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PI System: From Data Exploration to Notification

Learn more about how the features of the PI System can work in concert to successfully address an operating problem from actual process data.

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About this course

This lab targets PI System Users wanting to learn more about how the features of the PI System can work in concert to successfully address an operating problem from actual process data. It takes students through the process of data exploration, process modeling, operationalization and notification. Only PI System tools will be used.

By the end of the course, you will be able to...

  • Develop a rule for identifying EF’s based on process conditions.
  • Configure AF Analytics to generate advanced descriptive features impacting the predictive expression used to model the process.
  • Data Engineering with PI Integrator and Power BI will identify best modeling features.
  • Model development using DataLink and Excel.
  • Operationalization using AF Analytics, PI Notifications with PI Vision link contacting asset and time context.

Audience

This course is designed for: PI Users

Level: Intermediate

Study time: 4 hours

Course Access: Unlimited access to all content except the Training Cloud Environment (TCE). You have 30 days access to the TCE starting on the day you access module section "Launch Cloud Environment". 

After those 30 days you can purchase additional access with one of the two options below:

Prerequisites

This Course Includes...

  • Videos, discussion opportunities and quizzes to help you learn the material
  • A Cloud Environment accessible for 30 days and configured to complete all the exercises in the course
  • This course is self-paced for your convenience. Thus, there are no live components to the course, nor are there required login hours. Please use the video lectures for instruction along with the course exercises to gain experience working with the key concepts presented.
  • There is a final quiz which you must pass to obtain a certificate of completion.
  • Once you register for a course, you will have access to the course materials 24/7 on this website.

Further Information

  • The course is accompanied by an Azure-deployed virtual environment and a workbook, which allows you to walk through the contents in detail at your own pace.
  • This is a self-paced course. Any questions or assistance needed about the material can be asked in this course's space in the OSIsoft PI Square community
  • When you complete the examination at the end of the course, you will receive a certificate of completion which can be shared and directly posted on LinkedIn.
  • For more information about our Online Courses please visit our FAQ page

Software Requirements

  • PI Data Archive - 2018 SP3
  • PI Asset Framework (PI AF) server - 2018 SP3
  • PI Asset Framework (PI AF) client (PI System Explorer) - 2018 SP3
  • PI Analysis & PI Notifications Services - 2018 SP3
  • PI Vision - 2019
  • PI Integrator for Business Analytics - 2018 R2 SP1
  • PI DataLink - 2019 SP1 (5.5.1)
  • Microsoft PowerBI
  • Microsoft Office or equivalent is required to access the workbook and presentation provided.

Course Material

Curriculum

  • Getting Started
  • How to Navigate This Course
  • Discussion Forum
  • Offline Course Videos for Blocked YouTube Users
  • Course Workbook
  • Course Presentation
  • Training Cloud Environment
  • Launch Cloud Environment
  • Lesson 1 - From Data Exploration to Notification
  • Introduction (8:45)
  • Gathering Domain Knowledge (11:14)
  • Step-by-Step Guide to Complete ‘Gathering Domain Knowledge’ and ‘Process Improvement Idea’
  • Supporting AF Models and Features (4:22)
  • Step-by-Step Guide to Complete ‘The AF Model’
  • Lesson 2 - Exploration and Data Engineering
  • Objectives, Scenario and Approach (4:38)
  • "Good" Operating State (10:12)
  • Step-by-Step Guide to Complete ‘Good Operating State’
  • "Better" Operating State (10:48)
  • Step-by-Step Guide to Complete ‘Better Operating State’
  • "Best" Operating State (6:06)
  • Step-by-Step Guide to Complete ‘Best Operating State’
  • Add Descriptive Operating Features (12:18)
  • Calculate Dryer Utilization Metrics
  • Lesson 3 - Contextualization and Data Preparation
  • Objectives, Scenario and Approach (3:00)
  • Prepare Dryer Regeneration Features: Event Frame Template (4:45)
  • Step-by-Step Guide to Complete ‘Prepare Dryer Regeneration Features - Event Frame Template’
  • Prepare Dryer Regeneration Features - Asset Analytics (7:12)
  • Step-by-Step Guide to Complete ‘Prepare Dryer Regeneration Features – Asset Analytics’
  • Generate Regeneration Data for Analysis (5:02)
  • Step-by-Step Guide to Complete Generate Regeneration Data for Analysis
  • Lesson 4 - Data Analysis and Qualification
  • Objectives, Scenario and Approach (3:34)
  • Problem Assessment PI Integrator for Business Analytics & Power BI (4:51)
  • Step-by-Step Guide to Complete 'Problem Assessment - PI Integrator for Business Analytics and Power BI'
  • Assessment of Dryer Regeneration Data in Power BI (2:50)
  • Step-by-Step Guide to Complete 'Assessment of Dryer Regeneration Data in Power BI'
  • Model Development PI DataLink (8:08)
  • Step-by-Step Guide to Complete 'Model Development - PI DataLink'
  • Lesson 5 - Operationalization and Notification
  • Objectives, Scenario and Approach (0:55)
  • Forecast Deployment, AF Analytics (8:52)
  • Step-by-Step Guide to Complete 'Forecast Deployment - AF Analytics'
  • Proactive Solution, PI Notifications (1:12)
  • Analysis for Event Frame Generation (7:10)
  • Step-by-Step Guide to Complete 'Analysis for Event Frame Generation'
  • Create a Notification Rule (1:10)
  • Step-by-Step Guide to Complete 'Create a Notification Rule'
  • Configure Notification Message Format (5:26)
  • Step-by-Step Guide to Complete 'Configure Notification Message Format'
  • Confirming Notifications (1:40)
  • Step-by-Step Guide to Complete 'Confirming Notifications'
  • Lesson 6 - Summary
  • Revisit Learning Objectives (1:18)
  • Lesson 7 - Appendix
  • Predictive Model Development and Variable Selection
  • Final Exam
  • Final Exam
  • How did it go?
  • Course Evaluation

About this course

This lab targets PI System Users wanting to learn more about how the features of the PI System can work in concert to successfully address an operating problem from actual process data. It takes students through the process of data exploration, process modeling, operationalization and notification. Only PI System tools will be used.

By the end of the course, you will be able to...

  • Develop a rule for identifying EF’s based on process conditions.
  • Configure AF Analytics to generate advanced descriptive features impacting the predictive expression used to model the process.
  • Data Engineering with PI Integrator and Power BI will identify best modeling features.
  • Model development using DataLink and Excel.
  • Operationalization using AF Analytics, PI Notifications with PI Vision link contacting asset and time context.

Audience

This course is designed for: PI Users

Level: Intermediate

Study time: 4 hours

Course Access: Unlimited access to all content except the Training Cloud Environment (TCE). You have 30 days access to the TCE starting on the day you access module section "Launch Cloud Environment". 

After those 30 days you can purchase additional access with one of the two options below:

Prerequisites

This Course Includes...

  • Videos, discussion opportunities and quizzes to help you learn the material
  • A Cloud Environment accessible for 30 days and configured to complete all the exercises in the course
  • This course is self-paced for your convenience. Thus, there are no live components to the course, nor are there required login hours. Please use the video lectures for instruction along with the course exercises to gain experience working with the key concepts presented.
  • There is a final quiz which you must pass to obtain a certificate of completion.
  • Once you register for a course, you will have access to the course materials 24/7 on this website.

Further Information

  • The course is accompanied by an Azure-deployed virtual environment and a workbook, which allows you to walk through the contents in detail at your own pace.
  • This is a self-paced course. Any questions or assistance needed about the material can be asked in this course's space in the OSIsoft PI Square community
  • When you complete the examination at the end of the course, you will receive a certificate of completion which can be shared and directly posted on LinkedIn.
  • For more information about our Online Courses please visit our FAQ page

Software Requirements

  • PI Data Archive - 2018 SP3
  • PI Asset Framework (PI AF) server - 2018 SP3
  • PI Asset Framework (PI AF) client (PI System Explorer) - 2018 SP3
  • PI Analysis & PI Notifications Services - 2018 SP3
  • PI Vision - 2019
  • PI Integrator for Business Analytics - 2018 R2 SP1
  • PI DataLink - 2019 SP1 (5.5.1)
  • Microsoft PowerBI
  • Microsoft Office or equivalent is required to access the workbook and presentation provided.

Course Material

Curriculum

  • Getting Started
  • How to Navigate This Course
  • Discussion Forum
  • Offline Course Videos for Blocked YouTube Users
  • Course Workbook
  • Course Presentation
  • Training Cloud Environment
  • Launch Cloud Environment
  • Lesson 1 - From Data Exploration to Notification
  • Introduction (8:45)
  • Gathering Domain Knowledge (11:14)
  • Step-by-Step Guide to Complete ‘Gathering Domain Knowledge’ and ‘Process Improvement Idea’
  • Supporting AF Models and Features (4:22)
  • Step-by-Step Guide to Complete ‘The AF Model’
  • Lesson 2 - Exploration and Data Engineering
  • Objectives, Scenario and Approach (4:38)
  • "Good" Operating State (10:12)
  • Step-by-Step Guide to Complete ‘Good Operating State’
  • "Better" Operating State (10:48)
  • Step-by-Step Guide to Complete ‘Better Operating State’
  • "Best" Operating State (6:06)
  • Step-by-Step Guide to Complete ‘Best Operating State’
  • Add Descriptive Operating Features (12:18)
  • Calculate Dryer Utilization Metrics
  • Lesson 3 - Contextualization and Data Preparation
  • Objectives, Scenario and Approach (3:00)
  • Prepare Dryer Regeneration Features: Event Frame Template (4:45)
  • Step-by-Step Guide to Complete ‘Prepare Dryer Regeneration Features - Event Frame Template’
  • Prepare Dryer Regeneration Features - Asset Analytics (7:12)
  • Step-by-Step Guide to Complete ‘Prepare Dryer Regeneration Features – Asset Analytics’
  • Generate Regeneration Data for Analysis (5:02)
  • Step-by-Step Guide to Complete Generate Regeneration Data for Analysis
  • Lesson 4 - Data Analysis and Qualification
  • Objectives, Scenario and Approach (3:34)
  • Problem Assessment PI Integrator for Business Analytics & Power BI (4:51)
  • Step-by-Step Guide to Complete 'Problem Assessment - PI Integrator for Business Analytics and Power BI'
  • Assessment of Dryer Regeneration Data in Power BI (2:50)
  • Step-by-Step Guide to Complete 'Assessment of Dryer Regeneration Data in Power BI'
  • Model Development PI DataLink (8:08)
  • Step-by-Step Guide to Complete 'Model Development - PI DataLink'
  • Lesson 5 - Operationalization and Notification
  • Objectives, Scenario and Approach (0:55)
  • Forecast Deployment, AF Analytics (8:52)
  • Step-by-Step Guide to Complete 'Forecast Deployment - AF Analytics'
  • Proactive Solution, PI Notifications (1:12)
  • Analysis for Event Frame Generation (7:10)
  • Step-by-Step Guide to Complete 'Analysis for Event Frame Generation'
  • Create a Notification Rule (1:10)
  • Step-by-Step Guide to Complete 'Create a Notification Rule'
  • Configure Notification Message Format (5:26)
  • Step-by-Step Guide to Complete 'Configure Notification Message Format'
  • Confirming Notifications (1:40)
  • Step-by-Step Guide to Complete 'Confirming Notifications'
  • Lesson 6 - Summary
  • Revisit Learning Objectives (1:18)
  • Lesson 7 - Appendix
  • Predictive Model Development and Variable Selection
  • Final Exam
  • Final Exam
  • How did it go?
  • Course Evaluation