When critical equipment goes down, so can your whole process. And if spare parts inventory has been poorly managed, you may not have the part you need on hand for timely repair for critical equipment. When you factor in lead time required for restocking, your downtime may result in regulatory violations or expensive workarounds.  Risk-based spare parts management and optimization can prevent a nightmare scenario by basing spare parts stocking around risks and costs.

Spare parts optimization seems fairly simple: you just make sure you have the parts you need available for when critical repairs are required. But how do you decide which parts you need? Which assets to repair vs. replace? Which assets and repairs are critical? For most facility managers, spare parts stocking means relying on manufacturer, vendor, or engineering recommendations. But these sources of spare parts information are not truly stakeholders in the running of the facility. A clear spare parts stocking strategy is required to make sure you are not overstocking spares (and wasting money) or understocking spares and risking delayed repair times for critical assets.

Facilities with reactive Operation and Maintenance (O&M) programs tend to have ineffective spare parts stocking strategies. They may not even know what is currently on the shelf if inventory management has not been performed. Decisions about spare parts stocking may have been made years prior with little documentation or oversight to ensure critical spares remain stocked. Even more daunting, if parts are not cross-referenced, you may have the part on hand, but not in the expected location, causing unnecessary downtime as additional parts are located or purchased. A key step to improving O&M performance is the management of critical spare parts using a risk-based stocking strategy.

Costs of Stocking Spares

There are a variety of costs associated with spare parts stocking:

  • Ordering and vendor associated costs: the paperwork required to establish a credit or payment account, order supplies from a vendor, and reconcile payment.
  • The cost of the spare or replacement part, which can vary with time and technological advances.
  • Cost of carrying inventory, such as cost of warehousing, maintenance cost of spare inventory, potential loss of function (“rotting on the vine”) during storage.
  • Opportunity cost of spending budget on inventory based on speculation of need
  • Costs due to potential obsolescence as technological advances improve asset design.
  • Depreciation costs of holding assets and spares in reserve.
  • And other costs.

Of course, on the other hand, the risk of stockout includes costs as well: the cost of downtime, the potential for backorders and delayed delivery of part deemed unnecessary to have on hand, and the possibility that immediate need might increase cost of delivery. Balancing these costs is essential to developing an efficient and effective spare parts stocking strategy.

Maintenance and Spare Parts

It should be noted that a facility’s spare parts stocking strategy is inextricably linked to a facility’s maintenance strategy. It is maintenance personnel who maintain equipment and use spares. If your maintenance program is reactive, your spare parts stocking is likely to be reactive as well. When planning to improve your spare parts strategy, you should be focusing on improving maintenance strategies as well. Maintenance is essentially the source of spare parts demand

In fact, one of the best methods for establishing a risk-based spare parts strategy is to combine it with a Reliability Centered Maintenance (RCM) program. In RCM terms, maintenance is used to ensure that equipment continues to fulfill its function according to the demands of the system. To determine maintenance tasks, an RCM study will bring together a team of experts familiar with the equipment or assets involved. O&M personnel will use experience and history to develop the key failure modes and downstream effects of failures. The risk of failures identified in the RCM study are used to determine the criticality of assets and processes, and the best ways to reduce the consequences of failures.

Risk-based spare parts management begins with assessing asset criticality and employing a Failure Mode and Effects Analysis (FMEA) to identify likely failure modes and their causes. Spares recommendations will stem from the FMEA as a strategy to mitigate the risks of failures for critical equipment.  It is rare for spare parts management to be deployed as an isolated function of the FMEA. In general, the FMEA is used to identify opportunities to improve O&M workflows, preventive and predictive maintenance programs, design or redesign opportunities, and document management as part of a Reliability Centered Maintenance program initiative. Spare parts management is related to these other program improvements and utilizes the same FMEA to determine the risk of failure and the appropriate mitigating strategy. – e.g. spare parts.

Risk-based Demand Forecasting

Determining which spares are needed requires an understanding of demand models. In general, demand for spare parts is under-appreciated, unpredictable and intermittent. Spare parts may sit on shelves for a long time without demand, but then suddenly and critically be needed. Demand forecasting can help determine which parts or units to keep on hand based on the assumption of need. In a risk-based spare parts program, demand forecasting is managed per a triple bottom line (safety, environment, cost) risk assessment of asset failure. Where the risk of failure exceeds the facility owner’s ability to tolerate that failure, a mitigating strategy should be in place. Mitigating strategies include spare parts stocking recommendations.

In addition, spare parts inventory is cross-referenced and managed across a facility to prevent overstocking of, for example, a common bearing. If there are multiple pumps for which the bearing is critical to repair, an assessment of the risk of failure of more than one pump can be used to assess the quantity of bearings the facility should keep on hand. Rarely will this analysis lead to one-to-one, bearing to pump stocking. While bearings may be relatively inexpensive, this strategy pays off as we move to larger, more expensive redundant spares or spare parts.

Managing Spares Inventory

Once a risk-based spare parts strategy is initiated, it must be maintained. This means that maintenance work processes must be developed to ensure inventory is properly managed and documented. As spares are used in maintenance activities, critical parts should be reordered with sufficient lead time to prevent stockout should additional spares be needed. A periodic review of spare parts and stocking strategies should be undertaken when new assets or processes are added to the system, or on a time basis to determine whether the goals of the facility remain the same.

Risk-based Spares and Capital Costs

A risk-based spare parts program initiated during design and commissioning of a new facility can save facilities enormous capital costs associated with vendor recommended spare parts lists. For example, a client in the oil and gas industry employed PinnacleART to perform a spare parts analysis of a new facility. Vendor recommended spare parts for new equipment came in around $25 million—a hefty price tag. After initial review, PinnacleART reduced costs to $7 million by employing a risk-based spare parts stocking strategy. This saved the client $18 million in capital costs based solely on spare parts stocking according to risk rather than vendor recommendations.

And these savings do not come at the expense of reliability. Rather, the facility maintains only the parts critical to maintaining the function of critical equipment to the process, sustaining the reliability of the process. Additional spares may be better managed by vendors so long as lead time and delivery are within targets for maintaining process functionality. This improves efficiency of maintenance, and teaches maintenance staff to prioritize critical repairs that sustain critical functions, rather than falling back on “fix it when it breaks” reactive models of maintenance.