Predictive Maintenance for Asset Maintenance Optimization
Predictive Maintenance techniques are designed to help determine the condition of asset equipment in order to predict when maintenance should be performed. It is a form of maintenance that directly monitors the condition and performance of equipment during normal operation to reduce the failures. Predictive Maintenance allows organizations to evaluate equipment condition by conducting periodic (offline) or continuous (online) equipment condition monitoring.
The ultimate goal of the approach is to perform maintenance at a schedule point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold. This approach also promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted.
Predictive Maintenance and Preventive Maintenance
The two maintenance programs have similar objectives. Like any proactive strategy, these plans are set in place to establish a regular routine maintenance that allows company to reach minimum or maximum standards.
Though both methodologies work to extend the life of assets, prevent unexpected breakdowns, and preserve organization cash flow, Preventive Maintenance and Predictive Maintenance conduct different approaches.
Preventive Maintenance tasks are completed when the machines are shutting down, on the other hand Predictive Maintenance tasks are being carried out when the machine are still running. Predictive Maintenance schedules tasks based on time passed or sensory triggers. Technicians typically need to shut down and disassemble equipment to carry out these tasks, such oil and lubrication changing.
On the other hand, predictive maintenance identifies trends in data and predicts when failures are more likely to happen. Because this method collects real-time data of equipment performance, it can be done while the equipment is operating.
Predictive Maintenance Framework
To perform predictive maintenance best practices, an organization needs to fulfill a complete coverage of predictive maintenance area which is defined as PdM Framework. This framework will guide predictive maintenance program to be effective, cost-wise and time-wise. With the guidance of predictive maintenance, an organization will be able to achieve the best maintenance output.
PT Tiara Vibrasindo Pratama begin our PdM Framework from databse setup process, scheduled monitoring, measurement preparation, data management, analysis and recommendation, PdM analysis follow up, and cost-and-benefit analysis. These components are being compiled to make it possible for maintenance practitioners to see complete insights.
Database setup is the main key of conducting PdM activities. Aside from presenting tools hierarchy, databse setup should give parameter analysis and alarm setup based on failure of previous Life Cycle Strategy studies. By having scheduled monitoring, PdM also give the ability to review planned schedule periodically.
Preparation stage will cover the time, technology, and personnel needed in the process of data collecting activities. During this stage, all components in the organization should have standardized labeling, and measurement point of their asset maintenance. This will ease up the next process and have integrated analysis and data management at the final analysis and decision making.
Data management is related with how PdM team manages all PdM data in one good database. Every information can be monitored and read easily. PdM team can analyze and give recommendation based on data inputs in the database. Every failure found should be recommended a solution on how it can be fixed. Recommendations should be easily tracked to ensure its final result. The final stage pf the framework is cost benefit analysis. This allows organization to determine the best approach to achieve benefits while preserving savings. In this analysis, benefits and costs are defined in financially and time-wise.
One organization will have to define every possible needed action for each asset which will describe productivity loss, maintenance cost and time requirement. These descriptions will be ranked based on critical action as the most effective maintenance action that needs to be done. This will help practitioners to make the most effective decision and take actions for their asset maintenance activities both cost-wise and time-wise.
“Predictive Maintenance Framework will guide predictive maintenance program to be effective, cost-wise and time-wise.”