4 minute read • published in partnership with Cimlogic
Opinion: Connecting manufacturers with artificial intelligence
Increasingly manufacturers are asking the question “What can Artificial Intelligence do for me and my business?” Frustratingly, the answer for a long time has been along the lines of “Anything you want, just tell me what you want it to do” or “Just use our platform and you can do anything you want”. While that’s all great, it’s nice to know that the technology exists, but it still doesn’t answer the question: what can it actually do? Steve Wilkinson, chief technical officer at Cimlogic looks at what AI can do but also the business benefit it can bring.
There is a gap, a chasm in fact, that exists between leading-edge technology and actual business benefits, and bridging that gap can seem like an impossible task.
In our experience, more often than not, manufacturers and their suppliers are trying to cross that void, and failing. And when you fall to the bottom of a scary pit, it is hard to climb back out and take the leap again. But not only are people not making it across – they are not even jumping from the correct side!
Do not lead with technology
A fundamental rule of AI – don’t start with the technology. If you are doing a project just to find out how some technology can help your business (for example: “What can AI do for me?”), you are setting yourself up to fail. Yes, you might keep a few tech-savvy engineers entertained for a few months and may even create a pretty fancy pilot project. (“Look, we have demonstrated how the relationship between temperature and viscosity affects our packaging process”). But it won’t be long before someone asks, “So what? How will this improve my productivity, or quality, or reduce my overheads?” “Well, ermmm, it won’t, but look at our pretty charts!”
In our experience, this is why a huge number of technology-led projects fail to get past a pilot stage. They are a solution looking for a problem. A hammer searching for a nail. A nail in a haystack (you get the idea).
Start with the problem
Think about a true business problem that you have – perhaps you have a capacity issue and your lab is a bottleneck, perhaps you don’t even know where your bottleneck is (don’t worry, lots of people don’t). Maybe, you have an issue with quality resulting in poor yield or high levels of waste and rework. Or perhaps unplanned maintenance is throttling your productivity. These are real problems. Problems looking for solutions. And once you know the one you want to solve, you can then (and only then!) ask, “How can technology help?”
At Cimlogic we follow our RAISE™ process to ensure we are searching for the right business problems, before we even think about what technology could solve them.
Once we have identified and analysed the business challenges, and have prioritised the pressing problem and the business value that solving it could bring, we start to look at how. Obviously, we have a technology bias in our solutions, but we always appreciate that these puzzles will also be solved by understanding people and process.
It’s at this point we can draw on our 20+ years of experience solving of real manufacturing problems using technology, data and analytics. We have a wide set of skills and tools at our disposal from operational technology through MES and operational excellence and our most recent addition: predictive manufacturing.
Predictive manufacturing is Cimlogic’s phrase for solving business problems though the use of artificial intelligence and machine learning. “So that’s all great – but, what can AI do for me and my business?”
As I said – this isn’t the question you should be asking, but we have to break the chicken and egg cycle somehow. Thankfully, from our client discussions during our RAISE™ process, we have identified some common areas where manufacturers are seeing the benefits of predictive manufacturing and seeing real business benefits such as:
• Top line growth
• Cost reduction
• Regulatory compliance
• Productivity uplift
• Investment and asset optimisation
• New product introduction
These fall into the following 6 categories:
• Predictive operations & Process Optimisation
Predictive inventory and demand
• WIP Optimisation
• Predictive Replenishment
• Virtual assistant
• Decision support
• Yield Prediction & Optimisation
• Weight Control
• Predictive Quality
• Predict Equipment failure
• Recommend when Maintenance is required
• Utility Optimisation
So, in answer to the question, “What can artificial intelligence do for me and my business?“, there are huge opportunities for AI in manufacturing, but you need to ask a different question! What problem are you trying to solve? Cimlogic has the manufacturing industry experience and the technical expertise to guide you to the best solutions for your business.