The digital transformation of the production sector is setting the scene for a major industrial change. The need for supporting companies in this transformation is currently covered by several ...maturity models, generally operationalized through standardized questionnaires, which provide, as an outcome, an assessment of the current maturity stage and a set of general improvement recommendations according to it. However, to provide companies with a more tangible support, there is a need for more individual approach. In order to deal with this need, this paper proposes, following a design science research framework, a novel approach based on Problem-Based Learning for structuring the assessment procedure as a dialectic process. This approach aims at facilitating the contextualization of the assessed company and, consequently, the identification of context-specific improvement recommendations. The proposed approach, supported by a maturity model used for framing information collected during the assessment process, is tested in three industrial cases. Although these have been assessed at the same maturity stage, different improvement recommendations have been proposed according to contextual factors such as strategic goals, core processes and key performance indicators.
•Current status and future prospects of renewable and non-renewable resources are evaluated in light of COVID-19.•Providing a secure supply of electricity systems in terms of cyber-attacks and ...climate change are addressed.•Modernization and digitalization of the energy system are assessed.•The role of industrial 4.0 is discussed to achieve the SDGs and to enhance energy efficiency.•Integration of the smart grid with blockchain network is offered.
Taking into consideration of substantial role of energy system and sustainable development goals (SDGs) in modern society, it is critical to analyse current situation and forthcoming renewable energy development strategies under the impact of COVID-19. For this purpose, this paper provides significant new insights to assess effective approaches, opportunities, challenges and future potential capabilities for the development of energy systems and SDGs under on-going pandemic and in case of a future global crisis. The digital energy systems with Industry 4.0 (I4.0), which provide noteworthy solutions such as enhancing energy efficiency policy, providing clean, secure and efficient energy and achieving SDG targets, has been discussed and evaluated. Integration of the smart grid (SG) architecture with blockchain-Internet of Things (IoT)-based technologies is also offered. Alongside the various discussions, short-term, mid-term and long-term plans have been suggested in determining the well-defined renewable energy development and SDGs targets, struggling with climate change, transition to a more sustainable energy future and reaching global net-zero emissions. To achieve SDGs and provide more strong and sustainable energy systems under the continuing pandemic and in case of potential risk of forthcoming global crisis, this paper reveals significant perceptions that inform politicians and legislators in performing successful policy decisions.
•Digitalisation & intelligent robotics are tools in value chain of waste management.•Municipal waste management development is defined by Circular Economy Package.•4 segments: Collection & Logistics, ...Machines & WTP, Business Models and Data Tools.•Extensive survey of (inter)national data (period 2001–2019): 114 sources utilized.•Smart Waste Factory: Machines are digitally connected and communicate with waste.
The general aim of circular economy is the most efficient and comprehensive use of resources. In order to achieve this goal, new approaches of Industry 4.0 are being developed and implemented in the field of waste management. The innovative K-project: Recycling and Recovery of Waste 4.0 - “ReWaste4.0” deals with topics such as digitalisation and the use of robotic technologies in waste management. Here, a summary of the already published results in these areas, which were divided into the four focused topics, is given: Collection and Logistics, Machines and waste treatment plants, Business models and Data Tools. Presented are systems and methods already used in waste management, as well as technologies that have already been successfully applied in other industrial sectors and will also be relevant in the waste management sector for the future. The focus is set on systems that could be used in waste treatment plants or machines in the future in order to make treatment of waste more efficient. In particular, systems which carry out the sorting of (mixed) waste via robotic technologies are of interest. Furthermore “smart bins” with sensors for material detection or level measurement, methods for digital image analysis and new business models have already been developed. The technologies are often based on large amounts of data that can contribute to increase the efficiency within plants. In addition, the results of an online market survey of companies from the waste management industry on the subject of waste management 4.0 or “digital readiness” are summarized.
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•Eighteen challenges to Industry 4.0 initiatives for supply chain sustainability were identified.•The challenges were empirically analyzed in emerging economies in Indian context.•AHP ...ranks the challenges and their dimensions for their priority.•Organizational challenges dimension obtained the topmost rank.•Several noticeable implications and future research directions were provided.
Industry 4.0 initiatives can influence whole business system via transforming the means the products are designed, produced, delivered and discarded. Industry 4.0 is relatively novel to developing nations, especially in India and needs a clear definition for proper understanding and practice in business. This paper aims to recognize key challenges to Industry 4.0 initiatives and analyze the identified key challenges to prioritize them for effective Industry 4.0 concepts for supply chain sustainability in emerging economies by taking Indian manufacturing industry perspective. Industry 4.0 initiatives can help industries to incorporate environmental protection and control initiatives as well as process safety measures in supply chains towards sustainable supply chains. However, adoption of Industry 4.0 initiatives is not so easy due to existence of many challenges. Therefore, the present research identifies 18 key challenges to Industry 4.0 initiatives for developing supply chain sustainability using an extensive literature review. These challenges were analyzed through 96 responses received from Indian manufacturing sector using a questionnaire based survey. Explanatory Factor Analysis results classified identified challenges into four key dimensions of challenges. Analytical Hierarchy Process further ranks the identified dimensions of challenges and related challenges. Findings of the study revealed that Organizational challenges holds the highest importance followed by Technological challenges, Strategic challenges, and Legal and ethical issues. This work is very useful for practitioners, policy makers, regulatory bodies and managers to develop an in-depth understanding of Industry 4.0 initiatives and eradicate the potential challenges in adopting Industry 4.0 initiatives for supply chain sustainability.
•A comprehensive literature review of Industry 4.0 based on text mining was performed.•Four clusters emerged: “Business”, “Operations”, “Technological solutions” and “Work and skills”.•The analysis ...allowed the understanding of the evolution of research areas on the topic.•Prominent future research directions emerged from the analysis of recent studies.
The existing literature provides a ‘piecemeal’ approach to our understanding of Industry 4.0 as a ‘technological revolution’. However, such an approach leads to scattered literature and the possibility (or risk) that the focus could spin out of control in terms of the existing themes and future research trends. Consequently, the aim of this research is twofold: (i) to identify the main overarching themes discussed in the past and track their evolution over time, and (ii) propose a future research agenda for each overarching theme that considers the multidisciplinary nature of research efforts made on the topic. To reach the first objective, a method based on text mining was implemented. To reach the second one, a review based on recent and relevant paper was made for each overarching theme. Text mining suggests four overarching themes: (i) business, (ii) operations, (iii) technological solutions and (iv) work and skills. ‘Business’ includes studies that investigate the impact of Industry 4.0 on business perspectives and they suggest that governments and industries have a change in manufacturing perspective and attempt to benefit from this industrial revolution wave. ‘Operations’ includes studies investigating the impact of Industry 4.0 new technologies on production, logistics, and supply-chain processes. Manuscripts belonging to ‘Technological solutions’ discuss technological solutions at the core of Industry 4.0. ‘Work and skills’ stream of literature attempts to under the human element lurking behind the scene of Industry 4.0 regarding opportunities and implications. Finally, the paper suggests a future research agenda for each overarching theme, thus paving the way for new research on the topic.
•The food sector has shown low response to embrace IoT.•We present a framework to improve the resource efficiency of food manufacturing.•The framework is based on design and implementation of a ...number of IoT-based tools.•The framework helps monitoring food waste generation and use of energy and water.
The food sector is currently very inefficient due to a large amount of food waste it generates, and the volumes of water and energy used. This problem is aggravated by increasing economic costs and stricter regulations associated with the disposal and treatment of food waste, carbon emissions and wastewater discharge. Because of this, resource efficiency is key to a sustainable food system. In this context, it is essential to reduce food waste, energy and water through transparent and accurate real-time monitoring to be able to understand the real reasons behind their generation/use. Understanding these reasons would help food manufacturers to redesign their processes and achieve operational improvements. The Internet of Things (IoT), a relatively new manufacturing concept within Industry 4.0, can support this. IoT consists of an information technology infrastructure for data collection and distribution, that can significantly influence the efficiency and performance of manufacturing systems. This article presents an IoT-based framework for monitoring the generation of food waste and the use of energy and water in the food sector. The framework supports the identification of improvements to optimise the resource efficiency of food manufacturing through the design and implementation of a number of IoT-based tools.
Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data ...coming from Internet of Things (IoT) devices toward the Internet. In the next future, Edge-based approaches will be essential to support time-dependent applications in the Industry 4.0 context; thus, the paper proposes BodyEdge , a novel architecture well suited for human-centric applications, in the context of the emerging healthcare industry. It consists of a tiny mobile client module and a performing edge gateway supporting multiradio and multitechnology communication to collect and locally process data coming from different scenarios; moreover, it also exploits the facilities made available from both private and public cloud platforms to guarantee a high flexibility, robustness, and adaptive service level. The advantages of the designed software platform have been evaluated in terms of reduced transmitted data and processing time through a real implementation on different hardware platforms. The conducted study also highlighted the network conditions (data load and processing delay) in which BodyEdge is a valid and inexpensive solution for healthcare application scenarios.
The digital economy refers to the economic activities that emerge from connecting individuals, businesses, devices, data, and operations through digital technology. It includes online transactions ...across multiple sectors and technologies, such as the Internet, mobile technology, big data, and information and communications technology. The digital economy differs from a traditional economy because it relies on digital technology, online transactions, and its transformative effect on traditional industries Digital innovations such as the Internet of Things (IoT), Artificial Intelligence (AI), Virtual Reality, Blockchain, and autonomous vehicles all play a part in creating a digital economy. For this study, various papers on ”Digital Economy” and ”Industry 4.0” are identified from Scopus, Google Scholar and other research platforms and further studied briefly. This review paper has been developed after studying the digital economy and its needs in the Industry 4.0 Environment. The defining trends, key enablers, features and challenges associated with the digital economy towards Industry 4.0 are discussed briefly. Finally, the paper identifies and discusses the significant requirements of Industry 4.0 fulfilled through the digital economy. Today, customers are becoming aware of goods and services online and are turning to the industry for long-term solutions by deploying digital technologies. The digital economy is built on hyper connectivity, the growing interconnectedness of individuals, organisations, and machines due to the Internet, mobile technologies, and the IoT. Industry 4.0 technologies are automation, data exchange, cloud computing, robotics, big data, AI, the IoT, and other technological trends are all part of the industrial sector’s digital transformation, which aims to achieve industrial objectives and intelligent manufacturing practices that engage with customers, emerging technologies, and innovation. The economy is becoming more digital, changing how products and services are provided and consumed. A new road map is being provided by Industry 4.0 services to help many industries adapt their conventional methods and support the new revolution. In the digital economy, scaled-up, integrated ecosystems that leverage software platforms to generate value, build resilience, and stimulate innovation via networked goods, assets, people, and processes rapidly replace old, linear value chains with partner participation.
•The digital economy refers to the economic activities that emerge from connecting individuals, businesses, devices, data, and operations through digital technology.•It includes online transactions across multiple sectors and technologies, such as the Internet, mobile technology, big data, and information and communications technology.•This review paper has been developed after studying the digital economy and its needs in the Industry 4.0 Environment.•The defining trends, key enablers, features and challenges associated with the digital economy towards Industry 4.0 are discussed briefly.•Finally, the paper identifies and discusses the significant requirements of Industry 4.0 fulfilled through the digital economy.
Industry 4.0, referred to as the fourth industrial revolution, is becoming part of business life and it fundamentally influences the quality of business processes and products. In particular, ...intelligent technologies that are indispensable in this industrial revolution play a dominant role. This paper presents the results of empirical research focusing on the current state with implementing intelligent technologies, which are grouped into four categories: smart devices, identification technologies, localisation/navigation technologies and information technology/robotics. The empirical research was conducted from a large sample of industrial enterprises in the Slovak Republic. All enterprises were multinational companies whose parent companies reside abroad. Another question was what the expectations of quality managers with the deployment of intelligent technologies in 2025 are. Together, we have identified 14 technologies and 26 manufacturing and logistics processes. Based on the difference between the current state of use of intelligent technologies and their future deployment, we can identify their growth potential. This growth is quantified as the difference between the current state of the technology in the process and its future. In addition to the expectations of quality managers, we also determined the direction of product development in technological enterprises.
Supply chain disruption refers to a breakdown, often caused by an unforeseen incident or risk, in a supply chain's production or distribution process. Contemporary supply chains are globalized, ...complex, and extended, exhibiting an increased vulnerability to a multitude of risks and disruptions. However, the current trend of real-time data exchange through smart technologies, also known as industry 4.0, provides significant opportunities to reshape the conventional business operations and effectively cope with unanticipated supply chain breakdowns. Yet, limited attention has been paid to the role played by industry 4.0 technologies in mitigating supply chain risks and any resulting disruptions. By bringing together these inter-related yet often separate concepts, we devise a novel model that addresses this knowledge gap. In this article, we empirically test our model on a sample of 302 responses received from senior managers of the Australian food processing industry. We found that supply-demand mismatch, process risks, and transportation risks are currently the major sources of supply chain disruptions. Specifically, supply-demand mismatch appears to be the most severe and attention seeking risk, followed by process and transportation risks. We also reveal that industry 4.0 technologies significantly mitigate supply-demand mismatch and process risks and any resulting supply chain disruptions. Contrary to our expectations, however, the impact of industry 4.0 technologies on transportation risks is found to be positive but nonsignificant. This is the first empirical article to assess the extent to which the three critical supply chain risks may undermine firm performance and to explore the moderating effect of industry 4.0 technologies. We draw managers' attention to the detrimental impact of supply chain disruptions and the significance of industry 4.0 technologies in dealing with adversities.
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