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[Page last updated on 18 February 2021]

HEALTH Lab on Maximo Asset Health Insights 7.6.1

Disclaimer

This Lab is provided as-is and does NOT represent formal IBM documentation in any way. Please send any feedback directly to Christophe Lucas.

Before you begin: You must have completed the 1. Generate IoT data section of the MONITOR lab before starting this HEALTH lab. Note that it is not required to have completed the second 2. Monitor IoT data section to go on here.

0. Objectives

In this Module you will:

  • set up the required Assets and Meter Groups in Maximo,
  • register your IoT Devices and associate them to Maximo Assets and set up the required mappings between your IoT readings and Maximo Assets Meter readings.
  • create a sample Scoring Method to view the health of your Assets
  • create a final dashboard and retrospect on the data that we have been using since the start.

1. Setup Assets, Meters & Condition Monitoring in Maximo

1. Create 3 Assets & 1 Query in Maximo

  1. In Maximo, click the Go To Applications - Asset Menu. Click the + button to create an Asset, enter CL_Asset_1 in both the Asset ID & Description fields. Click Save. Repeat this step for CL_Asset_2 and CL_Asset_3.
  2. Click the List View menu. In the Asset field, enter CL_Asset*, click enter. This should return the list of your 3 just-created CL_Assets. Click the Save Query button, enter CL_Assets in both the Query Name & Description. Tick the Public box. Health1 

2. Create a Meter Group

In this section, we will create a maximo Meter Group containing 8 Meters that we will later associate to the IoT readings that we defined in the first section of the MONITOR lab.

  1. In Maximo to-left Find Navigation Item box, enter the Meter Groups application.
  2. Click the + button to create a Meter Group, enter CL_Asset in both the Meter Group & Description fields.
  3. Click New Row and in the Meter field, click Select Value. In the Select Value window that opens, enter Temp in the Meter field, hit Enter, select TEMP-C.
  4. Repeat previous step with the following Meters: VIBRATIONH, PRESSURE, SPEED, ACCELERAT, LOAD, TORQUE, STARTS. Click the Save button.

Note that, although Meters like PRESSURE often exist in Maximo installations out-of-the-box, some of the Meters appearing in step 4. might not exist in Maximo yet. In which case, do the following: (a) Go to the Meters menu via Find Navigation Item, (b) click Create new Meter, enter e.g. ACCELERAT (the maximum name length is 9 ), select GAUGE as Meter Type, then Save. That newly created Meter can now be added to the Meter Group in step 4. Health2 

3. Associate Meter Group to Assets & create Meter Readings

  1. In Maximo, click the Go To Applications - Asset Menu. In the Asset field, enter CL_Asset*, click enter. This will return the list of you 3 CL_Assets, click CL_Asset_1.
  2. Go to On CL_Asset_1, go to its Meters tab, click Meter Group - Select Value. In the Select Value window, CL_Asset*, click enter, select the CL_Asset Meter Group. Click Save. This has loaded all the Meters we defined in the Meter Group.
  3. In left Find Navigation item box, enter Enter M, click Enter Meter Readings. For each Meter, enter values within the ranges that we defined for the IoT readings at the beginning of the Monitor lab in 2. Create IoT Simulation. For example: TEMP-C = 37, VIBRATIONH = 4, PRESSURE = 22, SPEED = 17, ACCELERAT = 9, LOAD = 100, TORQUE = 12, STARTS = 1. Click OK.
  4. Repeat steps 1. to 3. for CL_Asset_2 and CL_Asset_3 with whatever Meter values you want. Health3 

4. Create a Condition Monitoring Rule

We are now going to create a Condition Monitoring rule. The ultimate idea here is that we will create upper and lower limits for the Meter Readings which, when passed, can automatically trigger work orders. Because we will later tie our original IoT readings from the Watson IoT Platform to Meter readings in Maximo, this will literally allow us to move towards a real Condition Based maintenance regime !

In this exercise, we will create such a rule for just 1 Asset (CL_Asset_1) and 1 reading (TEMP-C), but you can of course create more rules for other Assets and/or other readings.

  1. In Maximo, click the Go To Applications - Condition Monitoring Menu. Click the + to create a new Condition Monitoring. Name it CL_Asset. In the Point and Description fields, enter CL_Asset*. Next to the Asset field, click Select Value, search for CL_Asset_1, select it. Next to the Meter field, click Select Value, search for TEMP-C, select it.

  2. In the Upper Warning Limit field, enter 40, in the Lower Warning Limit field, enter 35. In the Upper Action Limit field, enter 45, in the Lower Action Limit field, enter 30. Note that those values roughly correspond to the "temperature": random(35,40), values we originally defined in our IoT Simulation. With those limits defined, Condition Monitoring should pick-up those anomalous "temperature": random(46,48), we generated !

  3. In the Upper Limit Job Pan field, click Select Value and select whatever existing Job Plan you want (we're just doing a demo here !). Do the same for Upper Limit Job Pan. Click Save. Your final screen should look like picture below. Health4 

2. Map IoT Devices & Readings to Maximo Assets & Meters

1. Register IoT Device Type as an Asset

[As earlier mentioned, this step assumes that the integration between the Watson IoT Platform and Maximo Reliability Engineer work centre exists. If not, here are the Integration Setup Instructions].

  1. In the left Find Navigation item box, enter Rel, click Reliability Engineer. This will open the Reliability Engineer work centre. In the left menu, click Integration. Click Next 3 times through the Select IoT Service then Configure IoT Service then Configure End Points then Register Device Types.

  2. On the Register Device Types page, select CL_Asset, click Register as Asset then Next. This will take you to the Map Data Schema page. Health5 

2. Map IoT Readings to Maximo Meters

  1. On the first Schema tab of the Map Data Schema page, tick Detect from a connected device and From first available then click Get now. If your IoT Simulation is still running, this will return a .json string similar to this: {"acceleration":10,"load":99,"temperature":39,"torque":14,"pressure":22,"vibration":2,"starts":86,"speed":19}. If that string is not returned (because e.g. your IoT Simulation is not running at this time), you can manually enter this value in the field. Click Save then switch to the Device Type Mappings tab.
  2. Click Add Mapping, then Select Meter. Find and select TEMP-C - that's the Maximo Meter. On the IoT Device Type Property, select temperature - that's the IoT Reading. In the Data Collection section, tick Aggregated with Value = AVG and Time Period = Hour. This means that once every hour, a Meter reading will be created with a value equal to the average of your IoT Readings for the past hour.
  3. Repeat steps 2. to 3. for the other readings, i.e. VIBRATIONH, PRESSURE, SPEED, ACCELERAT, LOAD, TORQUE. For STARTS, select COUNT instead of AVG. Health6 

3. Associate IoT Devices to Maximo Assets

  1. Move to the Associate Devices top-menu. On the first Associate Assets tab, filter on CL_Asset. This will display 1 row for each Asset and Meter, i.e. 8 rows per Asset. On all CL_Asset_1 rows, click the Device Type column, select CL_Asset, then on the next column, select CL_Asset_1.
  2. Repeat step 1. for all other rows corresponding to CL_Asset_2 and CL_Asset_3. Do not forget to click Save.
  3. Once that is done, those 24 rows will have moved to the Manage Assets. Health7 

3. Create Scoring Method and Dashboard

1. Create required Scoring Factors

Note that in most Maximo installations, some of the Meters like e.g. TEMP-C might already be defined as Scoring Factors. However, the Meters that we defined in 2. Create a Meter Group do not exist as Scoring Factors yet and we will define them in this. We will just use the sample of the Torque Meter here.

  1. Go to the left Scoring menu. Click on the Scoring Factors. Check which ones of the 8 Meters we defined already exist here. For each one which does not exist, click Create Factor.
  2. In the page that opens, click Select Meter, and search for e.g. Torque and click.
  3. Enter Torque in Factor Name. In the High Threshold, enter 15, and in the Low Threshold, enter 10. These threshold values are close to the range of the readings we defined for the associated IoT Reading in our initial IoT Simulation. Tick the Use Condition Monitoring ? box and click Save. Repeat this steps for all other Meters which do exist as a Scoring Factor yet. Health8 

2. Create Scoring Method

In the Health part of APM, we want to provide reliability engineers and maintenance professionals with a near real-time visibility of the health of their Assets. The health of an Asset is defined by a configurable Health Score. In this exercise, we will define a Scoring Method for the 3 CL_Assets we created.
A Scoring Method is defined by a 100% mix of 1 or n Drivers, each Driver being made of 1 or n Scoring Factors, each Scoring Factor corresponding to a Meter Reading value, and each Driver having a Weight expressed in %.

  1. Click the Scoring Methods tab and click the top-right Create Method. Tick the Multiple Drivers box and Next.
  2. In the Method ID and Description fields, write CL_Asset, click Next.
  3. In the Select Query field, search and click our earlier created CL_Asset query - you will see our 3 CL_Assets appear, click Next.
  4. In the Best Score enter 100, in the Worst Score enter 0. Click Save. Health9 

Let's now build this CL_Asset Scoring Method:

  1. Click the CL_Asset scoring method you just created. Click Create Driver. In Driver Name, enter Temperature, Vibration & Pressure. In the Weight field, enter 60. Tick the Use Factors? box.
  2. Click Select Factors. One by one, search and select the following factors and give them the following weight: TEMP-C = 60, VIBRATIONH = 20, PRESSURE = 20. Keep the Zero Override unticked. Click Save.
  3. Repeat steps 1. and 2. for (a) a Driver called Speed & Accleration (weight at 20) with the following Factors and associated Weight: SPEED = 50 and ACCELERAT = 50, (b) a Driver called Torque, Load & Starts (weight at 20) with the following Factors and associated Weight: LOAD = 25 and TORQUE = 50 and STARTS = 25.
  4. Back to the Scoring Methods menu, make sure you click the Active tick next to CL_Asset. Health10 

2. Create a new Card and contemplate your great work !

  1. Go to the Health left menu, and on the top-right, click Add Card. In Insight App, select Asset. In Insight Type, select Saved Query. In Insight Content, select your earlier created CL_Assets query. Click Save.
  2. This will create a new CL_Assets card, open it. This screen will list your 3 CL_Assets on the left, each with a Health Score, and provide a Health Summary of your 'fleet of assets' on the right. Click CL_Asset_1.
  3. First watch the Asset Health tab which details the 3 Drivers and associated Factors we created in the previous exercise. NOTE: if no score appears here on the first time, click Refresh Score and wait a couple seconds.
  4. Move to the Meter Reading tab. Observe that he TEMP_C Factor for which we defined a Condition Monitoring rule earlier is coloured. Click TEMP-C factor and Vie Selected Meter.
  5. In the Meter History, click Week or Day and wait a couple seconds. You can zoom in and out by using your mouse and 'drawing rectangles'. Notice several things here: (a) the red and orange lines correspond to the Condition Monitoring rules we defined here, (b) the green dots correspond to the Maximo Meter Readings we entered here, (c) the black lines actually are ... those same IoT readings we generated in the first steps of our MONITOR lab !
  6. As a final step, just remind yourself of how really integrated all this was: the anomalous IoT readings that we created and saw in the Watson IoT Platform on 30 November 2020, around 04:50 PM, were spotted by the Anomaly Detection functions that we created in Monitor, and are visible, finally, in this last HEALTH screen.

Health11 

Congratulations, again - you are now DONE with the HEALTH lab !

Do not hesitate to re-do all by creating your own assets, readings, anomalies, dashboards etc and by bringing your twists in ...