Turn-round maintenance in the oil and gas industry involves a four yearly total facility shut-down for equipment maintenance and overhaul. However, not all equipment qualifies for turnaround maintenance (TAM). Some maintenance can be carried out on the fly, while others can be carefully scheduled to fit into a specific maintenance cycle such as TAM. Weibull analysis was adopted and applied on live data from two Oil and Gas production platform DP-A to determine that equipment by evaluating their Availability, Unavailability, Reliability and Unreliability with beta β factor being the determinant factor for maintenance modelling. “β < 1” implies that reliability growth is occurring (decreasing failure rate- infant mortality); and “β = 0” implies no growth (constant failure rate-random failures). “β > 1” implies that deterioration is occurring (increasing failure rate-wear out) .Results show Beta factor for platform DP-A equipment as follows; Wing Valve positioner 0.95, Wellhead control panel 0.72, FRAMO pump 0.44, HVAC chiller 0.33, Water injection pump 0.95, HPU Compressor 0.74, Choke actuator 0.80, Heater blower fan 0.37. The model present can be used to predict and schedule m
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