The industrial use of artificial intelligence in manufacturing has increased, as show-cases presented during ARC’s European Industry Forum 2019 prove.
Under the title “Artificial Intelligence (AI) in Manufacturing - Value-added with Real-world examples”, Ebele Maduekwe, Analyst at ARC Advisory Group Europe, chaired an in-depth session at ARC’s European Industry Forum.
Across all industries and verticals, suppliers and OEMs are shifting away from traditional automation to intelligent/smart automation and will continue to be the trend for a long time. As a result, ARC is looking into AI solutions as well as real world examples that showcases possible applications within several technology clusters. These include applications for quality control with machine vision or maintenance with machine-learning (ML) as a technology cluster.
Use Cases for Artificial Intelligence in Manufacturing
The use of AI solutions based on machine learning have increased in industry sectors evidenced by the show-cases presented during the ARC European Industry Forum in Sitges, Spain. Several end-users and suppliers demonstrated applicable solutions in predictive maintenance and quality control. One OEM identified potential predictive failure detection solutions that provide proactive rather than reactive solutions for clients using their plastic mold machinery. Another OEM outlined several uses cases including a ML- based AI model to optimize speed control in robotic motion planning, as well as to improve simulation and parameterization in machine vision applications. It is interesting to note that these applications can be tailored easily to several industries/verticals.
AI Solutions Based on Machine Learning
From real world applications for maintaining and servicing plastic mold machinery to robotic applications for product assembly, we see ML-based AI solutions gaining lots of traction supported by the convergence of IT, Data Science and OT domains. Furthermore, deployment of ML-based AI solutions in manufacturing is currently also being positioned along the ISA95 layer. Deployment from the enterprise layer all the way to the field level is shaped mostly by objectives i.e., what does the client or end-user want to achieve, as well as the time factor involved. Easy access to more computing power at a cost-effective level is also a big driver for AI adoption as highlighted by the presentation on Edge computing.
In a nutshell, ML-based AI solutions in manufacturing are gaining more prominence. However, it is important to look at what is realistically achievable from machine data, as well as relevant applications in the industrial sphere. This will provide us with a clearer picture of the possibilities of data science and ML-based AI solutions in manufacturing. This counts as an important step towards critically examining the challenges and trends pushing AI adoption, as presented at the ARC EIF 2019 event.
ARC European Industry Forum
The ARC Advisory Group hosted its yearly European Industry Forum (EIF) in the Meliã Hotel Sitges in Spain on May 21-22, 2019. The European Industry Forum is part of ARC’s successful series of worldwide conferences in the USA, India, China, and Japan.