Declan Egan - Automation Design

“When it comes to automation, we try to minimise as much as possible what we call ‘drift’ which is the tiny incremental degradation of performance levels. We monitor that over the course of time, weeks or months, then correct the automation systems to stop that factoring into efficiency levels.”

If there’s one thing that connects companies that have had bad experiences with automation in manufacturing in the past, it’s not doing enough due diligence.

That’s the experience of Declan Egan, senior automation design engineer with DMI and someone who is in a good position to comment. Egan has 40 years’ experience under his belt working in manufacturing, both as an employee and as his own boss.

And time after time when he’s seen situations with companies where things haven’t turned out as planned, or have cost more than was expected, the reason ends up being highly predictable.

“It’s lack of preparation. Usually it dates back to when a company first started out with automation and didn’t lay the ground work properly for what they wanted to do, with the result that they end up paying a price for it later. This is how they end up with automation systems that aren’t fit for purpose,” he said.

“There are flaws in the equipment they buy, the system doesn’t deliver the output it was supposed to and the machines they’ve used weren’t spec’ed correctly from the outset. The reason is that they engaged too quickly with an automation company to build the machinery and didn’t do the right amount of risk assessments and due diligence. It’s a common story. And there are multiple reasons why it happens.”

Sometimes, Egan said, companies looking to automate production facilities don’t know exactly how to ask for what they need. They’re in a rush and under financial pressure to get a system up and running as quickly as possible.

Companies fall into the trap of identifying a problem, deciding automation is the solution but then rushing to execute because they’re under pressure. The missing piece of the process, according to Egan, is undertaking a de-risking exercise to make sure they have a deep understanding of what they are hoping to achieve.

“Say an automation company quotes you €5 million to build a machine and you create a purchase order, put down a 60 per cent deposit, or whatever it is, and head off on the journey. But it’s up to the customer to know what they’re asking for so that as delivery approaches, things stay on track.”

“For example, when they get to the point that the project is 80 per cent finished, it’s not uncommon to find that someone tells them it’s actually going to cost another €1.3 million to make the deadline. So they end up in a heated discussion and maybe there’s an argument but they’re against a wall and have no choice but to spend the cash. They’ll have a bad taste in their mouth but they’re caught.”

“Our job is to make sure that can’t happen.”

Egan started his career as an apprentice tool maker with the German company Krups in 1982, and was well positioned to see computer numerical control (CNC) systems revolutionise manufacturing. He moved on to working automation in the mid 1990s, research and development in the late 1990s and early 2000s, and eventually set up his own engineering company that specialised in high volume high precision automation.

Today with DMI, Egan applies all that experience to helping customers understand where they are on the automation journey, and where they could get to with the right assistance. Together with a team of automation engineers, he ensures that the companies that work with DMI know exactly what questions to ask to make sure the automation work they undertake is fit for purpose and future proof.

“It’s about taking advantage of our resources, our pool of data scientists, digital twin technology and practical real world experience, bringing them all together to de-risk spend on automation. Knowing how to spec a project properly is the greatest protection against the nasty surprise of over spend and delays,” said Egan.

“It’s also a protection against having an automation company pitching low to win the business and then landing you with a bill you can’t reverse out of.”

Egan has seen many trends and innovations reinvent the automation sector in manufacturing, with a career that started in the early 1980s and is still going. He describes himself as excited and optimistic about all the developments to come.

“We like to say anything is possible, and even when something seems impossible to achieve, that really just means it might take a little bit longer. But it’s about expertise, resourcefulness, adaptability and you only have to look at the way AI and machine learning are impacting almost everything to be excited to see what’s next?” he said.

“When it comes to automation, we try to minimise as much as possible what we call ‘drift’ which is the tiny incremental degradation of performance levels. We monitor that over the course of time, weeks or months, then correct the automation systems to stop that factoring into efficiency levels.”

“But with machine learning and AI we’re increasingly going to see self-correction become more prevalent, and not just that but machines that don’t even need to be told to watch out for it. They’ll have enough intelligence built in to understand how to watch out for any kind of problem, not just drift. That’s amazing.”