Revamps 2024 Issue

Improving preventive maintenance using equipment criticality

Case study demonstrates the importance of rating equipment criticality in an effective preventive maintenance plan while reducing overall cost

E. Charles Maier Becht

M aintenance has changed over time. It started as a reac- tive need to fix equipment when it broke. As equip - ment became more complex, repairs became more expensive. This drove the idea of ‘PM’ or maintenance that would enable equipment to last longer or fail less frequently. Preventive maintenance (PM) programmes expanded and the cost of the programmes grew as the focus was on improving their effectiveness. The focus on PM is now on maintaining its effectiveness while reducing the overall cost. Refinery maintenance is a complex process with many elements that interact with each other. For example, equip - ment reliability has a direct impact on maintenance cost. If equipment runs longer between failures, the total repair cost goes down. The run length can be a result of design, repair quality, and how the equipment is operated. Repair costs are impacted by the quality of repair plans, competence of the crafts executing the repair, and material availability. When analysing the elements that impact maintenance value, we can group them into three main categories: demand, which are the elements that result in the need for maintenance; efficiency, which are the elements that affect the efficiency of maintenance process; and support, which are the elements that support maintenance. Figure 1 shows the categories and examples of elements within each category. From benchmarking within the petrochemical industry, the contributions of the various drivers to maintenance value (measured by total cost) are: The demand driver has the largest contribution to main - tenance value. It is composed of elements that result in the need for maintenance. The quality of the PM programme is a key enabler for equipment reliability, which is a key ele - ment within the demand driver. The size of the programme has a direct correlation with maintenance value, and opti - mising it can greatly impact the demand driver. This is done through PM optimisation (PMO). PMO optimisation tools • Demand – approximately 60% • Support – approximately 20-30% • Efficiency – approximately 10-20%.

DEMAND

Items that result in the need for maintenance Examples include: Equipment reliability Operating limits Start - up procedures PM programme Maintenance strategy

EFFICIENCY

Items that aect the eciency of the maintenance process Examples include:

Planning/scheduling Productivity/tool time

Items that support maintenance Examples include:

Contractor labour Critical spares Organisational structure Warehouse

SUPPORT

Figure 1 Venn diagram explaining drivers of maintenance value

• Failure Reporting, Analysis and Corrective Action System (FRACAS). FMEA evaluates equipment at the component level, identi - fying failure modes for each component. The consequences of failure are quantified along with the probability of failure. Scenarios are considered for financial, health, safety, and envi - ronmental consequences. Mitigation strategies are developed to reduce risk to acceptable levels for each scenario. The miti - gation strategies are typically a combination of PM, predictive maintenance, and spare parts stocking strategies. A PM Library is a collection of PM by equipment type. It contains company or industry recommendations for PM. For a given piece of equipment, the recommended PM activity is adapted to local conditions (for example, climate or process) and implemented as the PM activity for that equipment. FRACAS was developed by the US Department of Defense and published in DOD MIL-STD-2155. It contains a three-step methodology. In step 1, the failure is reported, and initial data is gathered. In step 2, the failure is analysed

There are three main tools utilised for PMO: • Failure Mode and Effects Analysis (FMEA) • PM Library

Revamps 2024