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 MULTI-STAGE DECISION SUPPORT MODEL FOR COORDINATED SUSTAINABLE PRODUCT AND SUPPLY CHAIN DESIGN

In this research, a decision support model for coordinating sustainable product and supply chain design decisions is developed using a multi-stage hierarchical approach. The model evaluates alternate product designs and their corresponding supply chain configurations to identify the best product design and the corresponding supply chain configuration that maximizes the economic, environmental and societal benefits. The model considers a total life-cycle approach and incorporates closed-loop flow among multiple product lifecycles. In the first stage, a mixed integer linear programming model is developed to select for each product design an optimal supply chain configuration that maximizes the profit. In the subsequent stages, the economic, environmental and societal multiple life-cycle analysis models are developed which assess the economic, environment and the societal performance of each product design and its optimal supply chain configuration to identify the best product design with highest sustainability benefits. The decision support model is applied for an example problem to illustrate the procedure for identifying the best sustainable design. Later, the model is applied for a real-time refrigerator case to identify the best refrigerator design that maximizes economic, environmental and societal benefits. Further, sensitivity analysis is performed on the optimization model to study the closed-loop supply chain behavior under various situations. The results indicated that both product and supply chain design criteria significantly influence the performance of the supply chain. The results provided insights into closed-loop supply chain models and their behavior under various situations. Decision support models such as above can help a company identify the best designs that bring highest sustainability benefits, can provide a manager with holistic view and the impact of their design decisions on the supply chain performance and also provide areas for improvement

The Role Of System of Systems in Additive Manufacturing

The rapid growth in additive manufacturing technologies have brought various optimization techniques and methodologies to improve each phase that needs to be integrated and analyzed on system level to optimize the system performance. The challenges and limitations of each phase affect the system when integrated as a whole - creating a complex manufacturing environment that needs to be critically examined and managed. To have a better management of complex, emergent, and uncertain manufacturing system from design to recycling phase, a new way of thinking based on more holistic approach is necessary. In this paper, the system of systems paradigm (SoS) is introduced to treat additive manufacturing system as a whole and to present some SoS approaches that are based on holistic thinking. This paper provides a conceptual knowledge of SoS approach using systems principles, laws and approach emphasizing the characteristics and attributes of complex manufacturing system to the AM domain

Design of Closed Loop Supply Chains

Increased concern for the environment has lead to new techniques to design products and supply chains that are both economically and ecologically feasible. This paper deals with the product - and corresponding supply chain design for a refrigerator. Literature study shows that there are many models to support product design and logistics separately, but not in an integrated way. In our research we develop quantitative modelling to support an optimal design structure of a product, i.e. modularity, repairability, recyclability, as well as the optimal locations and goods flows allocation in the logistics system. Environmental impacts are measured by energy and waste. Economic costs are modelled as linear functions of volumes with a fixed set-up component for facilities. We apply this model using real life R&D data of a Japanese consumer electronics company. The model is run for different scenarios using different parameter settings such as centralised versus decentralised logistics, alternative product designs, varying return quality and quantity, and potential environmental legislation based on producer responsibility.supply chain management;reverse logistics;facility location;network design;product design

The Role Of System of Systems in Additive Manufacturing

The rapid growth in additive manufacturing technologies have brought various optimization techniques and methodologies to improve each phase that needs to be integrated and analyzed on system level to optimize the system performance. The challenges and limitations of each phase affect the system when integrated as a whole - creating a complex manufacturing environment that needs to be critically examined and managed. To have a better management of complex, emergent, and uncertain manufacturing system from design to recycling phase, a new way of thinking based on more holistic approach is necessary. In this paper, the system of systems paradigm (SoS) is introduced to treat additive manufacturing system as a whole and to present some SoS approaches that are based on holistic thinking. This paper provides a conceptual knowledge of SoS approach using systems principles, laws and approach emphasizing the characteristics and attributes of complex manufacturing system to the AM domain

TRANSFORMING A CIRCULAR ECONOMY INTO A HELICAL ECONOMY FOR ADVANCING SUSTAINABLE MANUFACTURING

The U.N. projects the world population to reach nearly 10 billion people by 2050, which will cause demand for manufactured goods to reach unforeseen levels. In order for us to produce the goods to support an equitable future, the methods in which we manufacture those goods must radically change. The emerging Circular Economy (CE) concept for production systems has promised to drastically increase economic/business value by significantly reducing the world’s resource consumption and negative environmental impacts. However, CE is inherently limited because of its emphasis on recycling and reuse of materials. CE does not address the holistic changes needed across all of the fundamental elements of manufacturing: products, processes, and systems. Therefore, a paradigm shift is required for moving from sustainment to sustainability to “produce more with less” through smart, innovative and transformative convergent manufacturing approaches rooted in redesigning next generation manufacturing infrastructure. This PhD research proposes the Helical Economy (HE) concept as a novel extension to CE. The proposed HE concepts shift the CE’s status quo paradigm away from post-use recovery for recycling and reuse and towards redesigning manufacturing infrastructure at product, process, and system levels, while leveraging IoT-enabled data infrastructures and an upskilled workforce. This research starts with the conceptual overview and a framework for implementing HE in the discrete product manufacturing domain by establishing the future state vision of the Helical Economy Manufacturing Method (HEMM). The work then analyzes two components of the framework in detail: designing next-generation products and next-generation IoT-enabled data infrastructures. The major research problems that need to be solved in these subcomponents are identified in order to make near-term progress towards the HEMM. The work then proceeds with the development and discussion of initial methods for addressing these challenges. Each method is demonstrated using an illustrative industry example. Collectively, this initial work establishes the foundational body of knowledge for the HE and the HEMM, provides implementation methods at the product and IoT-enabled data infrastructure levels, and it shows a great potential for HE’s ability to create and maximize sustainable value, optimize resource consumption, and ensure continued technological progress with significant economic growth and innovation. This research work then presents an outlook on the future work needed, as well as calls for industry to support the continued refinement and development of the HEMM through relevant prototype development and subsequent applications

Redesign of the milk powder production chain: assessment of innovative technologies

The dairy industry is energy intensive, mainly due to the use of thermal processes. Milk powder production involves many thermal processes, resulting in a high energy consumption. Over the past decades the current production process has been optimized to a large extent. In order to make the next step forward in energy reduction, as well as in environmental impact, it is necessary to redesign the milk powder production chain. Introduction of new technologies will be the key. Membrane distillation is investigated as an alternative to evaporation for the concentration of milk. Furthermore, a closed loop spray drying system is proposed, aiming to reuse the latent and sensible heat of the exhaust air. Optimization of single process units has an influence on up- and downstream process units. Therefore, it is important to take the whole production chain into account. By combining existing and innovative technologies, evaluating them on energy usage, LCA aspects, and economic aspects different processing chains are optimised. The result is an improved milk powder production chain.</p

A contribution to support decision making in energy/water sypply chain optimisation

The seeking of process sustainability forces enterprises to change their operations. Additionally, the industrial globalization implies a very dynamic market that, among other issues, promotes the enterprises competition. Therefore, the efficient control and use of their Key Performance Indicators, including profitability, cost reduction, demand satisfaction and environmental impact associated to the development of new products, is a significant challenge. All the above indicators can be efficiently controlled through the Supply Chain Management. Thus, companies work towards the optimization of their individual operations under competitive environments taking advantage of the flexibility provided by the virtually inexistent world market restrictions. This is achieved by the coordination of the resource flows, across all the entities and echelons belonging to the system network. Nevertheless, such coordination is significantly complicated if considering the presence of uncertainty and even more if seeking for a win-win outcome. The purpose of this thesis is extending the current decision making strategies to expedite these tasks in industrial processes. Such a contribution is based on the development of efficient mathematical models that allows coordinating large amount of information synchronizing the production and distribution tasks in terms of economic, environmental and social criteria. This thesis starts presents an overview of the requirements of sustainable production processes, describing and analyzing the current methods and tools used and identifying the most relevant open issues. All the above is always within the framework of Process System Engineering literature. The second part of this thesis is focused in stressing the current Multi-Objective solution strategies. During this part, first explores how the profitability of the Supply Chain can be enhanced by considering simultaneously multiple objectives under demand uncertainties. Particularly, solution frameworks have been proposed in which different multi-criteria decision making strategies have been combined with stochastic approaches. Furthermore, additional performance indicators (including financial and operational ones) have been included in the same solution framework to evaluate its capabilities. This framework was also applied to decentralized supply chains problems in order to explore its capabilities to produce solution that improves the performances of each one of the SC entities simultaneously. Consequently, a new generalized mathematical formulation which integrates many performance indicators in the production process within a supply chain is efficiently solved. Afterwards, the third part of the thesis extends the proposed solution framework to address the uncertainty management. Particularly, the consideration of different types and sources of uncertainty (e.g. external and internal ones) where considered, through the implementation of preventive approaches. This part also explores the use of solution strategies that efficiently selects the number of scenarios that represent the uncertainty conditions. Finally, the importance and effect of each uncertainty source over the process performance is detailed analyzed through the use of surrogate models that promote the sensitivity analysis of those uncertainties. The third part of this thesis is focused on the integration of the above multi-objective and uncertainty approaches for the optimization of a sustainable Supply Chain. Besides the integration of different solution approaches, this part also considers the integration of hierarchical decision levels, by the exploitation of mathematical models that assess the consequences of considering simultaneously design and planning decisions under centralized and decentralized Supply Chains. Finally, the last part of this thesis provides the final conclusions and further work to be developed.La globalización industrial genera un ambiente dinámico en los mercados que, entre otras cosas, promueve la competencia entre corporaciones. Por lo tanto, el uso eficiente de las los indicadores de rendimiento, incluyendo rentabilidad, satisfacción de la demanda y en general el impacto ambiental, representa un area de oportunidad importante. El control de estos indicadores tiene un efecto positivo si se combinan con la gestión de cadena de suministro. Por lo tanto, las compañías buscan definir sus operaciones para permanecer activas dentro de un ambiente competitivo, tomando en cuenta las restricciones en el mercado mundial. Lo anterior puede ser logrado mediante la coordinación de los flujos de recursos a través de todas las entidades y escalones pertenecientes a la red del sistema. Sin embargo, dicha coordinación se complica significativamente si se quiere considerar la presencia de incertidumbre, y aún más, si se busca exclusivamente un ganar-ganar. El propósito de esta tesis es extender el alcance de las estrategias de toma de decisiones con el fin de facilitar estas tareas dentro de procesos industriales. Estas contribuciones se basan en el desarrollo de modelos matemáticos eficientes que permitan coordinar grandes cantidades de información sincronizando las tareas de producción y distribución en términos económicos, ambientales y sociales. Esta tesis inicia presentando una visión global de los requerimientos de un proceso de producción sostenible, describiendo y analizando los métodos y herramientas actuales así como identificando las áreas de oportunidad más relevantes dentro del marco de ingeniería de procesos La segunda parte se enfoca en enfatizar las capacidades de las estrategias de solución multi-objetivo, durante la cual, se explora el mejoramiento de la rentabilidad de la cadena de suministro considerando múltiples objetivos bajo incertidumbres en la demanda. Particularmente, diferentes marcos de solución han sido propuestos en los que varias estrategias de toma de decisión multi-criterio han sido combinadas con aproximaciones estocásticas. Por otra parte, indicadores de rendimiento (incluyendo financiero y operacional) han sido incluidos en el mismo marco de solución para evaluar sus capacidades. Este marco fue aplicado también a problemas de cadenas de suministro descentralizados con el fin de explorar sus capacidades de producir soluciones que mejoran simultáneamente el rendimiento para cada uno de las entidades dentro de la cadena de suministro. Consecuentemente, una nueva formulación que integra varios indicadores de rendimiento en los procesos de producción fue propuesta y validada. La tercera parte de la tesis extiende el marco de solución propuesto para abordar el manejo de incertidumbres. Particularmente, la consideración de diferentes tipos y fuentes de incertidumbre (p.ej. externos e internos) fueron considerados, mediante la implementación de aproximaciones preventivas. Esta parte también explora el uso de estrategias de solución que elige eficientemente el número de escenarios necesario que representan las condiciones inciertas. Finalmente, la importancia y efecto de cada una de las fuentes de incertidumbre sobre el rendimiento del proceso es analizado en detalle mediante el uso de meta modelos que promueven el análisis de sensibilidad de dichas incertidumbres. La tercera parte de esta tesis se enfoca en la integración de las metodologías de multi-objetivo e incertidumbre anteriormente expuestas para la optimización de cadenas de suministro sostenibles. Además de la integración de diferentes métodos. Esta parte también considera la integración de diferentes niveles jerárquicos de decisión, mediante el aprovechamiento de modelos matemáticos que evalúan lasconsecuencias de considerar simultáneamente las decisiones de diseño y planeación de una cadena de suministro centralizada y descentralizada. La parte final de la tesis detalla las conclusiones y el trabajo a futuro necesario sobre esta línea de investigaciónPostprint (published version

MODELING AND OPTIMIZATION TO EVALUATE SUSTAINABILITY PERFORMANCE OF CUSTOMIZABLE PRODUCT SERVICE SYSTEMS

The aim of this thesis is to present a new methodology to evaluate and optimize sustainability of customizable product-service systems while ensuring economic, environmental and societal constraints are also satisfied. Activities across the total product lifecycle are considered to develop a model that evaluates closed-loop flow, while being monitored through the growth, maturity and decline stages of the product to provide a comprehensive analysis. A novel method to evaluate the customer satisfaction is also presented. The research considers a modular product where customization can be achieved by selecting from alternatives while ensuring the compatibility between these alternatives. A manufacturer will be able to use the tool developed to optimize the business models developed by maximizing their profitability, satisfying regulatory and customer requirements, and evaluating the metrics that determine the sustainability of the product. The tool primarily uses a Microsoft Excel based platform for calculation and analysis while using ILOG OPL software for optimization. The sensitivity analysis provides examples of the variety of information that can be generated through the model according to the interests of the user. The results demonstrate the usefulness of the tool as a ‘sustainable product configurator’ which can be integrated with conventional product configurators after further refinement