What are Industry 4.0, the Fourth Industrial Revolution, and 4IR?
Industry 4.0—also called the Fourth Industrial Revolution or 4IR—is the next phase in the digitization of the manufacturing sector, driven by disruptive trends including the rise of data and connectivity, analytics, human-machine interaction, and improvements in robotics.
Augmented reality, machine automation, and more: the 21st-century industrial revolution is digital. Industry 4.0, the Fourth Industrial Revolution, and 4IR all refer to the current era of connectivity, advanced analytics, automation, and advanced-manufacturing technology that has been transforming global business for years. This wave of change in the manufacturing sector began in the mid-2010s and holds significant potential for operations and the future of production.
Before 2014, the Google search term “Industry 4.0” was practically nonexistent, but by 2019, 68 percent of respondents to a McKinsey global survey regarded Industry 4.0 as a top strategic priority. Seventy percent said their companies were already piloting or deploying new technology.
4IR builds on the inventions of the Third Industrial Revolution—or digital revolution—which unfolded from the 1950s and to the early 2000s and brought us computers, other kinds of electronics, the Internet, and much more. Industry 4.0 brings these inventions beyond the previous realm of possibility with four foundational types of disruptive technologies (examples below) that can be applied all along the value chain:
Technology, however, is only half of the Industry 4.0 equation. To thrive in the Fourth Industrial Revolution, companies must ensure that their workers are properly equipped through upskilling and reskilling and then hire new people when necessary. Upskilling means that employees learn new skills to help them in their current positions as the skills they need evolve. Reskilling is the real challenge: workers are retrained with new skills that will enable them to fill different positions within their companies.
Guide to The Fourth Industrial Revolution (Industry 4.0) in 2024
What is Industry 4.0?
What are the benefits of Industry 4.0?
What are the components/technologies of industry 4.0?
What are the challenges that face Industry 4.0?
What is the future of Industry 4.0?
The global Industry 4.0 market was estimated at $70B in 2019 and is expected to reach $210B by 2026 as more manufacturing businesses are optimizing their digital transformation strategies. Industry 4.0, also known as the fourth industrial revolution, aims to create smart manufacturing machines and systems that are connected, automated, and analyzed thoroughly to improve production, reduce costs, and optimize processes. However, the fourth industrial revolution still faces challenges as more data privacy regulations are pressing through, and the gap in technical skills is widening.
In this article, we explore what is industry 4.0, where it emerged from, what are its components and related technologies, its examples, and where it is going in the future.
https://research.aimultiple.com/industry-4-0/
What is Industry 4.0?
Industry 4.0 refers to the fourth industrial revolution, although it is concerned with areas that are not usually classified as industry applications in their own right, such as smart cities.
What is the Fourth Industrial Revolution?
The first industrial revolution came with the advent of mechanisation, steam power and water power.This was followed by the second industrial revolution, which revolved around mass production and assembly lines using electricity.The third industrial revolution came with electronics, I.T. systems and automation, which led to the fourth industrial revolution that is associated with cyber physical systems.
Industry 4.0 Technologies
Generally-speaking, Industry 4.0 describes the growing trend towards automation and data exchange in technology and processes within the manufacturing industry, including:
The internet of things (IoT)
The industrial internet of things (IIoT)
Cyber-physical systems (CPS)
Smart manufacture
Smart factories
Cloud computing
Cognitive computing
Artificial intelligence
This automation creates a manufacturing system whereby machines in factories are augmented with wireless connectivity and sensors to monitor and visualise an entire production process and make autonomous decisions.
Wireless connectivity and the augmentation of machines will be greatly advanced with the full roll out of 5G. This will provide faster response times, allowing for near real time communication between systems.
The fourth industrial revolution also relates to digital twin technologies. These digital technologies can create virtual versions of real-world installations, processes and applications. These can then be robustly tested to make cost-effective decentralised decisions.
These virtual copies can then be created in the real world and linked, via the internet of things, allowing for cyber-physical systems to communicate and cooperate with each other and human staff to create a joined up real time data exchange and automation process for Industry 4.0 manufacturing.
This automation includes interconnectivity between processes, information transparency and technical assistance for decentralised decisions.
In short, this should allow for digital transformation. This will allow for automated and autonomous manufacturing with joined-up systems that can cooperate with each other.
The technology will help solve problems and track processes, while also increasing productivity
https://www.twi-global.com/what-we-do/research-and-technology/technologies/industry-4-0
How Industry 4.0 technologies are changing manufacturing
Industry 4.0 is revolutionizing the way companies manufacture, improve and distribute their products. Manufacturers are integrating new technologies, including Internet of Things (IoT), cloud computing and analytics, and AI and machine learning into their production facilities and throughout their operations.
These smart factories are equipped with advanced sensors, embedded software and robotics that collect and analyze data and allow for better decision making. Even higher value is created when data from production operations is combined with operational data from ERP, supply chain, customer service and other enterprise systems to create whole new levels of visibility and insight from previously siloed information.
This digital technologies lead to increased automation, predictive maintenance, self-optimization of process improvements and, above all, a new level of efficiencies and responsiveness to customers not previously possible.
Developing smart factories provides an incredible opportunity for the manufacturing industry to enter the fourth industrial revolution. Analyzing the large amounts of big data collected from sensors on the factory floor ensures real-time visibility of manufacturing assets and can provide tools for performing predictive maintenance in order to minimize equipment downtime.
Using high-tech IoT devices in smart factories leads to higher productivity and improved quality. Replacing manual inspection business models with AI-powered visual insights reduces manufacturing errors and saves money and time. With minimal investment, quality control personnel can set up a smartphone connected to the cloud to monitor manufacturing processes from virtually anywhere. By applying machine learning algorithms, manufacturers can detect errors immediately, rather than at later stages when repair work is more expensive.
https://www.ibm.com/topics/industry-4-0
Manufacturing 4.0 solutions in action
The digital transformation associated with Industry 4.0 brings about both cultural and operational evolution. By unifying and connecting people, data, and assets, you create an almost limitless range of potential optimizations. Below are a few examples of how Industry 4.0 solutions are improving efficiency, visibility, and sustainability in manufacturing and supply chains.
Collaborative Design Platforms: Industry 4.0 supports the creation of collaborative design platforms where R&D teams, product designers, and stakeholders from across your organization can access and contribute to design data and insights. This open approach fosters cross-functional collaboration, idea sharing and knowledge exchange, leading to more informed design decisions and the faster development of innovative, customer-centric products.
Predictive maintenance: By integrating IoT sensors and data analytics, manufacturing businesses can monitor equipment health in real-time. Predictive maintenance algorithms identify potential failures before they occur, allowing you to implement proactive processes which can reduce downtime by up to 50%, and extend asset lifespan as much as 40%.
Supply chain optimization: Industry 4.0 supports end-to-end visibility across your global supply chain. With real-time data from suppliers, inventory levels, production schedules, customer demand, internal teams, and much more, you can optimize logistics, balance supply and demand, improve order fulfillment, and enhance your overall supply chain and manufacturing efficiency.
Agile manufacturing: AI and advanced analytics allow you to gather and analyze real-time customer insights and feedback from sources like social media, online reviews, and customer support interactions. Your R&D teams and product designers can leverage this data to identify consumer preferences, pain points, and emerging trends. By incorporating this feedback into the design process, your teams can quickly develop products that better align with market demands, improving satisfaction and loyalty, and driving innovation.
Quality Control and Defect Detection: Leveraging IoT devices and machine learning algorithms, you’ll be able to collect real-time data from all your production lines. By continuously monitoring the manufacturing and production process, you can detect anomalies, identify quality issues, and take corrective actions quickly, making sure you’re always on top of product quality.
Circular Economy Practices: Industry 4.0 supports the implementation of circular economies, focusing on reducing waste and maximizing the reuse, refurbishment, and recycling of materials. By utilizing Big Data analytics and IoT networks, you can track product lifecycles, implement reverse logistics for product returns, and optimize the recovery of valuable resources. What’s more, AI-powered advanced analytics can also help your product designers to develop products – right from the drawing board – that are built to be more sustainable, waste fewer resources, and be more easily recycled or repurposed.
Carbon Footprint Monitoring and Optimization: Industry 4.0 technologies facilitate the collection and analysis of real-time data on energy consumption, transportation emissions, and other factors contributing to a company’s carbon footprint. By accurately measuring and monitoring emissions, you can identify areas for improvement, implement energy-efficient measures, and develop strategies to reduce your overall carbon footprint, helping you to meet your increasingly ambitious sustainability goals
https://www.sap.com/products/scm/industry-4-0/what-is-industry-4-0.html
Industry 4.0 and Smart Manufacturing
Manufacturing and industrial business operations are being transformed through the convergence of information technology (IT) and operational technology (OT) systems onto shared, intelligent, industrial-optimized compute platforms. This consolidation creates a responsive, interconnected system that eliminates data silos and provides access to deeper insights—powered by edge computing—and more flexibility and control.
With more intelligence at the edge—enabled by edge compute, artificial intelligence, and workload convergence—manufacturers can capture, process, and store more data from edge devices. That data can be analyzed closer to where it is collected and used, and manufacturers can make adjustments to operational systems in near-real time.
Intelligent edge systems are the backbone of Industry 4.0 and smart manufacturing. They enable data and information from multiple sensors, applications, and processes to be analyzed closer to the source, which helps reduce downtime, optimize operations, automate processes, and inform new solutions. Software-defined infrastructures enable near-real-time analytics across the supply chain to further advance efficiency, productivity, and data visibility.
As IT and OT converge, HPC for manufacturing allows manufacturers to deploy modeling and simulation workloads on distributed HPC systems—both in the cloud and on-premises—to help enhance product design, identify production challenges, and improve business results.
Together, these paradigm shifts are transforming manufacturing operations to be smarter, safer, and more efficient.
As your Industry 4.0 partner, Intel can help you accelerate time to value for data-driven, interoperable Industrial Internet of Things (IIoT) solutions. With our ecosystem of innovators and portfolio of flexible solutions, we can help you develop and integrate intelligent industrial edge and HPC solutions capable of reducing costs, increasing profits, and moving you ahead of the competition.
Our hardware portfolio spans the range of solutions that factories need, and our technology for IoT spans edge, network, data center, and cloud to deliver agile, intelligent IoT infrastructures. From low-power compute that can bring artificial intelligence (AI) to new places to edge servers capable of analytics tasks such as demand forecasting, Intel can help you deploy smart factory solutions capable of realizing new levels of productivity while revealing new opportunities to maximize revenue.
https://www.intel.com/content/www/us/en/manufacturing/manufacturing-industrial-overview.html
Top 10 AI Trends in Healthcare
How can your business benefit from the advancements of AI in healthcare? Explore our research on 3 103 healthcare AI startups & scaleups to identify the top technology trends & solutions. In this data-driven report, you can find startups working in the field of healthcare analytics, medical diagnostics, clinical decision support, and more!
Innovation Map outlines the Top 10 AI Trends in Healthcare & 20 Promising Startups
For this in-depth research on the Top AI Trends & Startups in Healthcare, we analyzed a sample of 3 103 global startups & scaleups. The result of this research is data-driven innovation intelligence that improves strategic decision-making by giving you an overview of emerging technologies & startups in the healthcare industry. These insights are derived by working with our Big Data & Artificial Intelligence-powered StartUs Insights Discovery Platform, covering 3 790 000+ startups & scaleups globally. As the world’s largest resource for data on emerging companies, the SaaS platform enables you to identify relevant startups, emerging technologies & future industry trends quickly & exhaustively.
In the Innovation Map below, you get an overview of the Top 10 Trends & Innovations in Healthcare that impact 3 103 companies worldwide. Moreover, the AI in Healthcare Innovation Map reveals 20 hand-picked startups, all working on emerging technologies that advance their field.
Top 10 AI Trends in Healthcare
Healthcare Analytics
Medical Diagnostics
Telehealth
Medical Robots
Hospital Management
Clinical Decision Support
Clinical Trials
Public Health Management
Cybersecurity
Personalized Healthcare
https://www.startus-insights.com/innovators-guide/ai-trends-in-healthcare/
3 fantastic opportunities the fourth industrial revolution is bringing to banking & finance
Despite the major challenges the fourth industrial revolution is bringing to banking and finance, it isn’t all doom and gloom. The opportunities it presents are equally as game-changing.
Fourth industrial revolution opportunity #1: Enhanced customer experiences
Technology is making it possible for companies to enhance their customers experience tenfold. It’s making it possible for them to offer intuitive, personal and connected experiences. With big data, companies have more access to in-depth insights into how their customers behave, what they like, what they don’t like, and what they want than ever before. And the huge advances in AI have given them the ability to tailor their customer’s experiences, reach them at crucial touchpoints and change their products and services accordingly, without much effort.
It’s worth noting that when choosing a banking or finance company, 70% of customers see connected processes as a key requirement and 59% see tailored and contextualised engagement based on previous interactions as key.
Fourth industrial revolution opportunity #2: Increased security and efficiency
Digital money (or cryptocurrency) is an inevitable consequence of the fourth industrial revolution, and one of the biggest trends to come out of it is Blockchain.
“Blockchain is a secure, decentralized, and transparent way of recording and sharing data, with no need to rely on third-party intermediaries.” – Salesforce
Just like the internet changed communications forever, Blockchain will change banking forever. Blockchain technologies record all transactions in a transparent and safe way: It allows people to send money (almost) immediately, to anywhere in the world, at a low cost. And because it doesn’t use any third parties, and each transaction is cryptographically protected, it drastically minimizes the risk of hacking.
“While there is no system that cannot be hacked, blockchain comes very close.” – WeForum
Fourth industrial revolution opportunity #3: Added flexibility
Thanks to the fourth industrial revolution, organisations across all industries are under more and more pressure to respond to customers and situations instantly, 24/7. As the banking sector is constantly evolving, this means that banks and financial organisations need to be as flexible and as agile as possible. A tricky concept to pull off if you’re a large, cumbersome financial corporation.
They need to be able to address problems and change direction quickly.
“High performing banks have discovered that the most cost-effective way of achieving this is through an enterprise-wide hybrid cloud.” – Wowsome
The Hybrid cloud is an IT infrastructure that connects the public cloud to private cloud spaces to create a single, flexible cloud environment. It not only gives organizations the benefit of having both a public and a private cloud space, but it also addresses issues surrounding data security, governance, and compliance, along with the ability to organize resources in minutes.
Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions
Abstract
The emergence of Industry 4.0 marks a transformative era for businesses and industries, characterized by advanced technologies like automation, Internet of Things (IoT), artificial intelligence (AI), smart factories, and cyber-physical systems. This revolution promises significant advantages, including enhanced productivity, sustainable progress, and heightened resilience. However, the integration of Industry 4.0 is challenged by the need for a skilled workforce with expertise in areas such as information technology and data analytics. Higher education institutions (HEIs) play a vital role in equipping future professionals with these skills, necessitating curriculum updates and infrastructure enhancements. Simultaneously, the importance of education for sustainable development (ESD) has been underscored by global initiatives like the Sustainable Development Goals (SDGs). ESD instills a sense of responsibility for economic, ecological, and equitable well-being. As digital technologies blur the lines between industries, education faces the challenge of adapting to evolving demands. The integration of AI tools in education has emerged as a catalyst for reshaping learning experiences, fostering innovation, and preparing individuals for the digital age. AI chatbots such as ChatGPT have garnered widespread attention and possess the potential to revolutionize various aspects of education. However, their integration raises ethical concerns, necessitates curriculum redesign, requires strategies for continuous learning, and demands alignment with industry standards. While the potential of AI integration in education is promising, there is a notable gap in the existing literature when it comes to exploring the ethical implications, the influence of AI on ESD, the impact on the structure of Blooms Taxonomy, collaboration between academia and industry, strategies for continuous learning, and the effective integration of AI tools for personalized learning. This paper aims to critically examine the integration of AI tools, with a specific emphasis on ChatGPT, in education within the context of ESD. It delves into the transformative potential, ethical considerations, imperatives for continuous learning, and the role of industry partnerships. By providing insights and strategies, this paper contributes to the ongoing discussion about the evolving nature of education in a technologically driven world, equipping academic institutions to navigate the complexities and opportunities associated with AI integration in education more effectively.
https://www.sciencedirect.com/science/article/pii/S0959652623046851
How the Industry 5.0 concepts emerged
Learning about the Industry 5.0 concepts and the history of this term can indeed be somewhat confusing. Especially since it tends to overlap with Industry 4.0, not just in terms of technologies and solutions but also from the temporal perspective.
The concept of Industry 4.0 is several years ahead, of course, but not for very long. It is considered that Industry 4.0 started trending in 2011, when the vision for the Fourth Industrial Revolution was presented at the Hannover Messe fair in Germany. Naturally, the initial vision of Industry 4.0 was also developed primarily for the German industrial automation and smart manufacturing market, as well as for other countries that are part of the EU and are subject to EU legislation. And even though soon Industry 4.0 became a global trend, for some time it had been perceived as primarily relevant to the European business environment and policies.
Industry 5.0, on the other hand, had a more global and international reputation from the very beginning. The origins of this concept, however, can also be traced back to Germany. It was at the CeBIT 2017 trade fair in Hannover where Japan presented its own vision for the future of industrial automation, robotics and smart manufacturing. Then, it was called Society 5.0. Reportedly, the Japanese vision gave birth to the concept of Industry 5.0 as an evolution of the original concept with enhanced role of humans, delivering business value alongside robots.
Recent experience of global COVID-19 pandemic and economic turbulence associated with it is another notable factor that played a big role in the rising popularity of Industry 5.0 as a new technology trend. A large supply of new data from companies that were implementing Industry 4.0 solutions and practices—prior to and during the COVID-19 crisis—shed light on many shortcomings of this concept and revealed areas that clearly required transformation.
https://www.clarify.io/learn/industry-5-0
The Difference between Industry 4.0 and 5.0
In the same way that industry 2.0 represents the shift from water and steam power to electrical, the term Industry 4.0 was originally described a transition in the German manufacturing industry toward digitization and automation.
This revolution is essentially enabled by IoT (the Internet of Things) and supporting technologies, allowing for integrated cyber physical convergence, digitization, wide-scale automation, and a fusion of IT and OT (Information and Operational technology) activities.
Additional tools and components include so-called cyber-physical systems, horizontal and vertical integration, the transition from industrial automation to industrial digital transformation, linked value chains, and others.
Many of the benefits promised by industry 4.0 innovations are only accessible at advance stages of implementation. Autonomous and semi-autonomous manufacturing processes, hyper-automation, advanced robotics, self-optimizing systems, data exchanges, are given a lot of emphasis in the Industry 4.0 phased vision, but can represent challenging implementation cycles. While 90% of Manufacturers regard industrial adoption of digital tools as a priority, only 1 in 4 see new revenue streams from present advancements.
Consequently, it seems fair to say that while many manufacturers have shifted their business models in an attempt to access industry 4.0 benefits, few have reached their overall transformation goals.
While the new wave of industrial innovation hinges on 4.0 technologies, Industry 5.0 aims to reinvigorate the push for industrial digitization by shifting the focus of innovation to human operators, operational resilience and true sustainability objectives.