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As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Since sustainable scheduling is arousing increasing attention from many manufacturing enterprises and energy consumption is a core problem regarding sustainability, the purpose of this paper is to develop an energy-efficient scheduling method to fulfill material delivery tasks in mixed-model assembly lines. In this research, the objective of minimizing the energy consumption is jointly integrated with the operational criterions when executing material delivery tasks. Owing to the NP-hard nature of the considered problem, a Taboo enhanced Particle Swarm Optimization (TEPSO) algorithm is developed to solve the multi-objective problem. Several improving strategies are applied to enhance the performance of the proposed TEPSO in order to obtain a stronger local search capability and faster search speed. The performance of the proposed TEPSO algorithm is evaluated by comparing with two other high-performing multi-objective optimization methods. Computational experiments are conducted in order to test and verify the effectiveness and efficiency of the proposed TEPSO algorithm. The achievements reported in this paper might be inspiring for further studies on energy-efficient production scheduling. [ABSTRACT FROM AUTHOR]

The role of smart technologies can become very important and useful to solve the main population issues nowadays and provide foundations for a sustainable future. A smart approach is an opportunity for knowledge integration, necessary to solve crucial problems of contemporary societies. Today, the main challenge is to reduce the effects of global warming and ensure a balanced economic development of society. The close collaboration of all involved engineering professions is mandatory to achieve interdisciplinary synergies and can bridge challenging engineering tasks. Intense research efforts should be directed towards balanced resource utilization, efficient energy conversion technologies, integration of renewable energy systems, effective approaches to enable circular economy framework, effective process integration as well as other issues important to the population. This review editorial is primarily focused on the contributions presented at the 3rd International Conference on Smart and Sustainable Technologies held in Split, Croatia, in 2018 (SpliTech2018). The SpliTech2018 conference was a multidisciplinary event with research topics related to the main conference tracks, i.e. Smart City/Environment, Energy, Engineering Modelling and e-Health. The strategic focus of the conference was to help solve crucial issues of our times, mainly related to the sustainability and smart utilisation of limited and valuable resources. This contribution brings new ideas and discusses present issues as well as challenges that should lead towards a sustainable future based on the application of the smart technologies. The herein addressed papers bring together latest research progress into four main topic areas: (i) Green Buildings, Energy Use and Consumption, (ii) Solar Energy Utilisation, (iii) Efficiency and Waste Elimination, (iv) Smart Cities and Internet of Things. The main results of this introduction review article include a discussion of different concepts and technologies that bring further development on a broad range of topics focused on efficiency improvement, smart and sustainable resource management, cleaner production concepts and on the discussion of the various actions which would lead towards a sustainable future. [ABSTRACT FROM AUTHOR]

Hot embossing is an efficient technology for the fabrication of glass micro- and nanostructures. However, the long cycle time, high energy consumption, and high nitrogen emissions in traditional hot embossing approach hinders sustainable production of glass micro-optics. Therefore, this paper proposes a novel two-stage gravity-assisted hot embossing process that enables the fabrication of high-quality glass micro-pillar arrays in a rapid, green manner. In this approach, the two-stage gravity loading unit provides accurate force on glass preform through a simple control system, and the tailor-made heating module based on Si 3 N 4 ceramic heaters requires an energy consumption of just 700 kJ per molding cycle. As a result, the proposed approach is featured by low energy consumption and high manufacturing efficiency. In this study, the effects of the embossing temperature, force, and time on the replication accuracy of a K9 glass micro-pillar array were investigated through a series of hot embossing experiments. Afterward, the form accuracy, uniformity of microstructures, and warpage of glass replicas under the optimal process parameters were evaluated separately. Finally, repeated hot embossing experiments were conducted to demonstrate the reproducibility of the hot embossing process. The experimental results show that embossing temperature had the most significant effect on the replication accuracy of glass micro-pillars. By optimizing the process parameters, the embossed glass micro-pillars could achieve transfer ratios of 99.00% and 95.14% in height and diameter, respectively. Moreover, the surface roughness of glass micro-pillars was less than 5 nm, and the warpage amplitude of glass replicas in a 3.9 × 3.9 mm area was smaller than 1 μm. The small discrepancy in geometric features of glass replica in the repeated trails reflects the satisfactory reproducibility of this hot embossing process on the micro and nano scales. The results indicate the strong industrialization potential of the proposed two-stage gravity-assisted hot embossing machine and hot embossing process for fabricating high-quality glass microstructures more cleanly and sustainably. • A novel gravity-assisted rapid high-temperature hot embossing apparatus is developed. • A novel hot embossing process is designed for fabricating high-quality glass micro-pillar arrays in a cleaner manner. • Effects of process parameters on the replication accuracy of glass micro-pillar arrays are evaluated. • Form deviation, uniformity of microstructures as well as warpage of glass replica are analyzed. • The reproducibility in replicating geometric features in the novel hot embossing process is demonstrated. [ABSTRACT FROM AUTHOR]

Abstract The more efficient use of energy is a policy issue worldwide. Smart use of technology and management of information is becoming crucial for increasing energy efficiency. The 7th Framework Program of the European Union supported international research to fulfill the potential of Information and Communications Technologies for Energy Efficiency. Using Social Network Analysis, this paper analyzes this research network and explores the links and influences in the cross-country knowledge flows generated. The analysis identifies some important differences in the position that countries hold on the network. Results highlight the importance of countries acting as hubs and gatekeepers in the promotion of research and the improvement of energy efficiency. Highlights • The network of the 7th Framework Programme on Information and Communication Technologies for energy efficiency is studied. • Countries with a central position in the research network benefit from energy efficiency gains. • A fast access to knowledge does not guarantee efficiency improvements. • Climate-resilient countries tend to have more adaptation in terms of efficiency. [ABSTRACT FROM AUTHOR]

Legislation targeting business carbon emissions typically excludes the significant portion of the economy comprised of small- and medium-sized enterprises (SMEs). As an alternative many governments have developed voluntary programs to assist SMEs to reduce emissions and increase their energy efficiency. To maximise benefits associated with such programs, this paper seeks to provide insights into key factors contributing to the design of successful voluntary energy efficiency programs for SMEs. This is achieved by comprehensively analysing the factors that impacted the uptake of energy savings measures by 202 SMEs which participated in the ClimateSmart Business Cluster Program (commencing in 2009). Expanding on previous research that has mostly focus on identifying inhibiting factors (barriers) to the uptake of energy savings measures, this paper offers a comprehensive assessment of barriers and motivating factors (motivators). A unique finding of this research is that SMEs experienced many different barriers and motivators while participating in the program, inferring great complexity to achieving the critical aim of reducing carbon emissions. Based on these findings, this paper argues that voluntary government energy efficiency programs should be flexibly designed and implemented to accommodate the many and various barriers. Motivating factors should be emphasised and barriers identified upfront so that the program can be tailored to the often idiosyncratic needs of SMEs. [ABSTRACT FROM AUTHOR]

This paper focuses on an analysis of the energy mix profile and energy efficiency of the Brazilian dairy industry. It investigates dairies’ energy mix and energy efficiency and identifies some actions for a cleaner energy mix. Primary data from 37 dairy cheese-making establishments distributed among the Brazilian regions were obtained from online surveys. The results indicate that woodfuel plays a critical role, being the most used fuel in thermal energy generation, while diesel is dominant in electric generation. It also emphasizes that only 51% of the dairy establishments utilize electric energy generators. Other alternative biomass sources are still incipient in the sector, restricted to just 9.5% of the cases for thermal energy generation and no cases for electricity. Regarding the energy efficiency analysis, the results suggest dairies are more scale efficient than pure technical efficient. However, the dairies present a low energy efficiency level. There is no evidence that inefficiencies are differently distributed according to their size. These findings are important for government agencies, industry associations, scientists, universities and research institutes. High inefficiencies, regarding the use of electricity and thermal energy, are a key issue in sustainable bioenergy production. [ABSTRACT FROM AUTHOR]

Issues relating to the illumination of historical minor centers have taken on increasing significance in debates on urban rehabilitation. Interventions must ensure balance with the surrounding environment whilst implementing high-efficiency, energy-environment systems, and enhance architectural structures. The research presented in this paper aims to identify appropriate strategies and effective criteria for lighting design in historical centers. The methodology developed is based on transcalar analysis and has been applied to a village in the Abruzzo Region (Italy). The methodology involved surveys carried out in the urban context together with up-to-date and detailed analyses aimed at highlighting the criticalities and potentialities of the village in the case study. This allowed the elaboration of intervention strategies applied to two different areas: one within the historical nucleus of the village and the other in a peripheral area. This research has contributed to enriching the current debate on so-called “inland areas”, including developing new ways to benefit from the special characteristics of these areas and implementing more sustainable action. [ABSTRACT FROM AUTHOR]

Nowadays, industrial enterprises are facing up to new challenges to well optimize their performances, with regards not only to conventional performances (e.g. reliability or productivity) but also to emerging ones as those related to sustainability issues. Indeed, sustainability indicators have to be considered now in the decision-making process of the plant to better control and maintain it to be consistent with Green Production requirements. In that way, indicators such as Energy Efficiency or Energy Consumption are promoted for the impact they have on these requirements in a Life Cycle Cost vision. Thus the core idea defended in this paper is addressing the necessary evolution of conventional maintenance decision-making process in industry for considering the energy efficiency indicator. To support the idea, the first objective is to define the concept of energy efficiency indicator which materializes the energy efficiency performance at a specific time. The definition is done for different abstraction levels such as component, function, system which are subjected to time-dependent degradation behaviors. So, the energy efficiency indicator concept is expressed as the amount of energy consumed per unit of useful output, which has to be seen as a sustainable performance measure of industrial system. Then a mathematical formulation is proposed to calculate energy efficiency indicator at any time of the performance by considering dependent factors (static and dynamic ones) impacting inputs and outputs of the system. The second objective is to propose a new concept named REEL (Remaining energy-efficient lifetime) for tracking the energy efficiency performance evolution. The REEL is defined by the time left before the system loses its energy efficiency property considered as a specific EEI value (EEI threshold) not to be exceeded. This specific value is technically and/or economically fixed in advance, given the current condition, past and future operation profiles. The REEL could be used as an appropriate indicator for maintenance decision-making process in a proactive vision. The third objective is to formalize a generic approach in the way assess the REEL value. The assessment requires to forecast the evolution of energy efficiency indicator (whatever the abstraction level is) by taking into account the static and dynamic factors. Finally, the feasibility and added value of our proposals are illustrated on a manufacturing platform named TELMA (TELeMAintenance). [ABSTRACT FROM AUTHOR]

Environmental Sustainability is one of the ‘Grand Challenges’ for manufacturing success in the 21st century. The present article mainly focuses on energy use during the manufacturing steps used for assembling products. In particular, industry still needs systematic and reliable ways to capture information for ultimately accounting for energy efficiency in manufacturing processes. For that purpose, an information model in the form of a formal ontology was created using information elements as building blocks, which emerge from manufacturing process models, supply chain operations, manufacturing process parameters, 3D form features and exergy-based thermodynamic analysis. These information elements were integrated by means of semantic relationships in an ontology. Once this information model was constructed, an application example of a welded hull panel assembly was used for verification of the model's representativeness and completeness. Results show that it is feasible to correlate all required data by means of semantic relationships for estimating energy efficiency indicators prior to physical prototyping, or ultimately comparing different alternatives for manufacturing processes regarding energy efficiency. However, manufacturing processes must be described in detail in order to allow energy efficiency analyses. In addition, geometric models need to be able to represent form features that can best relate to specific manufacturing process parameters. And finally, energy efficiency indicators, such as the degree-of-perfection can be derived from a comprehensive thermodynamic analysis, to be performed in each individual process step. Results indicate it is possible to provide an information structure for the calculation of the degree-of- perfection associated with an exergy-based thermodynamic analysis in assembly processes. Therefore, it has the potential to serve as a basis for a unifying framework for developing software applications that could allow the calculation of the degree of perfection in manufacturing operations. In addition, the resulting information model may facilitate data integration in the extended enterprise environment as well as the development of standards that can lead to seamless interoperability of manufacturing information systems. This paper presents the means by which energy efficiency can be accessed directly from an integrated semantic model, and opens the possibility to be extended for many different sorts of manufacturing processes. [ABSTRACT FROM AUTHOR]

Increased competition and reduced profit margins are pushing manufacturing plants to find ways to improve operational efficiency and reduce costs. At the same time, government incentives and community initiatives are encouraging the industrial sector to pursue sustainability in operation and energy consumption. This has introduced a paradigm shift where the focus of plant operation is moving from solely cost reduction to one that considers asset management, emission control, and utilization of alternative energy resources. Mathematically speaking, the problem is changing from a single objective optimization to one with multiple objective functions that may at times be contradictory. The focus of this paper is to propose a methodology for management of an industrial plant considering the above factors. It is assumed that the plant is equipped with distributed generation (DG), and can also participate in demand response (DR). Further, the effect of ambient temperature on the lifetime and available capacity of assets such as the plant transformer has been taken into account and incorporated into their daily schedule. The objective is then to find an optimal solution for operating various workstations in such a way that it minimizes the operational costs, the emissions produced, and the loss of life of assets exposed to excess temperatures. A multi-objective optimization problem is therefore formulated through extended lexicographic goal programming, which is further modified to ensure Pareto optimality. A case study has also been presented for a manufacturing plant for luxury vehicle cockpit assembly line. [ABSTRACT FROM AUTHOR]

This paper aims to develop an optimal real-life energy-efficient design for a production plant within the concept of the circular economy. The problem is to install a Heat Recovery System (HRS) that utilizes the hot oil used by the compressors to heat the water for the central heating system. To achieve the desired level of energy efficiency this design problem must be formulated from both the optimization and sustainability points of view. Additionally, this design problem must also consider the investment cost. In line with this purpose, this paper formulates this design problem as an optimization problem employing a mathematical programming approach as a single objective, and as a multi-objective optimization problem through a goal programming approach. Besides, this paper uses the return on investment as a key performance indicator, since it deals with a real-life design problem with an investment cost. The related design problem is solved with the single objective and multi-objective versions of the developed mathematical programming model via a commercial solver to identify different design alternatives and hence giving the decision-maker to make a selection option. Finally, the capability of the developed mathematical programming model is tested on a set of randomly generated problems. The obtained results indicate that the developed mathematical programming model is a successful decision support system since its single and multi-objective versions are capable of identifying energy-efficient production designs within the context of the real-life problem on hand and the circular economy. • A real-life energy-efficient design problem for a production plant is undertaken. • A heat recovery system is proposed within the concept of a circular economy. • The problem is modelled from both the optimization and sustainability aspects. • The problem is formulated as multi-objective models using goal programming. • The models are solved to minimize investment costs and maximize energy efficiency. [ABSTRACT FROM AUTHOR]

Modern long distance ore pipeline systems are subject to strong costs, both from the economic and environmental standpoints. The task of assessing the relative importance of energy and water consumption without a detailed engineering analysis is often not obvious. In the present paper, the relative importance of water and energy unit costs is assessed by a novel dimensionless formulation accounting for the essential hydraulic and cost elements that conform the slurry transport. It is found that, for conditions resembling those of copper and iron concentrate pipelines, the ratio between energy and water costs has a wide range, depending on the particular transport conditions and unit cost scenarios. Although operating at similar volume fractions, results indicate that energy/water cost relations may differ between copper and iron concentrate pipelines and local conditions, thus suggesting the need to explicitly include energy and water cost in the design strategy. [ABSTRACT FROM AUTHOR]

The aim of Sustainable Development Goal 7 is to ensure access to affordable, reliable, sustainable and modern energy for all. Increased energy efficiency is particularly important in the construction industry because urban agglomerations currently consume up to 80% of global energy, 40% of which is attributable to buildings. In countries like Italy however, where historical buildings constitute a significant part of the building patrimony, improving energy efficiency is not always straightforward as interventions must take into account the historical materials used as well as the context of the construction. Therefore, the aim of this research was to establish a methodology that would identify the most effective means of achieving energy efficiency taking into account the historical aspects of a building and its cultural context. The methodology proposed and described in this paper involves: preliminary analyses to identify the elements of value and the level of transformability of facades; the selection of different insulating materials; dynamic simulations of building behaviour; analyses of intervention costs in relation to each type of insulation and finally the preparation of a multi-criteria matrix to identify the most effective method of improving energy efficiency of a historical wall with differing degrees of transformability. Each insulating material was analysed in relation to heating and cooling requirements and material cost impact. The methodology was applied to a case study in the Province of L'Aquila, Italy. In the paper a multicriteria framework, for the improvements in the thermal efficiency of a building, it is presented. Specifically the attention is focused on heating requirements, cooling requirements and cost impact. The results indicate that, with respect to historical building, it is possible to adopt strategies finalyzed to improve the energy efficiency of these buidings, contributing in this way, also toward the SDG7. Specifically, the best performance for a wall with a high level of transformability can be obtained using calcium silicate, extruded polystyrene, kenaf and hemp, whilst, in the case of a wall with a low level of transformability, the best materials are calcium silicate, polyurethane and linen fiber. Finally, in the case in which external constraints prevent the application of a thick coat and internally there is limited space, the use of calcium silicate was found to be the best energy efficient measure. [ABSTRACT FROM AUTHOR]

Industrial manufacturing is the largest end-use sector in terms of both final energy demand and greenhouse gas emissions (more than 30% of the total); its increase is rapidly altering the world climate. The need to mitigate the environmental impacts of manufacturing processes makes energy efficiency a key success factor for sustainable production. Accordingly, the scientific community's interest in energy management has grown considerably, resulting in several literature reviews on energy modelling and production systems analysis, emissions calculation, sustainability tools and benchmarking techniques. However, a comprehensive analysis of methods and tools aimed at improving energy awareness and assessing their effects on energy efficiency is lacking. To address this gap, this paper undertakes a systematic literature review of energy assessment methods and tools. From the 1367 papers retrieved by searching scientific literature databases, 64 scientific articles met the inclusion criteria and were analysed in detail. The study aims to provide scholars with a picture of the current state of scientific research and to identify the scientific works that could help industry practitioners in energy management. Following the ISO 50001 framework, the methods and tools were divided into three main groups (i.e. energy analysis, energy evaluation and energy-saving measures methods) and the specific findings relating to each group were synthesized. Finally, the paper addresses unresolved issues and challenges and makes suggestions for future research directions. • A systematic literature review of energy assessment methods and tools are provided. • Relevant concepts, themes and characteristics has been summarized. • A classification of energy assessment methods and tools has been presented. • The limits and the possible solution strategies to overcome them are discussed. [ABSTRACT FROM AUTHOR]

Dielectric medium (kerosene) between the tool electrode and workpiece forms a reaction product, owing to thermal effect of discharge in the process of electrical discharge machining (EDM), which is emitted from the surface in the form of harmful gas and may get into the operator's body by breath system inhalation and contact with skin. Therefore, exhaust emissions should be considered as important performance indicators for the green machining in the process of EDM. Moreover, energy efficiency and machining productivity should be improved and the cut process must take ecological constraints into consideration. Thereafter, the definition of green manufacturing helps to evaluate different and sometimes conflicting aspects of the manufacturing process, such as machining productivity, surface quality, energy efficiency and exhaust emissions. But it is difficult to dynamically adjust the weights of different aspects according to the actual processing conditions. This paper proposes a framework for optimization of cutting parameters to minimize energy consumption and exhaust emissions during electrical discharge machining of Al 6061 and SKD 11. Three cutting process parameters (peak current, pulse period, and duty cycle) are tested against material remove rate (MRR), surface roughness (Ra), energy efficiency per volume (EEV), and exhaust emissions characteristics (EEC) for EDM of these two materials. First, the process energy and exhaust emissions are analyzed. The results show that EEV is negatively correlated with surface quality (Ra) for both Al 6061 and SKD 11 material. Second, two data analyses (Taguchi and adaptive-network-based fuzzy inference system (ANFIS) analyses) are utilized to obtain high MRR and best Ra, EEV and EEC for the desired machining performances and environmental sustainability. It is found that the relative errors between the predicted values and experimental results of MRR, Ra, EEV and EEC are all not more than 20%, and found that the maximum of mean relative errors of them is 13.04%. Finally, a framework implemented by an optimization system, based on ANFIS, enhanced cuckoo search (ECS) algorithm and desirability function, is built to obtain the desired cutting parameters. It is found that high peak current (8.94A) and pulse period (500 μ s) are recommended to obtain multi-objective optimization for machining Al 6061, and that the optimal solutions of the EEV and EEC are significantly decreased, by 87.13% and 37.09%, respectively. Similarly, high peak current (8.77A) and pulse period (261.5 μ s) are recommended to obtain multi-objective optimization for machining SKD 11, and the optimal solutions of the EEV and EEC are significantly decreased, by 93.73% and 46.85%, respectively. Thereafter, it can be concluded from the above research that the proposed technique offers significant advantages and potential for applications in the green manufacturing field. Image 1 • Energy efficiency per volume was negatively correlated with Ra. • Maximizing energy efficiency and minimizing exhaust emissions by empirical models were obtained. • Balancing the machining performances and environmental sustainability was considered. • An optimization system with manual multi-objective weights was build. • Green regions of exhaust-friendly and energy-friendly were acquired. [ABSTRACT FROM AUTHOR]