AI and IIoT Enhancing the Manufacturing Process



Manufacturing is extensively leveraging disruptive technologies like AI to enhance the market value and streamline production processes.

Artificial intelligence has been disrupting industries, making them agile and efficient in the process. Manufacturing Industry is also a strong beneficiary of the adoption of artificial intelligence and digital transformation. Industrial IoT also plays a pivotal role in the manufacturing industry by improving supply chain visibility, inventory management, and product quality. 

According to Markets and Markets research, AI in the manufacturing market is likely to reach US$ 16.7 billion by 2026 and is expected to grow at a CAGR of 57.2% during the forecast period 2020-2026. The report also states that big data, evolving Industrial IoT and automation, improving computing power, and increasing venture capital investments are the major drivers for the market. 


What can AI and IIoT do?

  • Predictive maintenance of machinery is a significant benefit of AI in the manufacturing industry. The maintenance of machines is usually expensive and eats up a lot of time. But, with predictive maintenance, AI algorithms can predict malfunctions ahead of time, thus preventing expenses and downtimes. Machine learning models can detect anomalies in the functioning of machinery and apply accurate corrective measures with less human labor. With the advent of Industrial IoT, the connectivity between the machines increases therefore extending predictive maintenance to a larger section. IIoT sensors are an important part of predicting and monitoring the conditions of the machines.
  • Better supply chain visibility and management are now possible with these disruptive technologies like AI, IIoT, and data analytics. Since IIoT works on sensors, real-time tracking of logistics and transportation becomes easier and faster. AI can use the data from these sensors to predict the time taken for transportation and suggest alternative routes in case of any potential issues. AI and IIoT together optimize the supply chain and forecast market demand for products to enhance productivity and business strategies. 
  • IIoT sensors can analyze products and provide insights that enable us to understand anomalies in product design and predict the impact of external factors like temperature. Further, quality control can be enhanced by using AI and computer vision. Computer vision will enable the employees to see and inspect products in their various stages of development and AI/ML algorithms can use the images to identify oddities like leaks, crevices, scratches, deformations, etc. Leveraging computer vision reduces defective products and promotes a safe manufacturing environment. IIoT combined with computer vision will improve the visibility of business operations and refine decision-making through continuously tracking machines.  
  • The advent of Edge AI is a great boon for the manufacturing industry. Edge AI uses the nearest local point to process and store data rather than an internet-based cloud system. Machine learning algorithms store the data it learns in the local hardware device thus eliminating the privacy concerns and latency issues of cloud systems. Edge AI can reduce the power consumption in autonomous cars and enhance surveillance systems by providing intelligence to the cameras. Edge AI will reduce the cost and enhance the safety of IIoT systems since the data produced will not be shared in a centralized cloud. 

The manufacturing industry is witnessing a brilliant transformation with emerging cutting-edge technologies. AI is an effective component in generative design and cost optimization in the industry. Technology is getting upgraded every day and companies will incur greater benefits and market value by adopting them.