It’s easy to imagine futuristic applications for AI in the factory. Unfortunately, many of those applications will not bring you significant ROI.
To make the most of this advanced technology, use it to support your maintenance, repair, and operations (MRO) teams' day-to-day tasks. This will bring small gains that add up to increase your factory's efficiency, reduce your capital expenditure, sharpen your competitive edge, and bring tangible ROI.
In this blog, we’ll look at one way AI can support your MRO team: optimizing spare parts spend.
We’ll dig into:
In general terms, spend is the total expenses an organization pays to run its business. This includes capital expenditures (CapEx), which refers to long-term expenses for acquiring or building new assets like buildings, equipment, and machinery. It also includes operational expenditures (OpEx), covering the business's daily expenses, such as payroll, utility, and MRO.
Within MRO, spending is divided between two primary areas: spare parts inventory and maintenance and repair processes.
MRO spend is particularly difficult to control, never mind optimize, due to a number of inventory challenges.
The first is a serious lack of spare parts data. As we covered in our blog post on how AI will improve spare parts data quality, MRO professionals don’t currently have access to correct, complete, and comprehensive data on their spare parts inventory. This makes it virtually impossible to know what spare parts they have on hand, limiting their ability to manage that inventory effectively.
To fill this data gap, many MRO professionals overstock spare parts “just in case,” resulting in significant, often unnecessary procurement costs. This also drives the need for extra spending to expand and maintain a larger factory storage footprint, increasing both CapEx and OpEx.
Moreover, this overstocking leads to nearly 50% of spare parts going to waste. Many are purchased as a precaution and never actually used. Once the machine is replaced and the parts become obsolete, they are discarded.
And that’s money that could have been used more effectively elsewhere in the organization.
Managing MRO spending is challenging because today’s procurement professionals cannot source spare parts at a fair price. This is due to two reasons.
The first reason is that parts vary widely, meaning that the spare parts required to repair one machine may differ substantially from those needed to repair another machine. As such, MRO professionals must procure many parts to keep a factory running smoothly.
The second reason is that several suppliers of these parts exist, and there is little transparency regarding which suppliers offer which parts.
These two problems add up to a situation in which MRO professionals need to buy a wide variety of parts but lack the data to help them determine where to buy what.
Martin Weber, SPARETECH CEO, says line builders use this uncertainty to make a profit:
“If you build a large factory, you work with line builders, and these builders will sell spare parts as their business. This is a well-known phenomenon: they generate little revenue from selling the machine, but they can sell spare parts at a significant profit margin. They purchase a standard part, apply a new label to it, and sell it for three times the original price.”
Simply put, when procurement teams are forced to buy parts at a higher price than the supplier offers, procurement spending increases significantly, which takes dollars away from the bottom line.
AI can help factories solve the inventory and procurement challenges outlined above.
As we showed in our blog on how AI will improve spare parts data quality, AI can help MRO professionals improve their spare parts data and ensure that there is a record for every spare part in the factory’s inventory. Once that data is clean, complete, and correct, MRO can effectively min/max their spare parts. This enables them to optimize their inventory levels so that each part has no more than necessary.
An optimized inventory also optimizes spend. It limits overstock and waste and enables factories to keep a smaller footprint, ensuring that every dollar the company spends goes where it’s most useful.
AI can also help factories improve spare parts transparency in the supply chain by compiling verified spare parts databases, complete with OEM information, so customers know where to buy which part and at which price.
"Today, spare parts are procured through many different channels, whether through automatic reordering, catalogs or free-text orders from distributors, line builders, or the original equipment manufacturer. AI can help streamline procurement channels and thereby reduce costs."
explains Felix Benak, Account Executive at SPARETECH.
With this information, they can make better choices about when and where to buy their parts and optimize their spending even further. As Weber explains,
“AI will be very helpful to the human who needs to decide, do I buy one part? Two? Ten? It’s a huge decision for the company, putting much pressure on the person making the final call. AI can help.
With the right data, MRO teams can decide to wait two weeks longer, buy a part from Europe instead of the US, or bundle all their parts from one supplier depending on what suits their priorities best.”
As they feed the AI models more data over time, factories can even train the AI to offer analysis, insight, and future predictions.
This can help MRO professionals move beyond static min/max optimization and begin performing dynamic inventory optimization, enabling them to make even smarter spending decisions.
“AI enables the company to gather more data,” says Weber. “The more data you have, the more the AI can contribute to decision-making. It can run projections based on your priorities—whether that's price, delivery time, risk profile, or others.”
With this level of AI-driven analysis, Weber explains, MRO professionals can make the most informed spending decisions. The outcome? Optimal spend management, reduced costs, and real savings that directly impact the factory’s bottom line.
As futuristic as this sounds, it’s not the only advanced use of artificial intelligence in MRO. Check out our other blogs to see how you can use AI for: