In part four of our Co-Creating the Future series, we investigate how manufacturers can take operational performance to new levels with intelligent prediction
In part three of our Co-Creating the Future series with GE Digital, we explored the potential of intelligent data analysis in optimising both machines and workflows. But digitalisation in industrial applications isn’t just benefiting performance now. Perhaps more importantly, it has the power to predict performance in the future.
Maintenance is a key strategic concern when developing and manufacturing products. But according to research cited by Deloitte, poor maintenance strategies can reduce a plant’s overall productive capacity between 5-20%, while unplanned downtime costs industrial manufacturers an estimated $50 billion a year. In the food and beverage industry, the cost of machine failure can be extremely high when it comes to compromised food safety.
Food and beverage manufacturers not only need to meet production demands and avoid unplanned downtime – they must also adhere to strict food and drink quality standards to ensure their products are 100% safe for consumers. This means making sure that every machine is in perfect working condition as a failure to do so could result in expensive product recalls with potential brand-damaging consequences.
SIG’s new partner, GE Digital, has been providing software solutions to manufacturers for over 20 years. Their software helps predict failures before they happen and optimise the way field service technicians are dispatched to resolve issues. Put simply, their predictive-based digital solution means manufacturers can operate machines for longer, boost productivity, lower costs, increase competitiveness and, crucially, ensure continual food safety.
Making the most of assets
With SIG and GE Digital, manufacturers can move from inefficient preventative maintenance to intelligent predictive maintenance. This means continually analysing behaviour data from connected equipment to determine actionable insights that predict when a part will fail –increasing uptime and improving asset efficiency. And, for GE Digital, predicting asset performance is also about determining which assets are the most critical to the overall health of operations.
“Manufacturers will sometimes have a clear idea of the most critical assets in their factories – it could be the most expensive to maintain, or it could be the one that creates the highest impact bottlenecks if it goes down,” says Jeff Erhardt, VP of Intelligent Systems at GE Digital.
“But sometimes, the most critical assets aren’t so clear. And in that case, we can work with manufacturers to help them either workshop their priority critical assets or experiment through proof of concept activities.”
GE Digital does this via its Predix Asset Performance Management application, enabling manufacturers to determine an asset’s health, accurately predict its performance and take decisive actions before problems occur. It connects disparate data sources and uses advanced analytics to turn data into insights while fostering collaboration and knowledge-management across the organisation.
Ultimately, this means manufacturers can transform their plants, turning insights into action with intelligent systems that seamlessly communicate and activate workflows between all operating layers.
To find out how to execute this digital transformation, check out part five of the Co-Creating the Future series. We’ll outline the digital roadmap for manufacturers, highlighting how, when and where to get started.