real time operational perfomance and variability supervision

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Real Time Operational Perfomance and Variability Supervision Diego Arenas CONTAC INGENIEROS CONTAC OPERATIONAL INTELLIGENCE TECHNOLOGIES Empowering your PI RtPM infrastructure

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CONTAC. Real Time Operational Perfomance and Variability Supervision. Diego Arenas CONTAC INGENIEROS. OPERATIONAL INTELLIGENCE TECHNOLOGIES Empowering your PI RtPM infrastructure. CONTAC. Why real time KPI´s?. Cost. Quality. Reliability. Efficiency. - PowerPoint PPT Presentation

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Page 1: Real Time Operational Perfomance and Variability Supervision

Real Time Operational Perfomance and

Variability Supervision

Diego Arenas

CONTAC INGENIEROS

CONTAC

OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

Page 2: Real Time Operational Perfomance and Variability Supervision

Why real time KPI´s?

MiningChemical Energy

Ore body

ROM Ore (run of mine)

Key Variables:· Ore Grade· Ore Hardness· Ore Type· Equipment availability

Low Grade Ore

Activities:· Stripping· Drilling· Blasting· Truck loading

Waste

Electrical Energy

Sulphide Ore

Oxide Ore

Process operations are complex systems, where perfomance goals are evaluated using different business KPI´s criteria.

Calidad Costos

Rendimiento Confiabilidad

Quality Cost

Efficiency Reliability

Business KPI time-frames ranges from long term “operational management control loops”, such as mine planing-mine operation, to short term, such as concentrator recovery control vs. short term program.

Despite the KPI time frame, most of the business KPI are rooted to the operation, it can be said that business KPI are built in real time.

CONTAC

Same for Steel, Pulp&paper, Petrochem, Utilities, etc.

Page 3: Real Time Operational Perfomance and Variability Supervision

The value fishbone, ...how the business KPI´s are built

A process bottleneck (leading to quality, throughput losses): a conveyor, or a pump or a control valve working at its maximum capacity or speed for an extended period of time

Calidad Costos

Rendimiento Confiabilidad

Quality Cost

Efficiency Reliability

A cascaded (and $$$$ amplified) variability: cyclone feed density variability that leads to a size variability that leads to a flotation recovery variability.

Quality losses (plus: energy, operational time, consumables, etc.): because of an inefficient operation of its regulatory system.

Business KPI´s are “built” in real time.

Gains and losses happen in real time

CONTAC

Page 4: Real Time Operational Perfomance and Variability Supervision

What we know about the process behavior?

• Large number of process variables• Complex cause-effect relationships• Different (time based) Operation Modes: drift,

noise, start-up, set point changes,

disturbances, etc.

• Large data bases for Real

Time and Historical information

about process variables and

equipment vital signs.

• How to determine early alerts if the process or machine is deviating from a pattern or moving to a new one, being an “on quality pattern”, a “throughput pattern”, a “malfunction pattern”, etc.?

• How to determine the “most influencing” factors that drives the evolution of a certain process variable or equipment vital sign KPI?

The Need: an automated system capable to online analize thousands of process variable data and generate context based meaningful information

CONTAC

Page 5: Real Time Operational Perfomance and Variability Supervision

CAPA DE PROCESOSProcess Layer

Performance Model

CAPA DE CONTROL

OutputsPerfomance

Goal

Perfomance

Perfomance Goal

Inputs

Potential Capacity ProductionCapacityFactor Factor

Factor

Factor

Factor

Factor

Critical Factor

Critical Factor

Critical Factor

Critical Factor

Inst. &CONTROL LAYER

With:

Real Time KPI index Perfomance Model

Mapping:

Op. Goals of:

Quality, Emissions

Energy, Consumables

Thoughput, etc.

CONTAC

Page 6: Real Time Operational Perfomance and Variability Supervision

Technology

• Control charts• Tree Map• Benchmarks• Star diagram• Dispersion diagram• Histogram• Other

• Statistical• Control Loop quality• Variability• Multivariable Analysis

Perfomance Tests (RtKPI) Visualization Modules

CONTAC

Page 7: Real Time Operational Perfomance and Variability Supervision

Technology, the architecture

DCS

PI System

AF Model

ACE

Calculation Engine

Operational Processes

Business Processes

Regulatory Systems

Perfomance Model

Real Time and Historical Information

Template Collection of perfomance tests (RtKPI)

The high level view

the detailed view

Visualization, reporting, alarming

CONTAC

Page 8: Real Time Operational Perfomance and Variability Supervision

Real Time variability Abnormal Op. Cond. Disturbances

Identify Measure Alert

Technology, the test template collection

Monovariate Indicator

Measures

D3 Index Scheffe’s test allows detecting important disturbances, given a determined reference

Harris’s Index Compares the variance of the controller with its minimal expected variance

Oscillation Index Index of oscillation of the controller for a given setpoint. It can also be used with a pair of related variables

Time in State Time in which the the controller has been in manual mode or another pre-defined state

Saturation % of time where the analyzed variable is above or below a certain limit

IAE Index The integral of the absolute difference between the SP and the PV

ACR Index Miao’s and Seborg’s oscillation index

FFT Index Oscillation index considering the fast Fourier transform

Standard Variation Index

Complement to the Harris’s index. It measures the deviation with respect to a reference point

Multivariate Indicator

Measures

VFA “Weight” or relative influence that a set of signals has on the variability of the process

PLS Soft-sensorsComparison between expected”and measured values (residual generation)Prediction of signal values

A collection of online KPI to:

GOAL: Business

KPI

CONTAC

Page 9: Real Time Operational Perfomance and Variability Supervision

PI-AF, PI-ACE, Technology, the implementation

The collection of RtKPI templates

A form to define the specific parameters for each RtKPI (tag´s, limits, offset, etc.)

CONTAC

Page 10: Real Time Operational Perfomance and Variability Supervision

Technology, the implementation

Applying the RtKPI to a perfomance Model

CONTAC

Page 11: Real Time Operational Perfomance and Variability Supervision

The implementation

Throughput and quality KPI

Factor A

Factor B Factor C

Ore Size

Sump Pump

Density Control Class. Harris Index

Perfomance

Calidad Costos

Rendimiento Confiabilidad

Quality Cost

Efficiency Reliability

The model is a context based representation of the Factor-Critical Factor-Cause&Effect relationships

CONTAC

Page 12: Real Time Operational Perfomance and Variability Supervision

The technology, summary

Allows for a direct mapping between the Business KPI and its Real Time drivers.

Allow for the implementation of an automatic, online perfomance supervision system, working in a 24x7 shift…

A scalable and modular technical architecture. Plants, Lines, Processes, Equipment models can be implemented.

Since the calculated index are sent back to the plant historian, the values can be trended, alarmed, shown on process diagrams, reported, e-mailed, etc.

CONTAC

Page 13: Real Time Operational Perfomance and Variability Supervision

The Implementation

DCS

PI System

AF Model

ACE

Calculation Engine

Operational Processes

Business Processes

Regulatory Systems

Perfomance Model

Real Time and Historical Information

Template Collection of perfomance tests (RtKPI)

Configurable RT Analysis

• Read data from PI

• Calculate Rt KPI

• Send calculated data to PI (as PI Tag´s)

---RT-Continuously-24x7---

AD-HOC -Project specific-(PI-PB, DL, WebParts, etc.)

RtIndex visualization, reporting and alarming

CONTAC

Page 14: Real Time Operational Perfomance and Variability Supervision

Implementation example

Reminder:

1. Core system: KPI templates, PI-AF/ACE calculations are standard

2. Reporting and visualization are built using standard PI-RtPM tools

3. Nevertheless, even PB and DL are project specific, since the construction are made using PI-AF context based models, it can be reused for other applications.

Again: what will be shown is a PB+DL app. , it can be modified, reused, re-done, etc., using the RT Indexes being calculated by the standard PI-ACE/AF RT KPI templates

CONTAC

Page 15: Real Time Operational Perfomance and Variability Supervision

ImplementationCONTAC

Page 16: Real Time Operational Perfomance and Variability Supervision

Índices Utilizados

Índices Monovariables

HarrisCompara la varianza del error con respecto a la mínima varianza alcanzable.

IAE (ITAE, ISE, ITSE)

Integral del valor absoluto del error.

Miao SeborgÍndice de oscilación basado en la auto covarianza.

Forsman StattingÍndice de oscilación. Comparación de áreas del error entre cruces por cero.

D3Test de Scheffe’s, detecta variaciones de una señal con respecto a una referencia.

Tiempo en un estado

Tiempo en que el controlador ha estado en modo manual u otro pre definido.

DistribuciónTiempo que una variable ha permanecido en determinados rangos de sus valores posibles.

Desviación Estándar

Medida de dispersión para un conjunto de datos.

CONTAC

Page 17: Real Time Operational Perfomance and Variability Supervision

RtKPI Portal (a PI-PB/AF app.)

Navigation tree

Date selection

Selected controller or variable

Variable values distribution histogram

Controller state statistics

Other reports

CONTAC

Page 18: Real Time Operational Perfomance and Variability Supervision

RtKPI Portal (a PI-PB/AF app.)RtKPI Portal (a PI-PB/AF app.)

IAE Trend

(cummulated deviation)Forsman Index Trend

(oscillations)

Miao Index Trend

(oscillation)

CONTAC

Page 19: Real Time Operational Perfomance and Variability Supervision

AutoCovariance Test

(variability-oscillations)

Variable values trend

RtKPI Portal (a PI-PB/AF app.)RtKPI Portal (a PI-PB/AF app.)CONTAC

Page 20: Real Time Operational Perfomance and Variability Supervision

Report Configuration

RtKPI Report (a PI-DL/AF app.)RtKPI Report (a PI-DL/AF app.)

Model Selection

PI-Server

Database and PI-AF Model Name

ex.: Plant, Area, Process, Water, Energy, Quality, etc.

Color highlighting configuration

Date selection

CONTAC

Page 21: Real Time Operational Perfomance and Variability Supervision

Report

RtKPI Report (a PI-DL/AF app.)RtKPI Report (a PI-DL/AF app.)CONTAC

Page 22: Real Time Operational Perfomance and Variability Supervision

Report Views

RtKPI Report (a PI-DL/AF app.)RtKPI Report (a PI-DL/AF app.)CONTAC

Page 23: Real Time Operational Perfomance and Variability Supervision

DEMO

CONTAC

OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

Page 24: Real Time Operational Perfomance and Variability Supervision

Real Time Operational Perfomance Supervision

OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

Luis Yacher S.;Felipe Kripper; Felipe Lineo

CONTAC INGENIEROS

CONTAC