FEATURE Smart factories and AI
The future of generative AI
Generative AI is changing UK manufacturing, writes Stephen Hayes, Managing Director of automation and control technology specialist Beckhoff UK
D
ouglas Eck, principal scientist at Google Research said: “Generative AI is like having a thousand artists at your
style and perspective.” This also translates generative AI is being introduced at every step, from design to maintenance of assets. According to a report by analyst house MarketsandMarkets, the global market for generative AI in manufacturing is expected notes that generative AI is being used in various manufacturing applications, including design and process optimisation and predictive maintenance, among others.
Benefits to manufacturing in manufacturing are clear in a recent generative AI to optimise the design of a gas turbine blade. The AI generated the number of individual components needed to make the blade, resulting in cost savings and shorter manufacturing time. Generative AI can also be used to reduce scenarios, and provide insights to improve manufacturing, particularly in areas such as engineering, robotics and automation, the introduction of generative AI could help bridge this gap. Not only can it help automate and optimise processes, but it and personalised feedback to accelerate their learning. This could be vital in the
14 July/August 2023 | Automation
Challenges security risks. A recent report by Deloitte stated that the manufacturing industry a survey by the National Association companies had experienced a cyber attack in the past year.
convincing phishing emails. Manufacturers recognise the evolution of cyber attacks. generative AI is the potential for hackers to manipulate the algorithms used in the design process. This could result in even harm to individuals. Additionally, hackers could use generative AI to create counterfeit designs, leading to intellectual property theft and revenue loss. Another significant risk is the potential for data breaches. Generative AI relies heavily on data, and if compromised, it could be used to create faulty designs or This could result in significant financial losses for manufacturers and pose a threat to national security in industries
such as defence. challenge that generative AI introduces. Generative AI can sometimes produce making it challenging to identify potential manufacturers should ensure that their AI systems are transparent and explainable to
Priorities To overcome challenges like these, manufacturers and engineers must prioritise cyber security and data management. This involves implementing robust security protocols, such as encryption and multi-factor authentication, to protect sensitive data. Regular risk assessments and penetration testing should also be conducted to identify
more of a priority at the machine building secure authentication processes to prevent unauthorised access.
CONTACT:
Beckhoff
www.beckhoff.com
automationmagazine.co.uk
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