Introduction to Spare Parts

Effective spare parts programs can help an organization save money by avoiding unplanned downtime and preventing an obsolete or overstocked inventory. On the other hand, poorly managed Maintenance, Repair, and Operations (MRO) can be a primary contributor to poor availability and a huge drain on an organization’s finances.

Let’s take a look at what spare parts is, why it’s important, what its limitations are, and what the future of spare parts warehousing looks like.

What Is a Spare Parts Program?

A spare parts program stocks and maintains an inventory of critical parts, materials, consumables, and tools required to keep a manufacturing or processing facility operational. A clear spare parts stocking strategy is required to make sure you are not over stocking spares (and wasting money) or understocking spares and risk delayed repair times for critical assets.

Spare parts are often referred to as Maintenance, Repair and Operations (MRO) because it not only involves the maintenance and repair of production assets but also includes inventory management of tools and consumables needed to run the process.

Spare parts programs have two parts. The first focuses on the inventory of spare parts. Often referred to as “right-sizing,” it aims to determine what parts need to be kept in inventory, how many of each of the parts, and min/max/reorder points. It also considers such things as vendor stocking strategies (whether to have a vendor house spare parts at their facility rather than at the plant) and kitting of parts needed to perform certain tasks. The second part involves the preservation of the parts stored in the warehouse. These activities are designed to preserve the parts in as new condition as possible by mitigating any damage that can occur if stored improperly.

Challenges with Spare Parts Warehousing

Many facilities are challenged with striking the proper balance of spare parts to be held in inventory. On one hand, downtime can be significantly reduced if all spares needed for a repair are immediately available. However, this practice is costly. On the other hand, if spares are not readily available, the wait time can cause production loss and may even jeopardize your facility’s regulatory compliance.

Challenges associated with spare parts warehousing generally include:

Reliance on Vendor Recommendations

Vendors are not stakeholders in the running of your facility and will oftentimes provide a list of spare part recommendations (RSPL) based solely on the equipment package they sold you, without taking into consideration the number of similar assets, the interchangeability of similar parts between other assets or the criticality of the assets. This practice often results in overstocking, which runs the risk of high carrying costs, loss of function costs, and potential obsolescence.

Demand for a Part

At the center of spares planning is determining the demand of parts to set inventory levels. The issue with this method is that most organizations do not have a good idea of part demand, which makes it difficult to plan an optimal spare parts stocking strategy.

Improper Storage

Many organizations do not store or preserve their equipment correctly, which can cause loss of function. An overstock situation can put greater burden on any preservation activities which could result in premature failure of the part causing additional downtime and rework.

What Does the Future of Spare Parts Look Like?

Major advancements in data acquisition, warehousing, modeling, and analytics, are now creating the opportunity to take the next leap in reliability analysis—and these capabilities can now be applied to optimizing spare parts. This leap is being made possible through Quantitative Reliability Optimization (QRO).

QRO’s data-driven approach to reliability modeling connects every relevant reliability data point at a complex facility to one integrated model, allowing for near real time complex decision making that will directly improve spare parts management by allowing users to:

  • More accurately determine the demand requirements for parts. Instead of relying on demand rates that are often determined from historical failure data or projected potential work, QRO’s data-driven approach uses the condition data of the asset to calculate its probability of failure. In turn, the demand rate for parts can then be quantifiably calculated and reevaluated as conditions of the asset change.
  • Evaluate and update min/max levels, safety stock levels, and reorder points based on the needs of the assets rather than a stagnant system based on historical events or recommendations. This ability will eliminate excess inventory carrying costs while ensuring sufficient stocking levels at the right time.
  • Determine which parts to stock through statistical analysis rather than a vendor recommended spare parts list.
  • Tie spare parts usage to the failure modes and mechanisms to further advance your reliability analytics.

 

Learn more about Quantitative Reliability Optimization (QRO).

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