The value of the smart manufacturing market was $88.7 billion in 2021. It is expected to progress at a CAGR of 18.5% from 2022 to 2027. And reach $228.2 billion at the end of the forecast period. This predicted growth is credited to the increased demand for efficient and cost-effective manufacturing processes and the need for better quality control and flexibility.
The Asia-Pacific region is expected to be the largest market for smart manufacturing during the forecast period, particularly in countries like China, South Korea, and Japan. This is attributed to the growing demand for smart manufacturing solutions in the region, owing to the presence of many manufacturers looking to adopt these solutions to improve their efficiency, productivity, and quality control.
Challenges to Smart Manufacturing
A 2022 study shows that the uptake of innovative manufacturing technology has been slow, despite the benefits it can provide businesses in terms of increased productivity and reduced environmental impact. One of the challenges facing companies is the lack of experience in using these technologies. Up to 73% of respondents have less than 2 years of experience using smart manufacturing technologies. This lack of experience can lead to businesses not fully utilizing these technologies’ potential.
Another challenge is the high cost associated with implementing smart manufacturing technologies. The initial investment required can be a barrier for many businesses, particularly, small and medium enterprises. However, as smart manufacturing technologies become more established and their costs decline, more companies will likely adopt them.
The Internet of Things in Manufacturing
The Internet of Things (IoT) refers to the ever-growing network of physical objects connected to the internet. These objects can include anything from consumer products like smart thermostats and refrigerators to industrial machines like lathes and milling machines.
Some ways that the IoT is being used in manufacturing include tracking inventory levels in real-time to avoid stockouts. Another use for these innovations is that various sensors are now available to monitor equipment performance for early detection of potential problems or automatically adjust production line speeds. And that’s a lot of potential data that can be collected and analyzed to improve efficiency, quality, and safety in the manufacturing process. Sensors Incorporated and other trusted industrial companies would agree that this data can also be utilized to fuel decisions by management and executives that can help the company grow.
3D printing and Additive Manufacturing
The potential for AM technology to revolutionize manufacturing is enormous. There are many types of additive manufacturing processes. All share the same basic principle: layers of material are added together to create an object. The most common type of 3D printing technology is called fused deposition modeling (FDM). In this process, melted plastic filament is extruded through a nozzle and deposited layer by layer to create an object. Other popular 3D printing technologies include stereolithography (SLA), selective laser sintering (SLS), and direct metal laser sintering (DMLS).
Additive manufacturing is already being used to create prototypes and production parts for various industries, including aerospace, automotive, medical, and consumer goods. As the technology continues to mature, we can expect to see more companies using AM to mass produce parts and products.
Robotics and Automation in Manufacturing
One of the advantages of using robotics and automation is that it can help improve quality control. Automated systems can be more precise than human workers and can also be programmed to follow specific quality standards.
In addition, robotics and automation can help to increase productivity. By reducing the need for human workers, companies can increase output without hiring additional staff. Companies can also reduce the risk of accidents and injuries by having robots handle dangerous tasks. However, this also means that many workers might potentially lose their jobs, especially if they don’t have the necessary credentials to operate such advanced machinery.
Predictive Maintenance for Smarter Factories
PdM is a type of condition-based maintenance that uses sensors and data analytics to monitor the health of equipment. It can help factories avoid unplanned downtime. By predicting when a failure will occur, factories can schedule maintenance during planned downtime, which is cheaper and easier to manage than unexpected downtime. This will save companies time and money.
Moreover, PdM can also help factories improve equipment utilization. By understanding how equipment is being used and what conditions are causing wear and tear, factories can change how they operate to extend the life of their equipment. Additionally, it can also help improve safety in factories. By identifying potential hazards before they occur, factories can take steps to mitigate the risks.
The smart manufacturing sector will continue to grow in prominence over the next few years. As technology advances and more companies adopt Industry 4.0 principles, it will be interesting to see how this affects the economy and job market.