Artificial Intelligence’s immediate impact may have been seen in the field of healthcare, hospitality, travel, and human resources. However, AI and machine learning are quietly making their way into manufacturing in the form of Industry 4.0, also known as the Fourth Industrial Revolution (4IR).
Simply put, Industry 4.0 is the standard defined for use of automation and data exchange in manufacturing technologies. This new form is set to revolutionise the way companies manufacture, improve and distribute their products. The idea is to allow manufacturers to integrate new technologies, including Internet of Things (IoT), cloud computing and analytics, and AI and machine learning into production facilities and throughout their operations.
How does AI and machine learning factor in manufacturing
With the help of artificial intelligence (AI) and machine learning, manufacturing companies will be able to take full advantage of the volume of information generated by them. This not only includes the data generated at the factory floor but across their business units. The manufacturing companies operating under the 4IR model will also be able to take advantage of the information from their partners and third-party sources.
There are other ways in which AI and machine learning can help, including insights that provide visibility, predictability, and automation of operations and business processes. The easiest way to imagine this in operation would be to look at industrial machines that are prone to breaking down during production.
Manufacturing companies can use the data collected from these machines to perform predictive maintenance based on machine learning algorithms. The output of this process will be more uptime and higher efficiency.
AI in manufacturing: three major advantages
As mentioned above, AI offers a number of advantages for the manufacturing industry. The advantages will be truly realised when applied with the right approach. The three advantages offered by AI right now can be classified into three categories as detailed below:
- Reduction in Error: A manufacturing company can start by training their algorithms on tasks that are prone to errors. Once the algorithm is trained and becomes intelligent, it can perform these error prone tasks and execute them with efficiency not possible with human operators. With algorithms being not susceptible to any external factors, they are unlikely to suffer from errors commonly impacting a business process.
- Reduction in Cost: One of the primary reasons that AI is being considered for every major industry is its ability to augment humans. We have already seen e-commerce platforms, banks, and the hospitality industry adopt AI or chatbots for their customer service. These robots or automated applications are so good at their job that humans are only needed for a complex problem. This allows companies to reduce their human cost and at the same time, allow their existing workers to upskill themselves and focus on less mundane work.
- Growth in operating revenue: With business processes working with little or no error and human employees focusing on critical business processes, an AI-fueled manufacturing company will function in an ideal way allowing decision makers to focus on core business values. They will also be able to offload less important work to AI-powered software.
Application of AI in manufacturing
In the past few years, we have seen AI being adopted in production lines and robots being available as a service to drive automation. This change has led to intelligent software and technologies being applied across diverse sectors. The industries adopting AI are automating and improving their processes faster than those not fueled by AI. Here are some examples of AI being applied in manufacturing right now.
- Agriculture: One of the manufacturing industries completely upended by AI is agriculture. Intelligent machines are taking over fields and carrying out the harvesting process without any human intervention. There are also automatic systems being deployed for diagnosing diseases or pests in individual plantations. From deep learning and computer vision, to big data and mathematical modelling, AI is truly transforming agriculture for good.
- Transportation: Transportation industry is already driven by a number of smart technologies. One of the most visible ones is the estimated transit time on a route provided by transit apps and navigation services. With smarter technologies like connected vehicles and sensors communicating with onboard cameras on these vehicles, these services can quickly alter their route, identify traffic signs, and allow for a truly autonomous driving experience.
- Industrial IoT: Industrial IoT or intelligent manufacturing relies on real-time data analysis, AI, and machine learning in the manufacturing process to accomplish optimisations necessary for the business to function in a streamlined way. Trendforce estimates this segment to be the most dominant one with the number of industrial robots installed in the factories growing to more than 2.6 million.