The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Very well into the dawn of the fourth industrial revolution (industry 4.0), we hardly distinguish between what is artificial and what is natural (e.g. man-made virus and natural virus). Thus, the level of discombobulation among people, companies or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector, makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption in the industrial sectors remains ill-defined in both academic and non-academic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technologies convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in Education industry (Education 4.0), Energy industry (Energy 4.0), Agriculture industry (Agriculture 4.0), Healthcare industry (Healthcare 4.0), and Logistics industry (Logistics 4.0) are described. The convergence of 12 disruptive technologies including 3D printing, Artificial intelligence, Augmented reality, Big Data, Blockchain, Cloud computing, Drones, Internet of things, Nanotechnology, Robotics, Simulation and Synthetic biology in agriculture, healthcare and logistics industries are illustrated.


Introduction
In the second decade of the 21st century, we stand on the cusp of industry 4.0 paradigm which has remarkably become a global emergence with a core of industrial transformation, revitalization and development [1]. Simply put, industry 4.0 is the integration of cyber and physical worlds through the introduction of new technologies in the industrial fields [2,3]. In other words, it is a technological revolution in every production system including operator and maintenance [4], which is quite unique from the previous revolutions as shown in Table 1 [5-9]. Industry 4.0 is the digitization of industrial value chain which has become unexampled for economic and social development in the recent years [10][11][12]. It allows the high-wage countries, for example Germany, to maintain their business responsiveness and competitiveness [13]. On the other hand, research and development units are organizationally, personally and methodically being aligned for innovation competitiveness [14,15].
Industry 4.0 is a data-driven production system which is progressing exponentially while reshaping the way individuals live and work essentially, but the public remains optimistic regarding the opportunities it may offer for sustainability and the future of quality work in the global digital economy [16][17][18][19][20]. Actually, industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies [21][22][23]. Moreover, it aims to improve the flexibility, adaptability, and resilience of the industrial systems [24,25].
Industry 4.0 has been considered a new industrial stage in which several emerging or disruptive technologies including Internet of things (IoT), Artificial intelligence (AI), 3D printing and Big Data are converging to provide digital solutions [26,27]. Industry 4.0 is characterized by the mass employment of smart objects in highly reconfigurable and thoroughly connected industrial productservice systems [28]. In this respect, industry 4.0 phenomenon is bringing unprecedented disruptions for all traditional production/service systems and business models (value chains), and hotfooting the need for redesign and digitization of activities [29][30][31][32]. Tout ensemble, it is retrofitting and/or redefining the patterns of value creation and annexations, production networks, supplier base and customer interfaces [33][34][35].
The concept of Industry 4.0 is greatly linked to other concepts such as servitization [36,37], crowdsourcing [38], circular economy (sharing economy) [39][40][41][42][43][44], green economy and bioeconomy [45]. Besides being complemental to a vast number of existing concepts, the main strength of industry 4.0 is the promises for shorter delivery time, more efficient and automated processes, higher quality, agility in production, profitable and customized products [46,47]. Further, it is expected to create extra values as the world is massively experiencing digital transformation [48]. In this regard, industry 4.0 has opened windows of opportunity for emerging economies but also brought its own bureaucracy in terms of the main challenges that these changes pose to firms, industrial systems and policy approaches [49].
The curiosity and the need to contemplate the meaning and concept of industry 4.0 has been ubiquitous among the academic and business communities, and thus, makes industry 4.0 to be one of the most important topic in the modern world as a result of digital milestones in innovation area [50]. So far so good, there are several ambiguities with almost 100 definitions and related concepts of industry 4.0 already in existence among academic and non-academic literature [51]. In academic community, engineering has incredibly gained more attention to industry 4.0 topic than other subject areas such as computer science, chemistry and energy ( Figure 1) [52].
The rapid and fascinating adoption of industry 4.0 topic among academic and business entities have led to the massive use of icon or neologisms "4.0" to depict industry 4.0 disruption in the systems, processes, activities or even industrial sectors. However, the collective numbers and names of the existing industry 4.0 neologisms has remained unclear [53]. In addition, industry 4.0 disruption through the convergence of its technologies has been ill-defined among previous researchers [26]. To this end, the outstanding contributions of the present study are trifold; (1) identify industry 4.0 neologisms used among the academic and business communities,

Methodology
A comprehensive literature search was conducted in electronic databases: Google scholar, ScienceDirect, Taylor & Francis, Springer and Emerald insight from January 2020 to May 2020 following procedures employed in previous studies [27,54]. The search was performed independently in all the databases and then combined with 'and' operators. The multidisciplinary databases included peer-reviewed journal articles, conference papers, books, theses, working papers, white papers, discussion papers, patents and reports published between 2015 and 2020. Thus, articles in the returned results were assessed concerning their inclusion in this study, and further searches were carried out at the Google search engine.
The literature search from the databases was done using the search terms: "Agriculture 4.0", "Education 4.0", "Energy 4.0", "Healthcare 4.0", and "Logistics 4.0". On the other hand, the search on Google search engine was accomplished with search terms: "3D printing and Agriculture", "Artificial intelligence and Agriculture", "Augmented reality and Agriculture", "Big data and Agriculture", "Blockchain and Agriculture", "Cloud computing and Agriculture", "Drones and Agriculture", "Internet of things and Agriculture", "Nanotechnology and Agriculture", "Robotics and Agriculture", "Simulation and Agriculture", "Synthetic biology and Agriculture", "3D printing and Healthcare", "Artificial intelligence and Healthcare", "Augmented reality and Healthcare", "Big data and Healthcare, "Blockchain and Healthcare", "Cloud computing and Healthcare", "Drones and Healthcare", "Internet of things and Healthcare", "Nanotechnology and Healthcare", "Robotics and Healthcare", "Simulation and Healthcare", "Synthetic biology and Healthcare", "3D printing and Logistics", "Artificial intelligence and Logistics", "Augmented reality and Logistics", "Big data and Logistics", "Blockchain and Logistics", "Cloud computing and Logistics", "Drones and Logistics", "Internet of things and Logistics", "Nanotechnology and Logistics", "Robotic and Logistics", "Simulation and Logistics", and "Synthetic biology and Logistics".
All the relevant literatures were downloaded (PDF files) and saved on the computer but only important literature that meet the scope of the present study were considered for the in-depth literature study. The first screening was done through evaluation of the title and abstract (TA) and then followed by full-text (FT) screening for inclusion in the study in terms of the availability of the requisite information for the present study ( Figure 2). The last search was done on 20 th May 2020. The search outputs were saved on databases and the authors received notification of any new searches meeting the search criteria (from ScienceDirect, Taylor & Francis, Emerald insight and Google scholar). = 1 + 2 + 3 + 4 + 5 represents the total number of pdf files downloaded from the respective databases

Industry 4.0 Neologisms
The concept of industry 4.0 originated from manufacturing industry purposely to improve the engineering excellence from machine building to informatization [55]. However, nowadays, the concept of industry 4.0 has expanded tremendously and its definition spans beyond engineering, smart and connected machines and systems, and has become a more general concept with mainstream appeal and applicability [56]. This is can be evidenced by a multitude of neologisms such as Fashion 4.0 and Care 4.0. Interestingly, the icon "4.0" and beyond (e.g. "5.0") have spread tremendously as witnessed by the fact that the combination of a noun and the icon "4.0" are used to signal and usher in discussions about the future of business and society [53]. In this study, 99 industry 4.0 neologisms were identified in published literature and categorized into 6 areas as depicted in Table 2. However, the previous study by Madsen [53] reported only 37 neologisms. This alone can divulge that there is an increasing disruptive landscape of industry 4.0 in business, society, services and industry sectors. Generally, education 4.0 came forth in response to industry 4.0 which is a technology-and datafueled world [188]. It has similar remarkable trends of (r)evolution just as industry 4.0. Table 3 shows the characteristics of each education evolution [189][190][191][192][193][194][195]. Education 4.0 is the most complex system as compared to the previous evolutions. This derives from the fact that industry 4.0 disruption is introducing rapid and unbelievable changes and challenges including the issue of skills and job profiles [196]. Therefore, it poses the question of how to educate and prepare new logical innovations and to develop not only left-brain skills but also right-brain skills [197]. As a result, education 4.0 topic has attracted a number of researchers in the recent year. Lately, the World Economic Forum developed education 4.0 framework that can be easily adopted and implemented by any institution, government or university as presented in Table 4 [198].

Learning Factory
As far as education 4.0 is concerned, adequate and innovative manufacturing education and training are required in order to prepare employees for changes in their working environment related to quickly advancing digitalization. Most importantly, theoretical knowledge and practical skills regarding data acquisition, processing, visualization and interpretation are needed to exploit the full potential of digitalization [199]. Consequently, the concept of learning factory (LF)/teaching factory and Innovation laboratory have egressed in the recent epoch as the lucrative approaches for qualification of participants from the field of Engineering, especially industrial and mechanical engineering [200][201][202][203][204].
LFs offer a suitable environment to combine theoretical learning and practical application and are therefore predestined to impart Industry 4.0 knowledge and skills [205]. LFs are employed to teach students, how the methods and concepts learned in theory work in a hands-on and industryrelated environment [200]. Elaborately, LFs are platform created to provide an effective learning environment that will bring about human capacity development in a bid to bridge the gap between learning and practice (i.e. the gap between academia and industry) [206,207]. The promising strength of LFs is the ability to solve problems in a structured way is an essential competence of people in a factory, from the shop floor operator to the management level factory [208]. Furthermore, LFs are an effective solution to deal with new technologies, new concepts and methods [209]. Generally, LFs develop a uniform, unambiguous concept of competence that can be applied to production technology in the engineering community [210]. However, the requirements for the planning, implementation and operation of an academic LF vary depending on the specific area of the respective institution [211]. For instance, the use of LFs differs for education in maintenance, manufacturing, production design and technology adoption [212]. To this end, several learning factories concepts have been developed including game-based learning or gamification for manufacturing education [213], and internet-of-things-laboratory (IoT-Lab) [214]. Table 5 outlines some examples of the learning factories launched majorly by institutions.  [227] 9. Industrie 4.0 learning factory Aims to support "Made in China 2025" strategy with necessary qualification of employees in Chinese production companies [228] 10. Training Factory

Stator Production
It aims at providing small and medium-sized companies, particularly those affected by change, with the opportunity to train their employees [229] S/N Example Description Reference(s)

11.
MTA SZAKI learning factory It aims at providing infrastructure, learning content and opportunities for future production engineers, with a strong emphasis on automation and human-robot collaboration [230] 12. Chair of production system (LPS) It aims at teaching Industry 4.0 requirements in application and development [231,232] 13 LogCentre learning factory It aims at availing a low-cost environment for the German Kazakh University in Almaty, Kazakhstan to learn how state-of-the-art concepts and technologies are applied in logistics systems e.g. RFID.

Overview of Energy 4.0
Despite the tremendous improvement in the industrial systems brought about by industry 4.0 in terms of the rudimentary achievements on higher level of operational efficiency, productivity and automatization, it brought bureaucracy as huge amount of energy and materials are demanded and extremely large amount of solid, liquid, and gaseous wastes or greenhouse gases are generated from these complex industrial systems [237,238]. Therefore, smart factories need to be sustainable and renewable in terms of energy pattern (electric system industry) [124,[239][240][241]. Further, the United Nation Industrial Development Organization (UNIDO) has set the relevancy of industry 4.0 and sustainability in the global Sustainable Development Goals (SDG 7 and 9) that digital industrial development should support the growth of industrial sustainable energy [242]. This has pointed towards the evolution of new energy concept known as Energy 4.0.
Energy 4.0 is a digital revolution in the energy sector, and also known as smart energy or green energy [99]. It present opportunities for companies to establish new business models and sustainable strategies of producing and delivering energy [99]. Moreover, the idea of energy 4.0 is based on accelerating clean energy through adoption of industry 4.0 concept in the energy sector [243]. The energy transition from 1.0 to 4.0 can be traced back in a similar manner to that of the web system as illustrated in Figure 3   The concept of energy 4.0 is nascent and therefore, no clear information on its concept exists so far in literature [99]. Nevertheless, renewable energy is fundamental to the energy 4.0 epoch. However, the transition to an intermittent energy production from renewable energy sources increases the complexity of providing reliable energy supply. This has been handled with the introduction of digital or smart energy systems [244]. The truth is that smart renewable energy ware systems lie at the core of industry 4.0, and a number of recent advanced technologies and approaches play pivotal roles, by exploiting innovative technologies and optimization methods [241]. For instance, the production of crude biofuels obtained from biomass and renewable energy sources is unheard-of. The biomass crude oil generation technology is currently up-to-date in terms of reducing dangerous emissions into the environment [245]. In addition, offshore and onshore wind energy harvesting has become the driving force towards the realization of energy 4.0 in most developed and developing countries [100].
Another key driver of energy 4.0 is how to reduce energy consumption whilst maintaining or increasing profits and productivity. The fact that energy requirements have grown due to automation of industrial systems makes energy optimization central in energy 4.0. Thus, a number of sophisticated energy efficient mechanisms and software have been developed including real-time embedded systems [246], and computational modeling (e.g. Energy Efficiency Analysis Modelling System) [247][248][249].
Additionally, the advancement in power distribution is another driver of energy 4.0. This is accomplished through the integration of conventional power grid system with industry 4.0 technologies including IoT, Big Data and AI. The combination of these technologies and power grid has been cited as smart grid [99].
Furthermore, the advancement in energy storage system which employed nanotechnology as one of the core technologies for its development is emblematic to energy 4.0. Currently, the nextgeneration lithium ion batteries are under rapid development using various nano-structured materials including silicon nanowires and silicon nanotubes which are two promising anode materials due to their high specific capacities [250].
Importantly, food and farming systems must reconcile the need to produce enough healthy and affordable food with the equally important motive of ensuring that we do not degrade the ecosystems on which we entirely depend for sustenance [171]. On one hand, agriculture industry is critical to sustainable development, and agricultural production by smallholders in lower-income countries contributes substantially to the food security of both rural and urban populations [267]. On the other hand, food industry is a key issue in the economic structure due to both the weight and position of this industry in the economy and its advantages and potential [268]. In order to harness and control both agriculture and food industries, a complex industry (Agri-Food) has emerged-better known as "Agri-Food 4.0" in the era of the fourth industrial revolution [96,98,269]. In fact, the term agri-food 4.0 is an analogy to the term industry 4.0, coming from the concept of agriculture 4.0 [95]. In this regard, agriculture 4.0 was adopted in this study to cover all the aspects of food and agricultural industries.

Convergence of Disruptive Technologies in Food and Agriculture
More like in manufacturing system, industry 4.0 is disrupting agricultural and food systems through the convergence of its technologies [26]. In order to understand and illustrate this fact, a massive exploratory literature search was conducted to identify the mentioned use cases or applications of industry 4.0 technologies (disruptive technologies) in published literature. In this respect, 12 disruptive technologies were considered [27] and these included 3D printing (3DP) AI, Augmented reality (AR), Big Data, Blockchain (BC), Cloud computing (Cloud), Drones, IoT Nanotechnology (Nanotech), Robotics (Robots), Simulation (Sim) and Synthetic biology (Syn-Bio). The identified applications were categorized into 10 major application areas in agriculture and food systems namely; Food processing and management (FPM), Farm equipment and facility maintenance (FEFM), Agriculture machinery automation (AMA), General Agri-Food planning and operation management (GAFPOM), Yield Prediction and Precision Farming (YPPF), Weather and environment management (WEM), Land preparation and planting optimization (LPPO), Crop and Livestock Growth, Improvement and Protection (CLGIP), Food Packaging and Storage (FPS), and Irrigation and water management (IWM) as shown in Table 6. These application areas were derived just from the mentioned applications in the collected relevant publications. So, by mapping the application areas with the disruptive technologies, the convergence of these technologies is clearly visible as illustrated in Figure 5. The quantitative analysis involved counting the converging technologies in each application area and calculating the percentage convergence as shown in Table 7. The result demonstrates that the application areas: GAFPOM and YPPF were the dominant with 17% technologies convergence followed by WEM and CLGIP with 15%, and then LPPO (11%) ( Figure 6). However, each application area has totally different set of technologies in convergence. For instance, the technologies converging in GAFPOM application area include AI, AR, Big Data, Blockchain, Cloud computing, Drones, IoT, Robotics and Simulation. Whilst the technologies converging in YPPF include AI, AR, Big Data, Cloud computing, Drones, IoT, Nanotechnology, Robotics and Synthetic biology. These differences are also observed in the other application areas.    The disruptive and transformative wave of Industry 4.0 which is incredibly retrofitting many industries has also paved its way into healthcare industry or medical fields including orthopaedics and dentistry. As the result of the tremendous disruption into the healthcare system, a new concept termed as "Healthcare 4.0" has evolved [398][399][400][401]. Although the implementation of healthcare 4.0 concept has been characterized as being highly complex and costly, and requires a more skilled labor force, a number of hospitals in the advanced countries are already embracing it [402,403]. The driving force behind this healthcare (r)evolution is the need to deploy industry 4.0 technologies to deliver more effective and efficient health care services including high security and privacy on the patients data electronic health record while allowing remote and real-time access, and diagnosis by the doctors or healthcare personnel [404][405][406][407].
Healthcare 4.0 is also known as hospital 4.0 [123]. It is a term that has egressed recently and derived from Industry 4.0. Simply put, healthcare 4.0 is a digital health, or the use of digital technologies for health. The term digital health is rooted in electronic health (eHealth). The eHealth is defined as the use of ICT in support of health and health-related fields. While the mobile health (mHealth) which is a subset of eHealth entails the use of mobile wireless technologies for health. On the other hand, healthcare 4.0 germinated as a broad umbrella term encompassing eHealth (which includes mHealth), as well as emerging areas, such as the use of industry 4.0 technologies including IoT, Big Data, 5G, AI, Computing (cloud, fog and edge), and Blockchain [408][409][410][411][412][413][414]. Holistically, the World Health Organization [408] reiterated the term healthcare 4.0 as a discrete functionality of digital technology that is applied to achieve health objectives and is implemented within digital health applications and ICT systems, including communication channels such as text messages. In a similar manner to industry 4.0, the healthcare industry has revolutionized from 1.0 to 4.0 as illustrated in Figure 7 [415][416][417]. Besides the implementation of industry 4.0 technologies in healthcare system, there are ongoing studies in the development of healthcare services including the Social Cooperation for Integrated Assisted Living (SOCIAL) [418], OpenEHR [419], GraphQL and HL7 FHIR [420]. This is because Healthcare services and management plays an essential role in human society [421,422]. These are also contributing a lot to shaping the journey of healthcare 4.0. One of the factors that is boosting the adoption of healthcare 4.0 is the concept of smart city. Smart healthcare is an essential part of creating a smart city because anyone can go to the hospital for treatment [423]. To this far, some of the major players in Healthcare 4.0 include Abbott Laboratories, Philips Healthcare, Life Watch, GE Healthcare, Omron Healthcare, Siemens Healthcare and Honeywell International Inc. [424]. Nevertheless, the healthcare industry lags behind other industries in protecting its data from cyber-attacks [425]. The strength and the benefit of healthcare 4.0 adoption has been witnessed in the fight of the novel Coronavirus (COVID-19) pandemic [426]. Coronavirus is one of the viral respiratory illnesses and can be fatal to some immunocompromised patients [427]. However, combating this pandemic has become a global hurdle. As a lifesaving strategy, a number of healthcare facilities have devoted to using 3D printed patient respiratory ventilators and breathing equipment to sustain the life of patients [428].

Convergence of Disruptive Technologies in Healthcare
As with agriculture 4.0, the convergence of industry 4.0 technologies in healthcare have been demonstrated. Here, the analysis was based on 10 application areas which include; Medical education, research and training (MERT), Medical devices and equipment (MDE), Pharmaceuticals, drug delivery and discovery (PDDD), Detection, diagnosis, prediction, prognosis, prevention and treatment (DDPPPT), Telemedicine and medical record (TMR), Healthcare facility management and process optimization (HFMPO), Surgery, Medical imaging, Monitoring, and Dentistry as shown in Table 8. The convergence of the disruptive technologies in these application areas is illustrated in Figure 8. The convergence of these technologies was quantified as shown in Table 9. The result depicts that convergence of the disruptive technologies was the highest in both DDPPPT and MERT with 13.5% followed by TMR and Monitoring with 12% ( Figure 9). The technologies convergence in DDPPPT for example, include Synthetic biology, Robotics, IoT, Drones, Cloud computing, Blockchain, AI, and Big Data while for MERT include 3D printing, AI, AR, Big Data, Blockchain, Drones, Simulation and Robots. However, Dentistry has received only one technology (3D printing). This could be because of limited studies on the technology's application in dentistry.  The intricacy of the disruptive and transformative powers of industry 4.0 including the process of globalization of the world economy is a prerequisite for the successful operation and disruption of logistics which is well-known today as logistics 4.0 [534,535]. In fact, the formation of logistics 4.0 banks in particular on cutting-edge technologies and the digitalization of business processes [534]. In addition, logistics 4.0 concept emerged purposely to overcome the growing uncertainty and dissatisfaction in implementing industry 4.0, new methods and tools that specifically address dedicated companies' areas, such as logistics or reverse logistics, supply chain management, and manufacturing processes [536,537]. For the case of supply chain management, industry 4.0 with its associated technological advances are increasing supply chain resilience or lean supply chain management which is highly linked to the general operation and performance of logistics industry [538][539][540].
Generally, logistics 4.0 refer to the combination of using logistics with the innovations and applications added by Cyber physical system. However, so many related concepts and definitions of logistic 4.0 exist today including smart services and products [541], green logistics [542], smart logistics or intelligent logistics and smart warehouse [543][544][545][546][547]. Furthermore, logistics 4.0 reflects logistics innovation [548], digitization in maritime logistics [549], digital supply chain [550,551], smart ships and autonomous vessels [130].
Logistics 4.0 is a new paradigm in logistics industry that focus on the description of the newest technologies in contemporary supply chains applications [552,553] Table 10 [ [562][563][564][565][566][567][568]. Globalization, finance, governance, leadership and society at large play astonishing role in enhancement of the general performance and development of logistics industry as well as economic growth in any country [569][570][571][572][573]. Most importantly, delivering on digitalization for large multinational business, in the contemporary context of global operations and real time delivery, is a significant opportunity to logistic industry [574,575]. In globalization, all the three modes including trade, financial and technological globalizations are now practiced everywhere in the world as an important and economic reason for company improvement [576][577][578]. However, globalization in the era of industry 4.0 has taken a quantum leap into a new concept known as "Globalization 4.0" which is among the main drivers of logistic 4.0 [579]. One of the key countries behind globalization 4.0 is China. The China's Belt and Road Initiative is an important vector for globalization 4.0 as it helps to bring its enabling infrastructure and technologies to all corners of the globe [580]. Table 11 shows the transition or (r)evolution from 1.0 to 4.0 for globalization, leadership and society [581][582][583][584][585].
Similarly, finance sectors in logistic industry is leapfrogging as disruptive technologies paved their ways into services and financial inclusion. In most organisations today, finance professionals are being asked to learn new skills, often related to such technologies because work is morphing into more project-oriented opportunities. For instance, the major challenges that Chief finance officers of logistics industry are facing include handling massively Big data, liquidity and cash flow, complicated cash lifecycle finding and retaining good talent [586]. In order to overcome these hurdles in finance systems for logistics industry, a new concept of finance called "Finance 4.0" was born, which is driven by digital transformation in finance and banking system [587][588][589]. Figure 10 illustrates three generations of finance and banking systems from 2.0 to 4.0 [145,[586][587][588]590].

Convergence of Disruptive Technologies in Logistics
In this section, 10 application areas in logistics were derived and defined majorly based on the selected studies [591,592]. These include Warehouse capacity optimization and automation (WCOA), Logistics assets and facility maintenance (LAFM), delivery and distribution (DD), Customer order picking (COP), Forecasting, planning and reporting (FPR), Dynamic route optimization (DRO), Procurement and financial management (PFM), Threat and fraud detection and prevention (TFDP), Monitoring, tracking and traceability (MTT), and Environment monitoring and management (EMM) as shown in Table 12. The mapping of the technologies in these application areas were conducted as demonstrated in Figure 11. The technologies convergence in the application areas was calculated as presented in Table 13. The result shows LAFM and DD were the dominant with 15% convergence followed by WCOA and FPR with 13% as illustrated in Figure 12. The technologies converging in LAFM include 3D printing, AI, AR, Big Data, Drones, IoT, Nanotechnology and Robotics. While for DD include 3D printing, AR, Blockchain, Drones, IoT, Robotics, Simulation and Synthetics biology. In WCOA, the converging disruptive technologies are 3D printing, AI, AR, Drones, IoT, Robotics and Simulation. In the same way, the technologies converging in FPR and the rest of application areas were elaborated.  TFDP: Theft prevention, after-sale service and warranty validation, [693] 9. Nanotechnology MTT: nanochips RFID labels for tracking [694,695] LAFM: Nano-based coatings to handle biofouling and corrosion, and grippers to locate single parcels, analyze their size and shape, and determine the optimal unloading sequence), assistance robots for local or home delivery (follow delivery personnel to transport heavy items, pre-sort shipments inside delivery vehicles, and autonomously deliver shipments to dedicated collection points), last mile delivery, and distribution centres [596,698,700,703] LAFM: perform maintenance [700] COP: Innovation in order fulfilment with human-robot collaboration [596] 11. Simulation DRO: evaluation and assessment of road transport [704] FPR: analysis of supply chain activities, supply chain management optimization and logistics cost control, design and implementation of reverse logistics networks, planning and monitoring of fourth party logistic (4PL) process, [598,[705][706][707][708][709][710][711] DD: define an optimal distribution cost for products shipped to wholesale customers [712,713] WCOA: flow-oriented models of inventory control systems [714] 12. Synthetic Biology DD: biofuels for trucks and ships vessel [715,716] MTT: biosensors, biosafety, biosecurity [717,718] WCOA