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Condition-Based Monitoring for Improved Machine Health

6.07.2022
Condition-based monitoring of critical assets helps to effectively manage machine health and avoid unexpected incidents.

For remote equipment and machinery, it can be difficult to prepare for and identify causes of productivity losses and downtime. Numerous manufacturers are utilizing digital transformation technologies, such as condition-based monitoring, with the goal of preventing unforeseen machine failure. 

Preventative maintenance, such as regular equipment upkeep and maintenance checks, is not always sufficient on its own to avoid downtime and escalated costs. Predictive maintenance, however, relies on continuous monitoring of asset performance through collected data and sending advance notifications of equipment issues. 

Many industries are shifting from time-based maintenance to condition-based maintenance strategies. Unnecessary maintenance can compromise productivity and waste resources, while condition monitoring helps to predict machine health via sensor data and other metrics. This ensures a satisfactory median between a proactive approach and maximizing productivity, in contrast to outdated methods such as breakdown maintenance. 

With the latest in industrial IoT hardware, network connectivity, and software solutions, manufacturers are able to observe and record machine health by monitoring individual factors of the machine’s performance—temperature changes, vibration, error trends, changeover efficiency, etc. For successful deployment and use, the ideal continuous equipment monitoring solution should be cost effective, easy to implement, and easy to utilize. It should act as a tool to see things the human condition cannot.
Predictive maintenance can minimize unexpected downtime and significantly boost the bottom line, an important benefit of full factory or operations connectivity. The real cost of downtime varies by industry, and includes lost capacity, lost production, and the expenditure of direct labor and inventory. Intangible expenses are also present, with these related to responsiveness, innovation, and more.

In our newest InnoTalks video, Matt Dentino for Advantech talks in detail with Danny Hsu, President of Monitoring SBU for Prowave, and Sen Wu, Product Manager of Smart I/O & Communication for Advantech, about condition monitoring trends, customer pain points for machine health, wireless technologies empowering real-time monitoring, such as LoRaWAN, real-life use cases, and more. Danny Hsu of Prowave offers his expertise for improving machine health via remote monitoring, and outlines Prowave’s ICP vibration solution that measures machine vibration and sends data back to users.

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