Abstract

Predictive Maintenance (PdM) assesses the equipment's health through diagnostics testings and / or on line monitoring. The machine's condition may be inspected and monitored using continuous or intermittent parameter measurement intervals. PdM techniques can detect trend changes in running conditions that could lead to catastrophic failures. They are used to identify or predict the early indication of failures, which in turn can provide greater lead-time for developing suitable action plans prior to the failure, resulting in reduced unscheduled down time and prevent any possible catastrophic failures.

There are many known technologies for PdM. The types of Techniques that have been implemented at Sumatra Light North Operations (SLN) - Indonesia are:

  • Vibration Analysis;

  • Thermography Inspection;

  • Reciprocating Tools Analysis;

  • Lubricant Analysis;

  • Ultra-Sonic Flow Rate Testing.

This paper will share five case studies of PdM in SLN operations. By implementing PdM technologies as demonstrated by these examples, the opportunity of having the risk of catastrophic failure will be minimized. This can be achieved by taking actions in advanced based on the information of equipment conditions discovered through data collection and analysis.

Introduction

The function of maintenance is to sustain the integrity of physical assets of the company over their planned life by repairing, modifying or replacing them as necessary within the agreed budget for supporting the attainment of the company goals that are to optimize the oil and gas productions. In doing so the life cycle costs (LCC) and its influencing factors should be the basis for decision making in putting any maintenance strategy in place. Those LCC factors include acquisition costs, running (operation, maintenance and energy) costs, and abandonment costs. Focusing on maintenance costs themselves, it involves cost factors such as: labor, materials, spare part ordering and holding costs, tools and equipment, engineering support costs, contractors and other overhead costs. With the above factors, several maintenance strategies can be selected based on the production targets, asset criticality assessment, risk based, or others that can be different from company to company depending on company goal.

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