Life is not easy if you’re a maintenance professional. Let’s be honest – keeping everything running smoothly in your organization is not simple. You need to juggle a million different tasks, from preventing equipment breakdowns to ensuring maintenance costs do not go through the roof, all while trying to stay ahead of the curve.
In short, you’re pretty much constantly putting out fires. That’s the crude reality of maintenance management. Whether you’re a seasoned facility manager or a detail-oriented construction manager, you continually have to face a barrage of maintenance challenges every day.
Here’s a mind-boggling statistic: According to the International Society of Automation, factories typically lose between 5% and 20% of their manufacturing capacity due to equipment failure and other causes of downtime.
Unexpected equipment failures mean that your production will slow down or halt. Both time and money will be lost, with the onus often falling on you. But here’s the good news: AI is stepping into the maintenance management industry and making our lives much easier. It’s just not a buzzword; it’s a powerful tool that can help you overcome maintenance challenges while transforming your whole maintenance strategy.
Think about it: machines can predict failures before they occur, repair schedules can be optimized to match available techs, and real-time data can tell you the health of your most critical equipment. This is the power of AI in maintenance.
In this blog post, we explore the top 10 challenges in maintenance management and how AI-powered solutions can help mitigate them.
Why is AI for maintenance management important?
Before diving into the top maintenance challenges and how AI can overcome them, it is essential to understand why AI is crucial for maintenance management.
For years, maintenance has been seen as a necessary evil—a cost center that was only used for resolving issues and addressing breakdowns and other problems occurring with machines and equipment in an organization.
Did you know that around 70 to 80 percent of the costs of a facility asset come from its operation and maintenance? That means maintenance can help you save a ton of money with the proper maintenance practices or lead to significant waste if it’s not managed properly–either by neglecting or overdoing it.
If your team is like the 61 percent of maintenance facilities surveyed by Plant Engineering, there is a high chance that most of your maintenance work will be reactive. This means you only perform maintenance when something breaks down.
To make things trickier, communication about these tasks often takes place manually through simple “tap-on-the-shoulder” conversations, notes, voice chats, and emails, making it equally challenging to stay organized.
Top 10 challenges in maintenance management and how AI can solve them
Below, we list the top 10 challenges maintenance managers face and the innovative ways AI can help solve them.
Problem # 1: Sudden breakdowns that throw your whole schedule off and cost you big time
Unplanned downtime is one of the biggest maintenance challenges for maintenance leaders.
Picture Sarah, a plant manager. Sarah’s production is just like her lifeline. When the production stops, everything comes to a halt. The cost isn’t just lost output; it’s missed deadlines, dissatisfied customers, and scrambling to get things back online.
There should be an intelligent solution that can help her predict failures so she can schedule maintenance proactively and minimize equipment downtime.
Solution: Predictive maintenance
With AI algorithms, you can analyze sensor data, historical maintenance records, and operational data to predict when a piece of equipment or asset will likely fail.
This allows maintenance teams, including plant managers like Sarah, to schedule and perform maintenance proactively, reduce unplanned downtime, and enhance equipment lifespan.
Problem # 2: Guessing when to do maintenance, instead of knowing for sure
Another top challenge for most maintenance professionals is having an inefficient preventive maintenance (PM) plan.
Mark, a facilities supervisor, is constantly stuck in a loop of scheduling PM tasks manually. He still relies on spreadsheets and paperwork and can’t figure out a smart way to schedule all PM tasks for the different pieces of equipment, each with varying PM requirements based on their health.
Solution: Smart PM scheduling
AI-powered scheduling tools can analyze patterns for equipment usage, maintenance history, and resource availability to create dynamic and optimized maintenance schedules for various equipment. This ensures that maintenance tasks are performed at the optimal time, leading to increased labor efficiency and minimal disruptions.
Problem # 3: Working in the dark, without real-time data
Lack of up-to-the-minute information on how your assets are performing means your teams are always playing catch up.
Let’s picture David here, an asset manager at a bustling construction site. He’s responsible for keeping a fleet of heavy machinery – cranes, bulldozers, generators – running smoothly. But David’s stuck since he has to rely on outdated reports. By the time he gets the data, the situation on the ground has changed.
A crane breaks down unexpectedly because he didn’t see the early warning signs. David needs to see the real-time health of his assets, the live status of his work orders, and the current availability of his technicians to make informed decisions and prevent these costly disruptions. He needs real-time visibility, not yesterday’s news.
Solution: Real-time data analytics
Imagine David; instead of relying on outdated reports, he has a live dashboard on his tablet. This dashboard, powered by AI and machine learning, shows him the real-time health of every crane, generator, and bulldozer on the site.
The AI constantly analyzes data from machine sensors, spotting subtle changes that indicate potential problems before they lead to breakdowns. It’s like having a team of experts watching every piece of equipment 24/7.
David can see live temperature readings, vibration levels, fuel consumption, etc. This means he can schedule maintenance precisely when needed, prevent costly downtime, and keep the project on track. He’s no longer reacting to emergencies; he’s proactively managing his assets.
Problem # 4: Trying to get the most of out of equipment that’s past its prime
When you cannot monitor the health of your aging assets, you fail to recognize any potential failures. Meet Linda, a maintenance director at a local county whose team is facing the challenge of keeping aging assets operational. Her team needs a way to increase the lifespan of these assets without making a compromise on equipment reliability.
Solution: Asset health monitoring
AI for maintenance can help Linda and her team monitor the health of the aging assets, providing early warnings of potential equipment failures and helping them prioritize maintenance efforts. With AI systems, maintenance teams can help monitor aging assets and know when a particular asset needs to be replaced or removed. This allows them to take timely action, preventing costly equipment breakdowns and enhancing asset lifespans.
Problem # 5: Dealing with constant stockouts, slowing down other things
Managing inventory can be a hassle in the maintenance management world. Imagine yourself in the shoes of a parts manager, Chris, who constantly has to deal with the stress of stockouts and overstocking. His phone rings continuously – “We need that valve, NOW!” or “Where’s the filter for the generator?”
Chris’s inventory problems aren’t just his problems but everyone’s problems. When parts aren’t available, maintenance teams are idle, and projects fall behind schedule.
It becomes difficult for him to track inventory levels and determine which stock needs replenishment and which doesn’t. He is in dire need of a system that can help him predict demand and optimize inventory levels accurately to fulfill maintenance needs.
Solution: Smart inventory management
AI systems can analyze historical data, usage patterns, and demand forecasts to optimize inventory levels. This ensures that the right parts are always available, minimizing stockouts and overstocking. With smart inventory management, Chris can always have the right parts at the right time.
Problem # 6: Finding, training, and keeping skilled technicians
Finding and retaining skilled labor is a significant challenge for maintenance leaders. Let’s talk about Alex, a team lead in an industrial facility, who faces the problem of the growing skills gap. It is becoming increasingly difficult for him to find and retain qualified technicians in the facility, which leads to a significant shortage of skilled labor.
Solution: AI-powered training and support
AI-powered virtual training platforms can help provide technicians with on-demand access to training materials, resources, and troubleshooting guides. AI can also offer virtual training and support to technicians, enabling even less experienced ones to perform complex maintenance tasks. Other than that, AI-powered chatbots provide real-time support, helping them resolve issues within no time.
Problem # 7: Constantly changing rules and tons of paperwork
Compliance and safety regulations also poses significant challenges for maintenance professionals. Jennifer, a compliance expert, has the responsibility of ensuring that her organization meets all regulatory requirements. One missed update or overlooked detail can lead to hefty fines, legal trouble, or even worse, a safety incident. She is looking for a platform that helps her streamline compliance reporting for different assets and stay on top of ever-evolving regulations.
Solution: Automated compliance reporting
AI platforms can automate the creation of compliance reports and keep track of regulatory changes. With AI for maintenance, Jeniffer can obtain real-time updates on all compliance and safety regulations.
She doesn’t need to spend hours filling out safety checklists and compliance forms. AI can do it for her. The system can automatically pull data from maintenance logs, equipment sensors, and work orders to create accurate reports in seconds. This can help her reduce the burden of manual reporting and ensure that her organization stays compliant.
Problem # 8: Trying to do more with less money
Managing budget spending and reducing costs is a significant challenge for maintenance leaders. Michael, a CFO at an industrial unit, wants to focus on reducing maintenance costs. He is looking for an innovative solution that helps him optimize maintenance spending without compromising operational efficiency.
Solution: AI-driven cost savings
AI systems can help maintenance experts and CFOs like Michael identify cost-saving opportunities, such as optimizing resource allocation and reducing unnecessary maintenance tasks. Think of regularly replacing parts that are still in good condition. Or continue using an asset that should’ve long been retired.
AI tools can help track the ratio of maintenance costs with the remaining useful lives of assets and help you make smarter repair or replacement decisions. This can help CFOs like Michael to significantly reduce maintenance expenses and achieve their financial goals without sacrificing the reliability of their equipment.
Problem # 9: Information getting lost in emails and phone calls
Due to gaps in communication and collaboration, many maintenance teams fail to coordinate maintenance tasks across teams. Emily, a project coordinator, is in the same situation. She is responsible for coordinating maintenance tasks across multiple teams within her organization.
Picture this: A critical repair on a production line gets delayed because the electrical team wasn’t informed about the mechanical team’s progress. A scheduled shutdown gets missed because the operations team wasn’t notified in time.
With information scattered across different systems, no one has a clear overview of the entire maintenance schedule. Therefore, Emily needs a platform that helps her smoothly communicate and collaborate across different departments.
Solution: Enhanced communication and collaboration
Instead of scattered emails and phone calls, imagine a centralized communication hub. AI-powered platforms can provide real-time communication tools, task assignments, and document sharing, ensuring everyone in the organization is on the same page.
AI can also organize documents and files for all the relevant work orders in one place, making it easy for techs to find schematics, manuals, etc.
This can eliminate the time wasted searching for information and streamline the entire communication process, leading to significant efficiency gains, all while improving coordination between maintenance teams and other departments.
Problem # 10: Technicians that are always fighting fires!
A proactive approach is always more effective and efficient than a reactive one. If your technicians can’t identify potential failures in your equipment, you will face unplanned downtime and increased maintenance costs.
Robert, a seasoned technician working at a manufacturing plant, understands the significance of a proactive maintenance approach. However, he’s still stuck in a reactive cycle, i.e., he is still reacting to equipment breakdowns when they occur. He is looking for a way to help him shift to a predictive maintenance strategy, knowing about potential equipment failures in advance.
Solution: Shift to proactive maintenance
AI solutions can help Robert transition from reactive to proactive maintenance by providing the data and insights he needs to forecast and prevent equipment failures. AI-powered predictive maintenance can analyze data to detect failures before they occur, allowing technicians to perform maintenance proactively. This lowers maintenance costs, reduces equipment downtime, and increases operational efficiency by optimizing maintenance schedules and resource allocation.
Real-world examples of using AI for predictive maintenance
Let’s explore ways AI can enable predictive maintenance in the following industries.
Manufacturing
Factories hate downtime, don’t they? Well, imagine what would happen if your equipment could tell you that they’re about to encounter a problem. That’s what AI in predictive maintenance is doing.
Companies like Siemens use AI to find out when equipment is going to break down so they can fix it before it does. It optimizes maintenance schedules. Moreover, predictive analytics can help ensure supply chains run smoothly, highlighting the benefits of AI in predictive maintenance.
Energy sector
Picture your local power company. There is a ton of equipment that you need to ensure is running smoothly. Utility companies use AI to monitor and maintain power generation equipment.
With AI, they can monitor everything so they can identify potential problems before they cause blackouts and power outages. General Electric (GE) is using AI to understand how their turbines are performing, and it’s making a significant impact on keeping everything reliable.
GE is working with major power generation companies to improve inspections using a cloud-based image analytics tool. By automating image-based inspections, companies can reduce costs significantly—research shows up to 20% savings on labor and asset maintenance.
Healthcare
Hospitals can never afford for their medical equipment to break down. It would be a nightmare for the doctors and especially the patients. Hospitals and healthcare institutes can use AI to ensure that medical equipment, devices, and critical equipment, from MRI machines to ventilators to monitors, are always running smoothly.
They can focus on fixing equipment when it breaks down and also know when it might. With AI, they can schedule preventive maintenance for medical equipment, showcasing the applications of AI in predictive maintenance.
A global medical technology company implemented an AI-based predictive maintenance system for their medical devices. With the AI solution, the company prevented up to 30% of device failures, ensuring smoother hospital operations and increasing the perceived value of its products.
Smart buildings
Have you ever been in a building where the AC or heating system seems to work smoothly? You wouldn’t believe it, but AI is often behind that. AI systems can help you monitor the HVAC and electrical systems in a building so you can ensure they are working fine.
The system automatically adjusts temperature and ventilation based on real-time occupancy data, reducing energy waste in unoccupied areas. Building managers can use AI to ensure everything is running efficiently and all occupants feel comfortable.
AI is similar to a smart building manager that never sleeps. Building management systems can use AI to simplify operations, further displaying the benefits of AI in predictive maintenance.
For instance, a shopping center in Quebec integrated BrainBox AI’s technology into its HVAC system, resulting in a 21% reduction in electricity consumption—saving 205,214 kWh—and monetary savings of CAD 19,249 within a year.
Leveraging AI in Maintenance Management
Having a plan is crucial if you want to use AI in maintenance management. First, you need to understand your biggest maintenance challenges and then determine which ones you need to solve first.
Notably, AI relies on high-quality data; it won’t be able to give accurate results if your data is not up to the mark. Therefore, make sure your information is appropriately organized and correct. One of the best ways to do that is by partnering with experienced AI providers and beginning with small test projects. This will help you know how AI can help with your specific situation.
Let’s face it: maintenance management is ever-evolving, and AI is at the forefront of this transformation. The key challenges in the maintenance management industry, like unplanned downtime, inefficient scheduling, and data silos, can be resolved only when you are able to embrace AI systems. With AI-enabled CMMS solutions, this becomes simpler. It is time for you to empower your teams with real-time insights, optimize and allocate your resources, and increase operational efficiency in your organizations.
So, are you ready to take the next big step? Let’s embrace AI and see how it can transform your maintenance management strategy.
