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Predictive Maintenance Software
Monitor your assets and optimise your workforce with real time predictive maintenance software
What is Predictive Maintenance Software?
Today, maintenance repairs can be expensive and time consuming, therefore it’s important to put processes in place in order to minimise and prevent them. Predictive Maintenance Software uses condition monitoring tools to monitor the performance and condition of equipment and determine when maintenance should be performed. The software predicts possible defects and estimates when they require fixing before a likely failure. As part of an organisations’ maintenance strategy, predictive maintenance differs from preventative maintenance whereby routine repairs and maintenance are scheduled to take place.
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. This data is then analysed and actioned to prevent failures occurring. Predictive maintenance sensors include monitoring equipment which can detect a variety of things such as vibrations, temperature or humidity.
What value does Predictive Maintenance Software provide for your organisation?
- Reduce costs associated with ordering spare parts and technicians’ costs related to labour time
- Optimise maintenance resources and increase workforce productivity with more time to spend on other jobs
- Maintain and improve product quality of equipment while preventing failures, breakdowns and downtime
- Improves overall availability of equipment in organisations
- Increase compliance and improve safety for staff fixing equipment as the software pre-empts when failures are about to occur rather than when in operation
Organisations can use the data driven from sensors to detect whether assets require attention, ensuring efficient service delivery before failures occur.
This visibility enables increased cost efficiencies by reducing the amount of downtime and labour required to fix equipment while improving safety amongst your workforce.
With access to real time information, your workforce can detect the condition of assets in advance improving overall productivity and capacity.
Customers can benefit from an improved service delivery with issues being prevented before they occur.
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.
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.
