Return on investment is the goal of any effort aimed at improving profitability. With the ‘Fit for the Future’ series so far, we’ve detailed the steps to take in achieving a digital transformation in manufacturing and with the topic of this article we’ll begin to explore the profitable outcomes available to a modern, competitive operation; specifically predictive maintenance.
Once you’ve made sure all your systems are up to date, the right support contracts are in place, your systems are secure and you’ve gained visibility of real time information alongside appropriate data collection, the foundations are in place to begin to capitalise on your data. One method of achieving this is through Predictive Maintenance, which is an automated analytical process through which a system provides detailed feedback on the condition of your equipment.
One of the best ways to derive value from your data is to increase the uptime of assets. Predictive Maintenance is a regimen for moving to condition-based maintenance, rather than reacting to breakdowns or taking equipment offline on a routine basis following manufacturer recommendations. Instead, Predictive Maintenance enables a maximisation of your assets through analysing sensor data to provide an intelligent profile of the condition of your equipment. Changing parts too early means a loss of value, while breakdowns cause costly downtime which can impact many other areas of your business.
On average, most manufacturers experience 25 instances of unplanned downtime per month totalling 27 hours of stoppage. Considering the average cost for an hour of downtime, roughly £300,000 for large manufacturing firms, the impact is considerable*. So exactly how does Predictive Maintenance mitigate these issues?
At its core, the technology is powered by machine learning. Finding correlations between sensor data and expected outcomes, the system can discover and highlight key insights which may even be difficult for a human operator to discover. These surprising insights come from your diverse data sources, enabling a real-time view of the condition of vital equipment and intelligent planning for optimal maintenance routines.
As the system learns the intricacies of your equipment, earlier warnings and increasingly rich condition analysis becomes available. The artificial intelligence behind a Predictive Maintenance system continues improve its understanding of your operation and as such provides an increasing ROI over time.
So, exactly how does this result in a return on investment? By introducing smart maintenance, several benefits are readily apparent. Firstly, increasing uptime means a mitigation of unplanned downtime, allowing for a more consistent operation with increased capacity and efficiency. Secondly, smart maintenance routines provide the confidence to hold fewer spares, reducing associated required spending. The system allows for ‘just in time’ ordering, meaning you won’t need to retain large inventories for maintenance purposes in the case of the unexpected.
Predictive Maintenance also reduces undue operator workload and supports agile decision making with clear, concise information and action points to rapidly resolve issues. Additionally, the technology mitigates equipment-related quality issues by informing your operators when expected behaviour is outside of tolerance.
With all your efforts so far in digital transformation, Predictive Maintenance is an overwhelmingly strong proposition for achieving a return on your investments to date.