Introduction
Industrial automation has become an integral part of the manufacturing industry, increasing efficiency while reducing labor costs. With increasing automation comes the need for predictive maintenance or condition monitoring to prevent unplanned downtime. This blog post aims to provide a factual comparison between predictive maintenance and condition monitoring to determine which is more effective in avoiding such downtime.
Predictive Maintenance
Predictive maintenance involves predictive analytics to determine when equipment is likely to fail, based on historical data and other factors such as temperature, vibration, and pressure. Predictive maintenance can prevent unplanned downtime, save money by reducing maintenance costs, and increase overall equipment efficiency.
According to a report by Allied Market Research, the global predictive maintenance market was valued at $3.23 billion in 2019 and is expected to reach $23.01 billion by 2027, growing at a CAGR of 30.0% from 2020 to 2027. This indicates the industry’s inclination towards predictive maintenance.
Condition Monitoring
Condition monitoring is the process of monitoring a specific piece of equipment for early signs of wear and tear, with the aim of performing maintenance before it fails. It monitors various parameters such as temperature, pressure, and vibration to detect early signs of damage. Condition monitoring can also help optimize maintenance schedules, leading to lower maintenance costs, increased production efficiency, and longer equipment lifetimes.
According to a report by Market Research Future, the global condition monitoring market is expected to reach a market size of USD 3.1 billion by 2023, growing at a CAGR of approximately 7%.
Comparison
Predictive maintenance and condition monitoring are similar in many ways, but predictive maintenance is more comprehensive and proactively analyses data to predict when a machine is likely to fail. On the other hand, condition monitoring focuses on monitoring specific parameters and detecting early signs of damage.
While both methods aim to prevent unplanned downtime, predictive maintenance is more effective since it uses predictive analytics to determine maintenance needs before a machine breaks down. Since it is based on data analysis, it is more automated when compared to condition monitoring, which requires more human monitoring and intervention.
Conclusion
In conclusion, predictive maintenance is more effective than condition monitoring in avoiding unplanned downtime, as it uses data analysis to predict equipment failure, leading to targeted maintenance that can prevent equipment breakdown. Although both methods have their advantages, predictive maintenance proves to be a more effective method in the long run.
References
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Allied Market Research. (2020). Predictive Maintenance Market by Component and End User - Global Opportunity Analysis and Industry Forecast, 2020-2027. Retrieved from https://www.alliedmarketresearch.com/predictive-maintenance-market-A06154.
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Market Research Future. (2018). Condition Monitoring Market Research Report - Global Forecast till 2023. Retrieved from https://www.marketresearchfuture.com/reports/condition-monitoring-market-6110.