This is about Industry 4.0

1. Industry 4.0 in IoT:
Transforming the Future of
Manufacturing
Course Teacher:
Md. Rafiqul Islam
Lecturer
Dept. of IoT and Robotics Engineering
Bangabandhu Sheikh Mujibur Rahman Digital University,Bangladesh

2. Table of Contents
● Definition of Industry 4.0
● Historical context and evolution
● Key principles
● Key aspects of the role of IoT in Industry 4.0
● Core Technologies in Industry 4.0
● Key Components of IoT in Manufacturing
● Benefits of Implementing Industry 4.0 in IoT
● Challenges and Concerns

3. Definition of Industry 4.0
Industry 4.0, also known as the Fourth Industrial Revolution, refers to the ongoing
transformation of traditional manufacturing and industrial practices through the
integration of digital technologies, smart systems, and data-driven processes.

4. Historical context and evolution
First industrial revolution
Starting in the late 18th century in Britain, the first industrial revolution helped enable mass
production by using water and steam power instead of purely human and animal power.
Finished goods were built with machines rather than painstakingly produced by hand.
Second industrial revolution
A century later, the second industrial revolution introduced assembly lines and the use of oil,
gas and electric power. These new power sources, along with more advanced
communications via telephone and telegraph, brought mass production and some degree of
automation to manufacturing processes.

5. Cont …
Third industrial revolution
The third industrial revolution, which began in the middle of the 20th century, added computers, advanced
telecommunications and data analysis to manufacturing processes. The digitization of factories began by
embedding programmable logic controllers (PLCs) into machinery to help automate some processes and
collect and share data.
Fourth industrial revolution
We are now in the fourth industrial revolution, also referred to as Industry 4.0. Characterized by increasing
automation and the employment of smart machines and smart factories, informed data helps to produce
goods more efficiently and productively across the value chain. Flexibility is improved so that
manufacturers can better meet customer demands using mass customization—ultimately seeking to
achieve efficiency with, in many cases, a lot size of one. By collecting more data from the factory floor and
combining that with other enterprise operational data, a smart factory can achieve information
transparency and better decisions

6. Key principles
Interoperability: The ability of machines, devices, sensors, and people to
connect and communicate with each other seamlessly. Interoperability
enables the exchange of data and information across the entire
production process.

7. Cont …
Information Transparency: Real-time data collection and sharing
provide transparency throughout the manufacturing process. This includes
insights into the status of equipment, inventory levels, and overall
production performance.

8. Cont …
Decentralized Decision-Making: In Industry 4.0, smart systems and
machines have the capability to make decentralized decisions based on
the data they collect. This reduces the need for centralized control and
allows for more agile and adaptive manufacturing processes.

9. Cont …
Technical Assistance: The integration of technologies like artificial
intelligence, machine learning, and augmented reality supports human
workers by providing technical assistance. This can include intelligent
automation, predictive maintenance, and augmented reality interfaces for
better decision support

10. Industry 4.0 is driven by various advanced technologies
● Internet of Things (IoT): Connecting physical devices and systems
to the internet, enabling them to collect and exchange data.
● Big Data and Analytics: Processing and analyzing large volumes of
data generated by connected devices to derive meaningful insights.

11. Cont …
● Cloud Computing: Providing scalable and on-demand access to
computing resources and storage over the internet.
● Artificial Intelligence (AI): Enabling machines to simulate human
intelligence, learn from data, and make autonomous decisions.

12. Cont …
● Additive Manufacturing (3D Printing): Building objects layer by
layer based on digital models, offering greater flexibility in
manufacturing.
● Robotics: Autonomous and collaborative robots that can perform
tasks in a dynamic and adaptive environment.

13. Role of IoT in Industry 4.0
The Internet of Things (IoT) plays a pivotal role in the implementation and success
of Industry 4.0 by providing the connectivity and data exchange necessary for
creating smart, interconnected systems

14. Key aspects of the role of IoT in Industry 4.0
Connectivity and Communication:
● Sensor Networks: IoT facilitates the deployment of sensors and
actuators across the manufacturing environment. These sensors
collect real-time data on equipment status, production processes, and
environmental conditions.
● Machine-to-Machine Communication: IoT enables machines and
devices to communicate with each other autonomously, sharing data
and insights without human intervention.

15. Cont …
Data Collection and Analysis:
● Real-time Monitoring: IoT devices continuously collect data, allowing
for real-time monitoring of manufacturing processes. This data
includes information on machine performance, energy usage, and
product quality.
● Big Data Analytics: IoT-generated data is processed through
analytics tools to derive meaningful insights. This analysis helps in
identifying patterns, optimizing processes, and making data-driven
decisions.

16. Cont …
Predictive Maintenance:
● Condition Monitoring: IoT-enabled sensors monitor the condition of
machinery and equipment. By analyzing this data, maintenance
needs can be predicted, and proactive measures can be taken to
prevent unplanned downtime.
● Reduced Downtime: Predictive maintenance helps minimize
equipment downtime, ensuring continuous and efficient production.

17. Cont …
Supply Chain Visibility:
● Tracking and Tracing: IoT devices are utilized for tracking and
tracing products throughout the supply chain. This improves visibility
into the movement of raw materials, work-in-progress, and finished
goods.
● Inventory Management: Real-time data on inventory levels and
demand enables optimized inventory management, reducing excess
stock and minimizing shortages

18. Cont …
Smart Manufacturing and Automation:
● Autonomous Systems: IoT technologies support the deployment of
autonomous systems, including robotics and automated guided
vehicles (AGVs). These systems operate collaboratively, enhancing
efficiency and flexibility.
● Adaptive Manufacturing: IoT facilitates adaptive manufacturing
processes that can dynamically adjust production based on real-time
demand, market conditions, and supply chain constraints

19. Cont …
Energy Efficiency:
● Energy Monitoring: IoT sensors monitor energy consumption across
the manufacturing facility. This data is used to identify energy
inefficiencies and implement strategies for reducing overall energy
consumption.
● Green Manufacturing: By optimizing energy usage and resource
allocation, IoT contributes to environmentally sustainable and green
manufacturing practices.

20. Cont …
Human-Machine Interaction:
● Augmented Reality (AR) and Virtual Reality (VR): IoT supports AR
and VR applications in Industry 4.0, enhancing human-machine
interaction. These technologies provide real-time information
overlays, improving decision-making and troubleshooting.
● Wearable Devices: IoT-enabled wearables, such as smart glasses or
sensors, offer workers access to information and instructions,
improving safety and efficiency.

21. Cont …
Quality Control and Traceability:
● Quality Monitoring: IoT sensors monitor product quality parameters
during the manufacturing process, enabling early detection of defects.
● Traceability: IoT ensures traceability by recording and tracking the
entire production process, aiding in quality control and compliance.

22. Core Technologies in Industry 4.0
● Cyber-Physical Systems (CPS)
● Big Data and Analytics
● Cloud Computing
● Augmented Reality (AR)
● Artificial Intelligence (AI)
● Additive Manufacturing (3D Printing) and Robotics

23. Key Components of IoT in Manufacturing
● Smart Sensors and Actuators: Devices for data collection and control within the
manufacturing environment.
● Connectivity and Communication Protocols: Standards facilitating
communication among IoT devices.
● Edge Computing: Decentralized processing of data closer to the source for
reduced latency.
● Data Security and Privacy: Ensuring the protection of sensitive information in
IoT systems.

24. Applications of Industry 4.0 in Manufacturing
● Smart Factories: Integration of smart technologies for efficient and automated
production.
● Predictive Maintenance: Anticipating equipment failures to optimize maintenance
schedules.
● Quality Monitoring and Control: Enhancing product quality through real-time
monitoring.
● Supply Chain Optimization, Digital Twins, Customization, and Mass
Personalization: Revolutionizing supply chain management and product
customization.

25. Benefits of Implementing Industry 4.0 in IoT
Increased Efficiency and Productivity:
● IoT Integration: Industry 4.0 leverages IoT to connect machinery, devices, and
systems across the manufacturing process. This connectivity enables real-time
monitoring, data exchange, and coordination, leading to streamlined operations
and reduced downtime.
● Predictive Maintenance: IoT sensors provide insights into the condition of
equipment, allowing for predictive maintenance. Proactively addressing potential
issues minimizes unplanned downtime, ensuring continuous production and
higher overall equipment efficiency (OEE).
● Automation and Robotics: With IoT-enabled automation and collaborative
robotics, routine and repetitive tasks can be automated, freeing up human
resources for more complex and value-added activities. This contributes to
increased overall efficiency and productivity.

26. Cost Reduction
● Predictive Maintenance: By predicting equipment failures and scheduling
maintenance activities accordingly, IoT helps reduce the costs associated with
unplanned downtime, emergency repairs, and replacement of critical components.
● Energy Management: IoT sensors monitor energy consumption in real-time,
allowing for optimization and efficient use of resources. This leads to reduced
energy costs and a more sustainable manufacturing operation.
● Supply Chain Optimization: IoT-driven visibility into the supply chain enables
better inventory management, minimizing excess stock and reducing carrying
costs. Efficient supply chain processes contribute to overall cost reduction.

27. Improved Quality and Flexibility
● Real-time Quality Monitoring: IoT sensors continuously monitor the production
process, providing real-time data on product quality parameters. This enables early
detection of defects and deviations, ensuring higher product quality.
● Adaptive Manufacturing: Industry 4.0 in IoT allows for adaptive manufacturing
processes that can quickly respond to changes in demand or product specifications.
Flexibility in production helps meet diverse customer needs and market dynamics.

28. Enhanced Decision-Making
● Data Analytics: The vast amount of data generated by IoT devices is processed
through advanced analytics tools. This data-driven approach provides
manufacturers with valuable insights for informed decision-making.
● Augmented Reality (AR) and Virtual Reality (VR): IoT supports AR and VR
applications, enhancing human-machine interaction. This technology provides
real-time information overlays, aiding operators and decision-makers in
troubleshooting and decision support.

29. Competitive Advantage
● Efficiency and Innovation: The increased efficiency, reduced costs, and
improved quality achieved through Industry 4.0 in IoT contribute to a competitive
edge. Companies adopting these technologies can respond more effectively to
market demands, outpace competitors, and stay ahead in the industry.
● Customer Satisfaction: Meeting customer expectations for quality,
customization, and timely delivery becomes achievable with Industry 4.0. This
leads to increased customer satisfaction and loyalty, further strengthening a
company's competitive position.

30. Challenges and Concerns
Cybersecurity Risks: The integration of IoT devices in Industry 4.0
introduces numerous entry points for potential cyber threats. The
interconnected nature of devices and systems makes them susceptible to
cybersecurity breaches, such as unauthorized access, data breaches, or
manipulation of critical processes. Ensuring robust cybersecurity
measures is crucial to protect sensitive data, intellectual property, and the
overall integrity of the manufacturing ecosystem.

31. Cont …
Workforce Skill Gaps: The adoption of Industry 4.0 technologies,
particularly IoT, demands a workforce with new skill sets. There is a
challenge in finding and training personnel who possess the required
expertise in data analytics, IoT device management, cybersecurity, and
other advanced technologies. Addressing this skill gap is essential to fully
harness the benefits of Industry 4.0 and ensure a smooth transition for the
workforce.

32. Cont …
Initial Implementation Costs: The upfront costs associated with
implementing Industry 4.0 technologies, including the deployment of IoT
devices, advanced analytics systems, and infrastructure upgrades, can be
substantial. Companies may face financial challenges in making these
initial investments. However, it's important to consider the long-term
benefits, such as increased efficiency and reduced operational costs, that
often outweigh the initial implementation expenses.

33. Cont …
Data Privacy Concerns: The extensive collection and sharing of data in
an IoT-enabled Industry 4.0 environment raise concerns about data
privacy. The interconnected nature of devices and the vast amount of data
generated can potentially expose sensitive information. Safeguarding data
privacy is critical to comply with regulations, maintain customer trust, and
mitigate the risk of unauthorized access or misuse of personal and
corporate data.

34. Thank You