Predictive Maintenance Software: The Complete Guide
Predictive Maintenance software uses real-time data to help field teams eliminate unplanned downtime, cut maintenance costs, and dramatically increase workforce efficiency.
What is Predictive Maintenance Software?
Predictive maintenance software uses condition monitoring tools to monitor the performance and condition of equipment and determine when maintenance should be performed. The software performs anomaly detection to predict possible defects and estimates when they require fixing before a likely failure.
Combined with the Internet of Things (IoT), predictive maintenance software evaluates the performance of an asset providing information in real time. This information is provided through capturing data from IoT enabled sensors, which is then analysed and actioned to prevent failures occurring.
This allows you to schedule maintenance only when and where it is needed, maximising equipment performance and lifespan while minimising costs.
Why Predictive Maintenance is a Must-Have for Field Operations
Your team can achieve significant improvements with the right predictive maintenance solutions.
See it in action with a demo- Reduce Unplanned Downtime: Forecast potential failures and perform repairs before a critical asset goes offline.
- Lower Maintenance Costs: Schedule maintenance only when it’s truly needed, reducing labor time and inventory costs.
- Boost Workforce Productivity: Your team can focus on high-value tasks instead of reactive, emergency repairs.
- Improve Customer Loyalty: Proactively resolving issues demonstrates a superior level of service that fosters long-term trust.
What helps deliver great Predictive Maintenance Software?
Drive operational efficiency and optimise your resources
By automating processes, organisations can benefit from improved service delivery, by allowing repair maintenance to be detected in advance and the appropriate action to be taken, saving significant costs and resources for both the organisation and the customer.
Empower your workforce
Provide your workforce with valuable information driven from data collected. Your workforce can undertake jobs which shouldn’t take as long as they are already informed of any issues. An increased understanding of your assets ensures your workforce has all the information they need to complete jobs efficiently.
Enhance data driven insights
Collect asset data information efficiently and consistently. Analyse real time data driven insights to optimise resources while improving your workforce’s safety. Historical data gathered from assets enables organisations to predict trends for the future, for example, when assets need replaced or when one asset might cause an issue over another.
Understand your assets
Predictive maintenance enables you to understand the performance of your assets through real time information, providing complete visibility and understanding of maintenance required before issues escalate. By continually monitoring assets, you can start to identify trends in asset performance.
How does predictive maintenance work?
Our predictive maintenance software automates the entire asset health cycle, from early detection to job completion. So your team always stays ahead of equipment failures.
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Define: Select the equipment to be monitored, set optimal operating parameters, and establish monitoring frequency.
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Monitor: IoT sensors and connected systems continuously capture performance data and asset health metrics.
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Analyse: The system processes incoming data, generating performance reports and predictive forecasts.
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Decide: If no anomaly is detected, monitoring continues automatically. If an abnormality is flagged, the software initiates the maintenance workflow.
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Plan: A work order is created, with date, required skills, and parts availability all optimized in the schedule.
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Repair: Technicians arrive prepared with the right tools and information, complete the work, and close the order.
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Resume: Monitoring resumes seamlessly, ensuring ongoing asset protection.
Who benefits from predictive maintenance?
Service Operations Managers
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Gain visibility into asset health and maintenance priorities.
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Automate scheduling and resource allocation based on real-time data.
Field Engineers
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Receive clear, data-backed work orders with required parts and skills.
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Minimise emergency callouts and reduce repeat visits.
Asset Owners & Customers
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Enjoy improved uptime and extended equipment lifespan.
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Benefit from faster response times and reliable service delivery.
Predictive Maintenance vs Preventive Maintenance – What’s the Difference?
Both predictive and preventive maintenance aim to address issues before they lead to downtime, but the way they achieve this differs:
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Preventive maintenance is carried out at regular, planned intervals, regardless of the asset’s current condition. The focus is on routine check-ups and servicing to reduce the chance of unexpected failures.
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Predictive maintenance relies on real-time data from connected devices and analytics to identify when an asset actually needs attention. Maintenance is triggered by asset condition, rather than a fixed schedule.
Predictive Maintenance Sofware FAQs
What is predictive maintenance software?
Predictive maintenance software is a tool that uses advanced analytics, data collection, and machine learning algorithms to predict when equipment failures might occur. The goal is to anticipate and prevent equipment failures before they happen, thus reducing downtime and maintenance costs while increasing operational efficiency.
What are the three types of predictive maintenance?
The three types of predictive maintenance are condition-based maintenance, predictive model-based maintenance, and statistical process control. Condition-based maintenance uses real-time data to monitor the condition of the equipment. Predictive model-based maintenance uses machine learning algorithms to predict failures. Statistical process control uses statistical methods to monitor and control a process to ensure it operates at its full potential.
What technology is used in predictive maintenance?
The technology used in predictive maintenance includes data collection devices like sensors and IoT devices, data analysis tools, machine learning algorithms, and advanced analytics software. This technology monitors equipment and analyses data to predict potential failures and schedule maintenance before these issues occur.
What are the four types of software maintenance?
The four types of software maintenance are corrective, adaptive, perfective, and preventive. Corrective maintenance fixes faults or defects, adaptive maintenance adapts the software to different environments, perfective maintenance improves performance or maintainability, and preventive maintenance detects and corrects potential issues before they become problems.
What are two examples of predictive maintenance?
Two examples of predictive maintenance might include using vibration sensors and thermal imaging on a production line to anticipate mechanical failures or using machine learning algorithms to analyse data from a fleet of vehicles and predict when certain parts might fail based on past performance and conditions.
Turn maintenance into a strategic advantage
See how predictive maintenance can cut costs, boost team efficiency, and keep customers happy.
