comma CMMS equipment maintenance blog
Machine health and maintenance quality visualizer and integration with comma CMMS.
Published 2023-07-12 by Rui J Alves (a 4.4 minute read) | Back to the main page
A new add-on feature we have been thinking about for quite some time has finally seen the light of day as a proof-of-concept.
We developed a machine simulator where we can virtually start and stop machinery and create issues that are then reported to comma CMMS. comma CMMS responds by issuing automatic work orders and corresponding notifications if the readings are judged to be of a failure mode. Failure detection algorithms are fully customizable and can be as simple as values out of bounds and as complex as analysis of a combination of multiple operational parameters along with time considerations.
PICTURE 1: our machine simulator interface. You can see that we can have up to 5 parameters per machine (simulator limit, not product limit) and that currently machine 1 (Axis #1) is running with no faults. All other machines are currently stopped.
Conceptually, any device that can report operational data can be used as a source of information. This includes sensors already used in the control process (data would be made available at the PLC level) or data sources that already aggregate system data like BMS alarm lists. In short, if the system under analysis makes data extractable then we can potentially tap into that source and poll relevant data which we place on our own database that is constantly monitored for failures which trigger comma CMMS.
PICTURE 2: Work order automatically generated when a failure was detected; notifications can be sent on these situations.
PICTURE 3: As with any other custom module, these scripts are perfectly integrated into comma CMMS and appear as an additional option on the user's menu.
Additionally to the behaviors described above and since we are already storing operational data on a database, it is only a matter of building a visualizer to assess the current and past condition of devices. Going even a step further, we can also simultaneously look at the maintenance database and implement KPI algorithms that provide a real-time assessment of the quality of maintenance actions. Putting everything together we end up with a general operational dashboard that implements a hierarchy of views of both devices and maintenance as can be seen on the following images.
PICTURE 4: the top level of the devices health and maintenance health. The top level can be left very simple. In this case, both the equipment and maintenance performance is good (green). Visualization is provided by Grafana in this case.
PICTURE 5: details of the devices area. Drilling down on the hierarchy we are able to look at all system's health in more detail.
PICTURE 6: Machine details. You can see that the voltage parameter has just crossed the upper boundary. On this example, this is cause for the creation of an automatic work request.
PICTURE 7: Maintenance details and KPI compliance visualizer.
Implementation challenges are diverse, the first relates to the complexity and costs of the infrastructure required if additional sensors are to be installed on-site which is of particular concern if this is a retrofit installation. Usually, it will probably be more reasonable to install devices on the most absolutely critical equipment that is not already the subject of process monitoring. Another challenge for cases where the information is aggregated on a central computer (which is an advantage in itself) is the lack of standards which will require custom development for each case which carries additional costs. The overall additional costs whether the site is new or old is possibly the biggest hurdle as the cost-benefit balance of this solution may be hard to justify since it is not a common application even with the popularity of the IoT concept which is where all these concepts originate.
Surely there are applications where the trigger of automatic work orders is an advantage and well worth the implementation cost as the fault resolution process starts at the detection of failure and the digital paper trail can be traced all the way through conclusion while recording all the steps and resources involved. Parafernalia, Lda., as the original developer and application consultants of comma CMMS are able to integrate all the components required to implement this device health and maintenance solution in any industry where efficient equipment upkeep is required. Contact us anytime at info@commacmms.com