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The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

The set of 2,509 documents related to the human-centric aspect of manufacturing were retrieved from Scopus database and systmatically analyzed. Using an unsupervised machine learning approach based on Latent Dirichlet Allocation we were able to identify latent topics related to human-centric aspect of Industry 5.0.

This study aims to create a scientific map of the human-centric aspect of manufacturing and thus provide a systematic framework for further research development of Industry 5.0.

In this study a 140 unique research topics were identified, 19 of which had sufficient research impact and research interest so that we could mark them as the most significant. In addition to the most significant topics, this study contains a detailed analysis of their development and points out their connections.

Industry 5.0 has three pillars – human-centric, sustainable, and resilient. The sustainable and resilient aspect of manufacturing has been the subject of many studies in the past. The human-centric aspect of such a systematic description and deep analysis of latent topics is currently just passing through.

This study aims to prevent occupational accidents occurring in the manufacturing industry by means of touch sensors. When the occupational accidents occurring in the manufacturing industry around the world are examined, it is seen that approximately 88% of occupational accidents occur from “dangerous movement” and 10% from “dangerous situation.” Although some studies related to safety culture studies, safety studies in design and collective or personal protective measures have been started, they have not been brought to an adequate level. It is observed that studies on dangerous movements continue even in many developed countries. In this study, first of all, a literature study was conducted. Occupational accidents experienced in the manufacturing sector in Turkey have been examined. In line with these investigations, a prototype circuit protection system has been developed that can prevent accidents caused by dangerous movement. With the circuit, its applicability and effectiveness were measured by conducting experiments on different manufacturing machines. The prototype circuit applied in this paper was made based on the logic of protective measures made on sawstop machines used in different sectors. In the experimental study conducted, it was observed that in 30 experiments conducted with a prototype on ten separate manufacturing machines, it stopped the machines 26 times at minimum and 29 times at maximum. On average, when looking at the system efficiency values, it was seen that the system was 81.6% effective, and it was observed that positive results could be obtained when converted into a real product.

In this study, their contribution to the prevention of work accidents caused by presses and rotary accents from machines used in the manufacturing industry by means of touch sensors used in Industry 4.0 was examined.

With Industry 4.0, different automation systems began to be switched in many areas and sectors. Studies have started on different sensors used also in Industry 4.0 in occupational health and safety studies, but it is seen that they have not been applied at an adequate level. It should be designed in such a way as to prevent errors or stop these errors in the studies performed. Today, sensors are produced at much lower costs than before. In addition, the constantly developing technology provides great convenience for these applications.

This study was applied for press and cylinder machines from manufacturing machines. This study has been tried for machines producing a maximum pressure of 300 tons.

A prototype was designed. Trials were done on some machines by prototype. There could be improve and find different solutions for safety problems in the industry with this perspective.

This paper aims to explore the intellectual structure shaping the circular economy (CE) discourse within the built environment in Africa.

The study adopted a bibliometric analysis approach to explore the intellectual structure of CE in the built environment in Africa. The authors collected 31 papers published between 2005 and 2021 from the Scopus database and used VOSviewer for data analysis.

The findings show that there are six clusters shaping the intellectual structure: demolition, material recovery and reuse; waste as a resource; cellulose and agro-based materials; resilience and low-carbon footprint; recycling materials; and the fourth industrial revolution. The two most cited scholars had three publications each, while the top journal was Resources, Conservation and Recycling. The dominant concepts included CE, sustainability, alternative materials, waste management, lifecycle, demolition and climate change. The study concludes that there is low CE research output in Africa, which implies that the concept is either novel or facing resistance.

The data were drawn from one database, Scopus; hence, adoption of alternative databases such as Web of Science, Google Scholar and Dimensions could potentially have yielded a higher number of articles for analysis which potentially would result in different conclusions on the subject understudy.

This study made a significant contribution by articulating the CE intellectual structure in the built environment, identified prominent scholars and academic platforms responsible for promoting circularity in Africa.

The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.

The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.

This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.

This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

The purpose of the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

The accelerating business transformation through Industry 4.0 (I4.0) is expected to create significant value in the manufacturing industry by delivering considerably high productivity, superior quality, better efficiency and effectiveness. However, its evolutionary processes have far-reaching challenging for humanity. This has triggered a need to analyze the impact of I4.0 on various people-centric variables (PCVs).

This paper attempts to analyze the interrelationship dynamics between the PCVs in the current digital-industry ecosystem using a focus-group approach and causal loop diagrams. Application of the SWARA (stepwise weight assessment ratio analysis) methodology has provided its prioritized ranking in terms of importance.

The study has highlighted that I4.0 has a significant influence on five of the 13 PCVs – human quality of life, digital dexterity, high-skilled talent, low-skilled employment and creativity which contribute to 80% of the total impact.

The prioritized weights of the human factors from the SWARA approach have facilitated the assessment of the Human Resource Development Index (HRDI). The study is also contributing in enriching the literature on the human impact of the growing I4.0 and triggered the researchers to study further its adverse impact on critical human factors.

1. The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

2. This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

3. The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

4. The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.