Utilizing AI to Maximize Equipment Availability at Minimum Operational Cost & Reduce Emission Impacts

Organizations striving for operational excellence must constantly evolve their ability to deliver customer value while increasing the cost-efficiency of their operations. The essence of this endeavor is to boost equipment ROI (Return On Investment) by prolonging its useful life and lengthening intervals between major maintenance overhauls, thereby reducing equipment renewal and operational costs while ensuring availability and integrity. AON's maintenance & reliability department has devised an optimal procedure called RBMO (Risk-Based Maintenance Optimization) to meet these goals. The process starts with a pre-selected list of equipment scheduled for next year's major overhaul according to OEM (Original Equipment Manufacturer) guidelines. Each piece of equipment undergoes four different assessments: AI-predicted performance using the CPAD (Computerized Predictive and Diagnostic) system, condition monitoring techniques (like vibration, oil analysis, thermography, etc…), historical reliability data, and a comparison of energy versus maintenance costs. Should all evaluations yield favorable results, extending the equipment's service life can be done safely. The development of the process began in 2023. The application of the new process commenced in the fourth quarter of 2023, resulting in an assessment of 11 pieces of equipment and deferring the maintenance overhaul (MOH) for 9 items to the following year. This decision was based on risk assessments that led to a savings of $1.9 million per year in maintenance costs and generated an additional $900K annually in production availability. In the first quarter of 2024, further assessments were conducted on 26 pieces of equipment, with 23 equipment MOHs being postponed to the subsequent year, saving another $875K in annual maintenance costs and enhancing production availability by $2.6 million. In total, these actions have saved $2.775 million per year in maintenance expenses.