Imagine living in a city driven by cutting-edge technology, where everything is computerized, making daily life easier and more efficient. This vision is becoming a reality with the development of smart cities.
A smart city is a modern urban area where technology and data collection enhance the quality of life, sustainability, and efficiency of city operations. These cities represent the future, with the United Nations predicting that 70% of the world’s population will live in smart cities by 2050.
Industries play a vital role in driving national economies. Their improved performance and efficiency lead to greater economic prosperity.
This article will explore the key technologies associated with smart manufacturing systems, the benefits of adopting Smart manufacturing processes, and the ways in which Smart Manufacturing is transforming the manufacturing industry.
Smart manufacturing (SM) uses advanced, integrated technologies to transform manufacturing processes. As technology advances and markets become more global and digital, manufacturers adopt smart manufacturing to stay competitive and profitable. This transformation is part of Industry 4.0, which combines various new technologies to optimize resource planning and make companies more agile.
Global Initiatives in Smart Manufacturing
- Germany: Launched Industry 4.0, focusing on interconnected systems for production planning, plant scheduling, product customization, and fault detection.
- China: Introduced the “Made in China 2025” plan and the “Internet Plus” program to advance their manufacturing industries.
According to McKinsey Global Institute’s report, the manufacturing industry has 60% of automation potential, which also indicates that smart manufacturing technologies can be implemented to the industries to boost their capacities.
Exploring Key Technologies in Smart Manufacturing
Smart manufacturing involves various new technologies working together to streamline production processes. Key tools include:
Internet of Things (IIoT), a network of interconnected machinery, tools and sensors that communicate with each other and the cloud to collect and share data. In smart factories, IIoT devices are used to enhance machine vision, track inventory levels and analyse data to optimize the mass production process. The IIoT not only allows internet-connected smart assets to communicate and share diagnostic data, enabling instantaneous system and asset comparisons, but it also helps manufacturers make more informed decisions about the entire mass production operation.
One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently. With IoT devices and sensors collecting data from machines, equipment and assembly lines, AI-powered algorithms can quickly process and analyse inputs to identify patterns and trends, helping manufacturers understand how production processes are performing. Companies can also use AI systems to identify anomalies and equipment defects. Machine learning algorithms and neural networks, for instance, can help identify data patterns and make decisions based on those patterns, allowing manufacturers to catch quality control issues early in the production process.
Robotics Robotic process automation (RPA) has been a key driver of smart manufacturing, with robots taking on repetitive and/or dangerous tasks like assembly, welding and material handling. Robotics technology can perform repetitive tasks faster and with a much higher degree of accuracy and precision than human workers, improving product quality and reducing defects. Robotics are also extremely versatile and can be programmed to perform a wide range of tasks, making them ideal for manufacturing processes that require high flexibility and adaptability. At a Phillips plant in the Netherlands, for example, robots are making the brand’s electric razors. And a Japanese Fanuc plant uses industrial robots to manufacture industrial robots, reducing personnel requirements to only four supervisors per shift.
Cloud computing helps organizations manage data collection and storage remotely, eliminating the need for on-premises software and hardware and increasing data visibility in the supply chain. With cloud-based solutions, manufacturers can leverage IIoT applications and other forward-thinking technologies (like edge computing) to monitor real-time equipment data and scale their operations more easily. Edge computing, on the other hand, is a distributed computing paradigm that brings computation and data storage closer to manufacturing operations, rather than storing it in a central cloud-based data center. In the context of smart manufacturing, edge computing deploys computing resources and data storage at the edge of the network—closer to the devices and machines generating the data—enabling faster processing with higher volumes of equipment data.
Blockchain is a shared ledger that helps companies record transactions, track assets and improve cybersecurity within a business network. In a smart manufacturing execution system (MES), blockchain creates an immutable record of every step in the supply chain, from raw materials to the finished product. By using blockchain to track the movement of goods and materials, manufacturers can ensure that every step in the production process is transparent and secure, reducing the risk of fraud and improving accountability. Blockchain can also be used to improve supply chain efficiency by automating many of the processes involved in tracking and verifying transactions.
For instance, an organization can utilize smart contracts self-executing contracts with the terms of the agreement written directly into lines of code to verify the authenticity of products, track shipments and make payments. This can help reduce the time and cost associated with manual processes, while also improving accuracy and reducing the risk of errors. Manufacturers can also utilize blockchain technologies to protect intellectual property by creating a record of ownership and improve sustainability practices by tracking the environmental impact of production processes.
Digital twins have become an increasingly popular concept in the world of smart manufacturing. A digital twin is a virtual replica of a physical object or system that is equipped with sensors and connected to the internet, allowing it to collect data and provide real-time performance insights. Digital twins are used to monitor and optimize the performance of manufacturing processes, machines and equipment. By collecting sensor data from equipment, digital twins can detect anomalies, identify potential problems, and provide insights on how to optimize production processes. Manufacturers can also use digital twins to simulate scenarios and test configurations before implementing them and to facilitate remote maintenance and support.
3D printing, also known as additive manufacturing, is a rapidly growing technology that has changed the way companies design, prototype and produce products. Smart factories primarily use 3D printing to manufacture complex parts and components quickly and precisely. Traditional manufacturing processes like injection moulding can be limited by the complexity of a prototype’s part geometry, and they may require multiple steps and operations to produce. With 3D printing, manufacturers can produce complex geometries in a single step, reducing manufacturing time and costs.
Smart manufacturing relies heavily on data analytics to collect, process and analyze data from various sources, including IIoT sensors, production systems and supply chain management systems. Using advanced data analytics techniques, predictive analytics can help identify inefficiencies, bottlenecks and quality issues proactively. The primary benefit of predictive analytics in the manufacturing sector is their ability to enhance defect detection, allowing manufacturers to take pre-emptive measures to prevent downtime and equipment failures. Predictive analysis also enables organizations to optimize maintenance schedules to determine the best time for maintenance and repairs.
What are the benefits of smart manufacturing?
Smart manufacturing can improve organizational efficiency by optimizing production processes and facilitating data convergence initiatives. By leveraging new information technologies, manufacturers can minimize production errors, reduce waste, lower costs and improve overall equipment effectiveness. Improved product quality: Smart manufacturing helps companies produce higher-quality products by improving process control and product testing. Using IIoT sensors and data analytics, manufacturers can monitor and control production throughputs in real time, identifying and correcting issues before they impact product quality. Increased flexibility:
Smart manufacturing improves production flexibility by enabling manufacturers to adapt quickly to changing market demands and maximizing the benefits of demand forecasting. By deploying robotics and AI tools, manufacturers can quickly reconfigure production lines throughout the lifecycle to accommodate changes in product design or production volume, effectively optimizing the value chain.
Challenges and Opportunities
While smart manufacturing offers immense benefits, it also presents challenges, these challenges can make it seem like a big problem: These are High upfront costs, technical complexity, and the need for organizational change can be daunting.
Large corporations with substantial resources may view smart manufacturing as a necessary investment. Smaller manufacturers might find it more challenging due to limited budgets and expertise. Organizations must weigh the risks against the potential rewards.
Implementing smart manufacturing requires careful planning, risk management, and a long-term vision. It’s not a one-size-fits-all solution; each organization must assess its unique situation. In summary, smart manufacturing is both a challenge and an opportunity. Whether it’s a “big” problem depends on how an organization perceives and approaches it.