Keith Smith is Co-Founder and Chief Operating Officer of IntelliAM, with 27 years of experience in manufacturing and engineering. He developed his expertise during a 16-year tenure at Mars Inc, holding various operational and engineering roles. At IntelliAM, Keith drives the development of innovative technologies that help manufacturers achieve world-class asset care standards through data-driven solutions.
Industry Trends and Challenges
What significant trends are shaping the manufacturing and engineering sectors?
“The integration of machine learning models (ML) and artificial intelligence (AI) for real-time analytics of billions of data points – making the previously unknowable, knowable.
For manufacturers, the answer to increasing equipment effectiveness can be found very close to home – hidden inside the plant and machinery of virtually every factory in the world.
Manufacturers can use the data taken from machine PLCs, drives and IoT devices, to understand how the overall equipment efficiency (OEE) can be improved, productivity increased, downtime minimised, and energy reduced.
As consumer demand rises in food and beverage production, companies are focusing on technology that helps meet these demands more efficiently.”
What challenges are companies facing, and how is IntelliAM addressing them?
“For manufacturers, a key goal is increased productivity – improving operational efficiency, reducing downtime, optimising supply chains, and enhancing sustainability.
Our solution uses edge technology, which allows us to extract millions of data points per day – no matter what the make or age of the machine is.
Companies are in real danger of creating huge technical debt by selecting partners with limited sensor solutions. We help businesses select the technology that meets the failure modes of the machines. By bringing the data together and using ML models, we can understand equipment faults and settings in all operating contexts.
We inform clients how to run equipment at their optimum levels and predict potential failures and prescribe action proactively – minimising disruptions and downtime and facilitating greater productivity.”
Innovation and Technology
How is IntelliAM leveraging automation, AI, or IoT to stay competitive?
“With our ML/AI solution, we’re powering a new industrial revolution that helps manufacturers stay competitive.
Many of the world’s biggest manufacturers, including half of the world’s top 10 food and drinks producers, use our solutions.
We’re using ML to process our customers’ equipment data, which enables us to identify patterns in performance and detect early warning signs of incorrect set up, poor materials, or any mechanical or electrical issues.
This optimises machine usage, energy consumption, production schedules, and predicts failures – ensuring higher efficiency, as a result.”
Can you share a recent innovation and its impact on customer operations?
“For one customer, we’ve implemented an OEE analysis and predictive maintenance system, which ingests over 400 million data points per month.
Our ML system analyses all machine alarms, settings, running parameters, and product details, and we have introduced reliability sensors to collect data – including temperature, vibration, and stress wave. From this, we provide actionable insights when the machine is not set up optimally, provide causal information on why faults occur, and predict equipment failure.
Since implementing this, line performance has increased by 10%.”
Sustainability and Environmental Impact
What steps is IntelliAM taking to improve sustainability?
“Energy optimisation and waste reduction are one of our four key priority workstreams.
Our ML algorithms help our customers to monitor and adjust equipment usage, minimising energy wastage – especially for older, less energy-efficient machines.
We also use data insights to streamline production and reduce food waste and packaging materials.”
How will sustainability influence the future of manufacturing?
“Sustainability will increasingly influence operations, as consumers and regulations demand greater environmental responsibility.
At COP29, for example, the Prime Minister announced the new target of the UK reducing its emissions by 81% by 2035. This will undoubtedly affect how UK industry operates.
We understand that not all customers can afford to replace aging equipment with new, more efficient counterparts though. That’s why we use ML to understand how older equipment can be run more efficiently.
Packaging materials are also changing to be more sustainable, and our ML can be used in the trial phases of changeover to help manufacturers understand the best machine settings or which material providers to use.”
Workforce Development and Skills
What skills are critical for the future workforce?
“The most critical skills in manufacturing now include data analysis, machine learning knowledge, and understanding IoT applications.
This will be key in enabling the success of Industry 5.0.
Maintenance teams also need skills to interpret machine data, conduct predictive maintenance, and troubleshoot complex machinery.
A big misconception is that AI is causing job loss. In actuality, it’s increasing opportunity – creating data science roles within engineering and operational teams.
The truth is that AI only works with manufacturing and domain expertise. We need engineering teams to tag, code, and teach the algorithm, so it can become self-learning. AI will revolutionise the way man and machine interact.”
How is IntelliAM investing in workforce development?
“We’re proud to be leading the charge in the science of manufacturing.
We’re delivering the tools to our customers that support them in understanding the digital transformation and machine learning – ensuring they’re prepared for the technology advancement that will allow them to make better, data-informed decisions.”
Globalisation and Supply Chain Management
How does globalisation affect IntelliAM’s customers, and how do you support them?
“Our ML system enhances visibility and flexibility, allowing our clients to better respond to market and supply fluctuations.
We’ve carried out extensive research and development to enable the use and ensure the quality of multiple hardware solutions. This allows us to tailor the solutions but also ensures we can diversify as and when required.”
What strategies ensure supply chain resilience?
“We’re giving our customers the tools to make more of their data – supporting resilience and flexibility.
One of our customers, for instance, has eight flour mills across the country, and complex supply chain decisions for each site. Our solution supports them in predicting volumes and how to best fulfil them as efficiently as possible.”
Leadership and Business Strategy
How does IntelliAM foster innovation and continuous improvement?
“We emphasise continuous improvement and a client-focused innovation strategy.
We work closely with manufacturers to understand their unique challenges with both modern and legacy systems, adapting our solutions to meet these needs effectively.
This collaborative approach ensures that our clients benefit from the latest advancements in machine learning and AI, without needing to upgrade their existing equipment. It also means we’re always in tune with the key challenges facing the sector and the frustrations plant managers have.”
What is your vision for IntelliAM’s future?
“Our vision is to be a leader in providing tailored machine learning solutions that empower manufacturers to achieve operational excellence and maximum productivity.
We already work with many of the world’s biggest manufacturers, including half of the world’s top 10 food and drinks producers, and we want to work with the other half – helping to boost productivity across the whole of the industry.
We aim to refine our predictive maintenance and operational efficiency tools to make them even more accessible and effective for all clients – helping manufacturers improve productivity, reduce costs, and meet sustainability goals, through using intelligent software solutions.”
For more information, visit IntelliAM’swebsite.