Artificial intelligence (AI) is playing an important role in the modern manufacturing industry. They help in predictive and preventive maintenance, defect detection, effective productivity measurement, etc. Therefore, AI has made outstanding breakthroughs in this industry and has been invested and applied by many big companies.
In modern manufacturing in the 4.0 revolution industry, we can easily see that AI-controlled machine equipment and AI-based technological solutions are gradually setting a clear path to the future. This brings many benefits and opportunities for businesses in automating production, thereby enhancing their competitiveness in the market.
AI plays an important role in the manufacturing sector
A statistic from Accenture (NYSE: ACN) states that:
By 2035, AI technologies are likely to increase production by 40% or more.
AI will drive economic growth by an average of 1.7% across 16 industries by 2035.
It is impossible to admit that AI plays an extremely important role in the modern manufacturing process. AI is the factor that directly automates or supports many activities in production, such as predictive and preventive maintenance, risk and error detection, productivity measurement, etc. Versions of new production systems equipped with displays, human-machine interfaces (HMIs) or electronic sensors to provide visual information on raw material availability, system status or consumption levels. power consumption, and many other factors.
Many manufacturing machines, especially robots today, are faster, more reliable and precise than humans. They help perform tasks far beyond human capabilities and replace humans to do dangerous jobs. However, at present, the majority of intelligent robots using AI intelligence are still under human control, and in some cases have to go through the opinions or decisions of managers.
As innovative technology increases and costs fall, manufacturers will discover applications where artificial intelligence algorithms can make difficult and complex decisions. Thanks to AI, many niches that have been idle for a long time have been discovered. And they promise a bright future in emerging markets.
With the current developments, here are the highlights related to 4 breakthroughs that will change the future of AI in manufacturing.
1- Machine Learning and autonomous AIs thrive
As we all know, the power comes mainly from Machine Learning and artificial neural networks (also known as Deep Learning). In addition, other self-organizing systems can develop their capacity to learn from their own experiences, without human intervention. These systems are fully capable of rapid development and can quickly uncover meaningful patterns in huge volumes of data beyond the capabilities of human analysts.
However, until now, the human factor still plays a role in driving the development of AI applications, when AI managers will proceed to encode expert knowledge from systems. previously designed by themselves. Basic knowledge as well as information about production such as which process is optimal, which stage is decisive, etc. will be provided to AI so that it can create a huge source of production Big Data.
Along with that, autonomous AI will automatically build and complete based on these data blocks and expertise. As a result, manufacturers will almost certainly benefit from sensors for preventative maintenance and process fine-tuning. This seems to be an important step towards renewing the future, getting closer to the day when machines can repair themselves. The moment the tools wear out, the AI system will adjust itself to maintain existing performance and send repair notifications to the staff.
2- AI creates flexible and optimal factories
In the future, we cannot deny the fact that AI applications not only be applied in the manufacturing process, but they can also directly support plant planning activities, such as layout, location of work area. AI can completely help manufacturers consider the safety factor at work and the flexibility to easily change depending on the requirements of a short-term production project with frequently changing labor processes. often.
We also cannot help but face the reality that it is impossible for us to deploy a factory every day differently. At the present time when technology is limited, frequently changing processes can lead to certain obstacles in terms of space and also the production process. Therefore, they can affect work performance and safety.
Currently, AI sensors have the ability to monitor and track factory activities. They observe processes and automatically measure risks. Therefore, there is a high probability that in the future AI can completely take care of both the process and the work of factory construction planning and flexible custom processes.
3- Factory "canning" (Factory-in-a-box)
The concept of a “canning factory” factory is perhaps a new concept. This word refers to the fact that a business can hire a third party to produce a certain product by coordinating the supplier. They will help businesses quickly own a mobile "factory" that can go to the production site. This may be very fanciful, but they are already starting to appear in many countries around the world.
Inside a "canning factory" will include a production line with complete electronics. They are capable of manufacturing printed circuit boards and conducting assembly of finished products and automatically checking their quality. Basically, this idea is not limited to electronics.
In fact the "canning factory" has been successfully manufactured by the UK's Smart Manufacturing Accelerator. They worked with manufacturer Dearman to create a prototype “canning plant” with hose assemblies for truck-mounted refrigeration systems. The necessary parts will be packed in the container including the robot along with the automatic devices. They cut the pipes, bent and braided them together. Finished assemblies will be automatically inspected and pressure tested prior to shipment. With this model, the human presence only plays a role in maintaining the system. The robot will do most of the work.
In the present time, people still directly design and make decisions, supervise the production process and work in some functions of the line. The mobile factory AI system only supports making recommendations to help humans make the most accurate decisions.
4- AI and Derivative Design – Generative Design
Generative Design can be considered as one of the outstanding new applications of AI in the future of the manufacturing industry. Derivative design is a term used to refer to a process in which engineers can enter design parameters such as materials and dimensions as well as weight, capacity, cost, manufacturing method, etc. … into a common software. When the software runs, they will analyze the combined variations so that they can come up with a solution that creates hundreds of different design options. This will help designers or engineers to select the best results, consistent with the original criteria set.
AI realizes its derivative design capabilities in the 3D printing industry. Specifically, a business providing 3D printing services Autodesk has collected a large amount of data about materials for manufacturing and used that data to guide a general design model. This prototype fully has a certain "knowledge" of certain properties of the material. They are fully customizable according to the manufacturing process.
AI with the potential to unlock thousands of designs, integrate simulation, realize production capabilities as well as merge finished products, and conduct synthetic design is the potential application of AI in the near future. . AI has become part of the workflow. This is the standard in product design and rapid product development with products that meet market needs at a more competitive cost.
With promising future potentials, we can realize that it is absolutely necessary to apply AI solutions in manufacturing right now. AI application is a modern door opening a great future for the world manufacturing industry. In the era of digital transformation, let’s remember, dare to change, dare to succeed and capture background about AI as soon as possible.