1. Streamlining Plant Maintenance
Leaders were already acutely aware of the need to avoid downtime — particularly unplanned downtime — with the latest estimates suggesting just 3.65 days of unplanned downtime a year (the equivalent of a 1% downtime rate) costs Energy businesses more than five million dollars. Given the current industry climate, there’s never been such an urgent need to improve this metric.
But improving your plant maintenance processes — let alone making the leap to predictive maintenance — is complex. Far from existing in a vacuum, plant maintenance sits across all three upstream, midstream and downstream segments, and cuts across multiple teams and departments — Work Order Management, Inventory and Materials Management, Procurement, AP — all of which tend to operate in their own siloes. For this reason, a limited BI, BPM or RPA tool that simply churns out more process data, or runs automations without actually streamlining your plant maintenance processes, isn’t going to make much of an impact.
This is why Process Intelligence is such a force multiplier: Unlike a standard BPM tool, Celonis not only mines your processes across your operation to give you holistic, real-time insights into performance, but also gives you the power to reimagine them with generative-AI-assisted process modeling, coupled with institutional knowledge on how your business operates. It then orchestrates continuous process improvements on your behalf – maximizing performance round the clock.
This means you can rapidly answer key questions — such as how your maintenance operations are affecting production uptime, how delays in material procurement and logistics are affecting their plant-maintenance schedules, and what the root causes of maintenance delays really are — and take immediate, data-driven actions.
For example: suppose you want to get to the bottom of why your scheduled adherence rate is low. A Process Intelligence platform will pull data from a wide range of source systems (Maximo, SAP, and beyond) to dive deep into all the variables that affect your rate, including mapping out the real-time flows between initial notifications, work orders, material reservations and purchase orders, revealing everything that happens along the way and flagging issues — plus next-best-action recommendations — automatically.
In the case of our example, suppose it reveals that one of the top inefficiencies bringing down your adherence rate is material delays. This is a valuable insight alone, but a Process Intelligence platform can dive much deeper into process analytics, revealing that your cooling towers and heat exchangers have the most work orders attached to them by far. In tandem, it can reveal process-related causes of delays, such as when your supplier was actually to blame due to delaying deliveries after you procured materials. Or when Procurement took too long to create a purchase requisition, and so on.
Armed with this level of insight, at scale, plus AI-enabled action recommendations, a Process Intelligence platform gives you all the tools you need to streamline your plant-maintenance processes, control plant maintenance continuously through process automation, and generate lasting, measurable value.
To learn more about how you can improve process performance in plant maintenance, watch Chevron’s Process Intelligence story, in conversation with Celonis.