Centralized Predictive Analytics & Diagnostics Value Creation

The implemented maintenance strategy for rotating equipment in the field was conventional time-based (6months-1year) maintenance. Due to this maintenance philosophy, many equipment's were serviced every 6-12 months including the stand-by equipment. Thus, material, spare parts and man-hours are consumed very frequently. In 2019, company decided to convert the maintenance philosophy from time-based to running-hours based and based on OEMs recommendations, 4000 running-hours was the optimum running-hours before the equipment maintenance. By implementing this technique, the frequency of equipment maintenance was reduced and thus maintenance cost and service cost were reduced as well. Moving towards the deployment of AI technology and digitalization world, a new requirement to deploy predictive maintenance analytics and tools elevated. The Centralized Predictive Analytics & Diagnostic (CPAD) which is a centralized ret time predictive monitoring solution for critical assets. The asset specific real time data from site historian will be replicated a centralized historian to enable continuous monitoring of these assets and failure predictions. The CPAD modules get these data streams and execute performance calculations for each asset based on first principle models and also monitor for the failure predictions through data driven models using APR methods. CPAD will generate fault notifications that will be transmitted to site experts for follow-up. CPAD project will be implemented in multiple phases. The first phase will be a pilot implementation as prove of concept and will include the deployment, commissioning and monitoring of all core applications. Once pilot prove of concept implementation schussed, it will to be followed by further implementation of remaining critical rotating equipment. The deployment of predictive maintenance and analytic diagnostics solutions will add value in different forms. It will support shutdown deferrals and planning for critical equipment, it will help in reducing maintenance cost of material, consumables, spares & man hour. In addition, it will help in the transition from preventive maintenance to proactive/predictive maintenance. Furthermore, the predication ability will help in early prediction and identification of potential failures and gives advisory recommendations to support rectifications of failures before the actual failure occur. The pilot implementation started in 2020 with the deployment of 54 critical rotating equipment. The cases reported in phase-1 pilot implementation reported around $3.000.000 savings and proved the CPAD concept. A plan were put in place to capture additional assets in the CPAD system. Additional 108 equipment were deployed in phase-3 implementation of the project.