Like the previous three revolutions, Industry 4.0 aims to transform manufacturing using the latest technologies. This time, advanced information and communication technologies create the Internet of Things (IoT). Industry 4.0 combines IoT with artificial intelligence, machine learning, and robotics to digitize manufacturing.
The Internet of Things (IoT) is a key part of the Industry 4.0 strategy, which aims to create flexible and interconnected digital factories, facilitating communication between all parts of the system. The best aspect of technologies like IoT, AI, and big data today is their breadth of application. These technologies are applicable to the factory floor as well as other areas such as planning and management. Manufacturers can even integrate customers and business partners into value and business processes.
As you can see, the Industrial Internet of Things (IIoT) has enormous potential to improve manufacturing. Today, almost every factory uses automation and robotics. The use of artificial intelligence is also accelerating, improving automation and manufacturing efficiency. With manufacturers seeking ways to embrace IoT and Industry 4.0, the smart manufacturing market is projected to reach $228.2 billion by 2027. Here are some ways the industry is moving towards this goal.
Internet of Things in Manufacturing Automation
Cyber-Physical Systems (CPS) are at the heart of the smart factory envisioned by Industry 4.0. CPS are systems that utilize sensors and software in all parts of manufacturing. These parts could be machines, vehicles, routes, inventory, and the plant itself. Sensors record and store data, which is then processed by computers to make decisions. These decisions directly impact the physical system through actuators and Human-Machine Interfaces (HMIs).
CPS (Computer-Generated Services) improves automated machines using the Industrial Internet of Things (IIoT). Conventional automated machines use software to isolate their work. In contrast, CPS collects and shares data with all assets and areas of the factory. Cloud computing is used to analyze this data to make decisions that optimize the system. Enterprises can also use AI and ML to make smarter optimizations based on previous results.
CPS and IoT complement each other to create smart factories. These competitive factories reduce downtime, increase efficiency, create better products, and improve productivity. Factories implementing IoT in manufacturing report cost reductions and quality improvements.
The three major advantages of the Internet of Things and Industry 4.0
Predictive maintenance
Maintenance is a major headache for any factory manager. The associated downtime and costs can prove prohibitively expensive. Classic methods of routine maintenance are inefficient, increasing the risk of machine tool breakage and wear, which in turn increases costs.
Predictive maintenance systems use the Internet of Things (IoT) to acquire real-time information about each asset in service. Based on this information, the system predicts when asset maintenance will be required. Manufacturing plants have interconnected systems where multiple factors are at play. Load, design, and process changes at one location can affect the entire plant. IoT-based predictive maintenance and cloud computing are particularly useful in such situations. The system uses data from assets around the plant to predict maintenance needs.
Intelligent maintenance management systems with IoT capabilities can also utilize artificial intelligence and machine learning. These can take into account the impact of all systems on manufacturing in order to make better and more accurate predictions over time.
Predictive maintenance is receiving particular attention due to its impact on the bottom line. According to a McKinsey report, predictive maintenance can reduce costs by 10-40% and downtime by 50%. These improvements affect factory efficiency and can even reduce overhead costs. To remain competitive, tomorrow's digital factories will inevitably incorporate predictive maintenance.
Smart Logistics Management
During the Covid-19 pandemic, the manufacturing industry faced unprecedented conditions, including social distancing requirements, worker shortages, and labor force size restrictions. All of these conditions significantly impacted factories and warehouses.
Logistics is the lifeblood of any business. The world has suffered supply chain disruptions as multiple industries face logistical challenges. These massive disruptions necessitate a move towards smarter logistics management.
Factories can utilize the Internet of Things (IoT) in many areas of logistics. From inventory and material handling to internal transportation and shipping, IoT can help improve the accuracy and efficiency of logistics management. The primary way IoT assists in these areas is through real-time location and condition data of assets. This helps optimize inventory usage and stock levels, improve asset tracking and material handling systems, and reduce accidents and asset losses. Information regarding production and transportation can be shared with partners and customers.
Amazon's warehouses utilize IoT and robotics to optimize their systems, with humans working collaboratively with connected robots. This human-technology hybrid approach has made Amazon a leader in warehousing. Other companies are expected to follow their successful model. With the advancement of Industry 4.0, the predictive maintenance market is projected to grow at a CAGR of 31% from 2021 to 2030.
Big data and cloud computing
Real-time data collection is a key advantage of digital factories and the adoption of the Internet of Things (IoT). Sensors on all factory assets collect vast amounts of valuable data. This data can provide important insights into factory performance.
Currently, only a small fraction of data is actually used for decision-making. These decisions may relate to changes in production, inventory levels, or forecasts. With the help of cloud computing and big data, businesses can extract invaluable insights from data.
The Internet of Things (IoT) and Cyber-Physical Systems (CPS) in the factory ensure you have data from all systems. Cloud computing transforms this data into useful information. Through visualization and correlation analysis, problems can be identified and hypotheses can be created regarding their causes. Solutions created to address these problems are implemented to test these hypotheses. AI is used to calculate the impact of changes and the optimal range of parameters. This data flow and advanced analytics help decode complex manufacturing processes and systems.
The Future of the Digital Factory: IIoT and Industry 4.0
IIoT and Industry 4.0 are creating new opportunities and possibilities for manufacturing. The digital factory is the future of manufacturing, and early adopters will have an advantage. However, it's important to remember that many of these technologies are constantly evolving. Businesses must plan ahead and develop technology adoption strategies to remain competitive.
