How to Fit Artificial Intelligence into Manufacturing | by Aurosikha Priyadarshini | Dec, 2020
Artificial Intelligence (AI) has been tainted with a lot of negative press since its conception. Many people in the workforce have started to question the motives for implementing AI in factories and other workplaces.
However, there are responsible AI practices aimed at making the workplace a better place for employees. A prime example of this includes the applications of AI in manufacturing. Its implementation in this industry proves that the tech is only good as its user.
What are some of those applications? Here is how to fit Artificial Intelligence into manufacturing responsibly:
Using in AI-powered computer-aided design programs
During the product development phase, there are a lot of designs being proposed for that particular project. When it’s time to choose the perfect design, there’s a lot of things to consider, including its materials, application, and specifications from the end-user, if any.
According to the experts on an online IT proofreading service, sometimes doing this manually can lead to a lot of waste because more prototypes will be made that are constantly being rejected. That is why a lot of manufacturing factories have started using computer-aided design programs. These programs can contribute greatly to product development, especially if AI powers them.
They can factor in all the elements that need to be considered to develop the best prototype that meets client specifications. Designers work in conjunction with the program by inputting all the parameters and taking a look at the 3D model before a prototype is created. That makes it much easier developing products that will get approval and it minimizes the waste of constantly creating new prototypes.
Testing durability and performance of a product
Another very important phase of manufacturing is stress-testing the product and trying to understand how it will perform as time goes on. This might be a little hard to do because you can’t predict the elements and environment the product will operate in.
As various research paper writing services put it, when predicting the life cycle of the product, it could be just guesswork that can backfire on you when that item fails sooner. Well, AI has a great solution to try and resolve this problem and it has become popular under the name “Digital Twins.” AI-powered computer programs can try and predict the life cycle and durability of the product over time.
Professional writing services say that the computer program can factor in the materials used, the kind of environment it will specifically be used in, and other elements that contribute to wear and tear. Afterward, the digital twin program will output the data you were looking for relating to the durability and performance of that product.
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Maintaining the machinery using predictive patterns
Running, managing, or maintaining a manufacturing factory can be a lot of work. The real problems start when production is halted due to machine failure. However, it does not need to be like that because many machine failures can be fixed easily with predictive maintenance.
Maintaining your machines at regular intervals before any damage has been done can save the factory a lot of money. It will also ensure that productivity continues since there will be no major machine failures every now and then. However, trying to create a predictive maintenance strategy manually is a little bit challenging.
The IT head at BrillAssignment says that the reason why it is challenging is that you do not fully understand what is going on inside the machine. AI can help maintenance teams and factory managers understand their machines better and when to maintain them. How so? Using a variety of sensors, AI-powered programs can pick up when a part of the entire machine needs some predictive maintenance.
Reducing environmental impact
One of the most innovative ways of using AI in manufacturing factories is optimizing the environmental impact your machines have. There are many energy-inefficient practices used by manufacturing firms, and some are unavoidable, but AI can help make it better. This was proved by a pilot project that Siemens did that was aimed at reducing the environmental impact of their manufacturing firm.
The company used an AI-powered program that reduced carbon emissions that originated from their factory. This program adjusted the rate of how much the valves opened based on how the machine was performing at that time.
If the machine was performing at half capacity, the carbon emissions would be reduced to match that performance at that moment. There are many other ways that AI can reduce the environmental impact of their manufacturing factories, including making the building more energy-efficient, etc.
AI-powered robotic machines
In manufacturing factories, society has seen an increase in the number of robotics used to help assembly line personnel and others in the workforce. This has made people very insecure about their job security since they think that these bots are here for their jobs. The truth is, a socioeconomically conscious factory will understand the impact of eliminating a human workforce.
The implications can be immense and therefore, many companies do not have the goal of eliminating their workforce. Instead, these robotics are being implemented to aid humans in tackling their daily tasks and improve production. For example, in an automotive assembly line, more cars can be assembled using AI-powered robotics than humans alone.
That ultimately significantly increases the production capacity of each factory and the sales thereof. In the long run, a company can scale operations and hire more people. Using robotics like this is one of the most sustainable ways to create long-term value.
Trying to monitor the stock levels of raw goods used for production and the manufactured products can be daunting. That is if you run a large operation that manufactures small items that can’t be easily stock taken. AI programs can help manufacturing units monitor the stock levels of their raw good so that they can know when to replenish.
At the same time, they can also monitor the manufactured product levels to see if targets will be reached. By providing a central system like this that is not prone to human error, you can significantly optimize supply chain operations. They will know when to restock to avoid running into dangerously low volumes of raw goods.
Also, employees will not spend a lot of time trying to figure out the individual amounts of raw goods and manufactured products. Instead, they can focus on other tasks that need immediate attention from a thinking human being.
Logistics make up a huge part of a manufacturing factory and especially if this aspect is handled in-house. There is a lot to consider when it comes to logistics and most of it is aimed at having optimized operations and cost savings. Therefore, matters such as route-planning and fleet-management are at the top of the list in problems solved by AI.
You can now get a comprehensive AI-powered logistics program that helps save costs by route planning and even manage your fleet for you. Other AI programs might also focus mostly on picking items that are ready to be shipped, which can be a major convenience for employees.
The latter also reduces human error in the process of picking finished products that need to be shipped to the customer. That helps contribute to a watertight logistics system in the long run.
The bottom line
AI-powered programs are here to stay and manufacturing factory managers should either embrace the change or suffer from the competition for dismissing these processes. There is a lot that AI can do for manufacturing companies nowadays. That ranges from inventory management, optimizing logistics, including robotics in the workplace, and reducing environmental impact. There are many other AI applications in manufacturing and you can choose the one most relevant to your operations.
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