Modern facility operations depend on the effective use of data for day-to-day operations.
Maintenance departments are no different.
They require high-quality, granular, up-to-date maintenance data which can be used to improve the effectiveness of maintenance programs while remaining cost-efficient.
Join us as we discuss ways to categorize maintenance data and the importance of data granularity. We will also touch upon the role of modern CMMS in handling all of your maintenance information.
The types and scope of maintenance data
Any data point that you can use to manage your physical assets and infrastructure can be considered maintenance data. Think historical maintenance records, operational data, machine performance data, maintenance metrics, asset tracking records, spare parts cost, etc.
The core reasons to collect, store, and analyze maintenance data are to make better maintenance decisions and to be able to execute maintenance work safely, effectively, and efficiently.
There isn’t one “official” or “right” way to classify maintenance data. For the purpose of this article, we will split it into three categories:
- Machine data
- Operational data
- Management data
Let’s explain each category briefly.
1) Machine data
With condition-monitoring sensors and equipment, you can track a vast amount of data on your machinery’s performance. This data can then be used to identify and predict faults, plan maintenance schedules, and determine the maintenance activity necessary for the machinery.
Machine data points you can track include:
- Machine speed
- Temperatures of different components
- Vibration levels
- Energy consumption
The exact machine data you will track will depend on the types of machines you run, which maintenance strategies you use, and what kind of technology you have access to.
2) Operational maintenance data
Operational maintenance data helps maintenance planners, supervisors, and technicians schedule and execute daily maintenance work. It can include:
- Historical records of maintenance activities
- Data concerning work requests, work orders, technician workload, tool and part availability
- Asset tracking data
- Machine manuals, policies, safety guidelines, procedures, and checklists (if you wanted to be stingy about it, you could claim that this is not data — it’s maintenance documentation; this is a valid argument, so we will not fight you on it)
Many other items could be a part of operational maintenance data, as long as it helps organize and perform day-to-day maintenance activities.
3) Management-level data
The purpose of management-level data is to provide an overview of machinery and facility performance.
Unsurprisingly, this data is most useful to maintenance managers and directors that need to prepare maintenance budgets, find opportunities to improve performance or cut costs, and make other strategic decisions.
Common examples of management-level data include:
- Maintenance KPIs
- Machine downtime, uptime, availability, and reliability metrics
- Operational efficiency metrics (like MTTR and PMP)
- Labor costs
- Spare parts inventory costs
- Total costs
Though management uses strategic data the most, that doesn’t mean that operations and maintenance teams can’t also use it to monitor and adjust their performance.
The importance of having granular maintenance data
The quality of your decisions depends on the granularity and accuracy of the data those decisions are based on.
Here’s an example: let’s say you use time-based maintenance for replacing parts. You have determined that you need to replace a particular motor belt every 90 days. And you do so, regardless of the condition of the belt.
Now, imagine you had the data showing how long the belt was in operation, did it experience any issues, and a way to track its overall condition. You could choose the right time to replace the belt, preventing a breakdown or reducing costs.
With enough data, you could also track how much downtime the issues have caused, calculate the total cost of ownership for the motor belt, compare MTBF for different motor belt OEMs, determine the expected life cycle, and so on.
We could provide hundreds of similar examples.
You need accurate and granular data for everything, from creating maintenance schedules and setting spar part reorder points, to prioritizing work orders or deciding which contractor is more cost-efficient.
Here at Limble, we put extra effort into giving you the ability to drill down into your data, ensuring that lack of data granularity never becomes a problem. The video below shows what that looks like in practice.
At the end of the day, maintenance data does not just help the maintenance team, or with maintenance costs. It helps your HR team hire and manage maintenance personnel, it helps you keep production and maintenance teams on the same page, and it helps top managers make the correct strategic decisions about capital investments and other major changes.
Using CMMS to handle maintenance data
Cloud-based CMMS software have become an integral part of the maintenance arsenal in modern facility operations. Here are a few reasons why.
Easy data storage and access
Cloud-based CMMS serves as a digital centralized platform that stores all of your maintenance data and streamlines your data management. This way, you can access it from anywhere, just a few clicks away, on your mobile device.
Of course, some users shouldn’t have access to all of your data. This is where role-based access control comes into play. Any modern CMMS system should help you define roles and their respective permissions, limiting access to sensitive information.
Automated data collection
You can manually add maintenance data to CMMS. You will often do that when you enter a new asset, part, vendor, etc.
However, the real value comes from automated data collection. You won’t realize how much background information CMMS collects and tracks for you until you actually start using it.
Imagine a simple work request coming in, getting approved, and a work order being scheduled and executed. During this process, your CMMS will collect:
- Who submitted the work order and when (the exact date and time)
- Description of the problem, urgency, as well as any other info provided by the work requester
- Who approved the work request and scheduled the work order
- Who performed the work
- How long did the work last
- Which materials and spare parts were used to complete the work
- When was the work completed
- Any relevant completion notes that the technician might have left
On top of that, after the completion of the work order, the CMMS will automatically update the maintenance history for the respective asset, as well as your spare parts inventory count.
And that is a lot of data in your information system — data you can use to improve internal processes and become more cost-efficient.
The goal of every maintenance team is to eliminate unplanned machine downtime, reduce labor costs, lower replacement costs, and improve machine performance, availability, and reliability.
Having the right data is essential for achieving these goals.
Rigorous analysis of maintenance data helps unearth meaningful insights that aren’t obvious by looking at high-level metrics. CMMS simplifies data analysis by:
- Keeping your maintenance records up to date
- Helping you set and track various metrics
- Automatically calculating relevant Key Performance Indicators based on those metrics
- Generating periodic reports based on the templates you set up
- Giving you access to real-time condition-monitoring data
- Helping you implement advanced analytics necessary for predictive and prescriptive maintenance
- Automatically forecasting your MRO inventory needs
- Giving you data granularity you can use to identify the root causes of most problems that plague your facility
Limble CMMS users can create an unlimited amount of custom variables that they can use to track and store almost any type of data. The same variables can be used to create a custom dashboard full of highly-customizable reports that get updated in real-time.
Here’s a lengthy video that showcases how insanely customizable our reports can be, while still remaining simple to set up.
Leverage your maintenance data
Having accurate maintenance data is critical for outlining an effective maintenance strategy and executing maintenance activities according to schedule. It also helps cut operational costs, reduce machine downtime, and increase equipment reliability.
In other words, having quality maintenance data is indispensable for making informed maintenance decisions.
With a centralized, cloud-based CMMS platform like Limble, you can seamlessly generate, store and access all of your maintenance data. Request a demo today and get a handle on your maintenance operations.