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  • Writer's pictureAnantaya Pornwichianwong

5 Trends of AI in Manufacturing



Over the last decade, there has been an exponential growth of AI adoption in manufacturing, resulting in the constant evolution of a smart factory powered by industrial intelligence. The use of AI and robotics in manufacturing leads to an exciting future that brings about the advanced and sophisticated level of automation and robotics into the factory that was once only found in science fiction.


Most importantly, according to the report, the use of AI in industrial factories can lead to reducing costs and generating revenue between $1.3 to $2.6 trillion. This represents a huge value that entrepreneurs simply can't overlook. The transition towards becoming a smart factory controlled by AI is now a path that manufacturers must take.


The use of AI in manufacturing can revolutionize almost every aspect of factory operations with a variety of technologies to choose from. It exceeds almost every limitation of traditional manufacturing. Sertis invites you to explore 5 trends of AI that are currently transforming the manufacturing industry to inspire readers to discover and adopt the right solutions for their business, in order to drive competitiveness and stand at the forefront of the industry.



1. AI can be used to build a smart factory.


Building an AI-powered smart factory focuses on the applications of robotics and AI that can assist human workers in tasks that require specialized expertise, such as machine control, safety protocol adherence, and efficiency improvement. AI can also help with production control and cost reduction. Currently, AI is widely used in the following functions:


  • Automate the complex tasks in the factory using robotics.

  • Use AI to detect abnormalities in machinery or product quality during production processes and in the system, and alert the technical team in real-time.

  • Build a centralized AI platform to manage operational data, making it easier to supervise and share data.

  • Use AI to facilitate production scalability to meet changing demands.

  • Ensure the safety of lives and properties in the factory with AI video analytics.


One interesting practical example that applies AI to all dimensions of factory work is the use of AI to optimize the production system. Computer vision acts as AI eyes to detect and supervise production, while data analytics powered by AI uses algorithms that act like the brain to analyze the production efficiency of various parts and adjust production to achieve maximum productivity. Additionally, robots can control production and plan the process and quantity. By doing so, AI can monitor production and enable it to work 24/7 without a break.



2. Natural Language Processing (NLP) can solve the problems in factories.


Natural Language Processing (NLP) is an AI technology capable of understanding and interacting in human language, as we have seen before in chatbots or a stunning innovation like ChatGPT that went viral all over the world. This type of AI can be applied in industrial factories as a chatbot, allowing factory employees to report problems or ask for directions on machine usage. The chatbot AI then quickly searches through the factory's databases and suggests effective solutions.


This solution reduces work time for both staff and supervisors, increasing reliability and efficiency in operations



3. AI can improve supply chain forecasting accuracy.


Currently, the supply chain system in the manufacturing industry has become more complex. Manufacturers have to deal with several issues, whether they are product aging, production scheduling for different types of products, fluctuations in product demand, as well as ensuring sustainability and transparency in the production process.


Therefore, AI and machine learning solutions can greatly contribute to increasing the accuracy of forecasting in the supply chain system. AI can assist in predicting situations across various sectors in real time, enabling faster decision-making. Additionally, it can improve production schedule efficiency, resolve bottlenecks in production, scale production capacity to meet demand, and plan efficient product distribution.


According to the report from a French food manufacturer, using AI to increase the accuracy of its operational forecasting in its supply chain reduced prediction errors by over 20 percent, sales losses by over 30 percent, and reduced the planning team's workload and time by over 50 percent.



4. AI can assist in product quality control.


One of the advantages of AI over other technologies is its high level of accuracy and discretion. Due to its ability to process enormous amounts of information in a second and scrutinize every detail, nothing can escape AI's eyes. This makes AI another promising trend for product quality control in manufacturing.


Even industrial robots, which have been used for many years, have a lower level of discretion than AI and are more prone to making mistakes. This can result in delivering defective products or low-quality products to customers, which can harm the brand's credibility and lead to customer churn and cost waste.


Therefore, by using computer vision with cameras and sensors, AI can help detect defects that may be too small for a robot to notice. Additionally, the Internet of Things (IoTs) can be utilized to connect all machines together and stop production when problems occur or remove problematic products from the conveyor belt. The AI can be trained with information about the quality of the products, allowing it to carefully determine which products are defective, don't meet the standard, or have properties that are different from the target products. This ensures that all products delivered to consumers meet the brand's highest quality standards.



5. AI helps build sustainable and eco-friendly factories.


AI can help build sustainable factories that are environmentally friendly. According to the BCG report, the use of AI in industrial plants has reduced greenhouse gas emissions by 2.6 to 5.3 gigatonnes, which is beneficial for our environment, as manufacturing is one of the sectors that emit a lot of greenhouse gasses into the atmosphere.


Moreover, factories can use AI to measure their carbon footprint and analyze operational data to identify the sources of carbon in the production process to improve and discover ways to reduce carbon emissions.


Additionally, AI can reduce waste in the production process by improving quality control, resulting in fewer products that don't meet standards and become waste. AI and robots can also separate and recycle waste. Furthermore, AI can analyze data to develop eco-friendly production methods, such as modifying packaging to reduce plastic use.


Various technologies have contributed to eliminating vulnerabilities and improving the manufacturing industry in many aspects. Many more technologies are waiting for us to utilize. However, as we always emphasize, the best technology is not necessarily the most advanced or expensive one, nor the technology that completely eliminates humans from the process. The best technology is the one that is suitable for your organization and helps drive competitiveness and unlock the potential to make the business grow exponentially.



Sertis is a leading AI Engine that provides customized AI solutions tailored to the unique needs of clients across every industry, designed to exceed all the limitations of clients' businesses to create the most cost-effective and value-added solutions. Partner with us to create the best AI solution.


Find out more about Sertis manufacturing solutions at: https://www.sertiscorp.com/services

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