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In a recent post, I examined how AI-powered manufacturing solutions enable manufacturers to aggregate data from multiple sources and apply AI for better outcomes. Now, it’s time to talk about how. Below, I have some recommendations on how to begin your AI-powered manufacturing journey.
Start small, start anywhere, start now
Some manufacturers are put off by the prospect of a complete overhaul of their processes. But you don’t have to dive headfirst into AI. The key here is to start small. Start anywhere. Start with outcomes. But whatever you do, start now. Even a small change can beget excellent results and, even more importantly, allow your organization to tip its toe in the water and learn.
If you’re not sure where to begin, we have some suggestions to help. While the starting point will vary from customer to customer, there are three main entry points you could consider:
- Enterprise asset management (EAM)
- Asset optimisation
- Operations optimisation
If you are completely new to AI-powered manufacturing, you might want to start with an enterprise asset management solution like IBM Maximo. Maximo helps you understand and manage your physical assets on a single platform. This means you can check asset health in real time, enable predictive maintenance, and streamline global operations from procurement to contract management.
If you already have an enterprise asset management solution, you might want to start thinking about predictive maintenance and asset performance optimization. Solutions like Maximo Asset Health Insights (MAHI) can help here, ensuring your assets are performing well, and that equipment issues are dealt with before they lead to breakages.
For those whose asset optimization is already underway, the next step is to start looking at how to improve your processes and operations as a whole. By looking at your data and infrastructure, we can identify suitable next steps based on your company’s unique set-up and challenges.
Wherever you are in your AI journey, we have solutions to help you take the next step. Let’s take a look at the IBM Watson IoT portfolio.
The IBM Watson IoT portfolio – leveraging the power of AI with IoT
IBM Watson IoT offers two broad advantages to manufacturers. In the first instance, it is uniquely placed to help companies get the most from their data. In the second, it enables cognitive and self-learning models.
Let’s discuss data first. The reason we need AI-powered solutions is that collecting data is not enough. Data sitting neglected in a ‘data lake’ – or data swamp, as I prefer to think of it – achieves very little. We need to understand it and integrate it. And for that, we need semantic modelling and ontologies that allow us to integrate the data into a holistic picture. This is what our IoT solutions can offer.
Second, there’s cognition, and again, this is where Watson comes into play. Gone are the days of calibrating models over and over again. Instead, we use machine learning and artificial intelligence to continuously improve them. They become self-learning, drawing on new data and interactions to get better over time.
With an Enterprise Asset Management market share of 18%+, we have significant experience and expertise to offer. This means we’re in a good position to take advantage of the advent of machine learning and artificial intelligence. Because of this, companies are increasingly approaching us to help them make better decisions in their factories in real-time, to achieve no unplanned downtime through better predictive maintenance, and to optimize not only their assets, but also their system-wide operations.
Ready for the next step? Talk to us
If you’re not sure where to start, or would like to talk to us about how to progress your journey, we would love to hear from you. You can email an expert with specific queries, or for more general information, take a look at our Manufacturing solutions.