Real Time Operational Perfomance and

Variability Supervision

Diego Arenas

CONTAC INGENIEROS

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OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

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.

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

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

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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

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CAPA DE PROCESOSProcess Layer

Performance Model

CAPA DE CONTROL

Outputs

Perfomance Goal

Perfomance

Perfomance Goal

Inputs

Potential Capacity Production Capacity Factor 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.

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Technology

• Control charts

• Tree Map

• Benchmarks

• Star diagram

• Dispersion diagram

• Histogram

• Other

• Statistical

• Control Loop quality

• Variability

• Multivariable Analysis

Perfomance Tests (RtKPI) Visualization Modules

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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

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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-sensors

Comparison between expected”and measured values (residual generation)

Prediction of signal values

A collection of

online KPI to:

GOAL:

Business

KPI

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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.)

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Technology, the implementation

Applying the RtKPI to a

perfomance Model

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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

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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.

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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

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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

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Implementation CONTAC

Índices Utilizados

Índices Monovariables

Harris Compara la varianza del error con respecto a la

mínima varianza alcanzable.

IAE (ITAE, ISE, ITSE) Integral del valor absoluto del error.

Miao Seborg Índice de oscilación basado en la auto covarianza.

Forsman Statting Índice de oscilación. Comparación de áreas del error

entre cruces por cero.

D3 Test 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.

Distribución Tiempo que una variable ha permanecido en

determinados rangos de sus valores posibles.

Desviación Estándar Medida de dispersión para un conjunto de datos.

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

Navigation tree

Date selection

Selected controller or variable

Variable values

distribution histogram

Controller state

statistics

Other reports

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

IAE Trend

(cummulated deviation)

Forsman Index Trend

(oscillations)

Miao Index Trend

(oscillation)

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AutoCovariance Test

(variability-oscillations)

Variable values trend

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

Report Configuration

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

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Report

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

Report Views

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

DEMO

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OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

Real Time Operational Perfomance Supervision

OPERATIONAL INTELLIGENCE TECHNOLOGIES

Empowering your PI RtPM infrastructure

Luis Yacher S.;Felipe Kripper; Felipe Lineo

CONTAC INGENIEROS

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