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If you are one of those, who either have a big vision of maintenance transformation or are working on optimizing one part of the maintenance management process, here is a suggestion on how to optimize to meet ambitious OPEX reduction goals while building sustainable and integrated Maintenance management processes.
My name is Aleksandra, and I am a maintenance domain expert in Cognite. Together with my colleagues, we have a mission to empower the maintenance ecosystem with the data and technology so maintenance professionals can efficiently optimize and transform their underlying and fundamental maintenance management processes.
Here are some tips on building with the end in mind and avoiding optimization in silos.
Optimize using data from multiple systems
Many companies these days are busy with the optimization of their maintenance strategy for equipment and moving it from calendar to condition-based maintenance (CBM), where possible.
One way of doing it is to use a centralized condition monitoring system to monitor equipment's failure modes (FM) with high risks to HSE, production, or cost. To do that, one needs data from multiple sources to understand and visualize the condition of critical equipment, have all the risks updated, and have all other necessary data from the surrounding context available. When done correctly, this would significantly increase the confidence in predicted failures and help the Subject Matter Expert (SME) to use such systems to make and prioritize maintenance decisions.
Unfortunately, the data needed to state the condition and risk with high confidence is often locked in dispersed systems. Without the right technology, any integration effort starts and ends with manual data liberation and extensive data preparation work, delaying professionals from solving complex use cases and optimization at last.
Condition Monitoring and similar applications that require extended context ought to be built on top of a data platform that provides all data already and makes it valuable for any end-user or application. This not only removes some of the frustrations, saves precious time for SMEs but ultimately increases confidence in the output from CM systems, making it more useful.
Later in this post, you can see how such a centralized condition monitoring module built on top of Cognite Data Fusion may look like as part of the E2E Maintenance solution.
Also, read more on how Cognite Data Fusion helps you to effectivize your end-to-end (E2E) Maintenance optimization and integration efforts here.
Integrate across E2E Maintenance
The Maintenance Management process is like a relay race, consisting of individual parts that, for optimal results and a trusted process, must exchange data to ultimately maintain equipment function (see Figure 1 Management of maintenance work process).
Figure 1: Management of maintenance work process, ref. NORSOK Z-008
In reality, most of these processes are disconnected today, which may cause they will also not to exchange value from individual optimization efforts.
Let's continue with an example of a centralized condition monitoring system built on top of the industrial DataOps platform. In this almost perfect scenario, the system can detect anomalies potentially leading to a critical event in x time and recommend, e.g., high-priority maintenance activity. Although it may sound perfect, it can also go wrong. If the recommendation is only displayed in the CM system and not integrated in real-time with CMMS, the event may be locked and lost in the silo. Moving from a calendar to a condition-based maintenance strategy (CBM) requires this integration, especially for equipment for which functional failures may have critical consequences to either HSE, production, or cost. NB: Accidents like that are already known in the industry.
The perfect scenario requires the integration to be a min semi-automated process, where notifications based on failure events from the CM system, robot, or person are tightly integrated with the CMMS and handed over for further handling and maintenance plan optimization.
While it is easy to focus on, e.g., improving algorithms for predictive maintenance, one still has to think outside of this process and address the exchange of data with downstream and upstream systems across the entire process. This will ensure that every step of the E2E Maintenance process can take advantage of any optimization efforts and, most importantly, create trust and ensure safety for critical operations.
Summary
Every step in Maintenance Management needs optimization, but to achieve cost-efficient, sustainable and long-term results, professionals must think outside of the silo and use all innovative technologies to build with the end in mind - an optimal and well-integrated E2E maintenance management process.
Figure 2 and the video below show how the integrated solution for E2E Maintenance can look in Cognite and deployed on top of Cognite Data Fusion.
Figure 2: Cognite solution for integrated E2E maintenance optimization
Video showing the demo of E2E Maintenance solution
I would also love to hear your story about integrating data and processes for maintenance purposes. What has been your biggest challenge, and how have you overcome it?
Stay tuned, next: How your data platform could support integration and optimization within the E2E Maintenance process.
