AI & MACHINE LEARNING
AI AND ML’s ROLE IN SMARTER FOOD SOLUTIONS
Tom Clayton, Co-Founder and CEO of IntelliAM,
discusses how AI and Machine Learning are powering a new industrial revolution in manufacturing
T
he art of manufacturing is becoming the science of manufacturing, thanks to technological advancements and increased knowledge.
Hidden inside plant and machinery in every factory in the world lies an opportunity to harvest rich data. But there has been no effective way to harness this data, until now. At IntelliAM, we’re supporting half of the world’s top 10 food and drink manufacturers and helping them unlock data which is giving them transformational insight. Using AI and machine learning, we’re tapping into hundreds of millions of data points and creating unique fingerprinting for every component.
Machine PLCs, cloud-based reliability systems or IoT devices managing vibration, oil temperature, energy usage, machine alarms, and more, are all potential inputs and rich sources of information.
Not only is AI and machine learning powering a new industrial revolution, but it’s also boosting productivity and enhancing efficiency, quality, and sustainability. It, therefore, needs to be a key factor in modern-day manufacturers’ strategies when looking to boost growth and productivity, alongside facilitating Industry 4.0. A shortage of skills and significant energy price increases in recent years have combined to heap pressure on businesses. Capital investment has slumped due to financial pressure and many industries are experiencing productivity stagnation. The good news is AI and machine learning can deliver seismic, and transformational, results. In many instances, this is without replacing plant and machinery. But a mindset shift is required and so is the acceptance that predictive maintenance is evolving. For one of our manufacturing clients, we’ve implemented an OEE analysis and predictive maintenance system, which ingests millions of data points per month. Our machine learning system analyses all machine alarms, settings,
running parameters, product details, and reliability data – temperature, vibration, and stress wave. We provide actionable insights for when the machine is not set up optimally, causal information of why faults occur, and predict equipment failure. Since implementing this, the performance of our client’s line has increased over 5%.
With vast new insight into both wear-related or random events, there can be timely adjustments in production to reduce waste streams, improve quality, reduce start up error, and increase throughput. The understanding of error leading to random events can now be predictive and prevented, so set up tolerances are improved, and optimum running or speed settings are achieved. Real bottlenecks or true causes can be understood, supply chain errors eliminated, and human training determined. IntelliAM was developed out of the technical sector expertise of 53North, which has a vast amount of experience in the application and delivery of asset management solutions. As both businesses have evolved and AI has developed, there are a lot of misconceptions within industry, and generally in business, about the impact of AI.
Will we become over-reliant on AI? Will it lead to a loss of control? How will it impact employees, and will there be job losses? There’s a lot to be excited about and little to fear, in my view.
AI will revolutionise the way humans and machines interact. However, it only works with manufacturing and domain expertise. You need engineering teams to tag, code, and teach the algorithm, so it can become self- learning – and that actually creates jobs. With stringent controls in place, and by layering and contextualising data, AI’s benefits far outweigh any perceived negatives. The UK food and drink sector accounts for
6 DECEMBER 2024/JANUARY 2025 | PROCESS & CONTROL
19% of the UK’s manufacturing output and directly contributes £33bn to the UK economy. To put that into context, that’s the size of the economic black hole cited by the government. With widespread adoption of AI and machine learning, demand can be accurately predicted, helping manufacturers optimise supply chain operations. Quality control is automated and food waste is minimised, leading to less overproduction. The complexity of food and drink manufacturing processes are often cited as a barrier to the implementation of AI and machine learning. Add in stringent food safety regulations and lack of technical skills within the industry and it’s plain to see why adoption is lagging compared to other industries like the renewable energy sector, which is using sensor technologies and satellite imagery, twinned with AI, to predict downtime periods and capacity levels, allowing them to adjust at pace. This is the kind of proactive approach more UK food and drink manufacturers need to take.
As the world's population grows, so does our demand for food. In fact, the amount of food that needs to be produced in the next 35 years is estimated to be more than the total amount of food ever produced in human history.
We need to scale up to meet world food demands and as new technology continues to evolve, innovation and sustainability in food production must increase. The results are set to be transformational and undoubtedly result in greater efficiency and a safe food supply for an ever-growing population. AI’s influence is vast and is the only viable response to a world demanding smarter, more sustainable food solutions.
IntelliAM AI
intelliam.ai
AI unlocks a wealth of contextualised data to boost productivity and reduce operating costs
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