How can a factory use artificial intelligence (AI) to boost its competitive edge? Not through futuristic applications but by tackling the most pressing challenges its employees face, particularly those involved in maintenance, repair, and operations (MRO).
Applying AI to help these real humans on the floor yields real benefits for the organization, such as efficiency gains, significant reductions in capital expenditures, and even tangible ROI.
This blog will explore how factories can make the most of AI by helping MRO professionals make better decisions and improve their productivity in day-to-day tasks.
We will look at:
- The challenges MRO professionals face in making good decisions
- The most common productivity drains in MRO processes
- How AI can solve these problems to enable professionals to make better decisions and work faster
- Ways AI can help MRO professionals make even better decisions in the future
Why it’s difficult to make good decisions in MRO
In our blog post on how AI will improve spare parts data quality, we covered the essential problem: MRO professionals often lack access to high-quality data on their spare parts inventory.
Spare parts records in any given factory’s ERP system are inaccurate, incorrect, and often missing. This makes it nearly impossible for MRO professionals to understand what spare parts they have on hand, preventing them from performing simple inventory optimization like setting a min/max.
Since MRO professionals can’t optimize correctly, they often buy extra inventory “just in case.” This ensures that they have the right part on hand to repair a machine when it breaks, but it increases procurement costs upfront and results in wasted capital when obsolete parts are eventually trashed.
In other words, poor-quality spare parts records force MRO professionals to focus on reducing downtime risks instead of making data-driven decisions on how many of each spare part to keep in stock. They also lack access to information about which suppliers offer which spare parts. As a result, they must source inventory from line builders, who sell OEM parts at a significant markup.
Simply put, the lack of data about the supply chain makes it impossible for MRO professionals to make smart choices about where to buy inventory and at what price.
Why MRO productivity is limited
The current state of MRO processes also limits professionals' productivity in their day-to-day work. Here are just a few examples.
Consider a factory that has built a new machine or upgraded or modified an existing one. In this situation, the maintenance professional will receive a list of spare parts to compare against capital equipment. They will enter the list of parts into the ERP system to create new records and determine which parts are already in inventory, which need to be procured, and which are obsolete.
Comparing a bill of materials (BOM) against capital equipment is extremely slow, tedious, and exacting, making productivity challenging. In a previous blog, SPARETECH CEO Martin Weber likened the MRO data-entry process to entering contacts into a smartphone. Everyone knows this challenge: the workflow is complex, leading to low productivity levels. Furthermore, it is highly prone to human errors, making it rarely done correctly, which contributes to the data challenges we discussed earlier.
MRO professionals also contend with a serious disconnect between maintenance and procurement teams.
Imagine that a factory maintenance professional opens the ERP, then types in a spare part to make an order, and presses enter. The procurement professional receives this order but doesn’t know what the part looks like. Maybe the factory’s ERP record is bad. Maybe it’s difficult to read; maybe it’s free text; maybe fields are missing.
“At this point, the procurement guy calls a vendor, and they say that they’re looking for motor v3-261. Is it available? The vendor says they just discontinued the part, but here’s a replacement. Will that work? The procurement person says, let me check with my maintenance people. So, he sends an email, and the maintenance person responds, I don’t know, did they say it would work?”
Explains Jack Reinke, SPARETECH Senior Account Executive.
This situation is frustrating and a waste of time for professionals with more important jobs. It also drains the factory’s overall productivity.
How can AI help?
The key to better decision-making and productivity is helping the MRO professional solve the challenges outlined above. “You have to think about the procurement person, whose job it is to buy these parts,” says Jack Reinke. “Or the maintenance person, who must keep production running now. How can you use AI to make their lives easier?”
Better decisions
The two biggest challenges to better decision-making in MRO are the lack of high-quality data on spare parts inventory and the lack of supply chain transparency.
As we’ve explored in other blog posts, AI can solve both problems by helping factories improve their spare parts records. It can use verified parts catalogs to clean up existing data and make adding new records easier for busy MRO professionals. It can even enrich the spare parts records with new information, such as which suppliers offer that part at what cost.
AI can ensure that MRO professionals have complete and reliable data on their spare parts inventory and a transparent view of the supply chain. This helps them make better choices by enabling them to perform processes like inventory and spend optimization.
“AI can be very helpful with this kind of choice. Providing better data will make ERP systems work how they were always meant to. MRO professionals can make better decisions and be faster, more confident, and more productive in their work.” says Martin Weber, SPARETECH CEO.
In addition, AI can consume historical data and learn to make predictions about the future. This will allow MRO professionals to make even smarter decisions about inventory and spend, reducing risk while increasing productivity.
Higher productivity
AI can also eliminate day-to-day productivity drains like those outlined above.
AI can significantly accelerate the tedious workflow of comparing spare parts against capital equipment. Imagine a simple interface that allows factory teams to drag the spare parts list into a window, after which the AI automatically performs the tedious, exacting data entry.
The system will also tell MRO professionals the parts they have at their factory and nearby parts, such as in Ohio. It can automatically generate complete, filled-out records for each new part, making it easy to add them to the ERP system without having to type.
AI will break down the barrier between maintenance and procurement by ensuring that MRO teams have complete and reliable data on existing inventory and making it simple to enter new spare parts records without error.
Now, when the maintenance person enters an order, they can attach a complete and correct record of the spare part. The procurement person who receives this order will know exactly which part to get. There will be no more confusion, and there will be no more wasted productivity communicating back and forth.
But what happens when the supplier doesn’t have the part? In the future, an AI interface (chatbot) could quickly recommend other suppliers with the part in stock from a reference database, eliminating the time-consuming back-and-forth and boosting productivity.
AI as a force multiplier for your factory
These are just a few examples of what AI can do to enable better decision-making and productivity in MRO. There are likely many more possibilities.
“Just think, how can we use it to get everyone in sync? How can we ensure there’s good data in the system and use it to make everyone’s work easier? That’s where AI is going.” says Jack Reinke.
Factories must consider this technology a force multiplier to make the most of AI. A tool that makes it easier for the human on the floor to do good work, not a tool that will do everything for them.
“AI will usher in a huge boost in efficiency for everyone, but how will you use it? To spend the least amount on inventory that you possibly can, or are you going to optimize for uptime while minimizing your inventory? You still need to decide what to do.” says Reinke.
Remember that you’re leveraging AI toward a goal. But you must still define the right goals, do the right work, and do it well. AI can give you a competitive advantage, but only if you use it thoughtfully.
If you focus on using AI to solve problems for the MRO professional on the floor—as we’ve explored throughout this blog and others—you will be on the right track to maximizing your factory's value.
What else can AI do?
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: