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Industry 4.0 (I4.0) brings a set of challenges that need to be settled to enable the expected industrial revolution. Cyber-Physical Systems (CPS) and Autonomous Robots are two of mainstream I4.0 technologies and can be combined with other Enabling Technologies to overcome main I4.0 challenges. This Systematic Literature Review (SLR) aimed to understand how these Enabling Technologies were combined with CPS and Autonomous Robots to achieve fully featured I4.0 solutions. The 5C is a CPS architecture which was used as a measurement to CPS compliance. After filtering and processing 15,144 papers from six different academic search engines, it was found that full 5C compliant solutions are rare to find; that not all enabling technologies were integrated; and most of existing research focused in implementing practical solutions, but comparison to conventional approaches is scarce. We conclude that there is a need for further research to accomplish full 5C I4.0. [ABSTRACT FROM AUTHOR]

The manufacturing industry faces a new revolution, grounded on the intense digitalization of assets and industrial processes and the increasing computation capabilities imposed by the new data-driven digital architectures. This reality has been promoting the Digital Twin concept and its importance in the industrial companies' business models. However, with these new opportunities, also new threads may rise, mainly related to industrial data protection and sovereignty. Therefore, this research paper will demonstrate the International Data Spaces reference model's application to overcome these limitations. Following a pilot study with a Portuguese machine producer/maintainer enterprise, this paper will demonstrate the development of a cutting and bending machine Digital Twin, leveraged on an International Data Spaces infrastructure for interoperability, for the plastic and metal industry and its importance to introduce this machine manufacturing company in a new business-to-business marketplace from the EU project Market 4.0. [ABSTRACT FROM AUTHOR]

In a world bombarded with unprecedented challenges, it is paramount for organizations to embrace resilience in all their processes, albeit supply chain management. In the wake of ever-intensifying race for digital transformation, it is crucial for organizations to follow structured roadmaps towards building digital supply chain resilience (DSCR) through striking a balance between supply chain resilience (SCR) and supply chain vulnerabilities (SCV), in a manner that does not erode profits, neither expose the organization to increasing vulnerabilities. The paper addresses the evolution of SCR, the SCR and SCV drivers, and recommends investment in particular Industry 4.0 (I4.0) enablers. The outcomes of this paper are (a) a discussion of the complementary relationship between SCR and SCV drivers; (b) a thorough understanding of the possible contributions of I4.0 technologies towards DSCR; and (c) a roadmap for future research into the integration of SCR drivers and SCV constrained by the resilience fitness space (RFS). [ABSTRACT FROM AUTHOR]

Industry 4.0 technologies create a connected ecosystem that allows for real-time monitoring, control, and optimization. This enables the manufacturing industry to move the ultimate goal of their businesses from lean to leagile. Then, to meet the needs of leagile manufacturing, an integrated production planning and scheduling system is needed. The academic world responds to the need by the growth of papers. Many methodologies, models, frameworks, and methods have been proposed. Literature abounds on classifying them, yet it remains inconclusive mainly on their applicability to Industry 4.0. In this regard, this paper conducts a literature review aiming to show the state of the art and discover the most promising production planning and scheduling method for Industry 4.0 among the many. Lastly, on the basis of this study, recommendations on possible future research directions are provided for researchers, and the design of the next-generation production planning and scheduling system for Industry 4.0 is also suggested. [ABSTRACT FROM AUTHOR]

The paper explores the barriers that impact operational excellence plans, when considering continuous improvement and Industry 4.0 practices. The paper is pioneering and transversal, considering organizations with different expertise, in 10 different countries. The study makes a joint quantitative and qualitative analysis and proposes a framework to show the impact on human resources and operations management. For this, it carries out a quali-quantitative study, carried out with the aid of a semi-structured questionnaire, sent to 91 organizations. The quantitative study was performed using interdependent multivariate analysis, resulting in an exploratory factorial study and exploration of principal components. The qualitative study evaluated propositions that impact operations management. The results show the variables that impact the operations management and human resources, in terms of quality, technologies and processes, when considering the implementation of an operational excellence plan and Industry 4.0 practices. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution, also known as Industry 4.0, stems from the rapid advancement of digital technologies such as the Internet of Things and Cyber-Physical Production Systems. It has the potential to weave positive changes to firms and impact organizational structure layers. Therefore, it provides an impetus for the collaboration of factories, suppliers, and customers. Nevertheless, due to the difference of Industry 4.0 vision among companies, there is a lack of unified perception and approach of its implementation roadmap. Therefore, many firms in both developed and developing countries that step in the way of digital transformation encounter not only organizational, technological, and operational challenges but are also compelled to cope with a large deal of confusion. Hence, this paper aims to identify the main concepts, characteristics, and technology enablers related to Industry 4.0 to provide stakeholders with a clear understanding of this paradigm. It then clusters and matches the derived concepts and characteristics associated with Industry 4.0. Further, the paper provides an analysis of how these clusters are supported by technology enablers of Industry 4.0, as well as managerial implications. [ABSTRACT FROM AUTHOR]

One of the key aspects of digitalization brought by Industry 4.0 is driven by the Internet of Things. Perhaps, the most interesting component of digital transformation is Augmented Reality. Augmented reality is merging the digital and physical worlds in the same experience. This new technology is accepted and applications are initiated in various areas including manufacturing. The main usage area in manufacturing is planning, execution, and verification of the assembly and maintenance operations. Likewise, augmented reality is used in the training of inexperienced people and to guide them by remote expert support. However, the augmented reality application selection, especially for non-technology savvy manufacturing organizations is challenging. Detailed and time-consuming analyses are required to understand the key features to compare and select the most suitable augmented reality application. In this paper, the most critical nine augmented reality software selection criteria are identified. To help organizations to apply such criteria and make a selection that is most suitable for the enterprise, a multi criteria decision-making approach is suggested. The suggested method is based on a fuzzy spherical number. The complex proportional assessment method is used to calculate the rankings. Therefore, the suggested method is called SF-COPRAS. Moreover, the detailed definition of augmented reality features and terminologies is explained. Several augmented reality use-case scenarios are discussed for manufacturing organizations on their Industry 4.0 initiatives. This paper aims to guide decision makers on their augmented reality software selection journey. The offered framework aims to save time for investigating augmented reality solution features systematically and objectively. [ABSTRACT FROM AUTHOR]

Industry 4.0 has become a key concept and buzzword in the global manufacturing industry. This paper argues that the concept has created an Industry 4.0 narrative that is having a decisive impact on the industry. The paper combines the literatures on the sociology of expectations and regional path development to develop an analytical framework which is employed in an analysis of the Raufoss region in Norway. We find that the expectations created by the global Industry 4.0 narrative have trickled down into national industry and innovation policies. This has resulted in the anchoring of innovation schemes, development of new educational provisions and generated technological capability building among manufacturers in the Raufoss region. In turn, we argue that these actions have enabled regional path extension. [ABSTRACT FROM AUTHOR]

China's foremost national goal is to become a major space power by 2030. Consequently, President Xi Jinping has made the launch of the BeiDou navigation satellite system (BDS) and promotion of a "BDS global network" a national priority. BDS represents a frontier technology of the "fourth industrial revolution" which ushered in the digital age. Using BeiDou as a case study, this paper attempts to analyze the structural features of China's frontier technology strategy and its impact on China's global influence. Significantly, BDS has both military and civilian applications, which is a prominent feature of today's cutting edge technologies. Therefore, a focus on BDS will deepen our understanding of how China is exploring these new types of dual-purpose technologies to expand its global reach. The paper argues that by dramatically restructuring its decision-making process under Xi Jinping, China has been able to adopt a state-led national strategy for using BeiDou domestically, while expanding its global reach through a market-driven approach. This strategy has facilitated the penetration of Chinese BDS applications into the economies and societies of many developing (and some developed) countries. [ABSTRACT FROM AUTHOR]

The current pandemic situation has forced organisations to adapt quickly and change processes through digital transformation. Businesses began to interact with consumers online and generally had to adjust existing processes and develop or improve the products and services offered. The agile transformation as part of Industry 4.0 started several years ago and in the current situation can be considered the best starting point for ongoing changes. The agile approach is mostly used in the field of IT, where it has penetrated mainly into software solutions and project management. Later, this concept began to penetrate deeper into several areas of the organisation, today we can talk about the company-wide transformation into an agile platform. While agility was initially perceived as a benefit, especially for software solutions, today it helps in successful business mainly by penetrating the organisational culture in which organisations define the desired values, ideas and procedures of employee behaviour in the organisation and is able to implement agile management principles. In the presented article, we present the results of research focussed on the analysis of the current state of application of agile management methods in companies operating in Slovakia and the Czech Republic. The aim of this paper is to identify the approach to building an agile culture as a basic prerequisite for their effective implementation. The contribution of this article to agile management research is to identify specific aspects of agile culture that support agile management functioning. The size of the examined sample and the comparison of the results between the group of companies in the Slovak Republic and the Czech Republic provide findings with a high degree of reliability. [ABSTRACT FROM AUTHOR]

New technological development enables to implement circular economy (CE) practices. This phenomenon is taking particular interest for the Academy. The aim of this study is to analyse the cognitive and intellectual structure of the relationship between CE and technology. The proposed research questions seek to answer how the evolution of the number of publications per year, the main authors, journals, institutions and countries in this field, and the most relevant topics and papers in the research area are. It is used a bibliometric approach of co-word analysis of 996 articles published on Web of Science. In addition, it is proposed a research agenda after reviewing the most cited articles and points the research trend topics. There is a need to include topics associated with the social sphere, since most of the research is focused on environmental aspects and economic effects. In recent years, research has been polarised towards the blockchain, Big Data and biorefinery technologies. Although these technologies are in demand, it should not ignore other emerging technologies that could be key to circularity, such as those related to product redesign or changes in production infrastructures. [ABSTRACT FROM AUTHOR]

In Industry 4.0 context, data valorisation allows industries to develop new capabilities, create competitive advantages and achieve manufacturing sustainability, but technological infrastructures are needed to support system interoperability and to manage datas. These infrastructures are not enough mature in many industrial environments, especially in small and medium enterprises (SMEs). Technology integration is challenging due to system and information heterogeneity, and even more so in SMEs that have constraint environment and which lack specific research study. . Although several approaches have been proposed, the literature lacks empirical evidence of the adoption of new technologies in SMEs. This paper presents a guideline for implementing a Cyber- Physical system (CPS) architecture in an SME and its application in an organic flour mill in Montreal. The case study provides evidence of the possibility to implement a CPS architecture in SMEs and can serve as an inspiration for SME to develop an Industry 4.0 strategy. [ABSTRACT FROM AUTHOR]

A key motivation to adopt data-driven solutions in facility-internal logistic systems is to create more responsive, efficient, and sustainable systems through a seamless data flow. There is thus a need to analyse the logistics system's requirements from a data efficiency perspective. This paper presents and demonstrates a novel method, based on established literature, to assure that a transition to data-driven internal logistics leads to improvements in operational performance objectives. First, we identify wastes on the shopfloor caused by inefficient data flows. Second, we portray the trajectories of managerial capacities enhancements, supporting decision makers toward a to-be scenario. Two case studies are presented where the method has been implemented and used for demonstration and validation purposes. The results show that the method is beneficial in a waste-elimination and continuous improvement setting, linking improvements, detected wastes, enabling technologies, and managerial capacities in terms of monitoring, control, optimization, and autonomy. [ABSTRACT FROM AUTHOR]

Conceptualizations of path creation proposed in recent years neglect the role of time and temporal mechanisms. This paper argues that a more comprehensive understanding of inter-path relations that incorporates both agency and relationships among temporal sequences can be achieved using the concept of critical conjuncture, which is overlooked in the contemporary path-creation literature. This paper draws on a case study of the industrial region of Upper Silesia, Poland, where a new regional trajectory is emerging as the result of the unpredicted critical conjuncture of the endogenously driven path of the information technology services sector and the exogenous foreign direct investment-based path of the automotive industry. [ABSTRACT FROM AUTHOR]

Collaborative engineering is not a new subject but it assumes a new importance in the Industry 4.0 (I4.0). There are other concepts frequently mismatched with collaboration. Thus, the main objective of this paper is to put forward a collaborative engineering concept, along its sub concepts, supported by an extensive systematic literature review. A critical analysis and discussion about the fundamental importance of learning, and the central human role in collaboration, in the I4.0, is presented, based on the main insights brought through the literature review. This study also enables to realize about the importance of collaboration in the current digitalization era, along with the importance of recent approaches and technology for enabling or promoting collaboration. Main current practices of human centered and autonomous machine-machine approaches and applications of collaboration in engineering, namely in manufacturing and management, are presented, along with main difficulties and further open research opportunities on collaboration.. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution shapes today's private and industrial environments, implying increased digitalization, connectivity, and artificial intelligence. Wearable devices support digital communication by displaying information and monitoring health-related aspects by measuring vital signs. Even though various wearables for measuring vital signs are already used in private life, they have not yet found their way into the production environment. This could be due to poor data quality or a lack of acceptance among employees regarding the usability of wearables during work activities. This paper aims to evaluate the accuracy and usability of selected wearable devices in manual assembly. Therefore, two user studies were conducted in a rebuilt production environment. The first study focuses on the data accuracy of the heart rate measurement of different wearables during manual assembly. In the second study, the usability of the selected wearables is evaluated with the thinking-aloud method during a manual assembly task and questionnaires. [ABSTRACT FROM AUTHOR]

One of the goals of the Industry 4.0 paradigm is the sustainable success within a mass customization environment, which in turn, depends on the manufacturing efficiency of the transformation processes. In this paper we propose to represent manufacturing efficiency within the context demand fulfillment. The main original contribution of this paper are two demand fulfillment analytical expressions. Their novelty is on the way they are expressed, that is, in terms of the structural elements that define a mass customization environment. Their usefulness was put to the test via a Discrete Event Simulation (DES) model of two different demand fulfillment strategies (namely inventory-oriented level and capacity-oriented chase strategies). The obtained results suggest that the analytical expressions act as a fairly good trend indicator of the missed demand values increase/decrease. A discussion of the managerial implications of these findings are presented at the end of this document. [ABSTRACT FROM AUTHOR]

Industry 4.0 revolutionizes the concept of automation and digitization within the organization leading to immense interest in academia and industry. The digitization of an organization in terms of horizontal, vertical, and end-to-end integration would change the roles an employee discharges in an organization. The main purpose of the paper is to successfully develop an employee adaptability road map for the successful implementation of Industry 4.0. This paper critically analyses the previous studies to develop a roadmap of employee adaptability skills for the successful implementation of Industry 4.0. This study uses deductive methodology using a systematic literature review to group and thematically analyse 52 articles to develop the conceptual model. Besides, this study also ranks these dimensions using an empirical study and finds the most critical employee adaptability dimensions. This is the first systematic literature review and empirical study carried out on employee adaptability skills in Industry 4.0. [ABSTRACT FROM AUTHOR]

In the third industrial revolution (IR), mechatronics engineering has emerged, which is the merger of mechanical and electronics engineering along with information technology to an extent. In the current industrial revolution (fourth), the amalgamation of mechanical with Artificial intelligence (AI) has been used to simulate human behaviour in machines. In the earlier decades, the application of AI in mechanical engineering has expedited and the increased volume of related research papers is a proof of this fact. The broad domain of mechanical engineering has a lot of potential for machine learning applications in order to detect errors, minimise rejection, improve product quality, optimise a system, and so on, as it has not been intensely explored although. This article’s goal is to give a structured evaluation of works that employ vision systems and to attract researchers to analyse its potential integration with machine learning (ML) techniques from the industry 4.0 viewpoint. Current trends and research gaps in the area of manufacturing in collaboration with ML are also discussed at appropriate places. A general procedure to carry out research in the field of mechanical engineering is also presented. The results of various studies highlighted in this paper confirm that the implementation of AI in ME has provided an optimum solution to many mechanical problems that improved product quality and minimised the associated cost. Finally, the authors have led a direction to empower researchers in order to explore various areas in mechanical engineering from Industry 4.0 and AI perspective and enable possible topics for future research. The article concludes by providing challenges that may be faced in the coming future about the use of machine learning in mechanical engineering problems. [ABSTRACT FROM AUTHOR]

The link between active learning and the development of graduate attributes has been cogently advocated in pedagogical research. Despite the extensive adoption of fieldwork in environmental and social sciences, enigmatically, there are no reported applications of fieldwork in construction and related engineering disciplines. This paper employs a case study approach to address this gap and exemplify the application of fieldwork in a postgraduate construction degree programme. It presents a robust design framework for assessed residential fieldwork that aids the scaffolding of a holistic set of graduate attributes. The framework promotes undertaking field-based experiential learning in international destinations in order to support the development of adaptable leadership and graduate future readiness for the fourth industrial revolution. After discussing its theoretical underpinnings, the paper presents the context for the case study, the design framework and stages of the fieldwork and concludes with an evaluation of its implementation, limitations and implications for practice. [ABSTRACT FROM AUTHOR]

Industry 4.0 is a new paradigm in the manufacturing world and it has deeply changed the Human–machine interaction. This paper focus is on the nature of this interaction, which is made possible thanks to the Internet of Things (IoT), and Cyber-Physical System (CPS). These Industry 4.0 key technologies are studied related to the standard Deming cycle, in order to underline the importance of Human–machine interaction. The Fourth Industrial Revolution involves several changes in the workforce's key features. In this paper, a new perspective based on the centrality of humans is given in the new Industry era. The importance of the human factor will be deeply studied through the implementation of the 'Sand Cone Model'. A new framework is proposed in order to explain the quality measures addiction on the workforce quality skills, and how it engraves on improving efficiency and effectiveness of an industrial process. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a key enabler and technological pillar of the fourth industrial revolution (Industry 4.0) as it increases productivity and improves resource efficiency. However, current AM systems present some limitations in terms of fabrication time, versatility, and efficiency. The concept of teams of robots represents a novel approach for AM aiming to address these limitations. This review paper discusses the current state-of-the-art of the use of cooperative AM systems based on gantry systems, robotic arms, and mobile robots. The information flow, path planning and slicing strategies are discussed in detail, and several examples of the use of cooperative AM systems are provided. Finally, major research challenges and future perspectives are discussed. [ABSTRACT FROM AUTHOR]

There is significant interest in emerging technologies. Universities, companies and other adopters are researching how and when these technologies should be implemented. However, this research area still lacks ways to evaluate the maturity level of the technologies and rapid experimentation concepts for testing the new technologies. This paper addresses the research gap by providing a new evaluation method and a rapid experimentation concept. This method and concept were successfully used in twenty-five Flash-projects, where five emerging digital Industry 4.0 themes evaluated. [ABSTRACT FROM AUTHOR]

This paper proposes a new Readiness Model, 3D-CUBE, to assess the current state of manufacturing companies in the digital transformation context. Using a systematic literature review with 8-Steps-Search-Flow and a hypothetical-deductive framework (considering maturity as an 'input' enabler and not as an 'output'), the best information of 63 existing models was selected from 486 studies found in 10 databases. The 3D-CUBE was elaborated, with 3 dimensions (X = Organizational , Y = Technological , and Z = Process Maturity), 6 sub-dimensions, and 21 elements, including a scale 0-5 to assess the company readiness level. For the company's Data Collection, a 3D-CUBE Questionnaire was developed, which provides a radar graph and calculates the company's score with a readiness vector R=(X,Y,Z). Based on the existing model's shortcoming, 3D-CUBE is a new contribution to this research stream, to help companies in getting ready for Industry 4.0.. [ABSTRACT FROM AUTHOR]

Companies across the globe have intensified the digital interconnectedness of their manufacturing processes. Much attention was devoted to how industrial employment will be affected in this new production paradigm. In this paper, we use survey data collected from German industrial workers in 2014 and 2020 to contribute to the literature on digitalisation and industrial employment. This is the first scientific study on Industry 4.0 that empirically deals with the development of key parameters of industrial employment over time. Our findings support the argument that whilst increased digital interconnectedness creates more opportunities for highly skilled workers, the extent to which manual workers will be substituted is often overestimated. Second, our data suggests that the operations of larger companies tend to be more highly digitally interconnected than those of smaller firms. We also provide evidence that German industrial workers are less likely to expect substantial job losses through digitalisation than in 2014. [ABSTRACT FROM AUTHOR]

Cross-docking is important for logistics because it reduces inventory, lead-times, and shipments. However, dynamic imbalances between supply and demand usually results in some inventory being warehoused in cross-docks. Therefore, flexible automation using robots, such as automated guided vehicles (AGV), can be used to improve performance of cross-docking, a trend in industry. This paper focuses on mathematical modeling of cross-docking operations when packages are moved in AGVs. A model based on Mean Value Analysis (MVA) is developed for determining the number of AGVs and estimating the service rate. This service rate is used as a parameter in a fork/join queuing model to characterize the performance of cross-docks in which outbound trucks get their packages directly from in-bound trucks as well as warehouses by estimating the queue lengths and mean sojourn times. The efficacy of the combined MVA and fork/join analytical models is verified using a discrete-event simulation as a case study, which shows that the models are largely in agreement in a test range with difference of 28% at the lowest throughput tested. Future study could use advances in sensors and Industry 4.0 for estimating parameters in the proposed models and improve performance and sustainability. [ABSTRACT FROM AUTHOR]

Industry 4.0 is one of the trending topics among the academicians and practitioners around the world. The pros and cons of Industry 4.0 are significantly important because it will help the organizations to make a sensible decision regarding its implementation. Though there are many studies on Industry 4.0, there is a dearth of academic literature which collates and analyses the Pros and Cons of Industry 4.0. The purpose of this paper is to investigate what are the pros and cons of implementation of Industry 4.0 in organizations from academic perspective. A comprehensive and systematic literature review is conducted on the earlier studies on Industry 4.0. Descriptive, categorical, keyword and thematic analysis are conducted on the final sample of sixty-four articles. This study finds nine pros and seven cons while implementing Industry 4.0 in organizations and also the future research directions is explicated. [ABSTRACT FROM AUTHOR]

The successful implementation of Industry 4.0 warrants a design of CPS architecture which considers the customer needs. The purpose of this paper is to develop the design of cyber- physical system (CPS) using 8 C architecture using the principles of LSS for a successful business system. Through an integrative literature review, this study analysis in depth the 8 C architecture and its possible integration with LSS methodology. The connection, conversion, cyber, cognition, configuration, coalition, customer, and content levels are examined in detail to include the LSS methodology in each phase of design. The future research directions are identified and the implications for practice are further expounded. This is the first paper which incorporates the principles of LSS to design a CPS architecture. [ABSTRACT FROM AUTHOR]

In this paper are investigated the re-engineering approaches for the optimization of pasta production processes. A preliminary study of technologies and information systems architectures to be applied to the entire pasta supply chain has been carried out. In the first part of the paper is presented an overview concerning Industry 4.0 enabling technologies, besides, in the second part are discussed the engineered processes improving production quality. Concerning simulation process, is designed by means of modelling workflows the wheat storage process, by simulating the automatism of silos controlled and managed by volume sensors. Finally, following Industry 5.0 facilities have been applied image vision and artificial intelligence methodologies suitable for auto-adaptive quality check of pasta. The paper discusses different models about production processes, efficiency, risks, costs and benefits. [ABSTRACT FROM AUTHOR]

The digitalization of industries is at the heart of today's global economy. However, there seems to be confusion about the most effective methods for initiating this transformation, and even more so for the manufacturing Small and Medium-sized Enterprise (SME). In a context of labor shortages, globalization and access to goods, services and skills everywhere and at any time thanks to the Internet, the need to stand out from the competition becomes a crucial issue. This research attempts to evaluate and identify the most effective ways to facilitate the digitalization in a context of manufacturing SMEs. Thanks to the measure of the digital performance and an 80-hour experience-based methodology using a questionnaire and field interviews, the determining factors of influence of the digital transformation could be raised. This paper uses a model of digital performance and hypothesis testing to try to identify the business practices and the 4.0 technologies that have the greatest effect on the performance of manufacturing SMEs. The results then intents to guide the efforts both in academia and in the field concerning digitalization of SMEs. [ABSTRACT FROM AUTHOR]

Today's global supply chain (SC) is grappling with unprecedented challenges, which rendered conventional SC resilience (SCR) inadequate. In the wake of the Industry 4.0 (I4.0) age, investment in digital SCR (DSCR) relying on I4.0 technologies can potentially enhance organizations abilities to detect, avoid, respond to, and recover from disruptions promptly and efficiently. Literature most focuses on traditional SCR, while DSCR remains incipient. From this, this paper conducts a comprehensive literature review on the SCR, I4.0, and investment (INV) interplays to identify potential research gaps and avenues. It is revealed the integration of SCR-I4.0-INV as a complex and multifaceted process that requires holistic approaches. Some research gaps include the need for empirical studies on DSCR impacts, the role of organizational culture in supporting digital transformation, and investment and resilience trade-offs. This research provides insights for decision-makers and policymakers seeking to develop strategies for promoting resilient SCs in the digital transformation era. [ABSTRACT FROM AUTHOR]

Monitoring multivariate and high-dimensional data streams is often an essential requirement for quality management in manufacturing and service sectors in the Industry 4.0 era. Identifying a suitable distribution for a multivariate data set, especially when the number of variables is much larger than the sample size, is often challenging. Consequently, in a high-dimensional set-up, that is, when the number of variables under investigation exceeds sample size, parametric methods are generally not reliable in practice. There are various nonparametric schemes based on data depth for multivariate process monitoring, which are applicable only when the sample size is reasonably larger than the number of variables in the process but not in a high-dimensional set-up. We discuss that most of these charts are not robust when the true process parameters are unknown. There are, however, some nonparametric schemes for a high-dimensional process, when true process parameters are known. Nevertheless, when process parameters are unknown, a highly robust nonparametric scheme for monitoring high-dimensional processes is not yet available. In this paper, we propose some Shewhart-type nonparametric monitoring schemes based on specific distance metrics for surveillance of multivariate as well as high-dimensional processes. Our proposed charts are easy to implement, interpret and also advantageous in simultaneous monitoring of multiple aspects. We discuss the design and implementation issues in details. We carry out a performance study using Monte Carlo simulations and illustrate the proposed methods using a dataset related to industrial production. [ABSTRACT FROM AUTHOR]

Industry 4.0 gives guidelines to drive production to overcome the consequences of the 2008 crisis in the manufacturing sector by emphasizing technological innovations, such as industrial internet, cloud manufacturing, etc. The proposed paper focuses on cognitive manufacturing within the framework of the Emergent Synthesis approach. Specifically, a Class III synthesis problem with reference to tool inventory management in a complex manufacturing environment is addressed. Such complex environment is proved to be affected by significant non-random uncertainty involving tool delivery time fluctuations and unpredictable tool demand. To deal with the complexity of the manufacturing environment, this paper presents bounded rationality as a characteristic of agents. The purpose of the implemented multi-agent manufacturing model is to manage the uncertainty in the perception, action and inner structure of the manufacturing system by introducing bounded rationality in agent characteristics and the probability–possibility transformation of historical data. The applicability and efficiency of the developed multi-agent manufacturing model are investigated in a real industrial case study. The results indicate that the complexity of a manufacturing system can be studied and solved as Class III synthesis problem and it is helpful to integrate bounded-rational agents in a multi-agent system. [ABSTRACT FROM AUTHOR]

Lean Management (LM) is one of the most widely used business strategies for the last three decades. Industry 4.0 shows all the promise of the fourth industrial revolution using automation technologies like cyber-physical systems, internet of things and cloud computing. The purpose of this paper is to propose an integration model of Industry 4.0 and LM. A summary literature review of Industry 4.0 and LM is carried out to construct a theoretical model of integration. The previous literature is used to develop and propose an integration model of Industry 4.0 and LM. The horizontal, vertical and end-to-end engineering integration model are integrated with LM methodology. Testable research propositions are proposed between Industry 4.0 and LM. The model proposed is novel and it raises the important issue of integration of LM with Industry 4.0. This is the first paper which proposes the integration framework of LM with Industry 4.0. [ABSTRACT FROM AUTHOR]

Industry 4.0 (hereafter I4.0) transformation in manufacturing sectors is considerably gaining a lot of attention from both researchers and practitioners. To increase the success rate of I4.0 transformation, manufacturers and policymakers need to understand barriers and how to overcome them. This paper proposes an analytical framework to prioritize the policy initiatives to overcome I4.0 transformation barriers, which have so far been ignored in previous studies. Since the prioritization of policy initiatives involves many evaluating criteria, multi-criteria decision-making (MCDM) is an effective method to evaluate and rank the best alternatives. Notwithstanding, the uncertainty is a major issue in any decision-making process. One of the latest emerging tools in dealing with the uncertainties is Pythagorean fuzzy set (PFS). The use of PFS allows experts with a larger domain to determine both membership and non-membership degrees. In this study, TODIM (an acronym in Portuguese for Interactive Multi-Criteria Decision-Making) under PFS is employed to prioritize policy initiatives to overcome I4.0 barriers. The proposed framework presented herein is illustrated by the case of Thai food processing industry. The results of this study can help the policymakers aiming to drive I.40 transformation to implement the policy initiative in a prioritize manner. Although the present work is focused on the food processing industry, the proposed framework can be further applied to other similar industries. [ABSTRACT FROM AUTHOR]

At the heart of the European Union's innovation policy is Smart Specialisation Strategy (S3) as embodied in the Research and Innovation Strategies for Smart Specialisation (RIS3) programme. So far, RIS3's efficacy on the revival of so-called lagging regions has been weak. This is in large part due to the weak initial endowments of technology, social/business networks, poor governance and institutional failures that typify lagging regions. This combination inhibits both the effectiveness of the programme and the ability of lagging regions to take advantage of the new opportunities proffered by Industry 4.0. This paper highlights some of these challenges and presents some policy directions for S3 and Industry 4.0 to deliver better regional cohesion and enhance inclusive growth. [ABSTRACT FROM AUTHOR]

Industry 4.0 aims to support the factory of the future, involving increased use of information systems and new ways of using automation, such as collaboration where a robot and a human share work on a single task. We propose a classification of collaboration levels for Human-Robot collaboration (HRC) in manufacturing that we call levels of collaboration (LoC), formed to provide a conceptual model conducive to the design of assembly lines incorporating HRC. This paper aims to provide a more theoretical foundation for such a tool based on relevant theories from cognitive science and other perspectives of human-technology interaction, strengthening the validity and scientific rigour of the envisioned LoC tool. The main contributions consist of a theoretical grounding to motivate the transition from automation to collaboration, which are intended to facilitate expanding the LoC classification to support HRC, as well as an initial visualization of the LoC approach. Future work includes fully defining the LoC classification as well as operationalizing functionally different cooperation types. We conclude that collaboration is a means to an end, so collaboration is not entered for its own sake, and that collaboration differs fundamentally from more commonly used views where automation is the focus. [ABSTRACT FROM AUTHOR]

Smart technologies with higher degrees of autonomy will be essential to achieve the next breakthrough in both agility and productivity in future manufacturing systems, often referred to as Industry 4.0. However, the technologies will also bring substantial design and integration challenges and novelty risks to manufacturing businesses. The aim of this paper is to analyse the current landscape and to identify the challenges for introducing smart technologies into manufacturing systems in Europe. Expert knowledge from both industrial and academic practitioners in the field was extracted using an online survey. A workshop was used to triangulate and extend the survey results. The findings indicate three main challenges for the ubiquitous implementation of smart technologies in manufacturing are: i) the perceived risk of novel technologies, ii) the complexity of integration, and iii) the consideration of human factors. Recommendations are made based on these findings to transform the landscape for smart manufacturing. [ABSTRACT FROM AUTHOR]

In the context of the Industry 4.0 and of the digital factory, digital twin and virtual reality represent key technologies to design, simulate and optimize cyber-physical production system and interact with it remotely or in a collaborative way. Moreover, these technologies open up new possibilities which can be involved in the co-design and ergonomics studies of workstations, based on Industry 4.0 components like cobots. In order to satisfy these needs and to create dynamic and immersive virtual environment, it is therefore necessary to combine the capacities of the digital twin to perform simulation of the production system with the capacities of the immersive virtual environment in term of interactions. This paper proposes a co-simulation and communication architecture between digital twin and virtual reality software, then it presents a use case on a human-robot collaborative workplace design and assessment. [ABSTRACT FROM AUTHOR]

Can tolerance limits in production be extended without violating the specifications of design and development? Adherence to tolerances is crucial for the technical quality of a manufactured good. Fit functions of modules often involve highly precise tolerances, incurring high costs. To avoid or at least reduce these costs, this paper develops a new approach to tolerances, the Dynamic Tolerance System. This approach allows the manufacturer to expand the tolerance limits of single parts of an assembly group and enables the production of assembly groups that are subject to specific fit functions. Thereby, the Dynamic Tolerance System does not intervene in the design process, does not require expensive machines or error-prone control-loops, and does not use complex assembly procedures. Rather, it relies on modern measurement systems and the infrastructure already developed and deployed within the framework of Industry 4.0 to extend tolerance limits in production without violating the designer's specifications. [ABSTRACT FROM AUTHOR]

The article aims to determine the current situation in economic subjects (ESs), what values and competencies are for managers and executives, and what motivational factors are essential for financial entities in the era of Industry 4.0. The article used standard scientific methods, such as analysis, synthesis, induction, and deduction, but also methods, such as content analysis of professional and scientific literature, comparison, modelling, and basic statistical methods, which verified the dependencies between the selected elements. The article processes data from a questionnaire survey conducted in 2020 (905 respondents) and 2021 (561 respondents). The respondents who filled out the questionnaire survey were managers or owners of ESs, which are based in Slovakia and are classified as micro, small, medium, or large enterprises. We found in the study that there is a dependence between the employment orientation of managers and the use of career motivation factors, as well as between the passion for work and the creativity of employees, and between the technological and IT skills of managers and executive employees. It is surprising that ES in Slovakia consider soft skills more important than technological ones despite the pressure to support and develop people’s digital skills. [ABSTRACT FROM AUTHOR]

The implementation of artificial intelligence and 4.0 technologies helps business leaders make better decisions to reduce costs, improve team performance, and increase productivity. It also enhances the quality of work life of workers, allows the optimization of the information obtained from the equipment in real time, in this way even unscheduled maintenance can be avoided. A systematic review of the literature regarding the applications and benefits that artificial intelligence has given to companies is presented, the information was obtained from databases such as Ebsco, Scopus, MDPI, ScienceDirect. Analyses, concepts, and contributions that have benefited the understanding of the need to embrace new technologies 4.0 and artificial intelligence are presented, for the benefit of companies and workers. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange. [ABSTRACT FROM AUTHOR]

The smart grid is a product of the advances in computer and communication technology and power electronics that creates a more resilient, reliable and one that supports a two-way flow of electricity and information. The smart grid enables more uptake of the variable renewables like wind, solar and variable loads like the plug-in cars and improves the efficiency of power systems and facilitate several products and services supported by the grid like automatic healing and re-routing of power in case of a fault and demand side management. The deployment and use of smart grids will enhance the realization of shared goals of grid stakeholders, promote energy security, enable economic growth, and help in the mitigation of climate change. [ABSTRACT FROM AUTHOR]

Open science has the capacity of boosting innovative solutions and knowledge development thanks to a transparent access to data shared within the research community and collaborative networks. Because of this, it has become a policy priority in various research and development strategy plans and roadmaps, but the awareness if its potential is still limited in industry. Additive manufacturing (AM) represents a field where open science initiatives may have a great impact, as large academic and industrial communities are working in the same area, enormous quantities of data are generated on a daily basis by companies and research centers, and many challenging problems still need to be solved. This article presents a case study based on an open science collaboration project between TRUMPF Laser- und Systemtechnik GmbH, one of the major AM systems developers and Politecnico di Milano. The case study relies on an open data set including in-line and in-situ signals gathered during the laser powder bed fusion of specimens of aluminum parts on an industrial machine. The signals were acquired by means of two photodiodes installed co-axially to the laser path. The specimens were designed to introduce, on purpose, anomalies in certain locations and in certain layers. The data set is specifically designed to support the development of novel in-situ monitoring methodologies for fast and robust anomaly detection while the part is being built. A layerwise statistical monitoring approach is proposed and preliminary results are presented, but the problem is open to additional research and to the exploration of novel solutions. [ABSTRACT FROM AUTHOR]

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Numerous challenges in automotive production lead to an increased need for transparency and optimization. Real-Time-Location-Systems (RTLS) is a key tool for achieving this goal. They enable intelligent and automated production processes. Existing solutions such as Ultra-Wideband, Bluetooth-Low-Energy, or Radio-Frequency-Identification have drawbacks in costs, range, or accuracy. 5G is a newly developing standard, recently including high-accuracy positioning. It is unclear, however, if 5G positioning has reached industrial maturity. This contribution aims to determine the state-of-the-art of 5G positioning by performing a systematic literature review and comparing its findings to industrial positioning requirements. 143 articles were analyzed and categorized as: the fundamentals of radio-frequency positioning, an overview of existing solutions, the state-of-the-art, and the maturity of 5G as an industrial positioning system. Results show that, theoretically, centimeter-level accuracies are pursued. However, practical tests are rarely conducted. Concluding, 5G positioning shows great potential, but industrial pilots are required to validate the theoretical characteristics. [ABSTRACT FROM AUTHOR]

Industry 4.0 technologies are a trend in the organizational environments of Micro and Small Enterprises (SMEs). Identifying which technologies need to be implemented to assist the value chain is a challenge for many Micro and Small Business managers. The objective of this study was to identify the relationships between Industry 4.0 technologies and Micro and Small Enterprises. To achieve this, a systematic literature review and content analysis were conducted. A total of 60 articles from the sample were coded, using selection criteria designed to find relevant studies in the domains of Industry 4.0 and Micro and Small Enterprises. Thus, 16 Industry 4.0 technologies were identified, as well as nine possible barriers to implementing them, and eight performance outcomes after adoption in such enterprises. [ABSTRACT FROM AUTHOR]