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The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype.

The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed.

The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment.

The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics.

The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

The world has witnessed three major individual revolutions until now. We are in the fourth industrial revolution, and there are technological breakthroughs that have not been seen before. Responding fast to changing consumer expectations in a competitive climate brought on by globalization has become a global reality, requiring enterprises to alter their manufacturing systems. The incorporation of machines that can interact and make decisions into production has altered the manufacturing processes. The application of the Industry 4.0 revolution to manufacturing processes has paved the way for the development of smart factories. Production may be made 24 hours a day in these factories where productivity grows with applications such as the internet of things (IoT), cyber-physical systems, augmented reality and artificial intelligence. All applications utilized in smart factories boost productivity and reduce costs and human error rates. Countries should undergo change in order to adapt to the competitive climate established by Industry 4.0, in which the entire world lives. Many industrialized countries have taken significant strides in this direction, including this process into their national policies. Turkey's ability to adapt to Industry 4.0 technologies in a digitalized competitive environment, as well as swiftly grow smart factory applications in altering production processes, is critical to its global economic standing.

The purpose of this paper is to establish a cyber physical environment for digital product design and manufacturing. To realize this goal, the specific issue of integrating design knowledge-based system (KBS) and 3D printing (3DP) system is focused. A graphics generation method is thereby developed to transform the KBS outputs into graphical format which can be directly read and manufactured by 3DP system.

A graphics generation method is proposed in this paper. Through organizing alphanumeric outputs of the consultation session with a design KBS into parametric format, the consultation results can be directly used by computer-aided design (CAD) tools to generate graphical models which can be further exported into a 3DP system to produce physical objects.

The proposed graphics generation method can be effective to link design KBS and 3DP. Therefore, the seamless connection between design and prototyping systems can be realized, which further lays the communication foundation for a cyber physical environment for digital design and manufacturing.

This study provides research insights about potential cyber physical system applications in digital design and manufacturing area. Moreover, this paper contributes an effective technique to integrate design KBS and 3DP.

The purpose of this study is to discuss the construction of a structural measurement model utilizing structural equation modelling (SEM) to confirm the link between Industry 4.0 technologies, sustainable manufacturing practices and organizational sustainable performance. Relationship among the paradigm has yet to be fully investigated, necessitating a more conceptual and empirical examination on what impact they have on organizational sustainable performance when used together.

Industry 4.0 and sustainable production practices aim to progress a company's business competitiveness, forming sustainable development that benefits manufacturing companies. The aim of the study is to analyze the relationship between constructs that lead to operational excellence in firms that use Industry 4.0 technologies and sustainable manufacturing techniques. Experts from diverse automotive industries, who are applying both Industry 4.0 and sustainable manufacturing practices, provided data for the study.

Statistical estimations (hypotheses) are created to substantiate the measurement model that has been developed. The structural model was analysed, and the findings were discussed. The statistical estimate is either approved or rejected based on the findings. According to the conclusions of this study, strong link exists between Industry 4.0 technologies and sustainable manufacturing practices that affect organizational sustainable performance environmentally, economically and socially.

The research was conducted in the framework of automobile component manufacturing companies in India. The outcomes of the study are practically feasible.

The authors' novel contribution is the construction of a structural model with Industry 4.0 technologies and sustainable manufacturing practices into account.

The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”. The ability of companies to cope with these changes is a key competitive advantage requiring the adoption/mastery of industry 4.0 technologies. Therefore, companies must adapt their business processes to fit into similar situations.

The proposed methodology comprises three steps. First, a comparative analysis of the existing CPSs is elaborated. Second, following this analysis, a deep learning driven CPS framework is proposed highlighting its components and tiers. Third, a real industrial case is presented to demonstrate the application of the envisioned framework. Deep learning network-based methods of object detection are used to train the model and evaluation is assessed accordingly.

The analysis revealed that most of the existing CPS frameworks address manufacturing related subjects. This illustrates the need for a resilient industrial CPS targeting other areas and considering CPSs as loopback systems preserving human–machine interaction, endowed with data tiering approach for easy and fast data access and embedded with deep learning-based computer vision processing methods.

This study provides insights about what needs to be addressed in terms of challenges faced due to unforeseen situations or adapting to new ones. In this paper, the CPS framework was used as a monitoring system in compliance with the precautionary measures (social distancing) and for self-protection with wearing the necessary equipments. Nevertheless, the proposed framework can be used and adapted to any industrial or non-industrial environments by adjusting object detection purpose.

The purpose of this paper is to report a study on analysis of barriers for cyber-physical system (CPS) adoption in small and medium enterprises (SMEs).

In Industry 4.0 scenario, Indian SMEs are struggling to bring their manufacturing processes in line with large manufacturing sector. CPS is considered as the backbone of Industry 4.0, and its implementation in SMEs will make significant changes pertaining to manufacturing automation. However, due to the lack of a proper CPS implementation strategy, SMEs face many challenges in its adoption. Hence, this study identified 18 possible barriers and seven performance measures pertaining to CPS adoption in Indian SMEs. Interpretive ranking process (IRP) is used to develop the contextual relationships among CPS barriers. IRP process include structured step-by-step matrix-based approach in which dominance among various alternatives is determined using performance measures developing a structured ranking model.

The developed IRP model revealed that CPS barriers “Lack of skilled manpower (CPSB2)” and “Lack of robustness with respect to environmental conditions in automotive environments (CPSB7)” are the most significant barriers (top two) hindering CPS adoption in SMEs.

In the present study, barriers for CPS adoption has been analyzed. In future, barriers for adopting other Industry 4.0 technologies could be analyzed.

The present research work is one of the few studies which analyzed CPS barriers in SMEs and provided improvement suggestions to the most significant barriers for its smooth adoption. The managerial and practical implications have been derived.

The analysis of barriers for CPS adoption in SMEs is the original contribution of the authors.

The Industry 4.0 phenomenon offers opportunities and challenges to all business models. Despite the literature advances in this field, little attention has been paid to the interplay of smart production systems (SPSs), big data analytics (BDA), cyber-physical systems (CPS), internet of things (IoT), and the potential business process management (BPM) improvements. This study aims to identify the main drivers and their implications for improved BPM.

This study employed a narrative literature review of studies concerning smart-production-systems-related issues in the context of Industry 4.0.

The study identified 26 drivers from the literature associated with SPSs that have an impact on improved BPM. These drivers are presented in an integrative framework considering BDA, CPS, and the IoT.

The framework's component integration is yet not tested. However, this study offers a significant theoretical contribution by presenting drivers that can be utilised to develop constructs, exploring critical factors related to the interplay of SPSs and improved BPM, and shading light on Industry 4.0's main elements. The study also makes suggestions for further research.

The proposed framework, with its 26 drivers, provides insights for practitioners and decision-makers interested in gaining an in-depth understanding of the complexities of SPSs and improved BPM.

This study integrates BDA, CPS, and IoT into a framework with 26 drivers associated with SPSs to improve BPM.

Despite the growing attention on the relevance of improved building management systems with cognition in recent years in the architecture, engineering, construction and operation (AECO) community, no review has been conducted to understand the human-environment interaction features of cyber-physical systems (CPS) and digital twins (DTs) in developing the concept of a cognitive building (CB). Thus, this paper aims to review existing studies on CPS and DTs for CB to propose a comprehensive system architecture that considers human-environment interactions.

Scientometric analysis and content analysis were adopted for this study.

The scientometric analysis of 1,042 journal papers showed the major themes of CPS/DTs for CB, and these can be categorized into three key technologies to realize CB in the AECO community: CPS, DTs and cognitive computing (CC). Content analysis of 44 relevant publications in the built environment assisted in understanding and evidently confirming the claim of this study on the integration of CPS and DTs for CB in construction by also involving the CC. It is found and confirmed that CB can be realized with CPS and DTs along with the CC. A CB system architecture (CBSA) is proposed from the three key technologies considering the human-environment interactions in the loop. The study discovered the potential applications of the CBSA across the building lifecycle phases, including the design, construction and operations and maintenance, with the potential promise of endowing resilience, intelligence, greater efficiency and self-adaptiveness. Based on the findings of the review, four research directions are proposed: human-environment interactions, CB for sustainable building performance, CB concept for modular buildings and moving beyond CB.

This study stands out for comprehensively surveying the intellectual core and the landscape of the general body of knowledge on CPS/DTs for CB in the built environment. It makes a distinctive contribution to knowledge as it does not only propose CBSA by integrating CPS and DTs along with CC but also suggests some potential practical applications. These may require expert judgments and real case examples to enhance reproducibility and validation.

Today humanity is facing a time period, in which the speed and rate of change in different fields are faced. The rapid and effective change in the technological, economic, military, social and cultural fields all over the world in recent years has had important results in many topics such as informatics, interactive communication, production, data production and sharing and forms of consumption and perception. Changes and developments at very high speeds and rates affect the personal life, social life and work life in a deep manner, especially after the 1980s, paving the way for many concepts such as globalization, Industry 4.0, digitalization, new economy, new world order and digital transformation age to be the leading variables in every field of social sciences.

Production, consumption and communication forms at the global level are becoming more and more in depth and predicting the future is becoming more and more difficult and valuable. Understanding, analyzing and predicting the future for national and international companies and organizations directly and indirectly affect all economic, military and political variables. At this point, competition stands out as one of the most critical concepts for survival and growth for profit-oriented companies.

Based on this, the topics and contents selected in this study were created to cover the field of management and strategy. Indeed, in this study, the concept of organizational agility is explored theoretically from a historical perspective on the concept of Industry 4.0 and especially emphasized the dimensions and components of agility used in today’s world.

Within the scope of this study, the aim is to define and present the general framework of the Industry 4.0 and agile firms, which aim to combine the conceptual and theoretical infrastructure with the implementation of the agile firms within the field. In this respect, the study defines the situation coming from the past together with the world of today in the relationship of the technological and economical dimensions of globalization with the digitalization and latest theoretical view for the agile firm’s structure and management. On the other hand; in this study, the possible effects of the recent COVID-19 pandemic crisis on the management of organizations are interpreted in the context of Industry 4.0 and agile companies. This aim will provide a foresight for the future periods, with the conclusions added with the theory of senism, which present the dominant value of the study.