David Gelernter has published an article titled “ Artificial intelligence isn’t the scary future. It’s the amazing present”, describing the equivalence of artificial minds with humans and the future growth of AI as innovative technology. Today AI is solving the toughest of problems faced by humans – be it in any sector. The advent and growth of AI are promising enough for companies to think of innovative ideas which incorporate the use of AI to solve industrial problems. AI can be also called as the major propellant of the fourth industrial revolution.
Importance Of AI in Manufacturing
The manufacturing industry shares a major portion of the economy of any country and thus asks for the strict quality demands of the final product. The industry thus relies heavily on automated processes for quality check. AI can be used to optimize a variety of processes related to manufacturing chain like production, quality inspection, and logistics. AI also brings a reduction in the cycle time of quality check as the algorithms of AI-based machine vision system requires seconds or even milliseconds to detect and process the image information.
AI in the manufacturing market estimated to be valued at USD 1.0 billion in 2018 and further expected to reach USD 17.2 billion by 2025, at a CAGR of 49.5% during the forecast period. Further, machine learning technology holds a major share of AI in manufacturing industries in 2018.
AI is not only limited to Quality Inspection and has a huge potential to solve problems of different areas like-
- Supply chain management:
Due to the diverse components used, the manufacturing industries have a complex supply chain. Any delays or breakdown can shut down the production line. AI comes into the picture here as manufacturers can predict the interaction between different production units and automate requests for parts, labors, and tools. According to McKinsey, AI can help companies to reduce forecasting errors by 20-50% to optimize stock replenishment.
- Predictive maintenance:
AI systems in conjunction with IoT data can predict and avoid machine failure. According to McKinsey data, the AI-based predictive maintenance system can reduce maintenance costs by 10%.
Apart from these AI has a huge potential to solve problems in the field of design, R & D and operations.
Affect Of AI In Manufacturing Industries
A human being who is in charge of inspecting the products in the stage of the quality check may miss out on the defects which are minute but a vision system equipped with AI-based software will not miss a beat. In a recent Forbes Insights survey on artificial intelligence, 44% of respondents from the automotive and manufacturing sectors classified AI as “highly important” to the manufacturing function in the next five years, while almost half—49%—said it was “absolutely critical to success.”
Why is AI so crucial for manufacturing industries? The main reason is the sheer scope of problems it can solve from real-time maintenance of equipment to smart supply chain, from the classification of parts to surface defects identification. The adoption of AI can help the manufacturing industries to save a lot of time for the tasks performed by human beings.
Challenges to Adoption
AI being a new technology, people are still hesitant to deploy AI-based systems, considering that:
- AI-based system requires a large amount of data to learn which is not readily available. Qualitas Technologies is trying to simplify this with easy to install cameras (like EagleEye inspection system).
Have a look at the below link for more information on EagleEye
- Solution development is time-consuming and requires specialization. We at Qualitas Technologies are trying to simplify this with easy to use training software (Like Eagle Eye Deep Vision).
- AI-based system will be expensive as this is emerging technology and thus requires specialized hardware and software licenses. However, this is changing quite fast and the cost is being driven down with adoption.
- All the problems related to Quality Inspection cannot be solved with AI (AI is suitable for repeatable processes). However, some tasks like measurements, etc are not suitable for AI.
Andrew Ng, co-founder of Coursera and Professor at Stanford University quoted AI as the new electricity-” Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’ think AI will transform in the next several years”. Electricity changed how the world operated. It appended transportation, manufacturing, healthcare. AI is poised to have a similar impact.
According to the report by Adobe, only 15% of enterprises are using AI as of today, but the growth shows that share will grow to 31% in another year. Also, the share of jobs requiring AI has increased by 450% since 2013. According to the data of BridghtEdge, the next big marketing trend is seen as being consumer personalization(29%), followed by AI(21%). Moreover, 47% of digitally mature organizations, are those with advanced digital practices, have a defined AI strategy.
Due to the increasing trend in the adoption of AI technology, the current time should be considered as ideal to invest in AI solutions and with the advancement, in this field, we can hope that AI should be able to solve bigger problems of manufacturing industries in future.