Machine Condition Monitoring – Benefits, Parameters and Solutions
How to maintain machine health, improve equipment efficiency and reduce shutdowns with web-based parameter monitoring and alarms.
Condition monitoring is becoming increasingly important and is applied in various industries such as manufacturing, steelmaking, food, robotics and packaging. Machine condition monitoring drives the product quality, improves the OEE and prevents downtimes. Condition monitoring monitors important parameters of the machine and other connected equipment - such as pressure and temperature - and looks for signals that a failure is imminent. This allows maintenance to be scheduled or other actions to be taken to prevent consequential damages.
The use of condition monitoring has a positive effect on the health of a machine (or the processes behind it). The Industrial Internet of Things has made it possible to monitor the machine’s condition without being physically present during up- or downtimes.
Condition Monitoring using a Web-based IoT Platform
Unscheduled downtimes of machinery and equipment reduce product and service turnaround times, leading to higher production costs and potential loss of revenue. IoT and web-based condition monitoring tools increase the production equipment efficiency throughout the life cycle of a machine.
An Industrial IoT platform – with condition monitoring features – helps protect against this unwanted downtime. Manufacturers are increasingly turning to IoT-driven machine condition monitoring to identify equipment issues that can affect the quality of production and to replace equipment before it gets worse. Remote troubleshooting and a maintenance plan to avoid costly downtimes is how they convert data into value.
Remote monitoring with an IoT platform supplier has the following advantages:
- Reduced implementation costs;
- Integration with other management systems (using API);
- Continuous updates and 24/7 monitoring.
The most important aspect is to get started quickly, and to create a solid foundation that allows you to capture the most complete machine data possible.
Curious to see how you can get started with condition monitoring in your operations using IXON? Then get in touch and an IXON expert will show you how to get the best out of your machines.
Getting started with Machine Parameter Monitoring
It’s easy to get started with a machine condition monitoring program. Most conditions can be easily measured by affordable sensors often connected to a PLC to keep track of important condition parameters. Data logging starts at the edge where the data is collected directly from the equipment, prepared and transferred to be stored in a well-secured database of the IoT platform. IXON’s intelligent measurement and control device, in combination with the web platform, allows fast and secure data transmission.
The first thing that needs to be set up is the collection of long-term (historical) data during stable machine operations. The historical data set, with condition records collected over time (e.g quarter or year), can be used for advanced machine learning algorithms that analyse and detect causal correlations in the incoming data records.
This IoT-driven approach makes it possible to detect equipment health by monitoring the machine parameters such as vibration frequency, rotations, engine temperature and ambient variables (e.g. temperature and humidity). Manufacturers in various industries can use IoT to monitor the condition of machinery and to check the quality of the products and components manufactured on it using dashboards.
Tip: When using an end-to-end IIoT solution like IXON Cloud, the IoT connectivity devices are fully integrated which makes setup really easy. IXON offers a solid infrastructure that makes it possible to capture machine data in no time.
Defining the right parameters to monitor
Condition monitoring allows you to adjust your schedules to actual performance, maximizing uptime and eliminating unwanted costs. Different machines are used in the industry. That’s why you need to select the right parameters and measure them over time to monitor or deliver condition-based maintenance.
Most machine and process characteristics that affect quality, availability, capacity or safety are continuously assessed over the lifetime of an asset. We have listed some key metrics that our customers use to track these characteristics.
Build your own real-time dashboards for Equipment Performance Monitoring
A web-based diagnostic system monitors critical components by logging their condition periodically or when it changes. This data, presented in real-time dashboards, makes analysing and predicting component failures tangible for operators and maintenance engineers. When the state of a parameter enters a critical value (or within a period of time), they must be informed and take action to prevent worse.
Starting quickly is the most important thing to do when setting up condition monitoring using data visualisation with the key metrics of your machine/process. Therefore a solid and easy to use dashboard builder will help you speed up this process. Compose your dashboards with the right data widgets, which represent your machine parameters in actual, average, min or max state. Or calculate the correct value (from one or a combination of parameters) on the PLC and present that value in your dashboard.
Display beautiful, intuitive charts or graphs to visually monitor individual components from the machine. Use data widgets to build your own reports and display them in your apps and web-portal. Create instant machine analysis for temperature, pressure, vibration and anything else you need to track with an unlimited number of dashboards and users.
With the IXrouter and IXON Cloud platform, engineers have a turnkey solution that covers not only condition monitoring but also remote maintenance and alarming for the machine and user-friendly asset management.
Moving Toward Predictive Maintenance and Alarms
Early warning (regardless of location) prevents unplanned downtime of machines and equipment. We’ve already pointed out that predictive maintenance is impossible without well-structured (historical) data. The results are displayed on your monitoring dashboard, and the values can be used to set up smart alarm triggers.
Predictive maintenance is based on data to determine the probability of a machine failure before it occurs. Triggers or conditions consist of a set of rules to match this data. When the data reaches a critical point, an alarm can be triggered to actively alert the operator or technician. This way you are always informed about the diagnosis of the machine wherever you want (any location) and you can identify and solve upcoming problems.
An open platform to connect apps for all your machine monitoring needs.
With IXON Cloud you can go beyond component and in-depth machine monitoring. When you build an app or connect to a platform that delivers next-generation monitoring or artificial intelligence the data of the machine, you need to combine machine, process and human data to give you real-time production visibility. That’s why we provide an API (well-documented in our Developer portal) to allow you to retrieve and integrate this data with other applications or platforms.
One of the many examples is IOdash, our customer who has created a comprehensive monitoring platform on top of IXON Cloud that combines data from multiple sources.
Curious how you can get started with online condition monitoring in your business operations? Get in touch and an IXON expert can show you how to get the most out of your machine monitoring. Or take a look around in our demo platform.