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Internet of Things in product life-cycle energy management

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Abstract

Internet of Things (IoT) as a new emerging and fast growing technology has attracted lots of attention from worldwide recently. Successful applications of IoT have been demonstrated in many fields. However, IoT is still at its infant stage when it comes to the applications in product life-cycle energy management (PLEM). In this paper, the concept, characteristics, and applications of IoT are briefly introduced first. Then, the energy consumption involved in the three phases of product life cycle (i.e., design, production, service) are concluded and analyzed. But what is the relationship between product lifecycle energy consumption and the IoT technology? Whether the IoT concept and techniques can be employed in manufacturing to reduce the energy consumption during design, production, serve process, and what are the potential applications? Therefore, in order to answer these questions, the existing applications of IoT in PLEM are summarized, and the potential applications and challenges of IoT techniques in PLEM are analyzed and pointed out.

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... x 26 May et al. (2017) x x 27 Meng et al. (2018) x Nara et al. (2020) x x x x 30 Nguyen et al. (2020) x x x 31 Nota et al. (2020) x x x 32 Oluyisola et al. (2020) x x x x 33 Oztemel and Gursev (2020) x x x 34 Park et al. (2020) x x x x 35 Pease et al. (2018) x x x x 36 Peng et al. (2018) x x 37 Pessôa and Becker (2020) x x 38 Scharl and Praktiknjo (2019) x x x x 39 Seixas et al. (2018) x x 40 Shrouf and Miragliotta (2015) x Tao et al. (2014) x x x 44 Tao et al. (2016) x Verhoef et al. (2018) x 46 Vrchota et al. (2020) x x x x x 47 x x 48 Wolniak et al. (2020) x x x x 49 Wu et al. (2019) x 50 Yadav et al. (2020) x Zhang et al. (2019) x x 52 Zhao et al. (2019) x x x x 53 Zhou and Yang (2016) x x x J o u r n a l P r e -p r o o f ...
... Businesses take different approaches to energy-sustainable product design (Yli-Ojanperä et al., 2019). Tao et al. (2016) believe that in the Industry 4.0 environment, energy-sustainable product design concerns the entirety of the product life-cycle, from design, prototyping, manufacturing, and usage to disposal. The implications of Industry 4.0 for sustainable new product development is threefold. ...
... Second, the application of collaborative digital technologies, augmented and virtual reality, 3D printers, and project and resource management digital systems across product development team significantly increase the effectiveness of NPD efforts (in terms of time to market, quality, resource-intensity, manufacturability, and customizability of products), and directly lead to the energy sustainability implications of NPD activities (Lin, 2018;Tang and Ghobakhloo, 2013). Third, product development teams throughout value networks can create a proactive life-cycle management system and employ data mining, IoS, predictive analytics, and digital twins to integrate the virtual and real-world product data seamlessly, thus, predict and further optimize the energy sustainability of newly designed products throughout their life cycle of ideation, materialization, and utilization across value networks (Pessôa and Becker, 2020;Tao et al., 2016). ...
Article
Understanding the interactions of Industry 4.0 and sustainability is a cutting-edge research topic. The present study aims to contribute to this research topic by explaining how Industry 4.0 may contribute to energy sustainability. The present study performs a content-centric qualitative review of the extant digitalization literature to identify the primary energy sustainability functions of Industry 4.0. The interpretive structural modeling technique is further used for mapping the interrelationships among various energy sustainability functions identified. The interpretive model developed, and the Matrice d'Impacts Croisés Multiplication Appliquée àun Classement analysis offered exciting insights into the Industry 4.0-energy sustainability interactions. Findings show that Industry 4.0 promotes energy sustainability via a very complex mechanism that involves ten interrelated functions. Contrary to the general opinion, production efficiency offered by the digitalization of the manufacturing industry is not the immediate and most essential energy efficiency outcome of the digital industrial transformation. Industry 4.0 primarily contributes to energy sustainability by enabling the energy industry to reshape its operating landscape and enjoy more advanced, intelligent, and complicated energy production and distribution equipment. The digitalization of the energy demand sector, digitalization of the manufacturing industry, and the introduction of smarter and more sustainable products are among the main opportunities of Industry 4.0 for energy sustainability. Overall, the study and the ISM model of energy sustainability developed explains how Industry 4.0 contributes to energy sustainability via different functions and how each function is placed within the structural model based on its driving and dependence powers.
... They can communicate with each other without human intervention. The information aggregated by different things can be accessed by these objects, or in another hand, these objects can be used as information to add to other services (Tao et al. 2016). Everyone can access all services based on IoT that will communicate possibly the internet with everything from anywhere at any time. ...
... Moreover, the flexibility of the IoT platform also allows the building of aggregated and versatile applications through third-party APIs (Application Program Interfaces) (Roman, Zhou, and Lopez 2013). Many advanced technologies such as perception technology, artificial intelligence technology, advanced network technology, and automated devices have combined to form a system to realize relationships between many objects and people (Tao et al. 2016). An IoT is a large number of links between devices, machines, and services. ...
... That article outlined the roadmap and guidance to promote the potential values of the IoT integrated PLEM system in smart manufacturing. More interestingly, (Tao et al. 2016) have described more clearly the relationship of the three product lifecycle design, production, and service processes with IoT applications. The authors have clarified the concept of energy estimation using product life cycle and synthesized prominent applications of PLEM in manufacturing areas such as product design, manufacturing, and services. ...
Article
Energy plays an important role in economic growth and environmental protection, is an important input of many manufacturing industries, and one of the essential commodities of households. The process of industrializa-tion and modernization is ever increasing, causing the skyrocket in demand for energy worldwide. Since, the nonrenewable energy sources are increasingly exhausted, there is a serious shortage of energy; therefore, saving and using energy effectively is extremely urgent. The application of the Internet of Things (IoT) has shown an interesting growth in production management, especially, its usage in controlling energy is emerging as an attractive concept in the future. Based on an idea about a framework to save energy in the production process, the discussion of the paper pays attention to analyzing the advantages of incorporating energy data in discrete production for production management decisions, and the approaches that enhance production management practices by this incorporation. The findings suggest that the Internet of Things solutions are state-of-the-art for decision-makers to improve their discrete manufacturing facilities in terms of energy efficiency. A further highlight reveals where practices should be located, and tools and energy data need for implementation and running, simultaneously advanced achievable benefits and related practices are also mentioned in this paper. ARTICLE HISTORY
... For this purpose and in contrast to conventional manufacturing systems, FASTEN will develop a fully connected and scalable manufacturing system, integrating robotic, automation, simulation, as well as optimization and prescriptive analytics technologies, to produce one-of-a-kind customer designs. The FASTEN framework will be the basis for a system developed to support smart manufacturing [17], to help decision making, and to act in real-time, in the context of mass customization, providing complete Sensors 2020, 20, 5499 4 of 25 integration at the horizontal, vertical, and end-to-end levels. The horizontal is the integration of IT systems used in the different stages of the manufacturing and business planning processes inside a company or between different companies. ...
... One of the requirements in these environments is to provide interoperability between robotic and manufacturing equipment through information exchange using standard protocols, and vertical connectivity with the IoT platform. The task of integrating robotic and manufacturing equipment of different purposes, architectures, and paradigms is still a major risk in automation projects, due to the variance of physical bus, communication protocols, and operating systems [17]. This situation often leads to system integrators typically specializing in a single vendor to ensure compliance of solutions and building expertise. ...
... With many things connected to the Internet, a huge amount of data in real-time will be produced automatically by the connected things making data analysis a fundamental task in the Industry 4.0 environment. Building systems into which big data from a variety of heterogeneous sources are integrated can be a challenging task [17,54,55]. In this way, existing standards for lifecycle management and value flow (IEC 62890), for the integration of corporate control systems (IEC 62264, ANSI/ISA-95) and for process control (IEC 612512, ANSI/ISA-88) provided a solid foundation for the development of the platform and also ensured the required compliance, accelerating the adoption of this technology by industrial companies. ...
Article
Full-text available
The Industry 4.0 paradigm, since its initial conception in Germany in 2011, has extended its scope and adoption to a broader set of technologies. It is being considered as the most vital mechanism in the production systems lifecycle. It is the key element in the digital transformation of manufacturing industry all over the world. This scenario imposes a set of major unprecedented challenges which require to be overcome. In order to enable integration in horizontal, vertical, and end-to-end formats, one of the most critical aspects of this digital transformation process consists of effectively coupling digital integrated service/products business models with additive manufacturing processes. This integration is based upon advanced AI-based tools for decentralized decision-making and for secure and trusted data sharing in the global value. This paper presents the FASTEN IIoT Platform, which targets to provide a flexible, configurable, and open solution. The platform acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions. Examples of these efforts comprise management, forecasting, optimization, and simulation, by harmonizing the heterogeneous characteristics of the data sources involved while meeting real-time requirements.
... However, the WWTPs system is huge and complex non-linear, with serious coupling of multidisciplinary (biological, chemical, computer technology, automatic control technology, etc.). Thus, how to achieve data and function integration, improve the economic and environmental benefits of WWTPs, and ensure real-time water quality standards is still an urgent problem [50][51][52][53]. ...
... In order to further evaluate the performance of DOIC, it is compared with DMOOC [33], RTO-NMPC [45], EMPC-OCI [25], and PID [52]. The detailed results are shown in Table 4. ...
Article
Wastewater treatment process (WWTPs) is an enormous and complex system, it involves multi-disciplines and multi-fields, which is a greatly challenge for industrial Information Integration Engineering (IIIE). In this paper, an integrated control framework for WWTPs is proposed using intelligent optimization to solve the problem of excessive pollutant and high energy consumption. It realizes the effective integration of data model, intelligent decision making, dynamic optimization and control. Firstly, a self-organization soft sensing method is adopted. It can predict the concentrations of ammonia nitrogen and total nitrogen in advance. And the early warning is provided for decision making. Secondly, for the complex dynamic characteristics of multi-performance indexes intercoupling in WWTPs, the dynamic multi-objective immune optimization algorithm is designed. And an optimized set point with high quality in real time is to be obtained. In addition, according to different over standard states, the intelligent decision scheme of WWTPs is designed. It can achieve the effective cooperation of over standard suppression and energy saving. Finally, BSM1 simulation model is used to verify the method. The experimental results show that the integrated framework can achieve the whole process of WWTPs real-time standards and can effectively reduce energy consumption, so it has competitive practical application prospect for IIIE.
... Those advancements in technology and industrialisation have led to higher energy demand worldwide by 2.3% in 2018 (IEA, 2019). Tao et al. (2016) reports about 37% of available global energy are consumed by the industrial sectors. And to date, a larger portion of current energy demand is met using fossil fuels such as oil 31.5% and coal 26.9% (IEA, 2020). ...
... Although Kevin Ashton introduced IoT technologies in 1998, yet the technologies are in the state of infancy, therefore, there is a lack of consensus on any universal definition of the technologies in academia (Čolaković & Hadžialić, 2018;Nord et al., 2019;Wortmann & Flüchter, 2015). Various definitions are presented based on the context of utilisation and vision of the researchers (Čolaković & Hadžialić, 2018;Gigli & Koo, 2011;Lee & Lee, 2015;Lund et al., 2014;Tao et al., 2016). However, most researchers have consensus on the operational mechanism, utilisation framework, and objectives of the IoT. ...
Article
Full-text available
The Internet of Things has become a spotlight in contemporary literature in the domain of industry 4.0 and emerging technologies. Majority of research studies focuses on technicalities and theoretical implications of implementing IoT in the energy sector. However, in practice, organisations face a combination of technical and non-technical challenges. There is a clear need for the studies to empirically evaluate IoT use cases, challenges, and a roadmap for successfully implementing emerging technologies. To fulfil the research gap and provide insights for practitioners, we conducted seven semi-structured interviews with professionals working in Finland's energy sector. Based on results retrieved through content analysis of transcribed interviews, we developed a roadmap with managerial implications for successfully implementing IoT and other emerging technologies. Furthermore, study results present practical insights on IoT applications, benefits, and major IoT utilisation challenges in the Finnish energy sector industrial ecosystem. In the end, conclusion and future research directions are discussed.
... However, the WWTPs system is huge and complex non-linear, with serious coupling of multidisciplinary (biological, chemical, computer technology, automatic control technology, etc.). Thus, how to achieve data and function integration, improve the economic and environmental benefits of WWTPs, and ensure real-time water quality standards is still an urgent problem [50][51][52][53]. ...
... In order to further evaluate the performance of DOIC, it is compared with DMOOC [33], RTO-NMPC [45], EMPC-OCI [25], and PID [52]. The detailed results are shown in Table 4. ...
Article
Wastewater treatment process (WWTPs) is an enormous and complex system, it involves multi-disciplines and multi-fields, which is a greatly challenge for industrial Information Integration Engineering (IIIE). In this paper, an integrated control framework for WWTPs is proposed using intelligent optimization to solve the problem of excessive pollutant and high energy consumption. It realizes the effective integration of data model, intelligent decision making, dynamic optimization and control. Firstly, a self-organization soft sensing method is adopted. It can predict the concentrations of ammonia nitrogen and total nitrogen in advance. And the early warning is provided for decision making. Secondly, for the complex dynamic characteristics of multi-performance indexes intercoupling in WWTPs, the dynamic multi-objective immune optimization algorithm is designed. And an optimized set point with high quality in real time is to be obtained. In addition, according to different over standard states, the intelligent decision scheme of WWTPs is designed. It can achieve the effective cooperation of over standard suppression and energy saving. Finally, BSM1 simulation model is used to verify the method. The experimental results show that the integrated framework can achieve the whole process of WWTPs real-time standards and can effectively reduce energy consumption, so it has competitive practical application prospect for IIIE.
... For example, by developing an intelligent street lighting solution using the Internet of Things, the right lighting level can be achieved (taking into account the city, time of day, season or weather), thus the amount of energy used for lighting can be reduced (Perera et al., 2015). Similarly, this technology can be used to save energy in indoor lighting and heating (Tao, Wang, Zuo, Yang, & Zhang, 2016). ...
... In terms of enterprises, energy parameters in the production process can be monitored in real time thanks to raw materials, components, machinery, products and facilities equipped with IoT technology (Tao et al., 2016). This helps businesses find the best solutions to save energy by making it possible to monitor not only the total energy consumption, but the individual energy consumption of all items in the production process, as well. ...
Chapter
Modern industry developed over several centuries and three industrial revolutions. Today, we experience the fourth era of the industrial revolution, Industry 4.0. The advance of industrialization brought along many problems, including environmental pollution, global warming, and depletion of natural resources. As a result, the concept of sustainability began to gain importance. Sustainability can be achieved through a balance between economic, social, and environmental processes. In order to establish such balance, businesses need new business models or insights. At this point, Industry 4.0 can be regarded as a new business mindset that will help businesses and communities move towards sustainable development. The technologies used by Industry 4.0 bear a strong promise to solve these problems, after all. Even though Industry 4.0 attracts a lot of attention lately, few works are available on its impact on sustainability. This chapter examines the impact of Industry 4.0 on sustainability.
... In the next step, the results of the studies (PSOI RANK) (graphical representation of the test results is shown in Figure 3) were compared with the current EU Competitiveness Reports and The Leaving-No-One-Behind Report. Comparing the level of smart (smartness) of organizations in individual EU countries (PSOI RANK) with the level of their competitiveness and sustainability in several reports, it can be seen that the PSOI confirms the trends visible, among others, in the Europe 2020 Competence Report and in the report "The EU Regional Competitiveness Index 2019" [124,125] as well as in the Europe Sustainable Report [124]. Comparing the level of smart (smartness) of organizations in individual EU countries (PSOI RANK) with the level of their competitiveness and sustainability in several reports, it can be seen that the PSOI confirms the trends visible, among others, in the Europe 2020 Competence Report and in the report "The EU Regional Competitiveness Index 2019" [124,125] as well as in the Europe Sustainable Report [124]. ...
... Comparing the level of smart (smartness) of organizations in individual EU countries (PSOI RANK) with the level of their competitiveness and sustainability in several reports, it can be seen that the PSOI confirms the trends visible, among others, in the Europe 2020 Competence Report and in the report "The EU Regional Competitiveness Index 2019" [124,125] as well as in the Europe Sustainable Report [124]. Comparing the level of smart (smartness) of organizations in individual EU countries (PSOI RANK) with the level of their competitiveness and sustainability in several reports, it can be seen that the PSOI confirms the trends visible, among others, in the Europe 2020 Competence Report and in the report "The EU Regional Competitiveness Index 2019" [124,125] as well as in the Europe Sustainable Report [124]. ...
Article
Full-text available
The Industry 4.0 Revolution that is taking place nowadays means that organizations face not only new opportunities, but also challenges related to the identification of their role in creating a modern smart world. The economies of many countries are under the significant and growing influence of various types of organizations, not only strong international business corporations, but also, more and more often, smaller but intelligent ones called smart organizations IR 4.0. Due to their unique characteristics, intelligent organizations are better able than others to cope with technological breakthroughs, social, and cultural problems as well as to compete effectively and develop in an environmentally sustainable way. With their growing potential, they are strengthening the economies of their countries of origin and daily operation. Their growing role is also visible in the processes of shaping competitiveness and achieving the sustainable development objectives of the European Union (EU). The countries that are able to organize an environment on their territory that is conducive to the smart organization’s development are clear examples not only of a high market competitiveness, but also of a dynamically growing commitment to the effective implementation of the challenges associated with the 17 objectives of sustainable development of the contemporary EU, according to the 2030 Agenda for Sustainable Development. This allows for a conclusion that the identification of the key factors for a smart organization’s development makes it possible to monitor and provide targeted support for the development not only of these organizations, but also for the competitiveness and sustainability of individual countries, both from the EU and other regions of the world. In light of the above, the aim of this article is therefore to propose an effective tool to monitor the use of power of smart organizations in the processes of building the competitiveness and sustainable development of countries, with particular reference to the EU. To achieve this objective, we constructed a synthetic power of smart organizations index (PSOI) based on previously collected data from EUROSTAT. This tool allows for the integration of micro (organization level) and macro (country level) economic aspects into a single construct. Based on the analysis of its results, countries wishing to actively engage in the development of their own and the EU’s smartness and sustainability can be offered several more or less intense navigation paths to market success, based on the development of smart organizations.
... An advanced hybrid power management unit for passive UHF RFID is presented by Sun et al. (2017) to increase the applications of RFID systems in part production process. To reduce the energy consumption during part design and production process, applications of internet of Things as well as RFID systems in product life-cycle energy management is developed by Tao et al. (2016). ...
... Dowling et al. (2009) A major step forward for energy efficiency in home and industrial applications using RFID-enabled temperature sensing devices is developed. Tao et al. (2016) Internet of Things in product life-cycle energy management is presented. ...
Article
Full-text available
Radio frequency identification (RFID) is one of the most promising technological innovations in order to track and trace products as well as material flow in manufacturing systems. High Frequency (HF) and Ultra High Frequency (UHF) RFID systems can track a wide range of products in the part production process via radio waves with level of accuracy and reliability. As a result, quality and transparency of data across the supply chain can be accurately obtained in order to decrease time and cost of part production. Also, process planning and part production scheduling can be modified using the advanced RFID systems in part manufacturing process. Moreover, to decrease the cost of produced parts, material handling systems in the advanced assembly lines can be analyzed and developed by using the RFID. Smart storage systems can increase efficiency in part production systems by providing accurate information from the stored raw materials and products for the production planning systems. To increase efficiency of energy consumption in production processes, energy management systems can be developed by using the RFID-sensor networks. Therefore, smart factories and intelligent manufacturing systems as industry 4.0 can be introduced by using the developed RFID systems in order to provide new generation of part production systems. In this paper, a review of RFID based wireless manufacturing systems is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.
... Üretim aşamasında enerji yönetimi üretim süreçlerinin daha iyi izlenmesi ve kontrol edilmesiyle başarılabilir. Örneğin, test verileri ürün yaşam döngüsü sırasında otomatik ekipmanlar tarafından üretilir, daha sonra teknoloji uzmanları veya tasarımcılar, farklı etki faktörleri ile bağlantılı test verilerinin ilişkisini analiz ederek karar verebilir ve en enerji verimli ürün tasarımını seçebilirler [31]. ...
... Dijitalleşme yardımıyla teknik olarak ürünleri internete bağlamak ve bir IP adresi atamak mümkündür, böylece birbirleriyle, diğer bileşenlerle ve hatta uzaktan kumandalarla iletişim kurabilir ve etkileşime geçebilirler. Bu nedenle, verimli nakliye planlaması, optimize edilmiş depo yönetimi, kapsamlı enerji kullanım kılavuzu, öngörücü ve önleyici bakım yoluyla bu engeller ile başa çıkmamızı sağlar [31]. ...
... Big data analytics in process control, for example, might help in pollution control and natural resource management [85]. Cyber-physical systems aid in production without generating waste or consuming unnecessary resources; the IoT enables mass customization and production that meets demand without producing excess inventory; cloud manufacturing enables controlled resource consumption (e.g., raw materials, energy, water); and additive manufacturing proactively maintains products, saves energy, and reduces waste from defective products [2, 20,86]. By designing goods based on precise consumption data, cyberphysical systems improve customer satisfaction. ...
... By designing goods based on precise consumption data, cyberphysical systems improve customer satisfaction. As a result, using the 5Rs technique (reduce, repair, re-use, recycle, and remanufacture) [86,87], it is feasible to develop goods with longer life spans. CPS and IoT aid in the planning of energy and carbonefficient logistics routes, as well as assisting suppliers in managing their own performance in terms of production planning, delivery quality and reliability, and environmental compliance via remote monitoring [88]. ...
Chapter
A supply chain is a network that links technology, activities, resources and organisations involved in the manufacturing and distribution of product and services. Supply Chain Operations Reference model (SCOR) defines basic processes of the supply chain (SC) into five categories as Plan, Source, Make, Delivery and Return. The search for a more sustainable production and consumption system is so relevant today that the United Nations (UN) have selected it as one of their paramount societal objectives for sustainable development. The implementation of sustainability in production and consumption processes aims to mitigate negative pressures on the ecosystem generated by products, services, and transportation. Industry 4.0 (I40) technologies have sparked interest in recent years. The advanced digital technologies of I40 such as big data analytics (BDA), artificial intelligence (AI), machine learning (ML), internet of things (IoT) and sensors, block chain technology (BCT), robotic systems (RS), cloud computing (CC), cyber-physical system (CPS), additive manufacturing (AM) /3D printing (3D), virtual reality (VR), augmented reality (AR), autonomous vehicles (AV), and drones have found applications in many processes of manufacturing, logistics and SC. The benefits are sustainability, efficiency, cost reduction, transparency, traceability, and collaboration. In addition to benefits, I40 implementation is not free from challenges.
... 1 IoT has become a very important hot topic both in business and in academia. [2][3][4] Health IoT links various medical equipment with remote monitoring of physiological data, chronic diagnosis of illnesses, recovery training and elderly treatment. In the meantime, IoT health may signi¯cantly increase the quality of healthcare and lower medical cost. ...
... 32,33 Big data are concentrated in healthcare on varied and vast sources of signi¯cant datasets that, for healthcare professionals to process and interpret using existing resources, are too large, too fast and too complex. 2,34,35 Their motivation is that health services should be continuously more productive and organized in order to prevent, respond early and manage them optimally. [36][37][38][39] The data-driven insights and actions of today's knowledge-driven societies endorse internet-of-thing (IoT) and big data utilization as an unprecedented opportunity to revolutionize healthcare delivery through data mining. ...
Article
The objective of the research work is to analyze and validate health records and securing the personal information of patients is a challenging issue in health records mining. The risk prediction task was formulated with the label Cause of Death (COD) as a multi-class classification issue, which views health-related death as the “biggest risk.” This unlabeled data particularly describes the health conditions of the participants during the health examinations. It can differ tremendously between healthy and highly ill. Besides, the problems of distributed secure data management over privacy-preserving are considered. The proposed health record mining is in the following stages. In the initial stage, effective features such as fisher score, Pearson correlation, and information gain is calculated from the health records of the patient. Then, the average values are calculated for the extracted features. In the second stage, feature selection is performed from the average features by applying the Euclidean distance measure. The chosen features are clustered in the third stage using distance adaptive fuzzy c-means clustering algorithm (DAFCM). In the fourth stage, an entropy-based graph is constructed for the classification of data and it categorizes the patient’s record. At the last stage, for security, privacy preservation is applied to the personal information of the patient. This performance is matched against the existing methods and it gives better performance than the existing ones.
... When analyzing the influence of specific technologies, several authors pointed out that AM technology has the potential to reduce the consumption of raw materials (Mellor et al., 2014;Oettmeier and Hofmann, 2017) and energy consumption (Campbell et al., 2011;Kellens et al., 2017;Rejeski et al., 2018). Other studies indicate that BDAA (Bahrin et al., 2016;Rüßmann et al., 2015), IoT (Shrouf et al., 2014;Lin et al., 2016;Tao et al., 2016;Wan et al., 2016) and VAR (Rodič, 2017) technologies also contribute to reduced energy consumption. Specifically, regarding to IoT, Lin et al. (2016) proposed a method for prolonging network lifetime, deploying energy-efficient systems and reducing the replacement frequency of faulty sensors to reduce consumption. ...
... The impact of BDAA and IoT is considered strong. In the literature, there are articles related with the positive impact of BDAA (Rüßmann et al., 2015;Bahrin et al., 2016;Prause and Atari, 2017) and IoT (Shrouf et al., 2014;Lin et al., 2016;Tao et al., 2016;Wan et al., 2016) but Prause and Atari (2017) did not detect evidence for IoT. On the other hand, the medium-level positive influences of AI, AV and RB, and the low-level positive impacts of CS and VAR on RIC, have been assessed. ...
Article
Full-text available
In the last decade, both Industry 4.0 technologies and the circular economy have expanded exponentially and they have received epistemological attention. However, there is a lack of studies about the influence that each of these technologies has on the main areas of action covered by the circular economy. This study responds to this gap by investigating the influence of the major technologies: Additive Manufacturing, Artificial Intelligence, Artificial Vision, Big Data and Advanced Analytics, Cybersecurity, Internet of Things, Robotics, and Virtual and Augmented Reality on the main areas of action covered by the circular economy. Namely, reduction of inputs consumption, reuse, recovery, recycling and reduction of waste and emissions. An initial study, based on a survey of 120 project managers, and a multiple case study of 27 projects, through 31 personal interviews and review of internal and external documentation have been conducted in order to investigate the real influence of each technology on the circular economy. Overall, the results confirm the existence of a wide range of influences that Industry 4.0 technologies offer to companies for improved circularity. These improvements are mainly related to reduce material and energy consumption, and waste and emissions generation. However, there are important differences between the potential impacts of each technology. In particular, there is most evidence of the positive impact of additive manufacturing and robotics. Likewise, the results obtained suggest the need to continue exploring the new impacts generated by the continuous development and integration of technologies.
... By applying LCA and IoT, Du et al. achieved efficient and intelligent management of renewable resources and discussed the environmental effects of various types of renewable resources [36]. Tao et al. [37]investigated the specific application of the Internet of things in each stage of product energy management. An LCA method for energy-saving and emission-reduction based on IoT and bill of material was designed and presented [38]. ...
Article
Full-text available
Life cycle assessment (LCA) is conducive to the change in the wind power industry management model and is beneficial to the green design of products. Nowadays, none of the LCA systems are for wind turbines and the concept of Internet of Things (IoT) in LCA is quite a new idea. In this paper, a four-layer LCA platform of wind turbines based on IoT architecture is designed and discussed. In the data transmission layer, intelligent sensing of wind turbines can be achieved and their status and location can be monitored. In the data transmission layer, the LCA platform can be effectively integrated with enterprise information systems through the object name service (ONS) and directory service (DS). In the platform layer, a model based on IMPACT 2002+ is developed, and four management modules are designed. In the application layer, different from other systems, energy payback time (EPBT) is selected as an important evaluation index for wind turbines. Compared with the existing LCA systems, the proposed system is specifically for wind turbines and can collect data in real-time, leading to improved accuracy and response time.
... This intelligent manufacturing approach improves the quality, performance, and service of the product, reducing resource consumption by decreasing the rejection rate [38]. Due to this smart approach, the maintenance strategies of the manufacturing industry drawing more attention in recent years, and various prediction and diagnostic methods are used for maintenance purposes [39]. Figure 11 shows the different maintenance strategies used in industries such as reactive, preventive, and predictive maintenance [40]- [42]. ...
Article
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An increase in unplanned downtime of machines disrupts and degrades the industrial business, which results in substantial credibility damage and monetary loss. The cutting tool is a critical asset of the milling machine; the failure of the cutting tool causes a loss in industrial productivity due to unplanned downtime. In such cases, a proper predictive maintenance strategy by real-time health monitoring of cutting tools becomes essential. Accurately predicting the useful life of equipment plays a vital role in the predictive maintenance arena of industry 4.0. Many active research efforts have been done to estimate tool life in varied directions. However, the consolidated study of the implemented techniques and future pathways is still missing. So, the purpose of this paper is to provide a systematic and comprehensive literature survey on the data-driven approach of Remaining Useful Life (RUL) estimation of cutting tools during the milling process. The authors have summarized different monitoring techniques, feature extraction methods, decision-making models, and available sensors currently used in the data-driven model. The authors have also presented publicly available datasets related to milling under various operating conditions to compare the accuracy of the prediction model for tool wear estimation. Finally, the article concluded with the challenges, limitations, recent advancements in RUL prognostics techniques using Artificial Intelligence (AI), and future research scope to explore more in this area.
... IoT can also be used for improving energy efficiency and reducing the impact of energy use on the environment. Tao et al. [30] investigated some applications of IoT technologies in manufacturing to reduce energy consumption during the processes of design, production, and operation. Motlagh et al. [12] classified different use cases of IoT in the energy supply chain, from power generation to end-use sectors, and discussed the advantages of IoT-based energy management systems in increasing energy efficiency and integrating renewable energy. ...
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In recent years, the application of traceability systems in the food and drug industry has developed rapidly, but it is rarely used for wind turbines. From the aspects of low information transparency and information islands in the supply chain process for wind turbines, a reliable traceability system is essential. However, the existing traceability systems are not suitable to be directly applied to wind turbines. Consequently, according to the characteristics of the wind power industry, a semi-centralized traceability architecture based on Internet of Things technology was proposed. Furthermore, a traceability platform was constructed by analyzing the information collected in each stage related to various user needs of wind turbines, and various applications, including manufacturing management and spare parts management, were developed. Compared with the existing systems, the proposed platform was wind-turbine-oriented, effectively improved traceability efficiency and enterprises’ information security, and extended the length of the traceability chain by integrating the after-sales information. The traceability of key components of wind turbines during their life cycle provides a useful reference for further improving the parts quality management system of the wind power industry.
... At HM it is possible to find startups and concepts geared towards agribusiness, such as the Weed Whacker, from the startup Odd.Bot, which brings a new concept of intelligent weeding to agricultural lands. This technology helps sustainable planting, increasing agricultural yields, reducing the exposure of farmworkers to toxic products and decreasing environmental degradation through intelligent machinery and sensing [3,39,110,111]. Its biggest differential is the application of chemical products to the crops through the Weed Whacker, mitigating the problem of contamination by chemicals harmful to health from pesticides [111,112]. ...
Article
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Sustainability 4.0 (S4.0) enables sustainable development through intelligent technologies to meet economic, environmental and social demands. The main objective of this article is to propose a framework for developing S4.0 in sectors of Triple Helix (TH) (Government, Organizations and Academy). The framework consists of benchmarking of policies and initiatives from the Science-Technology Scenario in S4.0 (STS-S4.0) and the authorʹs experience. The STS-4.0 is a snapshot of relevant initiatives from the countries that performed best in science and technology in S4.0. This work uses the methods of bibliometric studies and content analysis of scientific articles from the Scopus database and patents publications from the Orbit database. This research resulted in a total of 19 propositions for developing sustainability through I4.0. Of these, eight are for Government, six for Organizations and five for Academy. The main scientific contribution of this work is to expand and deepen the recent block of knowledge on S4.0. As for the applied contribution, this work contributes to the conscious and sustainable development of humanity through the technological elements of I4.0, contributing to the achievement of the following SDGs proposed by the UN: 9 (Industries, Innovation and Infrastructure), 11 (Sustainable Cities and Communities) and 13 (Climate Action). The main novelty of this article is the creation of paths for Government, Organizations and Academy to interactively lead the development of global sustainability through the smart technologies of I4.0.
... The system equipped modern sensors could be instated easily and effectively to manage the equipment as in light power, HVAC, fire, security, etc. and cloud-based dossier helps in supervise and oversight easily and efficiently [21][22][23]. Parameters as in temperature, automated door operation, humidity, air quality and pressure, etc. Apart from managing machinery as lift, escalators they also be prognosticate in case of disruption and be prompted for abrupt alleviative alacrity. ...
Chapter
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Smart Buildings should be seen from a multi-industrial standpoint, involving the right combination of architecture, structure, information technology, automation, environment and energy, services and facility management such as to minimize life-cycle costs, maximize comfort and adapt properly to cultural stimuli. Intelligent architecture concerns with intelligent design to meet cultural and contextual requirements , with proper use of IT and smart technology, as well as with optimal building exploitation and cost-effective maintenance over its lifetime. This might also include intelligent and responsive facades. Facility management looks for the best financial management for maintenance, rebuild and renovation, for the best space utilization, for the best daily operational services and for maximizing user satisfaction.
... Clearly, the spatial and temporal resolution of these public data sets can limit the extent of data science's utility in working with them. The Internet of Things continues to mature and offer opportunities to collect large data sets for energy management, most often in private industrial settings (Li and Kara, 2017;Shrouf and Miragliotta, 2015;Tao et al., 2016). Frequently-collected, public energy and water consumption data at high spatial resolution is a data gap for the United States. ...
Chapter
Assessing the sustainability of natural resource management choices for agricultural and forest lands requires quantification of potential changes to a set of environmental and socioeconomic indicators selected to characterize reference scenarios relative to projected future scenarios. Correctly framing the questions with local stakeholders is a critical first step in the sustainability assessment, and the questions that can be addressed are often limited by data availability. Selecting and prioritizing indicators with stakeholders to address their needs and concerns improves the likelihood of investment in monitoring and evaluation of those indicators over time. Computational techniques for analyzing interactions between the selected indicators are inherently affected by the scales and formats of the assembled indicator datasets. Data analytics have the potential to improve understanding of the potential synergies and tradeoffs involved with meeting multiple environmental and socioeconomic goals simultaneously, but timely and appropriate indicator datasets are not always available—even in this new era of “big data.” Continued improvements in data science and data analytics are needed to broaden understanding and acceptance of problems and to provide valuable information for natural resource management. Advances in these areas will enable society to design future landscapes that meet multiple objectives, including the provisioning of agricultural and forest resources along with a variety of ecosystem services (e.g., clean water and healthy soils).
... Industry 4.0 has accelerated the process of overcoming barriers to achieving circularity, and digitalization has increasingly emerged as a facilitator for the design of cleaner production Kang et al., 2016;Tao et al., 2016;Waibel et al., 2017;Bressanelli et al., 2018), then for a sustainable environment as a macrosystem of the sustainable ecological business as a whole and a sub-system (Fig. 5), in A. Hallioui et al. fact, as a more sustainable ecosystem (Fig. 10). According to Tseng et al. (2018), in times of industrial digitalization, the linkage between Industry 4.0 and the Circular Economy has clearly and persistently enabled the exploration of various ways to achieve ecological sustainability objectives. ...
Article
Sustainability is the core feature of 21st-century businesses—the management approach can be a lever. The 4th Generation Management arises as a systems-based approach to managing contemporary businesses before the advent of Industry 4.0 and during a low awareness of the Circular Economy. While the 4th Generation Management provides value to business by considering several resources, stakeholders, and interactions, making businesses customer-oriented, it fails to address the sustainability issue for contemporary businesses in the current context of Industry 4.0, Circular Economy, Competitiveness, and Stakeholders. Indeed, it fails to make businesses more contemporary (i.e., more open and sustainable) to adapt to their context. Moreover, in the literature, there is no work discussing how Sustainability, Industry 4.0, Circular Economy, Competitiveness, and diverse Stakeholders as contemporary issues are accounted for in business management. The main aim of this study is to propose a Re-engineered 4th Generation Management as a systems-based approach, enabling today's business to be oriented toward customer and sustainability. We have reviewed 181 articles published between 2005 and 2022 from Scopus, Web of Science, and Science Direct databases to pursue such a goal. The novelty of this work relies on presenting a systems-based approach, which is best suited for sustainable businesses in the context of Industry 4.0 digitalization technologies (e.g., Artificial intelligence, Blockchain, Cloud computing, and Big data analytics), Circular Economy, Stakeholders, and Competitiveness. Furthermore, propositions are formulated to reflect on the suggested framework based on recent literature. At the end of this work, research implications and future directions are provided.
... With the application of IoT, companies collect and manage big data that enable effective decision making. For example, business applications for improving the response of mobile taxis (Lanza et al., 2015) and the reduction of energy consumption in manufacturing and service processes (Tao et al., 2016). ...
Article
Organizations are struggling to leverage emerging opportunities for maintaining sustainability in the global markets due to many barriers in the era of Industry 4.0 and circular economy. The main aim of this study is to analyze these barriers to improve the sustainability of a supply chain. Our study identifies the major criteria for sustainable operations and barriers that need to be overcome to achieve the objectives of sustainability through literature review and experts’ opinions. An integrated approach comprising Analytic Hierarchy Process (AHP) and Elimination and Choice Expressing Reality (ELECTRE) is used to analyze these barriers and ensure the sustainable supply chain operations. Resource circularity, increasing profits from green products, and designing processes for resource and energy efficiency have been found to be as major sustainability criteria. There are many barriers to the implementation of Industry 4.0. These barriers include but are not limited to, a lack of a skilled workforce that understands Industry 4.0, ineffective legislation and controls, ineffective performance framework, and short-term corporate goals. The study finds that ineffective strategies for the integration of industry 4.0 with sustainability measures, combined with a lack of funds for industry 4.0 initiatives, are just two of the major barriers. The findings of the study will help organizations to develop an effective and integrated strategic approach that will foster sustainable operations through the utilization of improved knowledge of Industry 4.0 and the circular economy.
... Ownership of IoT device might change during its life cycle which requires an efficient and secure identity management. Several attributes are related to IoT device as in manufacturer, GPS coordination, serial number, and type that all require secure and trustworthy management [29]. Blockchain can be foreseen as a promising solution to mitigate the above mentioned challenges in the whole life cycle of IoT devices. ...
Article
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The constant development of interrelated computing devices and the emergence of new network technologies have caused a dramatic growth in the number of Internet of Things (IoT) devices. It has brought great convenience to people’s lives where its applications have been leveraged to revolutionize everyday objects connected in different life aspects such as smart home, healthcare, transportation, environment, agriculture, and military. This interconnectivity of IoT objects takes place through networks on centralized cloud infrastructure that is not constrained to national or jurisdictional boundaries. It is crucial to maintain security, robustness, and trustless authentication to guarantee secure exchange of critical user data among IoT objects. Consequently, blockchain technology has recently emerged as a tenable solution to offer such prominent features. Blockchain’s secure decentralization can overcome security, authentication, and maintenance limitations of current IoT ecosystem. In this paper we conduct a comprehensive literature review to address recent security and privacy challenges related to IoT where they are categorized according to IoT layered architecture: perception, network, and application layer. Further, we investigate blockchain technology as a key pillar to overcome many of IoT security and privacy problems. Additionally, we explore the blockchain technology and its added values when combined with other new technologies as machine learning especially in intrusion detection systems. Moreover, we highlight challenges and privacy issues resulted due to integration of blockchain in IoT applications. Finally, we propose a framework of IoT security and privacy requirements via blockchain technology. Our main contribution is to exhaust the literature to highlight the recent IoT security and privacy issues and how blockchain can be utilized to overcome these issues, nevertheless; we address challenges and open security issues that blockchain may impose on the current IoT systems. Research findings formulate a rigid foundation upon which an efficient and secure adoption of IoT and blockchain is highlighted accordingly.
... Toutes les informations liées aux soins de santé sont collectées par ces capteurs et gérées efficacement et elles peuvent être en mesure d'effectuer une surveillance à distance avancée et peuvent être en mesure de réagir rapidement en cas de besoin. Par exemple, l'application de détection des chutes peut aider les personnes âgées ou handicapées à vivre de manière plus autonome [44]. On peut prévoir que l'IoT avec des capteurs médicaux intelligents améliorera considérablement la qualité de vie et préviendra l'apparition de problèmes de santé. ...
Thesis
La connectivité des capteurs intelligents, communément appelée Internet des objets (IoT), fait progresser les niveaux de productivité et de communication. L'IoT a été confronté à de nombreux défis, c'est pourquoi le Futur Internet des Objets (FloT) a été fréquemment discuté. Le routage dans le FloT est un service essentiel pour permettre une communication efficace entre les objets intelligents, où la qualité de service (QoS) de ce routage est l'un des problèmes critiques de ces réseaux. Dans notre thèse, nous proposons deux algorithmes de routage pour les réseaux IoT. Notre premier algorithme de routage proposé est E-RPL, qui est une amélioration du protocole RPL. Nous améliorons le protocole de base avec de nouvelles modifications dans le mécanisme d'envoi des paquets de contrôle, ainsi que la proposition d'une nouvelle fonction objective multi-contrainte pour minimiser le coût de la route. E-RPL utilisera plusieurs propriétés de QoS comme métriques pour acheminer les paquets, ce qui diminuera la consommation d'énergie et la surcharge dans le réseau (Overhead). Il améliorera également la qualité des liens en diminuant le délai. Le deuxième algorithme proposé, FIRP, est un protocole de routage bio-inspiré conçu pour le FLOT. L'idée de cet algorithme est inspirée du comportement des lucioles. En imitant ce comportement, les objets intelligents peuvent acheminer leurs paquets vers la destination en s'appuyant sur les noeuds qui ont de meilleures performances dans le réseau en utilisant la méthode de prise de décision multicritères Simple Additive Weight (SAW). Les résultats de l'évaluation et les tests statistiques montrent l'efficacité de notre algorithme de routage.
... Based on this fact, the paper has completely investigated the specific item life cycle phases. The potential application of IoT is enormous, and IoT techniques can accompany the entire life cycle of the item for better vitality management [78]. Figure 12 shows the system architecture of the product lifecycle. ...
Article
Industrial Internet of Things (IIoT) is a convincing stage by interfacing different sensors around us to the Internet, giving incredible chances for the acknowledgment of brilliant living. It is a fast growing technology in the present scenario. IIoT has its effect on almost every advanced field in the society. It has impact not only on work, but also on the living style of individual and organization. Due to high availability of internet, the connecting cost is decreasing and more advanced systems has been developed with Wi-Fi capabilities. The concept of connecting any device with internet is “IIoT”, which is becoming new rule for the future. This manuscript discusses about the applications of Internet of Things in different areas like — automotive industries, embedded devices, environment monitoring, agriculture, construction, smart grid, health care, etc. A regressive review of the existing systems of the automotive industry, emergency response, and chain management on IIoT has been carried out, and it is observed that IIoT found its place almost in every field of technology.
... The issues with data acquisition have been addressed using standardized technology like RFID (Radio-Frequency IDentification) (Abdullah et al., 2020) and using IoT (Internet of Things) enabled smart devices for gathering data (Evtodieva et al., 2020). Elsewhere the use of cloud computing has been shown to provide solutions to issues of acquisition and scalability (Tao et al., 2016). Table 3 points out the proposed solutions to the aforementioned issues. ...
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In order to realize the goals of Industry 5.0 (I5.0), which has data interoperability as one of its core principles, the future research in the Supply Chain (SC) visibility has to be aligned with socially, economically and environmentally sustainable objectives. Within the purview of circular economy, this paper indicates various aspects and implications of data sharing in the SCs in light of the published research. Taking into consideration the heterogeneity of data sources and standards, this article also catalog all the major data-sharing technologies being employed in sharing data digitally across the SCs. Drawing on the published research from 2015 to 2021, following the PRISMA framework, this paper presents the state of research in the field of data sharing in SCs in terms of their standardization, optimization, simulation, automation, security and more notably sustainability. Using the co-occurrence metric, bibliometric analysis has been conducted such that the collected research is categorized under various keyword clusters and regional themes. This article brings together two major themes in reviewing the research in the field. Firstly, the bibliometric analysis of the published articles makes manifest the contours of the current state of research and the future possibilities in the field. Secondly, in synthesizing the research on the foundations of sustainability within the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework, this article deals with the various aspects and implications of information sharing in the SCs. By bringing these two themes together, this paper affords a prospective researcher with the research vis-à-vis the information sharing in SC, starting from the actual data standards in use to the modality and consequence of their application within the perspective of the circular economy. This article, in essence, indicates how all the aspects of data sharing in SCs may be brought together in service of the theme of I5.0.
... Many studies have developed IoT for different fields, and it has been executed in different domains, such as logistics and transportation, public and personal, environment (office, home, plant), energy, and biomedicine [88]. In the IoT-based energy domain, users are allowed to envision energy use in real-time. ...
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The current advances in the integration of devices through the internet of things (IoT) have encouraged researchers to focus on the applications of IoT in the automotive industry. Although different achievements in the in-vehicle network analysis and traffic management have been already reviewed, a comprehensive study to bring together the main applications of the IoT in the automotive industry is required. Internal combustion engines (ICEs) are established as the most common prime-mover for cars, however, with the depleting fossil-fuel resources, the interest in the usage of fuel cells and batteries has increased. In this regard, the main goal of the current study is to evaluate the application of IoT in batteries, fuel cells, and ICEs. This paper is also centralized on different types of IoT applications and combines them with empirical articles such as Random Location Detection, Vehicle Theft Prevention, Observation of vehicle performance, and industrial management of vehicles. As an output of this comprehensive review, different usages of the IoT in the automotive sector will be clarified. Also, this article can be considered as a basis for advancing the recent implementation of the IoT in the fuel cell, battery, and ICE domains.
... A IoT não é apenas o acionamento de "coisas" usando a Internet, faz parte dessa tecnologia também a coleta e o processamento de informações do ambiente ou das redes envolvidas (OLIVEIRA, 2017;ANDRADE, 2018). A IoT é um dos pilares tecnológicos da Indústria 4.0, também conhecida como 4ª Revolução Industrial (BARBOSA; CALEGARI, 2020; DOS SANTOS; DOS SANTOS; DE SOUZA SILVA JR, TAO et al., 2016), outros pilares são: Big Data e Data Analytics, Robôs Autônomos, Simulação, Integração de Sistemas, "Cibersegurança" (Cyber Security), Computação em Nuvem (Cloud Computing), Impressão 3D, Realidade Aumentada. Na prototipagem de soluções de IoT, basicamente, são utilizadas três famílias de placas microcontroladoras: Arduino, Raspberrry Pi e ESP8266. ...
... According to trustworthy data, the industry consumes more energy than other sectors, accounting for more than 37 percentage points of total world energy provided. In the industrial sector, manufacturing necessitates substantial energy [12,25]. e energy-saving and emission-reduction (ESER) plan are critical in ensuring the industrial industry's long-term viability in the green transition. ...
Article
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Economic progress is built on the foundation of energy. In the industrial sector, smart factory energy consumption analysis and forecasts are crucial for improving energy consumption rates and also for creating profits. The importance of energy analysis and forecasting in an industrial environment is increasing speedily. It is a great chance to provide a technical boost to smart factories looking to reduce energy usage and produce more profit through the control and optimization modeling. It is tough to analyze energy usage and make accurate estimations of industrial energy consumption. Consequently, this study examines monthly energy consumption to identify the discrepancy between energy usages and energy needs. It depicts the link between energy consumption, demand, and various industrial goods by pattern recognition. The correlation technique is utilized in this study to figure out the link between energy usage and the weight of various materials used in product manufacturing. Next, we use the moving average approach to calculate the monthly and weekly moving averages of energy usages. The use of data-mining techniques to estimate energy consumption rates based on production is increasingly prevalent. This study uses the autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) to compare the actual data with forecasting data curves to enhance energy utilization. The Root Mean Square Error (RMSE) performance evaluation result for ARIMA and SARIMA is 8.70 and 10.90, respectively. Eventually, the Variable Important technique determines the smart factory’s most essential product to enhance the energy utilization rate and obtain profitable items for the smart factory.
Chapter
This chapter aims to highlight the usage of IoT in the current world scenario and how it is extended and connected to the devices that we use in our daily life, making them smart and creating a global infrastructure for ambient living. The IoT offered making our life’s easier; hence, increasing the quality of life through ambient living environments. The chapter also presents an in-detail knowledge regarding different IoT protocols available and current state of the art for ambient living using IoT. The chapter will also give its readers a future direction to the topic by including a case study regarding the ‘Smart Geyser’. The case study concluded that implementing IoT on simple gas geyser is not only easy but it could give an energy savings up to 15%.
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The massive growth of diversified smart devices and continuous data generation poses a challenge to communication archi-tectures. To deal with this problem, communication networks consider fog computing as one of promising technologies that can improve overall communication performance. It brings on-demand services proximate to the end devices and delivers the requested data in a short time. Fog computing faces several issues such as latency, bandwidth, and link utilization due to limited resources and the high processing demands of end devices. To this end, fog caching plays an imperative role in addressing data dissemination issues. This study provides a comprehensive discussion of fog computing, Internet of Things (IoTs) and the critical issues related to data security and dissemination in fog computing. Moreover, we determine the fog-based caching schemes and contribute to deal with the existing issues of fog computing. Besides, this paper presents a number of caching schemes with their contributions, benefits, and challenges to overcome the problems and limitations of fog computing. We also identify machine learning-based approaches for cache security and management in fog computing, as well as several prospective future research directions in caching, fog computing, and machine learning.
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Purpose The concept of sustainable manufacturing has been adopted by manufacturing organizations to develop eco-friendlier products and processes. In recent times, industries are progressing toward Industry 4.0 (I4.0). Guided with smart intelligent devices, I4.0 can possibly decrease excess production, material movement and consumption of energy. If so, it is hypothesized that there is a good synergy between I4.0 and sustainability, which warrants an integrated approach for implementation. This amalgamation is termed as “Sustainable industry 4.0.” Hence, this paper aims to systematically identify and analyze the drivers for this integration. Design/methodology/approach This paper presents the analysis of 20 drivers identified from literature review for simultaneous deployment of I4.0 and sustainable manufacturing. Interpretive structural modeling (ISM) is used to derive the structural model for analyzing the causal association between drivers. Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis is being performed to group the drivers. Findings The results showed that the dominant drivers derived are societal pressure and public awareness (D18), government policies on support I4.0 (D12), top management involvement and support (D15) and government promotions and regulations (D16). Also, the MICMAC analysis revealed many driving, dependent, linkage and autonomous drivers. Research limitations/implications The opinion from experts with combined expertise on I4.0 and sustainability was obtained. The respondent size could be increased in future studies. Practical implications The study has been done based on inputs from industry practitioners. Managerial and practical implications are presented. ISM shows that the drivers for deploying sustainable I4.0 are highly inter-related. It also reveals the pre-requisites for each level of the drivers. Originality/value The idea of analyzing the drivers for sustainable I4.0 is the original contribution of the authors.
Chapter
To understand and optimize the impact of a product along its lifecycle, the consideration of social, economic and environmental factors is of increasing interest for customers and regulating institutions. In this context, Life Cycle Sustainability Assessment (LCSA) is used to monitor and understand the trade-offs of the three sustainability dimensions. Today, LCSA still faces major challenges, such as availability, actuality and validity of data or consistent and appropriate measures to support Design for Sustainability. New technological innovations may support the enhancement of the methodology. In the background of a digitized product and service lifecycle, especially Industry 4.0 technologies, Digital Twins and the integration of Artificial Intelligence may solve data and feedback challenges through new ways of data collection, transfer, validation and intelligent analysis. This paper aims at exploring this potential of new technological innovations for an enhanced LCSA of capital goods and durable consumer goods as well as related services and proposes a taxonomy. Therefore, a literature review to identify existing digital solutions and research gaps is established. For the identified gaps, a new concept, the Digital Lifecycle Twin for LCSA is presented. The authors address both, the positive but also the negative implications put on the LCSA framework from a sustainability perspective. Ultimately, these findings will contribute to the enhancement of the LCSA methodology as well as to the design of a support system to enable environmentally and socially sound design of products and services.
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With the rapid growth of advanced technologies in the manufacturing sector, a revolution in manufacturing systems is underway and smart manufacturing and its sustainability is becoming the key components towards the fourth industrial revolution. In this context, the IIoT (industrial internet of things), represents a bridge between the digital and physical environment by providing an interactive relation between smart devices and machines also through data sharing. Therefore, it creates a working environment where decisions are made in real-time. The huge data amount generated through the manufacturing system, the high reliability, low latency, and high connectivity demands of IIoT-enabled intelligent manufacturing system requires an advanced wireless transmission technology that goes far beyond the 3rd and 4th generation mobile network. 5G is the most appropriate communication technology for this new IIoT enabled smart manufacturing system’s requirements. Based on the requirements of sustainable smart manufacturing and the characteristics of the 5G wireless communication, this paper proposes a 5G-enabled IIoT framework architecture towards a sustainable smart manufacturing environment, that will allow the support of manufacturers and smart factories in the industrial 4.0 revolution. This is by improving while enhancing efficiency, process and product quality, and sustainability in the whole manufacturing system. Besides, the security threats and challenges of the 5G-IIoT enabled smart manufacturing are also analyzed.
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Traditional design requires designers to envisage a product operating environment in order to identify customer needs. Analyzing product usage context by collecting actual product operating data during the product in use empowers new opportunities for the projection of requirement specifications and understanding of use case scenarios. This paper proposes a data-driven inverse design optimization approach to provide decision support to product personalization design. A closed-loop decision-making framework is formulated by integrating forward design and inverse problem solving within a coherent framework of data-driven analysis. An application to the transmission system personalization design of wheel loaders is presented to demonstrate how personalized product usage contexts are identified through inverse analysis of product operating data under different operating conditions. A particle swarm optimization (PSO) algorithm incorporated with Simulink simulation is developed to solve the multi-objective optimization of power performance and fuel economy for wheel loaders.
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In recent trends, all industries are converted into smart and digital based concepts due to rapid production and quality assurance. The control system and computerized monitoring systems are used in modern industries. The sensors, software and other technologies are playing an essential role in industries. It is used to connect and exchange the data with other devices and systems through internet. These concepts are covered in Internet of Things (IoT) and it acts as a convergence of multiple technologies. The present paper is deals with the role of IoT in materials and manufacturing industries through different collection of literature reviews.
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Digitalization is an increasingly important direction of energy innovation moving forward. Nevertheless, which emerging digital technology is more crucial during the energy sector transformation stays underexplored. Using a near-universe of online job postings data collected between 2010 and 2019, we show that among the emerging digital technologies (i.e., Artificial Intelligence, Big data, Internet of Things, Robotics, Blockchain technology, and Cloud computing), Artificial Intelligence is the most widely adopted in the energy sector. We further calculate a systematic measure of the emerging digital technology intensity in job skill requirements and show that Artificial Intelligence proves to be the most valuable in the energy sector, either from the employee’s or the employer’s perspective. Particularly, Artificial Intelligence brings the highest wage premium to the average wage of the adopted energy firm and the local labor market. Meanwhile, Artificial Intelligence contributes the most to energy firms’ performance. Our findings suggest that energy firms should intentionally increase the requirement for Artificial Intelligence in hiring new talents. Our findings also indicate that major energy firms should take the leading role in adopting the emerging digital technologies to enjoy the predominant advantage as early as possible.
Chapter
Given the rapid development of the video game industry, it is valuable to understand the effectiveness of this media in inducing positive emotions towards tourism destinations and in shaping tourists’ visit intention. While research has begun to investigate video game-induced tourism (e.g. Dubois et al. Tourism Review, 73(2), 186–198, 2018, Current Issues in Tourism, 24, 1–13, 2020), this proposed conceptual chapter explores several known predictors of tourists’ intention to visit in the context of video game-induced tourism using the stimulus-organism-response (SOR) theory. Specifically, it considers the influence of presence—the psychological state of feeling lost or immersed—nostalgia and imagination proclivity as antecedents of visit intention. The chapter theorizes that the more players believe their virtual experience to be true, the more likely they will exhibit emotional reactions, and, in turn, increase their intention to visit the media-related destination.
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The main aim of using the IoT paradigm is related to the possibility of a connectivity extension of several common SHM devices by means of Internet. The connected devices are thus able to transmit and process data, guaranteeing new scenarios in the design of acquisition systems in different fields of science and engineering. The innovations have led the researchers to extend the application of the IoT paradigm to the SHM of masonry structures making sure that the experiments conducted in this framework are able to ensure good results with promising future improvements. The main uses, to date, have been implemented, for example, to monitor individual structural elements, reducing the risks for users due to partial or total collapses of the structure, or for the identification, detection and characterization of damage and degradation of construction materials. The aim of this work is to expose a general overview of the SHM systems used by the authors for masonry structures belonging to historical and cultural heritage, arguing their use for the protection from earthquakes with related advantages. This will be shown thanks to two preliminary SHM systems designed and implemented by the authors on two case studies using IoT, described in the paper with their related cyber and physical parts.
Conference Paper
The increasing number of sensors and communication technologies that are built into customer products make information about the product status accessible over the internet. Nonetheless, manufacturers’ Product Lifecycle Management (PLM) Information Systems (IS) do not integrate these product instance data. Furthermore, existing PLM IS do not support product related tasks after the manufacturing phase. In order to understand the impact of data from connected products as new sources of information on PLM, we conducted a systematic literature review. Our results led to a topic map that identifies drivers, use cases and barriers and contextualizes them. We further analyzed existing PLM models that support the analysis of product instance data. We found that the existing PLM IS have several limitations which hinder a successful realization in practice. The results of this review are a first step towards understanding how the Internet of Things (IoT) influences PLM on a firm level.
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Energy is one of the key inputs for a country's economic growth and social development. Analysis and modeling of industrial energy are currently time-intensive processes because more and more energy is consumed for economic growth in a smart factory. This study aims to present and analyse the predictive models of the data-driven system to be used by appliances and find the most significant product item. With repeated cross-validation, three statistical models were trained and tested in a test set: 1) general linear regression model (GLM), 2) support vector machine (SVM), and 3) boosting tree (BT). The performance of prediction models were measured by R2 error, root mean squared error (RMSE), mean absolute error (MAE), and coefficient of variation (CV). The best model from the study is the support vector machine (SVM) that has been able to provide R2 of 0.86 for the training data set and 0.85 for the testing data set with a low coefficient of variation, and the most significant product of this smart factory is Skelp.
Chapter
This chapter summarizes research needs in developing and enhancing data sets, data sources, and data science methods for applying data science to the broad field of sustainability. Overall, while there is a great need to develop environmental science, manufacturing and technology systems, and societal systems data at greater spatial and temporal resolution, there is also a need to consider what sustainability questions can be addressed by creative use of the data sets currently available. Furthermore, advances in data science remain foundational to realizing the potential of many techniques (including machine learning, artificial intelligence) to enhancing environmental and societal sustainability. Advances in explainable AI, edge computing, and applying the advantages of the 5G technology that is on the horizon are all required. Importantly, engagement of multiple disciplines – particularly computer science – along with multiple science and engineering disciplines will be foundational to bringing the power of data science methods to bear on the pressing sustainability challenges.
Preprint
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Water management system towards the country is the biggest challenge to distribute the water to each corner of the country and keeps track of all the information to store it centrally which helps the government in analyzing and predicting the water situation of the country. For implementing the above things the crucial barriers are electrification and network spread all over the country which is a difficult task. The main purpose of this suggested work is to design a wide area network using low power consumption called the LoRa network. Using this network the resultant value of the water meter can transmit to the cloud to make a secure centralized repository system which helps the government as well as different business organizations a lot. The proposed work explains the whole architecture of the end-to-end communication system from water meter to cloud as well as defines all the components for managing end-user and applications. Due to low power consumption the whole communication system, and water meter, can be powered through solar energy through which electrification supply is not required. Hence using the explained technique we can efficiently monitor and collect information from every corner of a country efficiently to manage the consumption of drinking water which helps society a lot.
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Purpose This paper concerns the Ecodesign Directive (2009/125/EC) and the implementing measures (IM) in which ecodesign requirements are set up for energy-using and energy-related products. Previous studies have found that the requirements have a unilateral focus on energy consumption and the use phase. This is not in line with the scientific understanding of ecodesign, where attention should be put on all life cycle phases and all relevant environmental impact categories. This study focuses on the requirements for televisions (TV). A life cycle assessment (LCA) is carried out on two TVs to analyse if other environmental hotspots and life cycle phases should be included in the requirements in the IM of the Ecodesign Directive besides energy consumption in the use phase analysis. Methods The consequential approach is used. The data for the LCA have been gathered from two manufacturers of TVs. In one case, the data were delivered in Excel spreadsheets; in the other case, the authors of this paper together with the manufacturer disassembled a TV and collected the data manually. Results and discussion When applying the consequential approach, the production phase has the highest environmental impact, which is in contradiction with the focus area of the IM. The result of the sensitivity analysis is that the source of electricity is a potentially significant contributor of uncertainty. However, even in a coal-based scenario, the contribution from the production phase is approximately 30 %. Conclusions Based on these results, it is concluded that for future requirement setting in IM, it is necessary to set up requirements that cover more life cycle phases of the product in order to address the most important impacts.
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Assignment problem is considered a well-known optimization problem in manufacturing and management processes in which a decision maker’s point of view is merged into a decision process and a valid solution is established. In this study, taking the complementary relations between expected value and variance in decision making and the synthesizing effect of random variables into consideration, a new model for random assignment problems is proposed; in which the characteristic of assignment problems are considered to present a concrete scheme based on genetic algorithms (denoted by SE ⊕ GA-SAF, for short). We study the model’s convergence using the Markov chain theory, and analyze its performance through simulation. All of these indicate that this solution model can effectively aid decision making in the assignment process, and that it possesses the desirable features such as interpretability and computational efficiency, as such it can be widely used in many aspects including manufacturing, operations, logistics, etc.
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As an example of a new communication technology that has reached a high penetration rate within only a few years, this article looks at the energy demand of mobile phone services in Germany. Mobile phone services combine two trends of modern communication technologies — mobility and connectivity. There have been some estimations of the energy usage of handsets in the past, but the energy usage of the network equipment, which makes the mobility possible, has not been analysed. In this analysis, the energy usage of mobile phones, including charging losses, is calculated using different customer profiles. Additionally, the amount of energy consumed by the network equipment is determined. The results show that the energy demand of mobile phone services is mainly caused by the operation of the network equipment and not by the handsets, even if the poor efficiencies of the charging processes are included in the calculations.
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Environmentally friendly water based fluids have been offered recently by many suppliers. On the other hand the G ratio values obtained for CBN grinding with water based coolants are much lower than with neat oil. This work presents a new water based grinding fluid formulation able to meet both the performance and environmental requirements for CBN grinding. The existence of a reaction between CBN grains and water is evaluated in grinding tests and also in a chemical reactor. The results show that the reaction between CBN grains and water is not significant when compared to the measured volumetric wheel wear in a grinding operation. Based on this fact, a new fluid concept consisting of a high concentration (up to 40%) of sulfonate vegetable oil in water is proposed and tested. In this way it was possible to combine high lubricity, better heat conductivity and good environmental properties in one fluid. The results show performance comparable to the obtained with neat oil.
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The importance of the maintenance(1) function has increased because of its role in keeping and improving system availability and safety, as well as product quality. To support this role, the development of the communication and information technologies has allowed the emergence of the concept of e-maintenance. Within the era of e-manufacturing and e-business, e-maintenance provides the opportunity for a new maintenance generation. As we will discuss later in this paper, e-maintenance integrates existing telemaintenance principles, with Web services and modern e-collaboration principles. Collaboration allows to share and exchange not only information but also knowledge and (e)-intelligence. By means of a collaborative environment, pertinent knowledge and intelligence become available and usable at the right place and time, in order to facilitate reaching the best maintenance decisions. This paper outlines the basic ideas within the e-maintenance concept and then provides an overview 2 of the current research and challenges in this emerging field. An underlying objective is to identify the industrial/academic actors involved in the technological, organizational or management issues related to the development of e-maintenance. Today, this heterogeneous community has to be federated in order to bring up e-maintenance as a new scientific discipline. (0 2007 Elsevier Ltd. All rights reserved.
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Energy consumption reduction is critical in various industrial environments. Machine tool manufacturers could contribute to this matter by developing advanced functions for machines. Power consumption of machining center was measured in various conditions. The conclusion was that modifying cutting conditions reduces energy consumption. This applies for either regular drilling, face/end milling or deep hole machining. Also, a new acceleration control method is developed to reduce energy consumption by synchronizing spindle acceleration with feed system. Experiments were performed to verify these methods and promising results were achieved.