy entrepreneurs’ and student involvement, on lock-ins and bottlenecks, and on convincing skeptical leaders

Transplanting EU waste law:The European waste electrical and electronic equipment directives as a source of inspiration to Brazilian law and policy

What are the legal instruments and policy choices producing improvements in e-waste management strategies worldwide? Could they be used from one legal system to another? The EU’s tradition of focusing on waste management and setting goals and responsibilities for all stakeholders involved in products life-cycle is remarkable. Its progress in policy and legal instruments on the field throughout the years represent a source of inspiration to other jurisdictions outside the European Union. At the same time, there have been developments in Brazilian law on the topic of waste management through the National Policy on Solid Waste (NPSW), Brazil’s most recent Act, the NPSW is a mark of progress, specifying priority waste streams and demanding well-structured and implemented take-back systems. Nonetheless, there have been considerable difficulties with moving further. This book studies and analyses the process of drafting and implementing the WEEE Directives in the European member states (MS) with the aim of identifying key policy and legal instruments that have contributed to fully working national WEEE systems. Supported by the Legal Transplants Theory it verifies the possibility for a jurisdiction to inspire others and, points out which lessons could be learned from the European experience that could contribute to the development of the corresponding laws in Brazil