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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]

This paper reviews the trends in income inequality over the last 40 years, and proposes a new explanation for their evolution – that it is hoped will be tested empirically by many studies in the years ahead – to see whether the observed increases in inequality of the last four decades have been caused by an aggravation of its traditional causes (such as land an human capital concentration), or by a widespread increase in instability in five key areas affecting inequality, the Human Development Index and human capabilities. The five areas where a sharp increase in instability has been observed concern: (a) the financial sector; (b) industry 4.0, especially the development of robotics and artificial intelligence; (c) diseases such as ebola, aids and covid; (d) number of conflicts and (e) a growing environmental crisis. A key unanswered question in the above proposed overall explanation is whether these five crises are interconnected and whether there is a primum movens that explains this series of problematic events. [ABSTRACT FROM AUTHOR]

Climate change, the growth in world population, high levels of food waste and food loss, and the risk of new disease or pandemic outbreaks are examples of the many challenges that threaten future food sustainability and the security of the planet and urgently need to be addressed. The fourth industrial revolution, or Industry 4.0, has been gaining momentum since 2015, being a significant driver for sustainable development and a successful catalyst to tackle critical global challenges. This review paper summarizes the most relevant food Industry 4.0 technologies including, among others, digital technologies (e.g., artificial intelligence, big data analytics, Internet of Things, and blockchain) and other technological advances (e.g., smart sensors, robotics, digital twins, and cyber-physical systems). Moreover, insights into the new food trends (such as 3D printed foods) that have emerged as a result of the Industry 4.0 technological revolution will also be discussed in Part II of this work. The Industry 4.0 technologies have significantly modified the food industry and led to substantial consequences for the environment, economics, and human health. Despite the importance of each of the technologies mentioned above, ground-breaking sustainable solutions could only emerge by combining many technologies simultaneously. The Food Industry 4.0 era has been characterized by new challenges, opportunities, and trends that have reshaped current strategies and prospects for food production and consumption patterns, paving the way for the move toward Industry 5.0. [ABSTRACT FROM AUTHOR]

This collection on 'Artificial intelligence, big data, algorithms and Industry 4.0 in firms and clusters' is introduced exploring the themes discussed by the nine papers and grouped into three categories to uncover new dynamics and identify future research opportunities for clusters and organizations in these transformative times. The first group explores theoretical aspects of AI and its evolution in social sciences, focusing on industry 4.0, smart cities, big data, and other related topics. The second group examines the role of industrial robots in employment, productivity, and knowledge absorption in industrial districts. The third group discusses innovation in the context of local production systems, AI ecosystems, and the growth and potential of the Metaverse. [ABSTRACT FROM AUTHOR]

Changes in average wage are usually attributed to technological change in the past industrial revolutions. With the emergence and gradual explosion of artificial intelligence (AI) in the 4th industrial revolution, this paper applies panel vector autoregressive technique, with annual data from the World Bank and global economy from 2004 to 2017, to examine the effect of artificial intelligence on average wages in Southern Africa. Findings from the study show that artificial intelligence has a significant negative relationship with average wages but is positively associated with gross domestic product per capita (GDPC), unemployment and inflation. The study also finds inflation and GDPC to be positively associated with average wage. Based on the finding, policy direction focusing on wage stabilisation, redistribution of income, advance learning and skill development training that promote competitiveness to computerisation is recommended. [ABSTRACT FROM AUTHOR]

While the rapid proliferation of the Industry 4.0 concept suggests that it brings about major economic change, the concept lacks a socio-economic foundation of change. In this context, the paper raises three questions: First, how sudden does the change brought about by Industry 4.0 occur, and, second, does it make a difference if it is conceived as sudden or not? Using a model of long waves of economic development and the concept of general purpose-technologies it is argued that much of the change brought about by Industry 4.0 is not of a sudden nature but largely represents the roll-out of the prevailing techno-economic paradigm, and that digitalization and artificial intelligence have the potential to trigger of a next long wave. The third question asks for possible implications of the long-wave perspective for adapting to an upcoming paradigm at the regional level. A major conclusion is that policy measures ought to reach beyond traditional innovation and technology-related policies and be implemented in the appropriate phase of a long wave. [ABSTRACT FROM AUTHOR]