27 August 2022 | Published by : Baturi | Views: 18 | Category: Tutorials
Practical Process Control Monitoring And Diagnostics
Last updated 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.38 GB | Duration: 6h 58m


Become an expert at monitoring PID controllers and responding quickly to problems.
What you'll learn
Become skilled in understanding process control quality monitoring criteria and statistics.
Master the use of control performance monitoring software Apromon and the technology behind it.
Become skilled on the application of online adaptive control technology using the control quality monitoring software.
Learn how to identify control problems in an online/real-time manner and take immediate corrective action using online adaptive control.
Learn how to significantly improve control quality at their plants, move the plant more stably and reliably in the direction of increasing profits.
Requirements
2-year or 4-year degree in engineering or operations and/or a few months of plant/ engineering experience is desirable, but not required.
Description
Chemical plants can have anywhere from about 50 PIDs in small plants to over 2000 PIDs in large refineries and integrated petrochemical complexes. In addition to simple PIDs, there are cascades, override controllers, model-based controllers, and multivariable controllers.As time goes by, even well-tuned PIDs and other controllers can slowly start to deteriorate. As deterioration progresses, process oscillations can start with small amplitudes and can grow large over time costing the plant significant monetary and/or quality losses. Or conversely, PIDs could become sluggish because of changes in process and operating conditions, once again causing the control quality to deteriorate.This course covers the technology and application of a control performance monitoring software (Apromon) that identifies poorly controlling PIDs (including single, cascade, override and complex PIDs). Apromon runs online using OPC and calculates several control criteria and generates control quality reports. Integrated with Apromon is a novel, breakthrough algorithm called TAD (True Amplitude Detection) that accurately isolates oscillating or sluggish controllers. This course shows how to improve and maintain the plant's primary and advanced control system and increase the plant's profits.This course explains how to identify control problems in an online/real-time manner and take immediate corrective action using online adaptive control. The course also shows how to implement true adaptive control inside the DCS by connecting the control quality monitoring software using OPC technology to the DCS/PLC and by designing special DCS/PLC-resident logic for triggering automatic control action.Learning Outcomes:At the end of the course, attendees will be skilled in understanding process control quality monitoring criteria and statistics. They will be skilled in the application, installation, and use of real-time software products for process control quality monitoring at any plant.Attendees will also be skilled in the application of online adaptive control technology using the control quality monitoring software and then linking it with closed-loop DCS based-adaptive control schemes. Using the knowledge, attendees on their own can build closed-loop adaptive control schemes at their plant inside the DCS/PLC using OPC connectivity.Attendees will be able to significantly improve control quality at their plants, and move the plant more stably and reliably in the direction of increasing profits with fewer shutdowns and fewer abnormal events. The plant will also see a reduction in the number of alarms and a reduced need for operator intervention. The following topics are covered in this course:Modern process control in plantsProcess interactions because of mass balance and heat balance integration Potential for process cycling and sustained oscillationsCauses of process oscillationsPitops simulations illustrating different oscillation casesPitops simulations illustrating excessive control valve movement Pitops simulations illustrating sluggish controlDefinition of various process control quality performance criteria Explanation of special new terms – crimp, cheat, vacillation, rope length, etc. Component breakdown of PID contributionsUse of process control monitoring software – Apromon-Excel Run example cases on Apromon-ExcelMore explanation of process control quality performance monitoring criteriaConduct what-if studies for example using Apromon-ExcelAdjust and understand oscillation tuning parametersSet up online OPC servers to simulate real-plant environment Use of Apromon-OPCRun example cases on Apromon-OPCImplement Apromon-OPC using the OPC simulation serverMore explanation of process control quality performance monitoring criteria Procedure and tips on implementing Apromon-OPC in a plant environmentNeed for detection of online oscillation in an industrial process Need for detection of sluggish control in an industrial process. Precise determination of oscillationPractical challenges of detecting oscillations reliably Understanding of true amplitude detection) algorithmSetting up Apromon-OPC and configuring it in online/real-time modeImplementing online adaptive control using DCS, Apromon, and a OPC server-based computer
Overview
Section 1: Introduction to Process Control Monitoring and Diagnostics
Lecture 1 Need for Process Control Monitoring and Diagnostics
Section 2: Error, Control Tightness, Dis-symetry and Master-Slave Criteria
Lecture 2 Error, Control Tightness, Dis-symetry and Master-Slave Criteria
Section 3: Oscillation Criteria
Lecture 3 Oscillation Critera
Section 4: Interaction Criteria
Lecture 4 Interaction Criteria
Section 5: Saturation, Signal, Control Valve, PID Tuning, Onstream Factor, Overall Health
Lecture 5 Saturation, Signal, Control Valve, PID Tuning, Onstream Factor, Overall Health
Section 6: Statistical Quality Criteria
Lecture 6 Statistical Quality Criteria
Section 7: Statistical Control Charts
Lecture 7 Statistical Control Charts
Section 8: Data Distribution Characterization and Confidence Intervals
Lecture 8 Data Distribution Characterization
Section 9: Data Transformations and Smoothing
Lecture 9 Data Transformation and Smoothing
Section 10: Apromon Online Control Monitoring Software
Lecture 10 Apromon Online Control Monitoring Software
Process Control Engineers, Advanced Process Control Engineers and Instrument Engineers,Lab Technicians and DCS/PLC Technicians,Managers and Supervisors


Homepage
https://www.udemy.com/course/practical-process-control-monitoring-and-diagnostics/




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