Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review.

Recently, there has been a growing interest in issues related to maintenance performance management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies indicate a lack of research on the systematic literature reviews and surveys of studies that would focus on the evolution of Industry 4.0 technologies used in the maintenance area in a cross-sectional manner. Therefore, the paper reviews the existing literature to present an up-to-date and content-relevant analysis in this field. The proposed methodology includes bibliometric performance analysis and a review of the systematic literature. First, the general bibliometric analysis was conducted based on the literature in Scopus and Web of Science databases. Later, the systematic search was performed using the Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria included the publication dates (studies published from 2012-2022), studies published in English, and studies found in the selected databases. In addition, the authors focused on research work within the scope of the Maintenance 4.0 study. Therefore, papers within the following research fields were selected: (a) augmented reality, (b) virtual reality, (c) system architecture, (d) data-driven decision, (e) Operator 4.0, and (f) cybersecurity. This resulted in the selection of the 214 most relevant papers in the investigated area. Finally, the selected articles in this review were categorized into five groups: (1) Data-driven decision-making in Maintenance 4.0, (2) Operator 4.0, (3) Virtual and Augmented reality in maintenance, (4) Maintenance system architecture, and (5) Cybersecurity in maintenance. The obtained results have led the authors to specify the main research problems and trends related to the analyzed area and to identify the main research gaps for future investigation from academic and engineering perspectives.

Respiratory Inductance Plethysmography to Assess Fatigability during Repetitive Work.

Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the challenges observed in those methods. Thus, the aim of this study is to analyze alterations in respiratory inductance plethysmography (RIP) to measure the asynchrony between thorax and abdomen walls during repetitive work and its relationship with local fatigue. A total of 22 healthy participants (age: 27.0 ± 8.3 yrs; height: 1.72 ± 0.09 m; mass: 63.4 ± 12.9 kg) were recruited to perform a task that includes grabbing, moving, and placing a box in an upper and lower shelf. This task was repeated for 10 min in three trials with a fatigue protocol between them. Significant main effects were found from Baseline trial to the Fatigue trials (p < 0.001) for both RIP correlation and phase synchrony. Similar results were found for the activation amplitude of agonist muscle (p < 0.001), and to the muscle acting mainly as a joint stabilizer (p < 0.001). The latter showed a significant effect in predicting both RIP correlation and phase synchronization. Both RIP correlation and phase synchronization can be used for an overall fatigue assessment during repetitive work.

Demonstration Laboratory of Industry 4.0 Retrofitting and Operator 4.0 Solutions: Education towards Industry 5.0.

One of the main challenges of Industry 4.0 is how advanced sensors and sensing technologies can be applied through the Internet of Things layers of existing manufacturing. This is the so-called Brownfield Industry 4.0, where the different types and ages of machines and processes need to be digitalized. Smart retrofitting is the umbrella term for solutions to show how we can digitalize manufacturing machines. This problem is critical in the case of solutions to support human workers. The Operator 4.0 concept shows how we can efficiently support workers on the shop floor. The key indicator is the readiness level of a company, and the main bottleneck is the technical knowledge of the employees. This study proposes an education framework and a related Operator 4.0 laboratory that prepares students for the development and application of Industry 5.0 technologies. The concept of intelligent space is proposed as a basis of the educational framework, which can solve the problem of monitoring the stochastic nature of operators in production processes. The components of the intelligent space are detailed through the layers of the IoT in the form of a case study conducted at the laboratory. The applicability of indoor positioning systems is described with the integration of machine-, operator- and environment-based sensor data to obtain real-time information from the shop floor. The digital twin of the laboratory is developed in a discrete event simulator, which integrates the data from the shop floor and can control the production based on the simulation results. The presented framework can be utilized to design education for the generation of Industry 5.0.

Human-Machine Integration in Processes within Industry 4.0 Management.

The aim of this work is to use IIoT technology and advanced data processing to promote integration strategies between these elements to achieve a better understanding of the processing of information and thus increase the integrability of the human-machine binomial, enabling appropriate management strategies. Therefore, the major objective of this paper is to evaluate how human-machine integration helps to explain the variability associated with value creation processes. It will be carried out through an action research methodology in two different case studies covering different sectors and having different complexity levels. By covering cases from different sectors and involving different value stream architectures, with different levels of human influence and organisational requirements, it will be possible to assess the transparency increases reached as well as the benefits of analysing processes with higher level of integration between them.

Framework for the Development of Affective and Smart Manufacturing Systems Using Sensorised Surrogate Models.

Human Factor strategy and management have been affected by the incorporation of Key Enabling Technologies (KETs) of industry 4.0, whereby operator 4.0 has been configured to address the wide variety of cooperative activities and to support skills that operate in VUCA (volatile, uncertain, complex, and ambiguous) environments under the interaction with ubiquitous interfaces on real and virtual hybrid environments of cyber-physical systems. Current human Competences-Capacities that are supported by the technological enablers could result in a radically disempowered human factor. This means that in the processes of optimization and improvement of manufacturing systems from industry 4.0 to industry 5.0, it would be necessary to establish strategies for the empowerment of the human factor, which constitute symbiotic and co-evolutionary socio-technical systems through talent, sustainability, and innovation. This paper establishes a new framework for the design and development of occupational environments 5.0 for the inclusion of singularized operators 4.0, such as individuals with special capacities and talents. A case study for workers and their inclusion in employment is proposed. This model integrates intelligent and inclusive digital solutions in the current workspaces of organizations under digital transformation.

Healthy Operator 4.0: A Human Cyber-Physical System Architecture for Smart Workplaces.

Recent advances in technology have empowered the widespread application of cyber-physical systems in manufacturing and fostered the Industry 4.0 paradigm. In the factories of the future, it is possible that all items, including operators, will be equipped with integrated communication and data processing capabilities. Operators can become part of the smart manufacturing systems, and this fosters a paradigm shift from independent automated and human activities to Vhuman-cyber-physical systems (HCPSs). In this context, a Healthy Operator 4.0 (HO4.0) concept was proposed, based on a systemic view of the Industrial Internet of Things (IIoT) and wearable technology. For the implementation of this relatively new concept, we constructed a unified architecture to support the integration of different enabling technologies. We designed an implementation model to facilitate the practical application of this concept in industry. The main enabling technologies of the model are introduced afterward. In addition, a prototype system was developed, and relevant experiments were conducted to demonstrate the feasibility of the proposed system architecture and the implementation framework, as well as some of the derived benefits.

The impact of Industry 4.0 on occupational health and safety: A systematic literature review.

INTRODUCTION: Industry 4.0 has brought new paradigms to businesses based on high levels of automation and interconnectivity and the use of technologies. This new context has an impact on the work environment and workers. Nevertheless, these impacts are still inconclusive and controversial, requiring new investigative perspectives. This study aimed to investigate the requirements sought, the risk factors identified, and the adverse effects on workers caused by the characteristics of I4.0. METHOD: The methodology was based on a systematic literature review utilizing the PRISMA protocol, and 30 articles were found eligible. A descriptive and bibliometric analysis of these studies was performed. RESULTS: The results identified the main topics that emerged and have implications for workers' Occupational Health and Safety (OHS) and divided them into categories. The requirements are related mainly to cognitive, organizational, and technological demands. The most significant risk factors generated were associated with the psychosocial ones, but organizational, technological, and occupational factors were also identified. The adverse effects cited were categorized as psychic, cognitive, physical, and organizational; stress was the most cited effect. An explanatory theoretical model of interaction was proposed to represent the pathway of causal relations between the requirements and risk factors for the effects caused by I4.0. CONCLUSIONS AND PRACTICAL APPLICATIONS: This review has found just how complex the relationships between the principles of Industry 4.0 are (e.g., requirements, risk factors, and effects) and the human factors. It also suggests a pathway for how these relationships occur, bridging the gap left by the limited studies focused on connecting these topics. These results can help organizational managers understand the impacts of I4.0 on workers' safety and health.

Exploring the status of the human operator in Industry 4.0: A systematic review.

Industry 4.0 (I4.0) promises to transform jobs and working conditions through the implementation of unprecedented human-machine interaction modes. As the operator working in these new settings, known as the Operator 4.0, is a relatively recent concept, and although technological developments are expected to support workers and require higher labor skills, the risks and health impacts resulting from these changes remain underexplored. This systematic review aims to (i) systematize literature findings on how workers are perceived and participate in I4.0 work systems; (ii) identify the main technological changes driven by I4.0; and (iii) instigate discussion regarding the impacts these changes may have for workers and the sustainability of work systems. Following a systematic review approach using the PRISMA protocol, the articles were organized into two main analysis axes: the technical changes brought about by I4.0, and the representation of the human worker within these new work settings. The findings reveal that a techno-centered approach still seems to be dominant in guiding the implementation of I4.0 models; secondly, as a consequence, the social dimensions of work tend to remain as residual issues, overshadowed by the promises related with technology (e.g., productivity, efficiency); finally, the representation of the Operator 4.0 remains blurry, as he/she is perceived as gender neutral, skillful, and perfectly fit for work, assuring the functioning (and compensating for the limits) of these systems. While I4.0 promises safer and more productive workplaces, issues related to employment conditions, emerging risks and health impacts become more prominent when analyzed from an activity-centered perspective. In terms of future research, a more heuristic analysis could be achieved through a participatory and work-centered approach and following a gender perspective. This way, visibility could be conferred to another side of I4.0, thus guaranteeing conditions for the sustainable development of these work situations.

Workforce and supply chain disruption as a digital and technological innovation opportunity for resilient manufacturing systems in the COVID-19 pandemic.

During the SARS-CoV-2 pandemic (also known as COVID-19), workforce downsizing needs, safety requirements, supply chain breaks and inventory shortages affected manufacturing systems' and supply chain's responsiveness and resilience. Companies wandered in a disrupted scenario because recommended actions/strategies to survive - and thrive - were not available an improvised actions to keep their operations up and running. This paper analyzes the COVID-19 impacts on the workforce and supply resilience in a holistic manner. The following research questions are discussed: (i) how can manufacturing firms cope with urgent staff deficiencies while sustaining at the same time a healthy and safe workforce in the perspective of socially sustainable and human-centric cyber-physical production systems?; (ii) is remote working (cf. smart working) applicable to shop-floor workers?; (iii) is it possible to overcome supply chain breaks without stopping production? In the first part, we propose three Industry 4.0-driven solutions that would increase the workforce resilience, namely: (i) the Plug-and-Play worker; (ii) the Remote Operator 4.0; (iii) the Predictive Health of the Operational Staff. In the second part, the concepts of (i) Digital & Unconventional Sourcing, i.e. Additive Manufacturing, and (ii) Product/Process Innovation are investigated from a novel business continuity and integration perspective. We ultimately argue that forward-looking manufacturing companies should turn a disruptive event like a pandemic in an opportunity for digital and technological innovation of the workplace inspired by the principles of harmonic digital innovation (that places the human well-being at the center). These aspects are discussed with use cases, system prototypes and results from research projects carried out by the authors and real-world examples arising lessons learned and insights useful for scientists, researchers and managers.

Human-centered design of work systems in the transition to industry 4.0.

The introduction of Industry 4.0-enabling digital technologies in industrial work systems are creating various sociotechnical challenges affecting overall system performance and human well-being. In this paper, we propose a framework for (re)designing industrial work systems in the transition towards Industry 4.0. The framework combines human factors and ergonomics, work system modeling, and strategy design. It accommodates implementation challenges we have identified through ten retrospective case studies. In addition, we present the systematic approach applied to developing and testing the framework. Lastly, the framework was tested in a collaborative workshop in an industrial company, and the results indicated its applicability.