An efficient k-means clustering algorithm: Analysis and implementation. After analyzing 70 research papers, it was found that only a minority of papers had resource efficiency as an explicit objective. ; methodology, L.W. Lane, S.; Martin, E.B. United States Data Center Energy Usage Report, The Art of Survival: Tourism Businesses in Thailand Recovering from COVID-19 through Brand Management, Determination of Soil Hydraulic Parameters and Evaluation of Water Dynamics and Nitrate Leaching in the Unsaturated Layered Zone: A Modeling Case Study in Central Croatia, An Authoritative Study on the Near Future Effect of Artificial Intelligence on Project Management Knowledge Areas, AI and Machine Learning towards Circular and Sustainable Industry, http://publica.fraunhofer.de/eprints/urn_nbn_de_0011-n-5491073.pdf, https://pub.towardsai.net/differences-between-ai-and-machine-learning-and-why-it-matters-1255b182fc6, https://www.ibm.com/cloud/blog/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks, https://sud.vdma.org/documents/15012668/26742261/!VDMA%20Quick%20Guide_Machine%20Learning_EN_1553781666349.pdf/47bd499f-087d-4650-0af6-a569d7825b0d, https://www.ressource-deutschland.de/fileadmin/user_upload/downloads/studien/VDI-ZRE_Studie_KI-betriebliche-Ressourceneffizienz_Web_bf.pdf, https://www.vdi.de/en/home/vdi-standards/details/vdi-4800-blatt-1-resource-efficiency-methodical-principles-and-strategies, https://www.ressource-deutschland.de/fileadmin/Redaktion/Bilder/Newsroom/Studie_Ressourceneffizienz_durch_Industrie_4.0.pdf, https://www.umweltbundesamt.de/publikationen/glossar-ressourcenschutz, https://eta-publications.lbl.gov/sites/default/files/lbnl-1005775_v2.pdf, https://creativecommons.org/licenses/by/4.0/, Naive Bayes classification; decision trees, Classification; modeling, language processing, Image recognition; modeling, language processing. This means that if a source deals with resource efficiency, it usually takes several aspects directly into account. We would like to thank VDI Zentrum fr Ressourceneffizienz GmbH for the professional management and Deloitte Consulting GmbH for the realization of the entire study Potenziale der schwachen knstlichen Intelligenz fr die betriebliche Ressourceneffizienz. The project has accrued almost $50million in annual savings so far. 2021; 13(12):6689. Traditional lean improvements often result in sustainability benefits as a byproduct. Ten activities are analyzed, including pig iron production, aluminum . Zendehboudi, A.; Baseer, M.; Saidur, R. Application of support vector machine models for forecasting solar and wind energy resources: A review. How to measure resource efficiency How to improve resource efficiency What is resource efficiency? Since the COVID-19 crisis started, sustainability and resource productivity have returned to the very top of the agenda for governments, investors, and customers. Within 47 papers, this was just seen as a positive side effect. ; Beghi, A.; McLoone, S. Anomaly detection through on-line isolation Forest: An application to plasma etching. Feature papers represent the most advanced research with significant potential for high impact in the field. This identity, first developed in the 1970s, is commonly used . The limits here are determined by the theoretical maximum efficiency of a process. Willenbacher, M.; Wohlgemuth, V. Einsatzmglichkeiten von Methoden der Knstlichen Intelligenz zur Optimierung von Stoff- und Energiestrmen und prototypische Umsetzung auf der Basis von Stoffstromnetzen. Energy efficiency and conservation - U.S. Energy Information Those changes are often beguilingly simple, such as repairing leaking steam traps, adjusting excess oxygen levels to optimize boiler combustion, or enforcing the correct settings on machines. Predictive maintenance, in this context, is made possible by recording relevant time series data over the use phase of a machine. . Sustainability improvements in industrial production are essential for tackling climate change and the resulting ecological crisis. ; Steinhilper, R. Pattern recognition in load profiles of electric drives in manufacturing plants. This section is divided into two subsections. Production planning can additionally be supported by analyzing and classifying different production methods, e.g., with regard to efficiency. Yang, Y.; Juntao, L.; Lingling, P. Multi-robot path planning based on a deep reinforcement learning DQN algorithm. Improving crop productivity and resource use efficiency to ensure food These are intended to map and monitor the condition of the infrastructure being analyzed. Principal component analysis: A review and recent developments. the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, Other aspects, such as human resources, system or product efficiency, are not considered in this paper and could be part of further research. Improvements in nitrogen (N) use efficiency (NUE) and water productivity (WP) are critical for sustainable agriculture. Available online: Wang, P. On Defining Artificial Intelligence. They were aided by new analytical tools that helped them identify and evaluate the impact of detailed process changes. ; Jau, L.W. Reger, A.; Oette, C.; Aires, A.P. ; Tegmark, M.; Nerini, F.F. Kaelbling, L.P.; Littman, M.L. ; Ibrahim, Z.; Khalid, M. A Hybrid Artificial Neural Network-Naive Bayes for solving imbalanced dataset problems in semiconductor manufacturing test process. Economic efficiency refers to how effectively a society's scarce resources are used to produce goods. 413422. ; Tama, B.A. Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive Among other things, they promised to take back from customers products at the end-of-life stage and to develop second-life markets and remanufacturing programs. That metric, we found, is compellingly simple: profit per hour. Hochreiter, S.; Schmidhuber, J. Multiple requests from the same IP address are counted as one view. ; Schtze, A. Vergleich Subjektiver und Automatisierter Merkmalsextraktion Sowie Einsatz Maschineller Lernalgorithmen zur Mikromagnetischen Materialcharakterisierung. Among those, energy efficiency was the most commonly addressed resource efficiency aspect. [. This scale includes: High influence, if a paper states an improvement in a resource efficiency aspect of 1% or more; Potential influence, if the AI application is able to improve a resource efficiency aspect, e.g., by optimizing a process and decreasing product errors. Operational trend prediction and classification for chemical processes: A novel convolutional neural network method based on symbolic hierarchical clustering. Glass furnaces typically operate at very high temperatures (1,200C to 1,700C) and process large volumes of material (300 to 600metric tons per day). Resource efficiency - OECD All these additions serve as checks and balances that can significantly increase the amount of recyclables your MRF can handle. Adamczak, S.; Wrzochal, M.; Durakbasa, N. Evaluation of a non-contact method for measuring vibration of rolling bearings in industrial conditions. [. Frontiers | A Theory on the Future of the Rebound Effect in a Resource Therefore, hotspots for a specific AI application should be identified, e.g., by an evaluation of the environmental impact via Life Cycle Assessment. Jns, T.; Kall, N.; Tth, Z.E. ; IEEE: Piscataway, NJ, USA; pp. Ph.D. Thesis, University of Stuttgart, Stuttgart, Germany, 2018. New right to repair legislation in Europe requires manufacturers of home appliances to offer spare parts for at least ten years after the date of original sale. Elsewhere, companies have transformed the performance management of their plants using the profit-per-hour approach. In another similar survey, 33% of the 360 firms from Spain and Mexico adopted the Kaizen methodology. ; Moon, S.J. Sustainability improvements in industrial production are essential for tackling climate change and the resulting ecological crisis. PDF Can Efficiency Improvements Reduce Resource Consumption - MIT Fit gap analysis templates and best practices - LogRocket Blog https://doi.org/10.3390/su13126689, Waltersmann, Lara, Steffen Kiemel, Julian Stuhlsatz, Alexander Sauer, and Robert Miehe. It needs to be taken into consideration that energy efficiency and GHG emissions are closely related and, thus, only a few papers address these aspects separately. Production planning can be supported by AI applications to determine future requirements, and thus to configure optimally designed production lines. GMA/ITG-Fachtagung Sensoren und Messsysteme 2019, Nachhaltige Betriebliche Umweltinformationssysteme, Charakterisierung von Mittels 3D-Druck Verarbeiteten Biogenen Holz-Filamenten unter Anwendung der Raman-Spektroskopie, Proceedings of the 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, 2017, Advances and New Trends in Environmental Informatics. As in other sectors, these companies are realizing that the journey to sustainability requires a holistic approach, combining actions both in the boardroom and on the shop floor(Exhibit 2). The databases Scopus and Web of Science were searched, with the following search string, consisting of the identified AI methods, business divisions, and resource efficiency terms: (Artificial Intelligence OR Linear Regression OR Nonlinear Regression OR Support Vector Machines OR Logistic Regression OR Decision Trees OR Naive Bayes Classification OR K-means OR Hierarchical Clustering OR Principal Component Analysis OR Isolation Forest OR Local Outlier Factor OR Convolutional Neural Network OR Pattern Recognition OR Recurrent Neural Networks OR Long short-term Memory OR Transformer OR Markov chain OR Stateactionrewardstateaction OR Deep Q-Network, Double Deep Q Network OR Q-Learning) AND (manufacturing OR industrial OR procurement OR product development OR logistics OR warehouse management OR facility management) AND (efficiency OR resource efficiency OR material efficiency OR energy efficiency OR water efficiency). BlackRock, the worlds largest asset manager, has told companies in its portfolio that it will vote against the reelection of directors at companies that fail to step up their efforts to protect natural resources and cut carbon emissions. Workflow Software. Editors Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. taking good care of the water we use. The company went on to define improvements to furnace load, operation, condition, and design that cut those losses by up to half, saving around 1.5million per year at two pilot furnaces. Automated visual inspection techniques and applications: A bibliography. Dong, B.; Andrews, B. Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings. AI thus provides support for the evaluation, identification and implementation of improvement measures in manufacturing companies. ; Zhou, Z.-H. The implementation of SCP as an integrated approach helps to achieve overall development plans; lower economic . And it illustrates the role a resource-productivity approach can play as part of a broader set of solutions to help industries grow sustainably. Moreover, the link between AI and resource efficiency could be displayed in more detail. Available online: VDMA Software und Digitalisierung. Deng, F.; Guo, S.; Zhou, R.; Chen, J. Sensor Multifault Diagnosis with Improved Support Vector Machines. IPA-IAO-Forschung und Praxis. Jagadish; Ray, A. Optimization of process parameters of green electrical discharge machining using principal component analysis (PCA). Define expected business results. The theoretical-limit approach has helped one glassmaker understand the gap between actual and theoretical performancewhich turned out to be a delta of 20to 40 percent in most cases. Regarding business units, in most papers, the (potential) influence on resource efficiency occurs within production planning and optimization. Unwanted material and energy losses due to wear and tear on tools and machines are prevented, and components are only exchanged if needed. Why does resource efficiency matter? - UNEP Against this background, this article provides an overview of the current AI applications and how they affect resource efficiency. Resource efficiency European Environment Agency Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for The identified AI applications showed that there is potential for improvements in both focused applications, such as increasing energy efficiency in lighting, and broad applications, such as holistic process improvement, taking all four impact categories of resource efficiency into account. Available online: Kavlakoglu, E. AI vs. Machine Learning vs. Markov chain modeling and forecasting of product returns in remanufacturing based on stock mean-age. 1. and S.K. Trans. To achieve their full potential, circular-economy concepts require collaboration across the full value chain, from the design of safe, easily recycled materials and of products that support repairs, upgrades, disassembly, and remanufacturing to the development of an ecosystem of providers to deliver those services. The changes required only limited capital investment, with a payback of two to five years. Decker, M. Entwicklung Eines Ganzheitlichen Prognosemodells zur Kompensation von Varianzen in Prozessfolgen Mittels Support Vektor Maschinen. A Theoretical Analysis of Deep Q-Learning. The paper provides a perspective on the challenge faced by science and technology in agriculture which must be met both in terms of increased crop productivity but also in increased resource use efficiency and the protection of environmental quality. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Windenergie: Zuverlssige Integration in die Energieversorgung, Energieeffizienz in DeutschlandEine Metastudie: Analyse und Empfehlungen, The Quest for Artificial Intelligence: A History of Ideas and Achievements, Encyclopedia of Life Support Systems (EOLSS), Business Intelligence for Enterprise Internet of Things, Startup mit System: In 24 Schritten zum Erfolgreichen Entrepreneur, Environmental and Natural Resource Economics, An Introduction to Data: Everything You Need to Know about AI, Big Data and Data Science, Applied Regression Analysis: Includes Disk, Statistical Methods for Engineers and Scientists, Pattern Recognition and Machine Learning, Corrected at 8th printing 2009. Resource efficiency Improving resource efficiency is among the top priorities in today's world, as governments, businesses and civil society are increasingly concerned about natural resource use, environmental impacts, material prices and supply security. However, further work could add to the selected methods, and thus provide a more complete picture of AI applications for resource efficiency. PDF Policy Guidance on Resource Efficiency - OECD Thats putting extra pressure on thousands of suppliers to reduce their own environmental footprints as well. Consequently, patterns are identified and deviations from the regular conditions of the monitored system are detected rapidly and, in some cases, proactively [, Consequently, various operational inputs such as, for example, capital, human resource and know-how-related aspects are not considered in particular [. Manuf. The authors declare no conflict of interest. Chin, R.T. Susto, G.A. Yiakopoulos, C.; Gryllias, K.; Antoniadis, I. Further research could focus on these aspects. Attention Is All You Need. Increasing resource and energy efficiency through circularity In a world facing resource scarcity, any successful strategy for sustainable development needs to find solutions for decoupling economic growth and the use of resources. In Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems (HIS), Malaxxa, Malaysia, 58 December 2011; pp. It is shown that AI methods have already been applied to increase resource efficiency in manufacturing companies, but only to a limited extent. Satisfactory Essays. The focus of our resource efficiency efforts are in three key areas: sourcing of renewable raw materials. ENERGY STAR is the simple choice for energy efficiency, making it easy to find products that will save you money and protect the environment. Therefore, the most frequently employed AI tasks are classification, with 23 papers, followed by modelling and language processing, with 17, trend analysis, with 13, and image recognition, with 12 papers. The most efficient companies are those that generate the most value from the fewest resources, whether those resources are labor and capital or energy, carbon emissions, scarce materials, and clean water. In Proceedings of the 2000 ACM SIGMOD International Conference on Management of DataSIGMOD 00, Dallas, TX, USA, 1518 May 2000; Dunham, M., Naughton, J.F., Chen, W., Koudas, N., Eds. Other AI methods are not used as frequently, as only five papers apply Naive Bayes classification, decision trees, LSTM, pattern recognition, Markov chain, k-means, and PCA. That extra capacity led them to identify important operational and reliability issues, such as recurring equipment failures, that could be addressed by targeted improvement initiatives. Available online: Sathya, R.; Abraham, A. ; Boullion, T.L. BASF has taken an important step by updating its sustainability assessment method TripleS (Sustainable Solution Steering) in order to further develop its product portfolio even more strongly in the direction of climate protection, resource efficiency and circular economy in the future and to meet the growing sustainability requirements in its markets with innovative solutions. Dobrev, D.A. For more information, please refer to ; Lee, S. Steel Surface Defect Diagnostics Using Deep Convolutional Neural Network and Class Activation Map. Ph.D. Thesis, Technical University of Darmstadt, Darmstadt, Germany, 2008. Incorporating these concepts allows an existing lean production system to evolve into a true sustainability-driven production system. A lot has happened in the intervening years as sustainability issuesparticularly those driven by climate changehave become far more urgent. Our first core belief is that resource-productivity strategy should be based on lean principles, making use of existing lean expertise within the company. Definition of Artificial Intelligence. Long short-term memory for machine remaining life prediction. Mech. Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. Flick, D.; Ji, L.; Dehning, P.; Thiede, S.; Herrmann, C. Energy Efficiency Evaluation of Manufacturing Systems by Considering Relevant Influencing Factors. Therefore, the chemical industry focuses on alternative designs and continuous improvement leading to improved resource efficiency in the production process, the use-phase, as well as the end-of-life. [. ; et al. Lean principles and sustainability are highly synergistic: both require organizations to eliminate waste and losses relentlessly wherever they find them and to strive to incrementally improve the performance and efficiency of their operations. These work management tools streamline your business processes by rooting out redundant tasks, automating steps that work and providing your team with a collaborative cross-functional platform. Building these factors into the profit-per-hour model allowed the plants management team to focus exclusively on the remaining efficiency gaps. Visit our dedicated information section to learn more about MDPI. ; Duran, B.S. But companies in every sector have found thousands of improvement opportunities. Climate Change 2014: Synthesis Report. PDF Can Efficiency Improvements Reduce Resource Consumption? - MIT A crop variety must possess several desirable characters like, high yield, superior quality, early maturity . However, getting the most from the approach will mean extending the lean tool kit to incorporate sustainability-specific concepts, such as energy recovery or waste-material reuse. The last of our five principles might have the most significant impact on the way industrial companies run their businesses in the coming years. permission is required to reuse all or part of the article published by MDPI, including figures and tables. Green AI. Other AI tasks and AI methods consider several resource efficiency aspects at once, and thus have a broader focus, such as classification with decision tree and logistic regression. and R.M. Over the past year, an extraordinary number of companies have made public commitments to ongoing reductions in carbon emissions and resource consumption, for example to achieve 100percent renewable-energy use or major carbon-footprint reductions per employee. Volume 469. An improvement in resource efficiency might involve, for example, a reduction in the amount of material used to manufacture or package the product, a reduction in the energy consumption of the product in use, extending the product's lifetime, or making it more recyclable or reusable at the end of its life. Within this research, the majority of papers were identified as (potentially) improving resource efficiency in the business unit of production. This paper contributes to research in this field by systematically examining papers and revealing research deficits. Thus, by taking the introduced definition into account, all impact categories are potentially affected. In this context, resource efficiency can directly lead to significant advancements in the ecological performance of manufacturing companies. Conversion Efficiency The amount of available sunlight that a solar panel converts to electricity is known as conversion efficiency. ; Akay, O.; Alim, F.; Bardak, S.; lmez, M. An automated industrial conveyor belt system using image processing and hierarchical clustering for classifying marble slabs. permission provided that the original article is clearly cited. In. 26132621. Too often, sustainability transformations run aground for the same reason other major change programs fail: too much focus on creating the perfect technical tools, such as cost curves, and too little on the humans who will use them. and J.S. Selver, M.A. This has been an area of significant progress in recent years. One medical-device manufacturer applied life-cycle analysis to reduce the carbon footprint of its insulin-pump design. MDPI and/or From the literature review, it appears that papers dealing with reinforcement learning applications are more frequently developed for scheduling problems, robot collaboration, or supply chain problems [. Ronowicz, J.; Thommes, M.; Kleinebudde, P.; Krysiski, J. Deep Learning-based Human Motion Prediction Considering Context Awareness for Human-Robot Collaboration in Manufacturing. To provide practitioners and applied research with possible starting points for the promising implementation of AI regarding resource efficiency, typical use cases were derived from the approaches. The aim is to provide a snapshot of some of the In framing the relationship between efficiency improvements and resource consumption, the familiar IPAT identity can be used. Di Vaio, A.; Palladino, R.; Hassan, R.; Escobar, O. Hsu, C.-H.; Wang, M.-J.J. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this paper identifies, categorizes, and analyzes seventy papers with a focus on AI tasks, AI methods, business units, and their influence on resource efficiency. The included papers were then analyzed regarding the identified AI tasks, AI methods, business divisions, and their (potential) influence on resource efficiency aspects. How to Increase the Efficiency of Your Material Recycling - Crigler That step becomes a catalyst for innovation, encouraging the development of novel approaches that deliver big efficiency improvements. SCP is about promoting resource and energy efficiency while providing access to basic services, green and decent jobs and a better quality of life for all. We are happy to say that the fundamentals still hold. In. Economists have several ways of measuring economic efficiency, based on the allocation of. ENERGY STAR Home Upgrade Service Provider Partnership The increase in energy efficiency was identified as being the most commonly addressed resource efficiency aspect, and the use cases for the increase in energy efficiency in production and facility management are defined accordingly. Schwartz, R.; Dodge, J.; Smith, N.A. In this context, digitized knowledge is very important in order to utilize the knowledge that is already available in a company for AI applications and, thus, to create an enhanced knowledge base [, The identification of AI methods is based on [, Linear regression examines a linear relationship between a so-called dependent variable and an independent variable (bivariate regression) and maps this relationship with a linear function or regression line [, Hierarchical clustering is a method of grouping objects into optimally homogenized sets based on empirical similarity measures and sorting them into hierarchically arranged structures [, SARSA is an algorithm for learning an action-value function. Isolation forest, Local Outlier Factor and Q-Learning were only used once, while SARSA, DQN, DDQN, and Transformer were not applied at all. And automakers are looking at ways to boost the use of recycled steel and aluminum in structural applications too. For Eng. We Improved Resource Efficiency by 10.1% By reducing the size and weight of our servers, PCs, network devices, and imaging devices, in FY 2021 we were able to improve resource efficiency by 10.1% with respect to efficiency in FY 2019.