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Like many other industries, manufacturing is slowly being transformed by the use of artificial intelligence.

AI is used in different ways, for example. B. for predictive maintenance, generative design, and market forecasting.

However, artificial intelligence is still in its infancy, which means that there are still pros and cons to introducing artificial intelligence into manufacturing.

If you run a manufacturing business and are considering further implementation of AI, it’s important to weigh the pros and cons first.

To get you started, below is an enlightening overview of the pros and cons of AI in the manufacturing industry.

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The state of AI in production

People usually prefer to have bad news first. So let’s look at the disadvantages of using artificial intelligence before we move on to the advantages.

1. AI can be expensive

Although the adoption of AI reduces labor costs, the initial implementation of AI can be quite expensive, especially for startups and small businesses.

However, you can reduce your AI implementation costs by choosing used CNC machines, such as those from the major brands at revelationmachinery.com.

However, there are other costs that you should be aware of. For example, you have ongoing maintenance costs and costs to protect your systems from cyber attacks.

2. You need experienced professionals

Because AI is constantly evolving, you will always need an AI expert with the right skills to, for example. B. to perform demanding programming.

Artificial intelligence specialists are rare and currently in high demand, which means you won’t find a professional anytime soon.

This also means that the cost of hiring an AI specialist will be higher than for other employees.

3. AI is open to vulnerabilities

AI is vulnerable to cyberattacks, and as AI becomes more advanced and ubiquitous, cybercriminals will continue to develop new methods of hacking.

If there is even a small deviation, it can disrupt your production line. One small violation can bring a production process to a standstill.

So you need to keep up to date with the latest security measures and be aware of the latest threats of cyber-attacks, which can be very costly.

Even with the most advanced security systems, hackers can still find loopholes.

The benefits of AI in manufacturing

While you should be aware of the drawbacks of using AI in manufacturing, you should also be aware of the many benefits of using AI.

You will have to weigh the pros and cons yourself, but it is generally believed that the benefits of AI in manufacturing outweigh the cons.

Here are some of the key reasons why you should consider using AI in your production.

1. Predictable maintenance means less downtime.

Sure, you have your own maintenance costs with AI processes, but with AI predictive maintenance you can quickly and accurately predict when the next machine, part or system failure will occur.

Knowing these things means you don’t have to suddenly shut down production when a machine, component or system fails, because you can fix the problem before it happens.

Studies consistently show that unplanned downtime costs manufacturers $50 billion each year, and 42% of this downtime is due to defective machinery or parts.

By implementing AI, you can avoid the costs associated with machine downtime. Predictive maintenance uses advanced AI algorithms to make predictions about asset failures.

2. AI offers better quality

It is becoming increasingly difficult for manufacturing companies to maintain a high level of quality and to comply with quality regulations and standards.

This becomes even more difficult as the time to market gets shorter and shorter.

Increasing production without addressing the quality issue can lead to defects and product recalls, which not only incur costs, but can also seriously damage the company’s brand.

AI guarantees the highest quality during the entire production process. Algorithms based on artificial intelligence can alert workers to production issues that could lead to quality problems.

By paying attention to these issues from the beginning, manufacturers can easily maintain quality levels.

3. AI can improve manufacturing projects

AI improves product design.

For example, one method is to have designers and engineers create a specification, which is then fed into the AI algorithm.

These summaries include, for example. B. Limitations and parameters related to material types, available production methods, time and budget constraints.

The algorithm then examines each possible configuration before returning a set of the best solutions. These solutions can then be tested with machine learning to determine the most effective method.

4. AI helps manufacturers adapt to an ever-changing market

The use of AI in manufacturing is not limited to design methods and ways to improve production on the machine builder’s shop floor. It can also be used to optimize production supply chains and detect market changes.

This gives the manufacturing company a big advantage, as it can switch from a reactive to a strategic mindset.

AI algorithms make predictions about market needs by recognizing patterns that connect elements such as location, political status, socioeconomic and macroeconomic elements, and consumer behavior.

With this data, production companies can optimize aspects such as inventory management, staffing, raw material procurement and energy consumption much better.

Final considerations

It should be clear that AI changes production in several ways. Benefits can be traced from the design process to production facilities and strategies to identify future market trends.

There are definitely some AI flaws, but one thing is for sure: Al is here to stay. Although AI is still in its infancy, it will change the way products and parts are made and the way manufacturers tackle industrial challenges.

So the sooner you can get started with AI for your manufacturing business, the better.

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