Revolutionizing Industry: The Journey from Industry 4.0 to 5.0

What is Industry 4.0 and the fourth industrial revolution?

Industry 4.0 refers to the Integration of advanced digital technologies into Manufacturing industrial process by delivering real-time decision making, enhanced productivity, flexibility and agility to revolutionize the way companies manufacture, improve and distribute their products.

So, what is the concept of Industrial revolution?

The concept of Industial revolution is simply refers to the periods of scientific and technological development that largely transform rural societies into industrialized, Urban ones. First industrial revolution began in Britain in 18th century and spread gradually around the World.

We will discuss about the current Industrial revolution and when the next revolution will happen and what are all the technologies will be introduced?

Driving technologies of Industry 4.0

Internet of Things

IoT is a Key component for Smart factories. Machines in the factory are equipped with sensors that feature an IP address to allow machines to connect with the Internet. This makes the way to collect large amount of real-time data that can be analysed and exchanged for predictive analysis and other machine learning projects to improve the quality of machines and products.

Cloud Computing

Cloud computing is the main component of Industry 4.0 Strategy. Smart manufacturing involves connectivity and integration of engineering supply chain, production, sales and distribution as well as service.

Typically, large amount of data being stored and analysed can be processed more effectively and cost-effectively with cloud. Cloud computing will greatly help in reducing startup cost for small- and medium-sized companies who can right-size their needs and scale as their business grows.

AI and machine learning

AI and ML allows manufactures to take full advantage of volume of information generated not only in factories but also across their business units. This can create insights providing visibility, predictability and automation of operation and business process.

Edge Computing

The demand of real-time productions operations made companies to do data analysis at the "edge" - that is, place where data is created. This minimizes the latency time. For instance, Predictive maintenance involve detection of a safety or quality issue, this might require near-real-time action with the machine. The time require to send the data from machine to cloud and then back to factory may take time and depends on the reliability of the network. Edge computing also means data stays near its source, reducing security risks.

Cybersecurity

With Industry 4.0, communications and cybersecurity cannot be viewed as isolated processes. In order to do digital transition, Companies have to consider the importance of cybersecurity or cyber-physical systems that encompasses IT and OT (field) equipment.

Digital twin

The digital transformation allowed manufacturers to create digital twins that are virtual replicas of processes, production lines, factories and supply chains. A digital twin is created by pulling data from IoT sensors, devices, PLCs and other objects connected to the internet. Manufacturers can use digital twins to help increase productivity, improve workflows and design new products. By simulating a production process, for example, manufacturers can test changes to the process to find ways to minimize downtime or improve capacity.

Benefits of Industry 4.0

1. Increased Productivity: Automation and smart technologies enhance production efficiency, reducing downtime and increasing output.
2. Improved Quality: Advanced sensors and AI-powered inspection systems help in maintaining high-quality standards by detecting defects early.
3. Cost Reduction: Optimized processes and predictive maintenance reduce operational costs and minimize equipment failures.
4. Enhanced Flexibility: Smart factories can quickly adapt to changes in production requirements, making it easier to customize products.
5. Better Decision Making: Real-time data analytics provide insights that help in making informed decisions, improving overall operational efficiency.
6. Supply Chain Management: Improved visibility and control over the supply chain led to better inventory management and reduced lead times.

Challenges of Industry 4.0

1. High Implementation Costs: The initial investment for setting up smart factories and integrating new technologies can be substantial.
2. Technical Skill Gap: There is a need for a workforce skilled in both manufacturing processes and digital technologies, which can be hard to find.
3. Data Security: With increased connectivity, the risk of cyber-attacks and data breaches also rises, necessitating robust security measures.
4. Interoperability Issues: Integrating new technologies with existing systems can be challenging due to compatibility issues.
5. Organizational Resistance: Getting management buy-in and overcoming resistance to change within the organization can be difficult.
6. Scalability: Scaling pilot projects to full-scale operations often faces financial and logistical hurdles.

Emergence of Industry 5.0

In order to remain the engine of prosperity, industries must stay in the way of digital and green transitions. By this approach, companies can aim beyond efficiency and productivity as sole goal and reinforces the role and contribution of industry to society.

Industry 5.0 will complement the existing "Industry 4.0" approach by specifically putting research and innovation at the service of the transition to a Sustainable, human-centric and resilient industry.

Technologies of Industry 5.0

Digital, information and operations technologies (Enabling technologies) collectively derive the ongoing and upcoming digital transformation under Industry 5.0. In 5.0, these technologies can be subcategorized into facilitating technology and emerging technology clusters.

Facilitating technologies such as big data analytics, cloud computing, or enterprise systems were introduced in third revolution and widely commercialized in industry 4.0 which made it indispensable part of industrial ecosystems. These technologies will become the fundamental building blocks of industry 5.0.

The emerging technologies of industry 5.0 are the most innovative and disruptive technological innovations that builds on the facilitating technologies to create more productive, eco-friendly and human-centric methods of value creation. The evidence gathered across the globe identified nine emerging technologies that support Industry 5.0.

Cognitive Cyber-Physical Systems (C-CCP)

C-CCP is an upgrade of cyber-physical-social system. This C-CCP acts on sense-analyse-compute-act cycle instead of sense-plan-act which makes industries effective in pattern recognition, failure correction, informed decision-making. Under this cycle, C-CCP can be characterized into Four properties of self-knowledge, Self-monitoring, Self-awareness, Self-informing. The major components of C-CCP are Sensors, actuators, robotic units, control systems, wireless communication systems (5G & 6G) and Human-machine interface.

Cognitive Artificial Intelligence (CAI)

By product of integrating AI with Artificial consciousness. The limitation of existing AI systems such as AI systems still not reached their potential will particularly restrict the implementation of AI in C-CCP. Experts believe in creating qualia out of the vastness of exploratory sensory information parallel with patten recognition would allow CAI to understand that outside world and can act like human. This would create self-healing AI to emerge. This makes CAI to help stakeholders make better decisions, reduces information overload, reduces errors and more.

Human interaction and recognition technologies (HIRT)

HIRT in 5.0 particularly aims in correcting the difficulty of last-gen HIRT in behavioural spatial complexity, emotions and action characteristics. The emerging HIRT aims in optimally correct interconnect and integrate humans with machines.

No sensing and cognition technology has the enough emotional intelligence to judge the working condition and arrive at the best replication of what human would genuinely do in given situation. Indeed, HIRT will deliver only its functions while interacting with CAI, C-CCP, cloud data, and edge computing.

Vision-guided robotics, short-wave infrared technology, sensor fusion, sensor data triangulation, embedded vision systems, adaptable human intention and trajectory prediction, and multi-lingual speech and gesture recognition are examples of vital emerging HIRT components.

Extended reality (XR)

This is an umbrella term for augmented, virtual and mixed reality technologies which is an essential technology constituent of Industry 5th stakeholders. Few implication examples of XR are customer experience, advanced industry and training, and improved safety and efficiency in processes. Experts believe that technical challenges of XR such as Data processing limitation, motion tracking and connectivity issues can be eased by Big Data, edge computing, 6G, AI.

Industrial Smart Wearable (ISW)

Human workers will play an essential role in value creation under this paradigm. Advance ISW allows workers to perform safer, faster and more productive. Bio-inspired protective gears and exoskeletons can improve capabilities, strength, productivity and stability of workers. Head-worn ISW helps in human operations navigations and information sharing capabilities. Clothing ISWs and embedded tracking ISW can also be developed in Industry 5.0. ISW operates under C-CCP and relies on CAL and industrial IoT to communicate and interact with other technologies such as 3D printers and autonomous vehicles.

Intelligent or Adaptive Robots

Although Traditional robots are characterized as fast and productive, yet they need to be isolated by physical barriers for safety purposes. This allows a higher level of human-centric automation in robotic industries. Precision component assembling, transportation of parts, advanced assembly, and soft-material surface processing are among the many application scenarios of adaptive robots under Industry 5.0. Robotic sector is expected to grow as computer vision, machine cognition, edge computing and AI technologies increasingly progress.

Intelligent Energy management system

This technology offers energy efficiency and sustainability. Although Industial productivity with energy efficiency is the primary objective of industry 5.0, the digitalization and the overall overconsumption and shorter product lifecycle lead to rebound in energy sector. IEMS and the complementing technologies such as cloud demand response systems, smart storage, intelligent charging technologies, microgrids, and blockchain-based peer-to-peer electricity trade help bridge the gap in developing renewable energy resources and integrating them into industrial and commercial operations.

Dynamic Simulation and Digital Twin (DSDT)

This technology will couple both physical and virtual worlds, allowing active Data analysis and monitoring of complex systems. DSDT has a capability of recreating exact copy of physical products, processes etc which makes industries to improve their business. DSDT allows predicting and optimization more efficiently and reduce the possibility of low quality. DSDT technologies are data-driven and build on AI, the Internet of Everything (IoE), big data, and adaptive analytics to integrate historical and real-time data to construct the underlying complex virtual models.

Smart Product Lifecycle Management (SPLM)

SPLM will plays a critical role in Materializing the smart product concept under the industry 5.0. SPLM facilitates process integration and networking by creating digital models of product, service, manufacturing, and supply chain processes. SPLM can integrate with smart product embedded software, corporate backend systems, cloud service, and Internet of Services (IoS) to offer complete control of early-to-end stage product data. Overall, smart and integrative SPLM critically contributes to the productivity, servitization, and product circularity objectives of Industry 5.0 by offering authoritative control over product and process data.

By taking the above technologies as reference, Industry 5.0 represents involving the digital transformation of value-creating and delivery process at micro and macroscopic level. Therefore, this concludes with six components that collectively constitute hyper-connected socio-ecological value creating ecosystem.

Industry 5.0 components

1. Adaptive Smart Factory (ASF)
2. Logistics
3. Suppliers
4. Products
5. Customers
6. Stakeholders

Industry 5.0 strategic value

strategic values of Industry 5.0, categorized into economic, environmental, and social sustainability contexts. Here’s a summary of the key points:

1. Economic Values: Manufacturing Resilience: Enhancing the ability of manufacturing systems to withstand disruptions. Business Model Innovation: Developing new business models to adapt to changing market conditions. Supply Chain Resilience: Strengthening supply chains to be more robust against disruptions. Industrial Productivity Growth: Increasing productivity within industries. Macro-regional Economic Development: Contributing to economic growth at a regional level.
2. Environmental Values: The paragraph doesn’t explicitly mention specific environmental values, but Industry 5.0 aims to integrate sustainability into industrial processes.
3. Social Values: Human-centric Automation: Developing technologies that prioritize human involvement and well-being. Personalized Therapy and Treatment: Using advanced technologies to provide personalized healthcare solutions.

These values are expected to be realized at different analysis levels: microscopic (firm level), mesoscopic (supply chain level), and macroscopic (regional level).

Conclusion

This study leverages a content-centric literature review to develop the architectural design of Industry 5.0. This design provides a comprehensive overview of Industry 5.0, including its technologies, principles, components, and strategic values. Rather than replacing Industry 4.0, Industry 5.0 is seen as a continuation that addresses Industry 4.0’s shortcomings by emphasizing societal and ecological values. It retains many features of Industry 4.0, such as merging physical and virtual worlds, integrating humans and machines, and advancing technology, but shifts the focus to a human-centred approach.