Create your own custom Demo in the new IBM Maximo Application Suite

[Although I work for IBM, the style and combination of words as they appear here are my own and are not IBM official statements]

I just published a new Health on Maximo Application Suite 8.3 Lab. It can be run either standalone or as a continuation of the Monitor Lab which was first published in December 2020 (and updated last month).

Since Christmas last year, I have had the chance to work a lot with the new Maximo Application Suite 8.3 release (aka MAS83). Running on a Red Hat OpenShift cluster that can be deployed on most Cloud providers or on premise, the MAS83 homepage appears to the user as one single point of entry to many integrated modules. It is fantastic !

In this version of the 2 labs, the students will use MAS83's Monitor, Manage and Health components. By the end of the labs, they will have gained a good understanding of how each module works and how they all integrate together, within the frame of a generic 'Asset Performance Management' story. The labs are fully data driven, they use generic IoT reading names (Temperature, Pressure etc) and generic asset names (i.e. CL_Asset_1), but instructions are provided at the beginning to enable students to use other readings and other asset names if they wish to. I really tried to make the labs easy and clear, with many images showing exactly what needs to be done and referring clearly to a step number. Ultimately, I hope this will enable students to create any custom MAS demo they need, relevant to any asset or readings they have.

Starting from scratch, and step by step, the students will:

In the Monitor Lab

Use Monitor's embedded Watson IoT Platform to create their own IoT readings corresponding to the 'standard operating conditions' of a simulated asset (e.g. Temperature between 35 and 40 Celsius). Then create short bursts of anomalous readings (e.g. Temperature above 46 Celsius) and, via the use of physical and logical interfaces, send the IoT data to Monitor's data lake.

Discover Monitor's capabilities, including creating new data items and discovering Monitor's rich functions catalog. Learn about Anomaly Detection possibilities (supervised or unsupervised) and use Monitor's out of the box Anomaly Detection machine learning models to detect the IoT anomalous readings that were earlier generated in the Watson IoT platform. Then learn how to create dynamic alerts based on them. Finally, discover how to create and edit a detailed summary dashboard that displays all the relevant data that was generated throughout the Lab. Expect 2 to 2.5 hours to complete this lab.

In the Health Lab

Use MAS83 Manage & Health to associate meter readings and other extra data to the generic asset. Define Condition Monitoring points for (some of) your readings, and generate real meter readings for your asset. Then, understand and build one by one all the Health scoring methods and cards (i.e. Health, Criticality, Risk, Age, Next PM, MRR) that will provide an overview of the health of your asset. Finally, tie the original IoT readings that flow to Monitor to the asset meter readings in Manage - thus closing the loop between the first step of the Monitor Lab and the last step of the Health lab ! Completing both Labs should give you a good understanding of how a real Condition-based maintenance regime could be achieved in your organisation. Expect 2 to 2.5 hours to complete this Lab.

Note that - as per the prerequisites -, these labs assume that you have a fully working and integrated environment set up and the IDs required to access it. These labs do not show how to set up such a MAS83 integrated environment. Also, these labs are delivered as-is, and are not formal IBM documentation.

I hope you enjoy the labs - please do not hesitate to send me your comments, any issue, suggestion etc.

I thank a lot of people without whom I could not have built those labs in the About & Feedback section, but a special shoutout here to Arif Ali and David Boggs who provided such a great support as I was heavily testing the systems while building this.