ARTIFICAL INTELLIGENCE
Mark Spurdens says: “To capture the potential of AGI, businesses should develop digitisation plans and be open to support from external experts.”
Left: Robots in production image courtesy of Chef Robotics Inc. Below: HMI image courtesy of AJS Automation and Control
DIGITISATION AND AI - IT’S ALL IN THE PLANNING
This article, based on practice and research within the UK food and drink manufacturing industry, is written from the perspective of Mark Spurdens, from the University of Lincoln’s National Centre for Food Manufacturing (NCFM). All views expressed are his own
enley Business School recently reported: “AI is revolutionising the way we work. But too many leaders are rushing in without a plan or considering their organisation’s needs”.
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There has been such interest in AI that the NCFM has been approached by businesses requesting it as a solution without defining a problem or opportunity. On one occasion the reason for the request was that “the CEO has told us we need to get it”.
Possibly driven by this demand, systems deploying relatively simple algorithms are being branded as AI enabled. In some cases, these are solutions that have been used for over 20 years such as:
• Multi-head weighers selecting combinations of buckets to make the closet match to the target weight.
• Programmable ovens moving through phases as set point temperatures of humidities are met.
• Checkweighers that adjust rejects to optimise use of average weights tolerances. Is any Proportional Integral Derivative (PID)
controller feedback-based control loop mechanism, which we use to continuously monitor and automatically adjust a process, what we mean by AI? If so, the CEO can relax, they had AI for decades.
We are also seeing the deployment of machine learning approaches by some businesses, for example:
• Of optical recognition systems where off the shelf solutions allow cameras to differentiate between characteristics with a few iterations of feedback
• Of complex robotic pick and place solutions used to assemble ready meals where integrated weighing and vision systems provided performance feedback for optimisation. That learning is consolidated from the whole fleet of robots deployed across multiple businesses to inform the operation of the fleet.
Systems that learn, might be closer to what is envisaged when a business asks for AI. However as indicated by Henley Business School and others, businesses that consider their needs and approach solution providers with a digitisation plan (or for help in developing one) are better placed to benefit from AI.
Plans might include the digitisation of data that enables AI to conduct analysis and identify patterns, and the integration of AI with human interfaces that augment engineers and others in real time. This approach might support solution developments that include: • Identification of patterns within equipment and plants that supports asset management to optimise up time and asset life. • Augmented reality interfaces that support
36 MARCH 2025 | PROCESS & CONTROL
engineers in fault finding repair and decision making.
• Systems that gather and analyse process data and provide insight that we did not even know was possible, showing us trends and improvements we did not know to ask for. This might be better described as Artificial General Intelligence (AGI), to distinguish it from AI that can only do one thing. AGI is likely to reshape automation and control, our industry and society in ways that we do not understand yet. It is a long way from a PID algorithm and legacy systems that are being branded as AI. To benefit from the opportunity, food and drink businesses (and others), should consider: • Developing a digitisation plan in house or reaching out to those who can provide support, such as Made Smarter UK. • Identifying and defining business opportunities or problems and remaining open to the source of solutions (moving from “we need AI” to “how can we solve this”). • Digitising all data sources not just process data and equipment condition. In engineering we think of quantitative data, but the opportunity includes quantitative data such as meeting transcripts (captured by AI meeting summarising apps).
• Using AGI to analyse that data by asking open questions.
Businesses taking this approach are likely to more closely match solutions including AGI to the needs of their business and differentiate themselves from those doing surface digitisation.
NCFM
E:
MSpurdens@lincoln.ac.uk www.lincoln.ac.uk/holbeach
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