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E-SPIN
Wednesday, 28 July 2021 / Published in Global Themes and Feature Topics, Industries, Manufacturing

How to establish a successful predictive maintenance program

Many business operations had been affected since the outbreak of COVID-19. Organisation has to embrace various methods and alternatives in order to sustain their businesses. The methods also include leveraging their assets and reducing cost. Predictive maintenance can be viewed as one of the way out as it offers benefits such as increase in return of investment (ROI), reduction in maintenance costs and lowers the probabilities of the occurrence of unplanned downtime. A successful predictive maintenance approach is the key factor in achieving a good ROI. In order to gain successful predictive maintenance program, an organisation should understand the correct way in implementing it. How to establish a successful predictive maintenance program?

Predictive maintenance usually starts once an organisation secures their stakeholder buy-in, has a finalised budget calculation, finalises their decision on the type of software required and also sets the key performance indicators (KPIs). The following are the steps in establishing a successful predictive maintenance program.

Step#1 : Identify priority or critical assets
Critical assets are assets that require high repair and replacement costs. Knowing or determining critical assets allow organisations to have accurate understanding of their ROI with predictive maintenance.

Step#2 : Conduct staff Training
Predictive maintenance involves the use of a lot of new tools that require skilled workers. The skills include the knowledge of handling, maintaining and repairing the new tools.

Step#3 : Define condition baseline
Predictive maintenance approach is a condition-based maintenance. The maintenance is triggered by the condition of the machines in real time. Condition baselines ensure maintenance can be carried out when the condition of the machine does not meet criteria set in the baseline.

Step#4 : Install the tools (IoT devices and sensors)
The tools being installed depends on the condition baseline set by your organisations. The examples of the tools include gas sensors, temperature sensors, pressure sensors, vibration sensors and much more such as custom application performance monitoring (APM), and define various components, clusters and groups that will trigger as early warning, downtime, critical and non-critical components .

Step#5 : Connect devices to CMMS tool
CMMS tools refers to Computerised Maintenance Management System that functions to manage assets, schedule maintenance and track work orders. Connecting the devices to CMMS tools enables the organisation to monitor the assets data more easily.It is common to integrate it within the domain of modern network performance monitoring and diagnostics (NPMD), since the modern definition covers the AI, APM, flow, SNMP/WMI that can provide the baseline for the predictive maintenance operations.

Step#6 : Run a pilot test
Running a pilot test any of your important assets helps the organisations test and validate the effectiveness of the predictive maintenance program.

Predictive maintenance has shown various positive results to organisations such as 10% to 40% reduction in maintenance costs and 10% to 20% reduction in waste. However, without a proper implementation, the program will only become another additional burden to an organisation.

E-SPIN Group in the enterprise ICT solution supply, consulting, project management, training and maintenance support for multinational and government agencies, across the region E-SPIN do business. Please feel free to contact E-SPIN for your inquiry and requirement, so we can assist you on the exact requirement in the packaged solutions that you may require for your company digital transformation (DT), industry 4.0 transition requirements. Implementing infrastructure continuous monitoring and providing proactive alerting, early warning and insight for minimising unplanned downtime is just one of the many areas we may help.

Tagged under: Digital Transformation, Network Performance Monitoring and Diagnostics (NPMD), Predictive maintenance (PdM)

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