How to Collect & Use Maintenance Data Effectively

Maintenance data is all of the information collected regarding a company’s assets, including everything from equipment to facilities to parts inventory. This data is collected in a variety of ways, including automated equipment sensors that constantly monitor various aspects of your machinery as well as records kept by maintenance technicians during and after inspections and maintenance tasks.

All of this data is integral to effective maintenance management, as it can be leveraged to track performance against key performance indicators (KPIs), schedule routine maintenance and inspections, manage parts inventory, estimate equipment lifespans and enhance overall decision-making.

Let’s you’ve been collecting extensive data about your conveyor system through sensors and historical maintenance records. Based on your maintenance analytics, you’ve come to the conclusion that the conveyor belt needs to be replaced every five years on average due to wear and tear from continuous operation, material load and external factors. With this data-backed insight, you know exactly when to replace the part to prevent breakdowns or downtime.

It may seem obvious that raw data can be beneficial to your maintenance department, but it’s only as good as the data being collected. That means setting up proper maintenance software, combined with implementing solid processes on how to record, collect and analyze data are crucial to using data effectively. Read on to learn how to do just that to ensure good data quality, which will translate to better maintenance planning and profitability in the long run.

Types of Maintenance Data

Effective maintenance data collection comes from a variety of channels to track the status of equipment and support your decision-making around maintenance and inspections. Common types of data that need to be collected include:

Sensor/Machine Data

Sensors capture real-time data from machinery about its current condition and performance. These sensors commonly monitor temperatures, vibration, pressure and other critical metrics to recognize exactly how your equipment is currently functioning. By tracking this data 24/7, maintenance teams can spot irregularities like sudden jumps in temperature or abnormal vibration patterns to address issues quickly before they result in broken machines and downtime.

Operational Data

Collecting operational data allows organizations to track the impact of daily usage and workloads on critical equipment and systems. Monitoring production schedules, equipment runtimes and usage rates can help to understand exactly how often equipment is being used and for how long. 

Analyzing this data allows maintenance teams to craft unique strategies for each machine based on its specific demands and usage time, making it easier to schedule preventive maintenance and inspections at optimal times based on actual usage. 

Management Data

Management maintenance data involves collecting information around the administrative and coordination components of an effective maintenance strategy including: 

• Budgeting
• Resource allocation
• Work order scheduling 
• Labor hour monitoring

For instance, you could calculate metrics like mean time to repair (MTTR) to determine how long it’s taking individuals to perform their tasks. Tapping into management data gives leaders a high-level overview into how efficient and costly their maintenance efforts are, making for more informed decisions around improving processes, upgrading infrastructure and hiring new technicians to match broader organizational goals. 

How to Collect Maintenance Data

Effective maintenance data collection involves both manual recording and automated recording through software and sensors. Here are the pros and cons of both:

Manual Recording

Recording maintenance data manually involves having maintenance technicians document equipment issues, repairs and maintenance tasks by hand with paper or spreadsheets. This approach is essential when a manufacturing environment lacks automated systems or can’t afford upfront technology costs.

Detailed logs support the tracking of wear and tear, identification of recurring problems and coordination of proactive maintenance. Having historical data simplifies auditing, meeting regulatory requirements and helps with better resource allocation. 

Pros:

• Lower initial setup costs
• Doesn’t rely on the internet or IoT technologies in remote settings or harsh conditions 

Cons:

• Higher risk of errors due to manual data entry
• Time-consuming process with limited options for automations
• Easy to misplace or lose critical data with paper-based filing 

Automated Recording

Automated maintenance data recording uses sensors, computerized maintenance management system (CMMS) software and other digital platforms to frequently monitor equipment performance and track maintenance activities in real time. This modern approach is essential because it enhances accuracy, reduces human error and offers instant insights for making better maintenance decisions. 

Automatically collected data can be integrated with predictive maintenance analytics, making it substantially easier to detect early signs of potential failures. And using CMMS software for digital data storage simplifies the process of retrieving and comparing information, streamlining compliance checks and performance analysis.

Pros:

• Real-time, accurate data collection
• Faster trend analysis and predictive insights

Cons:

• Higher upfront investment in technology
• Requires technical infrastructure and internet access

Using Maintenance Data to Improve Operations

You can leverage maintenance data to drastically improve how your organization plans, schedules and allocates resources. Maintenance data provides critical information to boost efficiency, identify recurring issues and enhance decision-making across business processes, from daily to-dos to long-term resource allocation. Paying specific attention to key maintenance KPIs makes it much easier to boost reliability, reduce expenses and provide your team with the tools and data they need to achieve peak performance.

You can enjoy the following benefits with proper maintenance data collection: 

Increased Efficiency

Having the right data helps you determine if you’re servicing critical assets at the right intervals. Constant breakdowns can be indicative of a need for more proactive maintenance processes; whereas, prolonged uptime could indicate over-servicing. Collecting data on failures and unplanned downtime allows you to refine your maintenance schedule to ensure you’re performing inspections and routine maintenance only as needed and not wasting resources. Ultimately, timely service boosts asset lifespans while reducing the chances of unexpected breakdowns, without overspending on labor costs.

Improved Equipment Performance

Extensive data sets provide a clear picture into how your assets are performing over time. Instead of relying on anecdotal evidence, you’ll have access to conclusive metrics such as mean time between failure (MTBF) or average downtime per incident. These KPIs specify the overall health of your machinery and help determine which equipment requires immediate attention or part replacements. 

Better Parts Inventory Management

Historical data around wear and tear and usage rates can help in your decision-making around parts inventory management. Having the exact parts you need available at the right time reduces equipment downtime while preventing unnecessary purchases and overstocking. Data-driven inventory strategies balance both cost and efficiency, supporting ideal stock levels without overspending on unnecessary supplies.

Decreased Maintenance Costs

Collecting real-time data on labor hours, parts usage and service frequency provides clear context around overall maintenance expenses. Assessing budget trends can pinpoint which assets are costing the most and whether you’re allocating your funds effectively. Transparency around these expenditures helps with informed decisions about extending asset lifespans, refurbishing equipment or replacing outdated machinery.  Ensure every dollar spent is maximizing operational efficiency.

Fewer Bottlenecks

Understand where your technicians are facing delays or recurring setbacks to improve maintenance operations. Data can point out issues like a shortage of specialized skills or a lack of required tools and parts on hand. By recognizing these types of bottlenecks, you can act accordingly to support your maintenance team with new hires, specialized training and improved asset management.  Addressing maintenance bottlenecks allows for smoother workflows and saves time and money. 

How a CMMS Can Help

A CMMS like Coast stores all of your maintenance data within a simplified digital platform, automatically integrates real-time data from sensors and systems, and pulls it into intuitive maintenance reports for more simplified decision-making. All of this helpful data can be used to schedule inspections and routine maintenance from one easy-to-use software.

Don’t wait to enhance your data collection processes. Get started with Coast for free today!