Interested in better monitoring the health of your assets? Want to learn how to use various components of the PI System to enable both usage-based and comparison-based methods of condition based maintenance (CBM)?
In this course, you will learn how to use AF templates and asset analytics to implement advanced logic to evaluate your equipment's health, as well as how to use PI Notifications to receive alerts based on deviations in your process data. Additionally, you'll see how easy it is to use tools like PI Coresight and PI DataLink to visualize important information about your equipment and make informed maintenance decisions.
This course is self-paced for your convenience. Thus, there are no live components to the course, nor are there are required login hours. Please use the video lectures for instruction along with the course exercises to gain hands-on experience working with key concepts. Most importantly, get involved in the discussion forums here on the PI Square community and interact with your peers and experts both at OSIsoft and other organizations, post questions, answer questions posted by others, and overall help each other learn as you would in a classroom environment.
If you’re enrolled in a facilitated session of this course, you also have the opportunity to earn a certificate of completion by submitting a final project to your course facilitator. Please see the final project for details.
This course is primarily suited for operators who are considering implementing a condition based maintenance (CBM) strategy. It is for someone who wants to help their organization eliminate unnecessary maintenance, minimize unexpected failures, maximize use of resources, increase reliability and availability, and extend the lifetime of various assets.
Overall, this course is intended for those interested in how the PI System can enable a proactive strategy driven by the actual condition of an asset rather than planned calendar-based maintenance schedules.
No 3rd party / CMMS integration is currently covered in this course.
Basic knowledge of the PI Asset Framework.
Each learner will be required to use their own software and their own data structures. This allows each learner to leave the course with something immediately valuable in their enterprise.
This course uses the Asset Based PI Example Kit for Pump Condition Based Maintenance as the basis for it's AF structure. This, along with all of our other Asset Based PI Example Kits, can be downloaded and imported into your own AF Server, enabling you to get hands on experience with the same sample data! There is also an Asset Based PI Example Kit for Condition Monitoring, although it is not used in the videos for this course.
However, this course will not cover installation of the AF Server or PI client tools, so students needs to ensure they have the following:
Students should also have read access to PI Point data on their organization's PI Data Archive, and optionally the permissions to create PI Points and write data to them.
Below are the video lectures for this course. We have placed the topics in the same order as they would be presented in a live instructor-led course. However, feel free to view the videos in any order, spread over any interval. You can also rewind and rewatch parts of the videos that you need to view again. Also be sure to check out the Online Course Videos - Tips and Tricks if your videos look fuzzy!
Introduction to CBM and the PI System
Optional - For more information on the AF Example Kit used in this course, please watch the following video before continuing with the other course videos
Demonstrating CBM within the PI System
Deep Dive into Sample CBM Logic in PI AF
For more information on Condition Based Maintenance (CBM), please check out the CBM Guidebook available here.
Want to earn a certificate in this course? Register for the next session here.
Currently enrolled in the course? Jump to the discussion forums here.
The following exercises serve to reinforce the concepts learned in the course videos. You should think about the processes and AF model at your own facility and utilize the skills taught in the video lectures to complete the following exercises.