Predictive Maintenance Strategy: Achieve Maintenance Excellence
Reliability managers who are utilizing Industry 4.0 technologies and best practices to achieve high production levels and lower maintenance costs are likely to be aware of the advantages of predictive maintenance. A predictive maintenance model can generate significant benefits in the right circumstances, giving you accurate outcomes by using the rightmaintenance strategy, the right tools, and the right implementation.
Today we will discuss how organizations can maximize their cost savings and uptime by ensuring that their computerized maintenance management system (CMMS) is fully optimized. We’ll also highlight how LLumin’s powerful and unique CMMS+ delivers the necessary features and functionalities to provide the most accurate data that will ultimately reduce false positives, produce accurate outcomes, and maximize uptime.
Predictive Maintenance Strategy to Achieve Accurate Outcomes
Predictive maintenance models are known to reduce unplanned and planned downtime and save organizations money spent on unnecessary maintenance tasks by leveraging the power of advanced software, artificial intelligence (AI), machine learning (ML), and the Internet of things (IoT) technologies.
When combining these technologies with a predictive maintenance strategy, they can analyze and learn from failure patterns over time, accurately identifying impending mechanical issues before they disrupt daily operations.
While a predictive maintenance model can be very attractive for several reasons, it’s critical to understand the risks involved with poor implementation and subpar CMMS solutions that can lead to inaccurate data, incorrect actions, and additional costs.
Companies can avoid poor outcomes by ensuring that an organization’s CMMS solutions are fully optimized and can provide accurate real-time data sharing, continuous data compilation and analysis, conditions-based monitoring, and leverage all machine data sources, including IoT technologies.
LLumin’s CMMS+ utilizes these features and functionalities, which can provide the most accurate data, reduce false positives, and assist organizations in achieving the outcomes they envisioned before implementation.
Optimized CMMS features capable of improving your predictive maintenance strategy include:
- Real-time data sharing
- Data compilation and analysis
- Condition-based monitoring
- Integration with machine controls systems and IoT technology
Let’s dive in and discuss these features in greater detail.
Real-Time Data Sharing
Predictive maintenance employs advanced analytics, machine learning, and AI to improve quality in real-time, extend equipment lifespan, and decrease machine downtime. However, a company’s predictive maintenance model is only as good as the data it collects.
A CMMS system’s single most important feature is its ability to collect, compile, and analyze real-time data. An inability to perform these predictive maintenance tasks for large amounts of normalized data while maintaining data integrity can result in inaccurate data and false positives.
LLumin’s CMMS+ solution utilizes a cloud platform to integrate asset management to collect large volumes of data that are then analyzed with machine learning algorithms. LLumin’s cloud-based software always works around the clock—syncing and analyzing critical data.
Organizations can enhance and streamline their predictive maintenance strategy using LLumin’s CMMS+ and its intelligent, cloud-based approach, which enables remote asset monitoring for any type of asset and any type of machine data source. LLumin enables you and your team to track all machinery and asset infrastructure across multiple plants and locations, giiving visibility to their real-time status.
Data Compilation and Analysis
Predictive maintenance models rely on sensors and connected devices, advanced monitoring software such as LLumin’s CMMS+, and advanced data analysis techniques to detect equipment operational anomalies and potential defects.
Recent advancements in CMMS software enable assets to be interconnected and monitor data from each individual asset. This process is beneficial because assets do not operate independently from each other. By interconnecting assets and analyzing compiled data, eliminating false positives and identifying a problematic machine becomes easier.
LLumin’s integrated cloud-based approach enables organizations to adopt a coordinated approach and streamline their predictive maintenance strategy. LLumin learns more about a facility and its assets over time. As more data is compiled and analyzed, our AI and ML technologies produce better and more accurate results. The CMMS+ can detect patterns humans cannot, as well as predict breakdowns and equipment failures with remarkable accuracy.
Condition-based monitoring involves tracking several parameters (such as output quality, equipment vibration, power consumption, temperature, and idle times) to identify anomalies and predict future mechanical failures. This approach utilizes condition-monitoring sensors to collect data from multiple company assets.
These equipment sensors enable real-time communication between company assets and your CMMS. The information gathered from equipment sensors can then be compiled and analyzed to determine whether assets are operating efficiently and to reveal their level of wear and tear. This information enables your CMMS solution to quickly recognize error codes and initiate maintenance procedures with required parts to resolve mechanical issues.
LLumin’s CMMS+ is a complete solution for condition-based monitoring. The software monitors real-time, machine-level data and analyzes data based on historical information and machine-learning algorithms, helping maintenance managers stay ahead of mechanical failures, reduce unnecessary maintenance tasks, and maximize equipment uptime.
To support a highly effective predictive maintenance model, your CMMS solution should utilize industrial Internet of things (IIoT) technology to converge disparate data into a single comprehensive system. By interconnecting equipment and integrated sensors using IIoT technology, data can be collected and communicated to determine the operational condition of assets.
A comprehensive analytics-driven CMMS system will also gather historical data about maintenance actions, machine environment, application factors, operator input, and historical failure rates, in addition to critical machine data via machine-level sensors. An advanced CMMS solution, like LLumin’s CMMS+, can analyze this data to reduce false positives and provide the most accurate insights possible.
Implement Predictive Maintenance With LLumin
A predictive maintenance model can provide several desirable benefits, including lower maintenance costs, improved profitability and satisfaction, and reduced equipment downtime. However, an organization must ensure that the CMMS solution it selects provides the right combination of advanced features and functionalities capable of supporting a predictive maintenance strategy.
When working with advanced maintenance software like LLumin’s CMMS+, organizations can ensure they’re on the right track to Industry 4.0. The CMMS+ software is capable of working with your existing machine-level sensors and control systems to monitor and analyze the status of your company assets. The cloud-based and mobile-ready software can help support and streamline your predictive maintenance model and all activities required to optimize performance levels.
LLumin’s easy-to-use CMMS+ predictive maintenance software combines data from machine sensors with condition-based workflows to execute immediate responses and actions for optimal asset management. LLumin provides powerful but nimble dashboards and visualizations that enable remote asset monitoring and visibility to all asset conditions and statuses, along with tools for scheduling, monitoring, managing personnel and supplies, and many other resources for successful maintenance management.
Our implementation process is second to none and is executed to ensure the effective use of your new CMMS+ software. We provide continual training and support to our customers so they can adapt to and perform well in rapidly changing market conditions.
So if you are looking for a cutting-edge CMMS+ solution combined with a seamless and rapid implementation process, then LLumin is a perfect fit.
Getting Started With LLumin
LLumin develops advanced CMMS software to manage and track assets for industrial plants, municipalities, utilities, fleets, and facilities. If you’d like to learn more about how CMMS software can help improve your predictive maintenance strategy, we encourage you to schedule a free demo or contact the experts at LLumin to see how our CMMS+ software can help you reach your performance goals.