Economies worldwide boomed after reaping the benefits of the third industrial revolution, where robots replaced humans performing repetitive tasks with minimized errors and human efforts. However, these robots without human operators were useless, and humans wanted to give these robots “a brain of their own.”
With the ever-changing consumer behavior and markets, people today are more attracted to unique and more complex products. This has compelled the industry to adapt to a more decentralized approach replacing the conventional manufacturing methods with more intelligent, automated, and digitally linked systems.
All of these reasons gave water to the seeds of Industry 4.0. The fourth industrial revolution means the age of the application of intelligent manufacturing robots. They are self-sufficient and self-corrective in nature. The intelligent factories hosting these smart robots aim to self-regulate to maximize efficiency and reduce the cost of the complete process by folds. Digital manufacturing forms the building block of such intelligent factories, and this article takes a look into it.
What is digital manufacturing and where is it headed?
Digital manufacturing is a novel technology that can create designs and manufacture products with unimaginable speeds and efficiency. With the world progressing in technologies like AI and ML, Industry 4.0 is not a distant dream. Intelligence would no longer remain a human trait when the autonomous robots working in smart factories would take smart decisions every time. Terabytes of data are generated every minute around the world by IoT devices. This data also called modern-day ‘gold’ could make autonomous technologies more robust unlike ever before.
Market giants would invest heavily in these technologies both in the developing and developed nations which would surely act as a balm on the scars that COVID-19 left on the world economy.
Even with such technologies in hand, the current Information and Communications Technology (ICT) structure is not ready to support the complete deployment of digital manufacturing. The very first challenge would be to develop a standardization process to ensure the successful implementation of the strategic vision of Industry 4.0.
Understanding digital manufacturing
Digital manufacturing refers to the use of computer systems to simulate, manufacture, and analyze the complete process of manufacturing, supply chain management to service delivery by linking all the bits and pieces to form a robust and digital linked system.
Digital manufacturing is utilized in various manufacturing sectors. In automotive industries, the Original Equipment Manufacturers (OEM) can digitally simulate all the processes like tooling, machining, assembly sequencing, and factory layout while the design team is working on the designs. The manufacturability of these designs can be precisely analyzed and commented upon by the OEM, saving the company a lot of time and resources.
All of these are possible because of the evolution of data-driven autonomous systems and machine learning tools. Organizations look to connect IoT devices, collect critical metrics, visualize data in real-time, analyze results, and optimize manufacturing processes. Digital manufacturing enables manufacturers to eliminate bottlenecks, reduce inventory, improve quality, shorten time to market, pivot quickly to meet customer needs, and expand the number of products made.
What is a smart factory? How does it employ digital manufacturing?
A smart factory could be referred to as the end product of the digitization process. It is a smart factory floor where each and every device is aware of its surroundings and the complete ecosystem interacts with each other to bring out the desired output. Overall, the characteristics of a smart factory are:
1. Data analysis of the huge amount of data produced by various sensors and meters.
2. Interconnected systems use the real-time data for immediate consumption by other nodes of the factory and are also analyzed by the software stack of the company.
3. Customized manufacturing for customized needs of different customers. By using advanced simulation software applications, new materials, and technologies such as 3-D printing, manufacturers can easily create small batches of specialized items for particular customers. Whereas the first industrial revolution was about mass production, Industry 4.0 is about mass customization.
4. Better and transparent supply chain where relevant information is shared with different nodes of the supply chain.
Technologies used in smart factories
Smart factories use a variety of different technologies to optimize smart manufacturing processes.
These technologies include:
1. IIoT (Industrial Internet of things) - This is a key component of smart factories. Machines on the factory floor are equipped with sensors that feature an IP address that allows the machines to connect with other web-enabled devices.
2. Cloud Computing - The huge data collected from the different nodes of the complete process is stored, analyzed, and computed in the cloud.
3. AI and Machine Learning - AI and machine learning allow manufacturing companies to take full advantage of the volume of information generated not just on the factory floor, but across their business units, and even from partners and third-party sources. AI and machine learning can create insights providing visibility, predictability, and automation of operations and business processes
4. Digital Twin - The digital transformation offered by Industry 4.0 has 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.
Use cases enabled by digital manufacturing
Digital manufacturing with its numerous advantages enables a lot of use cases. One of the most popular ones is predictive maintenance in industries to avoid costly breakdowns. With the real-time sensor data in the system and AI/ML integrations, industries can carry out real-time monitoring of system health and eliminate any unwanted downtimes in the process. Furthermore, digital manufacturing makes it possible to have quality sensing and detecting to monitor and test equipment and products in real-time with visual analytics. This optimizes workstations to benefit the entire production line and to have the ability to adjust production to meet changing customer needs and hot orders.