You’ve likely been there before and it’s never good – a critical machine fails unexpectedly and production is shut down. Your team works around the clock to get it back online to minimize the impact. The costs – from emergency repairs, to lost productivity, and ultimately lost product – are significant.
Maintenance Strategy – To address the issue, you’ve invested in various maintenance plans throughout the years from run to failure, to proactive maintenance, preventative maintenance, and more. You may still come across situations where an experienced operator walks onto the site and knows almost immediately that something isn’t right. They hear things or smell things or have a gut instinct that production isn’t happening the way it’s supposed to. But, when that operator goes home at night – or worse, retires – you lose all of that knowledge. How can a junior operator be equipped with the same knowledge that an asset is about to fail and needs maintenance?
The impact of data – Today, sensors and instrumentation create data that is now fed into systems that can continuously monitor assets. Rapid advances in technology mean that maintenance managers no longer need to look in the rear view mirror using lagging indicators to drive maintenance schedules. Data can be harnessed to identify conditions that compromise assets (or quality or production) so that issues are predicted, and proactive steps taken.
How to get started – Today, the cost and complexity of managing machines reliably and consistently with emerging analytics technologies, like machine learning, has been significantly reduced. You can use cost-effective solutions quickly and even make the case to senior management that they can be funded with a reallocation of the cost savings that will be achieved by avoiding downtime or extending the life of assets. But,
How do you know machine learning systems will work in your plant and for your team?
Do you have the data required?
Will the alerts provided enable the right employee to take the right action at the right time?
Will your team trust the data or will they continue doing their job in ways that worked in the past?
To answer these questions and achieve meaningful results, the right approach is to start small, think big, and go fast.
Begin with a few assets on one line at one site – no risky capital investment required.
- Get your maintenance and reliability engineers involved early.
- Learn from the first dashboards and alerts created and improve on them often and quickly.
- Get buy-in from senior management to move forward based on the cost savings you can prove with your small project.
- Expand to more assets, more lines, and more sites.
- Follow a lean approach to maintenance strategy to ensure success at each stage.
At Mariner, we have worked manufacturers – large and small – to monitor assets to reduce unplanned downtime, improve quality, and optimize maintenance. We created Spyglass Connected Factory to get you started and seeing improvements in less than 4 weeks. Learn More.