Predictive Maintenance Checklist
Predictive Maintenance Checklist
Predictive maintenance (PdM) is a proactive maintenance approach known for its ability to optimize maintenance and asset management operations, reduce downtime, improve machine performance, reduce costs, and enable data-driven decision-making.
However, before you can reap the benefits, you must successfully integrate predictive maintenance into your facility’s process structure, which will require an upfront investment in equipment, software, personnel training, and stakeholder buy-in. Nevertheless, predictive maintenance will deliver the results you hoped for with a well-planned implementation project combined with ongoing training, monitoring, and management.
For those implementing or upgrading PdM strategies, this article provides key recommendations for developing a comprehensive predictive maintenance checklist to monitor asset condition and performance, maintenance KPIs, and personnel.
Clearly Defining a Predictive Maintenance Checklist
Before getting started, it’s important to note the similarities and differences between preventive and predictive maintenance. Both maintenance strategies involve planned maintenance to keep equipment running at peak performance.
However, preventive maintenance involves regularly scheduled maintenance tasks and inspections, while predictive maintenance uses condition-based data and data analysis to schedule maintenance based on real-time equipment performance.
A predictive maintenance checklist simply outlines the steps and tasks required to implement and maintain a predictive maintenance program. By following a carefully designed checklist, you can ensure that all necessary steps are taken to fully optimize your PdM program, resulting in more efficient and effective maintenance operations.
Creating an All-In-One Predictive Maintenance Checklist
PdM is a type of condition-based maintenance that continuously monitors the operational status of company assets to reduce the likelihood of mechanical failures and unexpected breakdowns. This process reduces unnecessary maintenance and repairs and forecasts future maintenance requirements based on historical data and data trends.
PdM is supported by the use of artificial intelligence (AI), machine learning (ML), the internet of things (IoT), machine-level sensors, and advanced monitoring software, such as LLumin’s computerized maintenance management software (CMMS+). These technologies work together to track real-time equipment failure patterns and anomalies and forecast maintenance needs.
Creating a predictive maintenance checklist can help identify gaps in your maintenance team’s knowledge, verify your predictive maintenance equipment remains operational, and ensure your PdM continually improves.
Predictive Maintenance Equipment Checks
To maximize the benefits of a PdM program, it’s crucial to take proactive steps such as setting alarms and alert thresholds, regularly reviewing collected data, and training staff to interpret that data. By doing so, you can identify potential problems early and take corrective action before equipment fails.
A checklist can help ensure that all necessary steps are taken to establish and maintain a successful PdM program, from sensor installation to data collection and analysis to maintenance planning and scheduling.
We’ve provided an example predictive maintenance checklist below that includes important factors to monitor when managing predictive maintenance equipment and personnel.
|Predictive Maintenance Equipment Checklist|
|☑ Verify that machine-level sensors are directly integrated with the CMMS|
|☑ Verify that sensors are properly installed and securely attached|
|☑ Check that sensor readings are accurate and up-to-date|
|☑ Check that sensors are clean and free of debris|
|☑ Verify that data communication hardware (e.g. gateways, controllers, etc.) are connected and powered on|
|☑ Check data communication hardware to ensure it is operating properly|
|☑ Verify that the CMMS is properly configured to receive data from sensors|
|☑ Check CMMS software to ensure it is operating properly|
|☑ Verify that data is being transmitted to the CMMS on schedule|
|☑ Check that the CMMS is correctly processing and analyzing the data|
|☑ Verify that the CMMS is creating work orders based on predictive maintenance results|
|☑ Check that the CMMS is accurately tracking maintenance history and costs|
|☑ Verify that the CMMS is properly integrated with other software systems (e.g., ERP, SCADA, etc.)|
Predictive Maintenance Personnel Checks
A fully-trained maintenance team will be required to support your PdM strategy. And while it may be easy to overlook the importance of assessments and ongoing training, they are necessary for ensuring you get the best ROI on your maintenance strategy.
It will also be necessary to monitor key performance indicators (KPIs) like mean time between failure (MTBF), mean time to repair (MTTR), and overall equipment effectiveness (OEE). Tracking performance KPIs will be essential in enabling your maintenance team to improve the efficacy of your program.
We’ve included an example of a predictive maintenance personnel checklist with essential factors to monitor below. These skills are in addition to the importance of your entire team’s training and proficiency with your chosen CMMS software.
|Personnel Title||Ongoing Training Requirements|
|Technician||☑ Technical skills
☑ Communication skills
☑ Adherence to safety protocols
|Data Analyst||☑ Data analysis skills
☑ Knowledge of predictive maintenance software
☑ Attention to detail
|Manager||☑ Knowledge of equipment and maintenance practices
☑ Ability to manage a team
☑ Strategic planning skills
☑ Understanding of equipment operation
☑ Ability to recognize abnormal equipment behavior
☑ Adherence to maintenance protocols
|Engineer||☑ Technical knowledge of equipment design and operation
☑ Ability to develop and implement maintenance strategies
☑ Analytical skills
Why LLumin’s CMMS+ Supports the Best ROI on PdM
Creating a comprehensive predictive maintenance checklist will be an essential step in ensuring your maintenance delivers the results you envisioned from the start, with the benefits of lower costs and downtime with increased efficiency and productivity.
But, it will require coordinated efforts during and after your PdM implementation project. By tracking the right KPIs, monitoring equipment conditions in real-time, and ensuring that personnel receives ongoing training to stay up-to-date with the latest techniques and tools, organizations can take proactive steps to get the best results.
Further, working with the right CMMS software, such as LLumin’s advanced CMMS+ system, can help take PdM to an even higher level of performance, helping to streamline work order management, easily tracking KPIs, and gaining access to highly-accurate predictive maintenance insights needed to fully optimize asset performance and extend equipment lifespans.
At LLumin, we prioritize excellent customer service throughout a PdM implementation project. Our implementation team will tailor the software to support your company’s specific goals and business processes, providing you with a complete implementation plan and a support team to accelerate and guide your digital transformation.
If you are looking for a cutting-edge CMMS+ with a seamless implementation process and an expert customer support staff, then LLumin is a perfect fit. Join the many satisfied customers who have experienced the benefits of LLumin’s CMMS+ software today.
Getting Started With LLumin
LLumin develops innovative CMMS software to manage and track multiple assets and facilities for industrial plants, municipalities, utilities, fleets, and facilities. To get started and improve your CMMS ROI, we encourage you to schedule a free demo or contact the experts at LLumin to see how our software can help you reach your management goals.