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  October 1st, 2020 | Written by

AI is Transforming the Manufacturing Industry: Pros and Cons

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  • Rather than stop the whole production to detect-and-fix the problem, AI predictions pinpoint anomalies more quickly.
  • AI goes a long way in sustaining your manufacturing business, even amid constant change.
  • When AI technology is adopted in the supply chain process, there's transparency and increased data.

The expansion of the global economy continuously triggers the use of new technologies across sectors. There’s no doubt that the manufacturing industry headlines the application of artificial intelligence technology. From product design, production, supply chain, and logistics, manufacturers are using AI software.

The use of these AI analytics and data has helped improve product quality and efficiency. It has also improved the safety of employees and delivery processes.

However, the AI-powered industrial revolution is not without criticisms. Thus in this post, we’ll consider the pros and cons of AI in transforming the manufacturing industry.

Pros of AI transformation of the Manufacturing Industry 

Generally, AI’s beneficial to the various aspects of manufacturing and product distribution. Here are the positives of artificial intelligence:

Predictive Analytics for Increased Production Output

AI manufacturing systems make use of predictive analytics and machine learning algorithms. Since the manufacturing sectors have a large volume of data, the AI predictive analytics is powered from this data. Data are kept in the cloud for analysis and monitoring of any process or equipment disruption.

With this predictive setup, companies can now easily apply a predict-and-fix maintenance model. The guesswork regarding what is wrong with the equipment or process is eliminated. Rather than stop the whole production to detect-and-fix the problem, AI predictions pinpoint anomalies more quickly. It likewise suggests tools and solutions to correct the problem.

Furthermore, manufacturers can also sync production schedules to enhance production output. A report from Mickensey says that an AI predictive maintenance model can increase productivity by 20%. And it can decrease maintenance costs by as much as 10%

Better Generative-Design Process

Another AI advantage is that manufacturers can create better ways of designing their products. With generative-designs, the designer can input product details. Such details include the type of material, appropriate production methods, budget, and time. The designer is also able to input all possible constraints. Using an AI algorithm, the details can be processed to meet a list of possible product options.

The appropriate solution is then tested to suit manufacturing conditions. What makes the generative-design stand out is it eliminating human bias design options. And then it proposes more suitable performance demands.

Improved Process Quality 

Artificial intelligence technology enables a more innovative production process and better product quality. It ensures that products meet the required quality standards and regulations. Manufacturers can achieve this by using equipment that operates with AI technologies like ML and big data.

For instance, tracking sensors could be used in logistics and haulage. It will help to monitor location, take stock, freight charges, and more. According to reports, automation of inventory improves process services by 16%. At the same time, inventory turnovers are likewise increased by 25%.

Such inventory data is used to check for any impending faults that may affect the product delivery service. Thus the company can attain a higher level of specialization. It also eliminates process downtime and increases productivity.

Ever-changing Market Adaptability 

Besides production, there are other significant aspects of manufacturing where AI is pivotal. These include distribution and supply chains, monitoring, customer behavior, and change patterns. Therefore, AI in manufacturing ensures that companies can predict possible market changes. With this, they can go ahead to strategize towards better production and other cost management processes.

Additionally, manufacturers can use AI algorithms to estimate market demands. Such estimates are possible because AI uses the information gathered from different sources. Such as consumer behavior, inventory of raw materials, and other manufacturing processes.

Optimizing Supply Change

When AI technology is adopted in the supply chain process, there’s transparency and increased data. It’s used to enhance manufacturing processes and customer service further. Data from multiple devices are collected and analyzed in real-time to get a more in-depth insight like a possible challenge. Manufacturers are then able to make informed industry-related decisions. AI helps minimize cost and time that may be incurred on warehousing and shipping in the event of any mishap.

AI tools and solutions also help schedule factory activities, demand and supply gaps, and avoid over or under production. Mckinsey estimates that AI technology-based supply chain management enables businesses to cut down forecasting errors by 20-50%.




Furthermore, AI chatbots enable taking care of client inquiries using human-type interactions. In turn, it helps to free up human resources. Such technology allows manufacturers to address clients’ requests and enquires quickly. For instance, a custom writing review service like Online Writers Rating may need to go through thousands of papers daily. And, at the same time, they’ll have to address customer inquiries. But with chatbots, AI provides the necessary customer support, while employees focus on the papers.

Cons of AI in the Manufacturing Industry

As earlier stated, AI in manufacturing is not without criticisms. These are contained in the following artificial intelligence cons:

It’s on the Pricey Side

Artificial intelligence implementation and maintenance costs are on the high side. The budget is one that is often too pricey for small companies and start-ups. Although AI cuts manufacturing labor costs, it still requires installation and maintenance fees. You also don’t want any cyberattacks on your systems, so you’ll also need to consider the cost of cyber threat protection.

Scarcity of Experts and Skills Persons 

Because AI tech is a continually evolving field, thus AI experts with the requisite skills are usually few. Since these tools need regular sophisticated programming, it’s essential to consider expert availability. And also, because they are in high demand, the cost of employing such hands will be on the high side.

Open to Vulnerabilities

Another artificial intelligence con is its vulnerability to cyber-attacks. A recent World Economic Forum report shows that cyber-attacks are among the top five global stability risks. Such information can be pretty scary for any manufacturer using AI software. As AI becomes powerful and wide-spread, cybercriminals are working hard to device new hacking methods. One minor breach can disrupt or fully shutdown a manufacturing business.


AI goes a long way in sustaining your manufacturing business, even amid constant change. It provides predictive analysis that can help manufacturers make more informed decisions. From the product design down to customer management, there’re several positives of artificial intelligence. These include an improvement in process quality, optimized supply chain, adaptability, etc.

However, AI technology isn’t without its cons. Such as expensive budgets and vulnerability to cyber-attacks. Yet the pros of AI outweigh these cons. Therefore, the manufacturing industry can only improve by leveraging AI applications.


Frank Hamilton has been working as an editor at essay review service Best Writers Online. He is a professional writing expert in such topics as blogging, digital marketing and self-education. He also loves traveling and speaks Spanish, French, German and English.