Program for North American Mobility in Higher Education

1
NAMP
Program for North American Mobility in Higher
Education
Module 8
Introduction to Process Integration Tier I
PIECE
Introducing Process integration for Environmental
Control in Engineering Curricula
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How to use this presentation

• This presentation contains internal links to
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• Example of a link (text underlined in grey) link
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• link to the tier table of contents
• link to the last slide viewed
• when the user has gone over the
  whole presentation, some multiple choice
  questions are given at the end of this tier. This
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  statement if a wrong answer has been given

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Table of contents

• Project Summary
• Participating institutions
• Module creators
• Module Structure Purpose
• Tier I
• Statement of Intent
• Sections
• 1.1 Introduction Definition of Process
  Integration (PI)
• Brief history of PI
• Modern context of PI
• IEA definition of PI
• M. El-Halwagi definition of PI
• Nick Hallale definition of PI
• NAMP-PIECE definition of PI

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Table of contents (2)

• Tier I
• 1.1 Introduction Definition of Process
  Integration (PI)
• Possible objectives of PI
• Summary of PI elements
• Conclusion
• 1.2 Overview of PI tools
• Overview of PI tools
• Process Simulation
• Data Treatment Reconciliation
• Pinch Analysis
• Optimization by Mathematical Programming
• Stochastic Search Methods
• Life Cycle Analysis
• Data-driven Process Modeling
• Integrated Process Design Control

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Table of contents (3)

• Tier I
• 1.2 Overview of PI tools
• Real Time Optimization
• Business Model Supply Chain Modeling
• 1.3 Around-the world tour of PI practitioners
• Institutions World Map
• Institutions North South America
• Institutions Europe
• Institutions Asia, Africa Oceania
• Companies
• Quiz

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Project Summary

• Objectives
• Create web-based modules to assist universities
  to address the introduction to Process
  Integration into engineering curricula
• Make these modules widely available in each of
  the participating countries
• Participating institutions
• Two universities in each of the three countries
  (Canada, Mexico and the USA)
• Two research institutes in different industry
  sectors petroleum (Mexico) and pulp and paper
  (Canada)
• Each of the six universities has sponsored 7
  exchange students during the period of the grant
  subsidised in part by each of the three
  countries governments

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PIECE
Process integration for Environmental Control in
Engineering Curricula
NAMP
Program for North American Mobility in Higher
Education
8
Module 8
This module was created by
Carlos Alberto Miranda Alvarez
Paul Stuart
Host Institution
From
Host director
Martin Picon-Nuñez
Jean-Martin Brault
9
Structure of Module 8

• What is the structure of this module?
• All modules are divided into 3 tiers, each with a
  specific goal
• Tier I Background Information
• Tier II Case Study Applications
• Tier III Open-Ended Design Problem
• These tiers are intended to be completed in that
  particular order. Students are quizzed at various
  points to measure their degree of understanding,
  before proceeding to the next level. Each tier
  contains a statement of intent at the beginning
  and a quiz at the end.

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Purpose of Module 8

• What is the purpose of this module?
• It is the intent of this module to cover the
  basic aspects of Process Integration Methods and
  Tools, and to place Process Integration into a
  broad perspective. It is identified as a
  pre-requisite for other modules related to the
  learning of Process Integration.

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Tier IBackground Information
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Tier I Statement of intent

• The goal of this tier is to provide a general
  overview of Process Integration tools, with focus
  on their link with profitability analysis. At the
  end of Tier I, the student should be able to
• Distinguish the key tools of Process Integration
• Understand the scope of each Process Integration
  tool
• Have an overview of each Process Integration tool

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Tier I Contents

• Tier I is broken down into three sections
• 1.1 Introduction and definition of Process
  Integration (PI)
• 1.2 Overview of PI tools
• 1.3 Around-the-world tour of PI practitioners
  which focuses on their expertise
• A short multiple-choice quiz will follow at the
  end of this tier.

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Tier I Outline

• 1.1 Introduction and definition of Process
  Integration
• 1.2 Overview of Process Integration tools
• 1.3 Around-the-world tour of PI practitioners
  which focuses on their expertise

1.1 Introduction and definition of Process
Integration 1.2 Overview of Process Integration
tools 1.3 Around-the-world tour of PI
practitioners which focuses on their expertise
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1.1 Introduction and definition of Process
Integration
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Introduction and Definition of Process Integration

• The president of your company probably does not
  know what Process Integration can do for the
  company.........
• .......... but he should. Lets look at why...

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Introduction and Definition of Process Integration
A brief history of Process Integration

• 1960s-1970s Linnhoff started the area of Pinch
  (bottleneck identification) at University of
  Manchester Institute of Science and Technology
  (UMIST), focusing on the area of Thermal Pinch.
  At about the same time, the UMIST Department of
  Process Integration was created, shortly after
  the consulting firm Linnhoff-March Inc. was
  formed
• 1980s-1990s Concept expansion from energy to
  process design
• 1990s-2000s Analogies used to derive Pinch
  concept from heat exchanger networks to mass
  transfer, water treatment and hydrogen systems
• PI is not really easy to define

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Introduction and Definition of Process Integration
Modern Process Integration context

• Process Integration might be regarded as a set of
  early stage process techniques for both new and
  retrofit design
• Business objectives drive the development of PI
• Emphasis is on retrofit projects in the new
  economy driven by Return on Capital Employed
  (ROCE)
• PI is finding value in data, especially as real
  time data systems have been implemented
• Corporations wish to make more knowledgeable
  decisions
• For operations
• During the design process
• A strong trend today is to move away from unit
  operations and focus on phenomena. We no longer
  look at integration between units only, but also
  at integration within units (Process Integration
  Primer, IEA)

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Introduction and Definition of Process Integration
Definition of Process Integration

• The International Energy Agency (IEA) definition
  of Process Integration (1993)
• Systematic and general methods for designing
  integrated production systems, ranging from
  individual processes to total sites, with special
  emphasis on the efficient use of energy and
  reducing environmental effects

Process Integration is the common term used for
the application of methodologies developed for
system-oriented and integrated approaches to
industrial process plant design for both new and
retrofit applications. Such methodologies can
be mathematical, thermodynamic and economic
models, methods and techniques. Examples of these
methods include Artificial Intelligence,
Hierarchical Analysis, Pinch Analysis and
Mathematical Programming. Process Integration
refers to optimal design examples of aspects
are capital investment, energy efficiency,
emissions, operability, flexibility,
controllability, safety and yields. Process
Integration also refers to some aspects of
operation and maintenance
? Sustainable Development
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Introduction and Definition of Process Integration
Definition of Process Integration

• El-Halwagi, M. M., Pollution Prevention through
  Process Integration Systematic Design Tools.
  Academic Press, 1997.
• A chemical process is an integrated system of
  interconnected units and streams, and it should
  be treated as such. Process Integration is a
  holistic approach to process design,
  retrofitting, and operation which emphasizes the
  unity of the process. In light of the strong
  interaction among process units, streams, and
  objectives, Process Integration offers a unique
  framework for fundamentally understanding the
  global insights of the process, methodically
  determining its attainable performance targets,
  and systematically making decisions leading to
  the realization of these targets. There are three
  key components in any comprehensive Process
  Integration methodology synthesis, analysis, and
  optimization.

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Introduction and Definition of Process Integration
Definition of Process Integration

• Nick Hallale, Aspentech CEP July 2001 Burning
  Bright Trends in Process Integration
• Process Integration is more than just Pinch
  technology and Heat Exchanger Networks. Today, it
  has a far wider scope and touches every area of
  process design. Switched-on industries are making
  more money from their raw materials and capital
  assets while becoming cleaner and more
  sustainable

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Introduction and Definition of Process Integration
Definition of Process Integration

• North American Mobility Program in Higher
  Education (NAMP)-January 2003
• Process Integration (PI) is the synthesis of
  process control, process engineering and process
  modeling and simulation into tools that can deal
  with the large quantities of operating data now
  available from process information systems. It is
  an emerging area, which offers the promise of
  improved control and management of operating
  efficiencies, energy use, environmental impacts,
  capital effectiveness, process design, and
  operations management.

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Introduction and Definition of Process Integration
Definition of Process Integration

• So What Happened?
• In addition to thermodynamics (the foundation of
  Pinch), other techniques are being drawn upon for
  holistic analysis, in particular
• Process modeling
• Process statistics
• Process optimization
• Process economics
• Process control
• Process design

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Introduction and Definition of Process Integration

• Here are some of the design activities that these
  techniques and methods address today
• Process modeling and simulation, and validation
  of the results in order to have accurate and
  reliable process information for both new and
  retrofit design
• Minimize total annual cost by optimal trade-off
  between energy, equipment and raw material.
  Within this trade-off minimize energy, improve
  raw material usage and minimize capital cost
• Increase production volume by debottlenecking
• Reduce operating problems by correct (rather than
  maximum) use of Process Integration
• Increase plant controllability and flexibility
• Minimize undesirable emissions and promote
  pollution prevention
• Add to the joint efforts in the process
  industries and society for a sustainable
  development

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Introduction and Definition of Process Integration
Possible objectives

• Lower capital cost, for the same design objective
• Incremental production increase, from the same
  asset base
• Marginally-reduced unit production costs by
  process optimization
• Better energy/environmental performance, without
  compromising competitive position

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Introduction and Definition of Process Integration
Summary of Process Integration elements

• Improving overall plant facilities energy
  efficiency and productivity requires a
  multi-pronged analysis involving a variety of
  technical skills and expertise, including
• Knowledge of both conventional industry practice
  and state-of-the-art technologies commercially
  available
• Familiarity with industry issues and trends
• Methodology for determining correct marginal
  costs
• Procedures and tools for energy, water, and raw
  material conservation audits
• Process information systems

Real-Time Process Data
Process knowledge (models)
PI systems Tools
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Introduction and Definition of Process Integration
Conclusion

• Process Integration has evolved from heat
  recovery methodology in the 80s to become what a
  number of leading industrial companies and
  research groups in the 20th century regard as the
  holistic analysis of processes, involving the
  following elements
• Process data
• Systems and tools
• Process engineering principles and in-depth
  process sector knowledge
• Targeting

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Tier I Outline

• 1.1 Introduction and definition of Process
  Integration
• 1.2 Overview of Process Integration tools
• 1.3 Around-the-world tour of PI practitioners
  which focuses on their expertise

1.1 Introduction and definition of Process
Integration 1.2 Overview of Process Integration
tools 1.3 Around-the-world tour of PI
practitioners which focuses on their expertise
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1.2 Overview of Process Integration Tools
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Overview of Process Integration Tools
Business Model and Supply Chain Management
Real Time Optimization
Pinch Analysis
Optimization by Mathematical Programming
Data Treatment and Reconciliation
Stochastic Search Methods

• Process Simulation
• Steady-state
• Dynamic

Life Cycle Analysis
Data-Driven Process Modeling
Integrated Process Design and Control
Process Data
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Overview of Process Integration Tools

• Business Model
• Supply Chain Management

Real Time Optimization
Pinch Analysis
Data Treatment and Reconciliation
Optimization by Mathematical Programming
Stochastic Search Methods

• Process Simulation
• Steady state
• Dynamic

Life Cycle Analysis
Data-Driven Process Modeling
Integrated Process Design and Control
Process Data
NEXT
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Process Simulation
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Process simulation

• Simulation what if experimentation with a
  model
• Simulation involves performing a series of
  experiments with a process model

A model does not include everything ngtm and
kgtt All models are wrong, some models are
useful George Box, PhD, University of Wisconsin
Figure 1
In the process industry, we find two levels of
models plant models, and models of unit
operations such as reactors, columns, pumps, heat
exchangers, tanks, etc.
There are two types of simulation steady-state
and dynamic
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Process simulation Process modeling
Process Modeling is an understanding of the
phenomena of a given process and the
transformation of this understanding into a model.
What is a model used for?

• A model is an abstraction of a process operation
  used to build, change, improve, control, and
  answer questions about that process
• A model can be used for different basic problem
  formulations simulation, identification,
  estimation and design
• A model can be used to solve problems in the
  areas of the process design, control and
  optimization, risk analysis, operator training,
  risk assessment, and software engineering for
  computer aided engineering environments

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Process simulation Steady-state Dynamic

• Why is steady-state simulation important?
• Better understanding of the process
• Consistent set of typical plant/facility data
• Objective comparative evaluation of options for
  Return On Investment (ROI) etc.
• Identification of bottlenecks, instabilities,
  etc.
• Performs many experiments cheaply once the model
  is built
• Avoids implementing ineffective solutions

Why is dynamic simulation important?
Figure 3
Figure 2
Next Tool
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Data Treatment and Reconciliation
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Data Treatment Reconciliation

• Objectives of Data Treatment
• Provide reliable information and knowledge of
  complete data for validation of process
  simulation and analysis
• Perform instrument maintenance
• Detect operating problems
• Estimate unmeasured values
• Reduce random and gross errors in measurements
• Detect steady states

• Objectives of Data Reconciliation
• Optimally adjust measured values within given
  process constraints
• Improve consistency of data to calibrate and
  validate process simulation
• Estimate unmeasured process values
• Detect gross errors to further investigate
  operation/instrument problems

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Data Treatment Reconciliation
                    
                                                
                

• Data Reconciliation
• Data Reconciliation is the validation of process
  data using knowledge of plant structure and of
  the plant measurement system

                  
                                                
           
                  
            
Figure 4
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Data Treatment Reconciliation - Benefits
Next Tool
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Pinch Analysis
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Pinch Analysis
What is Pinch Analysis?

• In the process industries, the prime objective
  of Pinch Analysis is to optimize the ways in
  which process utilities (particularly energy,
  mass, water, and hydrogen) are applied for a wide
  variety of purposes
• Pinch Analysis does this by creating an
  inventory of all producers and consumers of these
  utilities and then systematically designing an
  optimal scheme of utility exchange between these
  producers and consumers. Energy, mass, and water
  re-use are at the heart of Pinch Analysis
  activities
• With the application of Pinch Analysis, savings
  can be achieved in both capital investment and
  operating cost. Emissions can be minimized and
  throughput maximized

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Pinch Analysis
Features

• The basis of Pinch Analysis
• The use of thermodynamic principles (first and
  second law)
• The use of design and economy heuristics
• Pinch Analysis is a technique to design
• Heat Exchanger Networks (HEN) Mass Exchange
  Networks (MEN)
• Utility Networks
• Pinch Analysis makes extensive use of various
  graphical representations
• In Pinch Analysis, the engineer controls the
  design procedure (interactive method)
• Pinch Analysis integrates economic parameters

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Pinch Analysis

• In addition, Pinch Analysis allows you to
• Update or develop process flow diagrams
• Identify process bottlenecks
• Run both departmental and full plant facilities
  simulations
• Determine minimal heating (steam) and cooling
  requirements
• Identify cogeneration opportunities
• Estimate costs of projects to achieve energy
  savings
• Evaluate new equipment configurations for the
  most economical installation
• Substitute past energy studies with a live study
  that can be easily updated using simulation

• Possible Benefits
• One of the main advantages of Pinch Analysis over
  conventional design methods is the ability to set
  a target energy consumption for an individual
  process or for an entire production site before
  designing the processes
• Pinch Analysis quickly identifies where energy,
  water, hydrogen and other material savings are
  likely to be found
• Reduction of emissions
• Pinch Analysis enables the engineer to find the
  best way to change a process, if the process
  allows it

Next Tool
44
Optimization by Mathematical Programming
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Optimization of Mathematical Programming
Mathematical Model

• A Mathematical Model of a system is a set of
  mathematical relationships (e.g., equalities,
  inequalities, logical conditions) which
  represents an abstraction of the real world
  system under consideration
• A Mathematical Model can be developed using
• Fundamental approaches
• Empirical methods
• Methods based on analogy
• A Mathematical Model of a system consists of four
  key elements
• Variables
• Parameters
• Constraints
• Mathematical relations

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Optimization of Mathematical Programming

• What is Optimization?
• An optimization problem is a mathematical model
  which in addition to the key elements stated in
  the previous slide contains one or more
  performance criteria
• The performance criteria are represented by an
  objective function. This function can be the
  minimization of costs, the maximization of profit
  or yield of a process, for example
• If we have multiple performance criteria, the
  problem is then classified as a multi-objective
  optimization problem
• There are different classes of optimization
  problems linear and non-linear programming, LP
  and NLP, mixed-integer linear programming (MILP)
  and mixed-integer non-linear programming (MINLP)
• Whenever possible, linear programs (LP or MILP)
  are used because they guarantee global solutions.
  MINLP problems also feature many applications in
  engineering.

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Optimization of Mathematical Programming

• Applications
• Process Synthesis
• Heat Exchanger Networks (HEN)
• Mass Exchanger Networks (MEN)
• Distillation sequencing
• Reactor-based systems
• Utility systems
• Total process systems
• Design, scheduling, and planning of process
• Design and retrofit of multiproduct plants
• Design and scheduling of multiproduct plants
• Interaction of design and control
• Molecular product design
• Facility location and allocation
• Facility planning and scheduling
• Topology of transport networks

Next Tool
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Stochastic Search Methods
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Stochastic Search Methods

• Why Stochastic Search Methods?
• All of the model formulations that you have
  encountered thus far in the Optimization section
  have assumed that the data for the given problem
  are known accurately. However, for many actual
  problems, the problem data cannot be known
  accurately for a variety of reasons. The first
  reason is due to simple measurement error. The
  second and more fundamental reason is that some
  data represent information about the future
  (e.g., product demand or price for a future time
  period) and simply cannot be known with
  certainty.

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Stochastic Search Methods

• There are different types of stochastic
  algorithms
• Simulated Annealing (SA)
• Genetic Algorithms (GAs)
• Tabu Search
• These algorithms are suitable for problems that
  deal with uncertainty. These computer algorithms
  or procedure models do not guarantee global
  optima but are successful and widely known to
  come very close to the global optimal solution.
• SA takes one solution and efficiently moves it
  around in the search space, avoiding local optima
• GAs have the capability of collectively searching
  for multiple optimal solutions for the same
  optimal cost
• Tabu Search is an iterative procedure that
  explores the search space of all feasible
  solutions by a sequence of moves

Next Tool
51
Life Cycle Analysis (LCA)
52
Life Cycle Analysis
What is Life Cycle Analysis?

• Technique for assessing the environmental aspects
  and potential impacts associated with a product
  by
• Establishing an inventory of relevant inputs and
  outputs of a system
• Evaluating the potential environmental impacts
  associated with those inputs and outputs
• Interpreting the results of the inventory and
  impact phases in relation with the objectives of
  the study
• Evaluation of some aspects of a product system
  through all stages of its life cycle

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Life Cycle Analysis
Figure 5
54
Life Cycle Analysis
Possible Benefits

• Improves overall environmental performance and
  compliance
• Provides a framework for using pollution
  prevention practices to meet LCA objectives
• Increases efficiency and potential cost savings
  when managing environmental obligations
• Promotes predictability and consistency in
  managing environmental obligations
• Measures scarce environmental resources more
  effectively

Next Tool
55
Data-Driven Process Modeling
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Data-Driven Process Modeling

• Process Integration challenge
• Make sense of masses of data
• Necessity to work on bigger samples if full
  advantage is to be taken of all accessible
  information

Drowning in data!
Data-Rich but Knowledge-Poor

• Interesting, useful patterns and relationships
  not intuitively obvious lie hidden inside
  enormous, unwieldy databases. Also, many
  variables are correlated
• Data mining techniques Neural Networks, Multiple
  Regression, Decision Trees, Genetic Algorithms,
  Clustering, MVA, etc.

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Data-Driven Process Modeling
Theoretical vs. Empirical Model

• Theoretical model ? uses First Principles to
  mimic the inner workings of a process
• Empirical model ? uses the plant process data
  directly to establish mathematical correlations
• Unlike the theoretical models, empirical models
  do NOT take the process fundamentals into
  account. They only use pure mathematical and
  statistical techniques. Multivariate Analysis
  (MVA) is one such method, because it reveals
  patterns and correlations between variables
  independently of any pre-conceived notions

58
Data-Driven Process Modeling
What is MVA?

• Multivariate Analysis (gt 5 variables)
• MVA uses ALL available data to capture
  information as much as possible
• Principle boil down hundreds of variables down
  to a mere handful

Benefits

• Explore inter-relationships
•  What-if  exercises
• Software sensors
• Feed-forward control

Next Tool
59
Integrated Process Design Control
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Integrated Process Control Control
Context

• Safety issues, energy costs, environmental
  concerns have increased complexity and
  sensitivity of processes
• Plants become highly integrated in terms of mass
  and energy and therefore, process dynamics are
  often difficult to control
• Objectives
• Product specifications variability should be kept
  at a minimum ? process variability (to control
  product quality)
• Control is essential to operate a process in the
  best conditions

61
Integrated Process Control Control
Controllability
Controllability is the property of a process that
accounts for the ease with which a continuous
plant can be held at a specified operating regime
despite bounded external disturbances and
uncertainties and regardless of the control
system imposed on such a process
62
Integrated Process Control Control
Why is Controllability important?

• Smoother operation of process closer to
  operating limits

Flexibility

• Stability and better performance of control loops
  and structures
• System relatively insensitive to perturbations
• Efficient management of interacting networks

Improvement of current dynamics
Next Tool
63
Real-Time Optimization (RTO)
64
Real Time Optimization
Context

• The process industries are increasingly compelled
  to operate profitably in a very dynamic and
  global market. The increasing competition in the
  international area and stringent product
  requirements mean decreasing profit margins
  unless plant operations are optimized dynamically
  to adapt to the changing market conditions and to
  reduce the operating cost.

Importance of real-time or on-line optimization!
65
Real Time Optimization
What is Real-Time Optimization (RTO)?

• Real-Time Optimization is a model-based
  steady-state technology that determines the
  economically optimal operating regime for a
  process in the near term
• The system optimizes a process simulation, not
  the process directly
• Performance measured in terms of economic benefit
• Is an active field of research ? model accuracy,
  error transmission, performance evaluation

66
Real Time Optimization
Business objectives Economic data Product
specification
RTO - Schematically
Reconciliation gross error detection
Updating process model (Steady-state?dynamic simul
ation)
Optimization (objective functions)
Steady-state detection
Cost, process, Environmental product Data
Plant facility
Next Tool
Figure 6
67
Business Model and Supply Chain Modeling (BM-SCM)
68
Business Model and Supply Chain Modeling (BM-SCM)
Cost, Process, Environmental Product Outcomes
Process Design Analysis And Synthesis
Process Operation Analysis and Optimization
Integrated Business Process Model
Cost, Process, Environmental Product Data
Back to PI Tools
69
BM-SCM Cost, Process, Environmental Product
Data
Integrated Business Process Model
Cost, Process, Environmental and Product Data
Once the model is built, it can be used to
validate and reconcile data
Plant Facilities
70
BM-SCM Integrated Business Process Model
Data Driven Models
1st Principles Models
Process Simulation Models
71
BM-SCM Supply Chain Environmental Supply Chain

• Supply Chain (SC) is a network of organizations
  that are involved, through upstream and
  downstream linkages, in the different processes
  and activities that produce value in the form of
  products and services in the hands of the
  ultimate customer

Environmental Supply Chain (ESC) holds all the
elements a traditional Supply Chain has, but is
extended to a semi-closed loop in order to also
account for the environmental impact of the
Supply Chain and for recycling, re-use and
collection of used material (Beamon 1999)
72
BM-SCM Supply Chain Environmental Supply Chain

• Objectives of the SC and ESC models
• To integrate inter-organizational units along a
  SC and coordinate materials, information and
  financial flows in order to fulfill customer
  demands and to improve SC profitability and
  responsiveness
• To gain insight on the total environmental impact
  of the production process (from supplier to
  customer and back to the facility by recycling)
  and all the products that are manufactured
  (closely linked to LCA)

Back to PI Tools
BM-SCM
73
Tier I Outline

• 1.1 Introduction and definition of Process
  Integration
• 1.2 Overview of Process Integration tools
• 1.3 Around-the-world tour of PI practitioners
  which focuses on their expertise

1.1 Introduction and definition of Process
Integration 1.2 Overview of Process Integration
tools 1.3 Around-the-world tour of PI
practitioners which focuses on their expertise
74
1.3 Around-the-world tour of PI practitioners
which focuses on their expertise
75
Around-the-world tour of PI Practitioners

• Courtesy mainly of the World Wide Web ? to
  capture the flavour of the evolution of Process
  Integration
• PI is relatively new
• Researchers build on their strengths
• Many of the ground-breaking techniques are coming
  from universities
• When techniques become practical, the private
  sector generally capitalizes and techniques
  advance more rapidly

Institutions
Companies
END
76
Around-the-world tour of PI Practitioners
Institutions
Click on a continent to view institutions from
that continent
77
Around-the-world tour of PI Practitioners
Institutions-North and South America
Canada (2)
Mexico (1)
USA (8)
Brazil (1)
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click on the flag of the country of choice
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78
Around-the-world tour of PI Practitioners
Institutions-Europe
Belgium (1)
Greece (1)
Spain (1)
Sweden (1)
Denmark (1)
Hungary (1)
Finland (3)
Norway (1)
Switzerland (1)
France (1)
UK (5)
Portugal (2)
Germany (2)
Slovenia (1)
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click on the flag of the country of choice
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79
Around-the-world tour of PI Practitioners
Institutions-Africa, Middle-East, Asia and Oceania
South Africa (1)
Israel (1)
India (1)
Australia (3)
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click on the flag of the country of choice
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80
Around-the-world tour of PI Practitioners
Canada
École Polytechnique de Montréal, Department of
Chemical Engineering, Montréal
Major Contact Professor Paul Stuart
Web http//www.pulp-paper.ca
Research areas the application of Process
Integration in the pulp and paper industry, with
emphasis on pollution prevention techniques and
profitability analysis, the efficient use of
energy and raw materials (including water),
process control, and plant sustainability
Consortium "Process Integration in the Pulp and
Paper Industry Research Consortium" with 13
members (2003) including operating companies,
engineering contracting companies, consulting
companies and software vendors in pulp and paper
industry

• Current research in Process Integration
• Process Simulation
• Data Reconciliation
• Process Control
• Networks Analysis (HEN and MEN)
• Environmental technologies (e.g. LCA)
• Business model
• Date-Driven Modeling

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81
Around-the-world tour of PI Practitioners
Canada
University of Ottawa, Department of Chemical
Engineering, Ottawa
Major Contact Professor Jules Thibault
Web http//www.genie.uottawa.ca/chg/eng/
Brazil
Universidade Federal do Rio de Janeiro, Rio de
Janeiro
Major Contact Professor Eduardo Mach Queiroz
Web http//www.poli.ufrj.br/
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82
Around-the-world tour of PI Practitioners
Mexico
Universidad de Guanajuato, Department of Chemical
Engineering, Guanajuato
Major Contact Dr Martín-Picón-Núñez
Web http//www.ugto.mx
Research areas hosts the only course Masters
Program in Process Integration in North America.
Analysis of processes, Power Systems, and
development of environmentally benign technology

• Current research in Process Integration
• Synthesis of processes modeling, simulation,
  control and optimization of processes new
  processes and materials
• Heat recovery systems renewable sources of
  energy thermodynamic optimization
• Contaminated atmosphere rehabilitation
  treatment of effluents environmental processes

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83
Around-the-world tour of PI Practitioners
USA
Carnegie Mellon University, Department of
Chemical Engineering, Pittsburgh
Major Contact Professor Ignacio E. Grossmann
Web http//capd.cheme.cmu.edu/
Research areas recognized as one of the major
research groups in the area of Computer Aided
Process Design. In Process Integration, the group
is recognized for its work in Mathematical
Programming, Optimization, reactor systems,
separation systems (especially distillation),
Heat Exchanger Networks, operability and the
synthesis of operating procedures
Consortium CAPD (Centre for Advanced Process
Decision-making, founded 1986, 20 members (2001))
including operating companies, engineering
contracting companies, consulting companies and
software vendors

• Current research in Process Integration
• Insights to aid and automate synthesis
  (invention)
• Structural optimization of process flowsheets
• Synthesis of reactor systems and separation
  systems
• Synthesis of Heat Exchanger Networks
• Global optimization techniques relevant to
  Process Integration
• Integrated Design and Scheduling of batch plants
• Supply chain dynamics and optimization

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84
Around-the-world tour of PI Practitioners
USA
Texas AM University, Department of Chemical
Engineering, College Station
Major Contact Professor Mahmoud M. El-Halwagi
Web http//process-integration.tamu.edu/ and
http//www-che.tamu.edu/cpipe/
Research areas Recognized as a leading research
group in the areas of Mass Integration and
Pollution Prevention through Process Integration

• Current research in Process Integration
• Global allocation of mass and energy
• Synthesis of waste allocation and species
  interception networks
• Physical and reactive Mass Pinch Analysis
• Synthesis of Heat-Induced Networks
• Design of membrane-hybrid systems
• Design of environmentally acceptable reactions
• Integration of reaction and separation systems
• Flexibility and scheduling systems
• Simultaneous design and control
• Global optimization via interval analysis

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85
Around-the-world tour of PI Practitioners
USA
Auburn University, Auburn
Major Contact Professor Christopher Roberts
Web http//www.eng.auburn.edu/department/che/
Massachusetts Institute of Technology (MIT),
Department of Chemical Engineering, Cambridge
Major Contact Professor George Stephanopoulos
Web http//web.mit.edu/cheme/index.html
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86
Around-the-world tour of PI Practitioners
USA
Princeton University, Princeton
Major Contact Professor Christodoulos A. Floudas
Web http//chemeng.princeton.edu/html/home.shtml
Purdue University, West Lafayette
Major Contact Professor G.V. Rex Reklaitis
Web https//engineering.purdue.edu/ChE/index.html
and https//engineering.purdue.edu/ECN/
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87
Around-the-world tour of PI Practitioners
USA
University of Massachusetts, Amherst
Major Contact Professor J. M. Douglas
Web http//www.ecs.umass.edu/che/
University of Pennsylvania, Philadelphia
Major Contact Professor Warren D. Seider
Web http//www.seas.upenn.edu/cbe/chehome.html
Back to Americas Institutions
88
Around-the-world tour of PI Practitioners
Belgium
Université de Liège, Laboratory for Analysis and
Synthesis of Chemical Systems (LASSC), Liège
Major Contact Professor Boris Kalitventzeff
Web http//www.ulg.ac.be/lassc/
Denmark
Technical University of Denmark, Lyngby
Major Contact Professor Bjørn Qvale
Web http//www.et.dtu.dk/
Back to Europe Institutions
89
Around-the-world tour of PI Practitioners
Finland
Åbo Akademi University, Process Design
Laboratory, Åbo
Major Contact Professor Tapio Westerlund
Web http//www.abo.fi/fak/ktf/at/
Lappeenranta University of Technology,
Lappeenranta
Major Contact Professor Lars Nyström
Web http//www2.lut.fi/kete/laboratories/Process_
Engineering/mainpage.htm
Helsinki University of Technology, Laboratory of
Energy Engineering and Environmental Protection,
Helsinki
Major Contact Professor Carl-Johan Fogelholm
Web http//eny.hut.fi/
Back to Europe Institutions
90
Around-the-world tour of PI Practitioners
France
INPT-ENSIGC, Chemical Engineering Laboratory,
Toulouse
Major Contact Professor Xavier Joulia
Web http//www.ensiacet.fr/ENSIA7_FR/FORMATION/IN
GENIEUR/GPI/gpi.shtml
Greece
Chemical Process Engineering Research Institute,
Hellas
Major Contact Professor I. Vasalos
Web http//www.cperi.forth.gr
Back to Europe Institutions
91
Around-the-world tour of PI Practitioners
Germany
Universität Dortmund, Dortmund
Major Contact Professor A. Behr
Web http//www.bci.uni-dortmund.de/tca/web/en/ind
ex.html
Technische Universität Hamburg, Harburg
Major Contact Professor Günter Gruhn
Web http//www.tu-harburg.de/vt3/
Back to Europe Institutions
92
Around-the-world tour of PI Practitioners
Hungary
Budapest University of Technology and Economics,
Budapest
Major Contact Professor Zsolt Fonyo
Web http//www.bme.hu/en/organization/faculties/c
hemical/
Norway
Norwegian University of Science and Technology,
Process Systems Engineering in Trondheim (PROST),
Trondheim
Major Contact Professor Sigurd Skogestad
Web http//kikp.chembio.ntnu.no/research/PROST/
Back to Europe Institutions
93
Around-the-world tour of PI Practitioners
Portugal
Universidade do Porto, Porto
Major Contact Professor Manuel A.N. Coelho
Web http//www.fe.up.pt/
Instituto Superior Técnico, Lisboa
Major Contact Professor Clemente Pedro Nunes
Web http//dequim.ist.utl.pt/english/
Back to Europe Institutions
94
Around-the-world tour of PI Practitioners
Slovenia
University of Maribor, Maribor
Major Contact Professor Peter Glavic
Web http//www.uni-mb.si/
Switzerland
Swiss Federal Institute of Technology, Lausanne
Major Contact Professor Daniel Favrat
Web http//leniwww.epfl.ch/
Back to Europe Institutions
95
Around-the-world tour of PI Practitioners
Spain
Universitat Politècnica de Catalunya, Chemical
Engineering Department, Barcelona
Major Contact Professor Luis Puigjaner
Web http//tqg.upc.es/
Research areas pioneering work in Computer Aided
Process Operations. In Process Integration, the
group is recognized for its contributions in
time-dependent processes, such as Combined Heat
and Power, Combined Energy-Waste and Waste
Minimization, Integrated Process Monitoring,
Diagnosis and Control and Process Uncertainty
Consortium "Manufacturing Reference Centre" with
12 members (1966) including Conselleria
d'Indústria and associated operating companies,
engineering and contracting companies,
consultants and software vendors. Also the TQG
(General Chemical Technology) research group has
grown steadily with research related to kinetics,
process design and operation

• Current research in Process Integration
• Evolutionary modeling and optimization
• Multi-objective optimization in time-dependent
  systems
• Combined energy and water use minimization
• Integration of thermally coupled distillation
  columns
• Hot-gas recovery and cleaning systems

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96
Around-the-world tour of PI Practitioners
Sweden
Chalmers University of Technology, Department of
Heat and Power, Göteborg
Major Contact Thore Berntsson
Web http//www.hpt.chalmers.se/
Research areas methodology development and
applied research based on Pinch Technology.
Emphasis on new retrofit methods including
realistic treatment of geographical distances,
pressure drops, varying fixed costs, etc.
Important new concepts include the Cost Matrix
for Retrofit Screening and new Grand Composite
thermodynamic diagrams for heat and power
applications (including gas turbines and heat
pumps). Research in pulp and paper with focus on
energy and environment
Industry Close cooperation with some of the
major pulp and paper industry groups, including
training courses and consulting

• Current research in Process Integration
• Retrofit design of Heat Exchanger Networks
• Process Integration of heat pumps in grassroots
  and retrofits
• Gas turbine based CHP plants in retrofit
  situations
• Applied research in pulp and paper industry,
  such as black liquor gasification and closing the
  bleaching plant
• Environmental aspects of Process Integration,
  especially greenhouse gas emissions

Back to Europe Institutions
97
Around-the-world tour of PI Practitioners
UK
Imperial College, Centre for Process Systems
Engineering, London
Major Contact Professor Efstratios N.
Pistikopoulos
Web http//www.ps.ic.ac.uk/ and
http//www.psenterprise.com
Research areas recognized as the largest
research group in the area of Process Systems
Engineering (PSE), which includes
Synthesis/Design, Operations, Control and
Modeling. The group is recognized as a world-wide
centre of excellence in Process Modeling,
Numerical Techniques/Optimization and Integrated
Process Design (includes simultaneous
consideration of Process Integration and
Control). The Centre is also an important
contributor in the area of integration and
operation of batch processes
Consortium Process Systems Engineering (PSE)
with 17 members (2003) including operating,
engineering contracting companies, software
vendors

• Current research in Process Integration
• Integrated batch processing
• Design and management of integrated Supply Chain
  processes
• Uncertainty and operability in process design
• Formulation of mathematical programming models
  to address problems in process synthesis and
  integration

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Back to Europe Institutions
98
Around-the-world tour of PI Practitioners
UK
UMIST, Department of Process Integration,
Manchester
Major Contact Professor Robin Smith
Web http//www.cpi.umist.ac.uk/
Research areas recognized as the pioneering and
major research group in the area of Pinch
Analysis. Previous research includes targets and
design methods for Heat Exchanger Networks
(grassroots and retrofits), Heat and Power
systems, Heat driven Separation Systems,
Flexibility, Total Sites, Pressure Drop
considerations, Batch Process Integration, Water
and Waste Minimization and Distributed Effluent
Treatment
Industry Research Consortium in Process
Integration created in 1984 and now formed by 26
major companies representing different aspects of
the process and utility industries

• Current research in Process Integration
• Efficient use of raw materials (including water)
• Energy efficiency
• Emissions reduction
• Efficient use of capital

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99
Around-the-world tour of PI Practitioners
UK
University of Edinburgh, Edinburgh
Major Contact Professor Jack W. Ponton
Web http//www.chemeng.ed.ac.uk/
University College, London
Major Contact Dr. David Bogle
Web http//www.chemeng.ucl.ac.uk/
University of Ulster, Coleraine
Major Contact Professor J.T. McMullan
Web http//www.engineering.ulster.ac.uk/
Back to Europe Institutions
100
Around-the-world tour of PI Practitioners
Israel
Technion, Israel Institute of Technology, Haifa
Major Contact Professor Daniel R. Lewin
Web http//www.technion.ac.il/technion/chem-eng/i
ndex_explorer.htm
India
Indian Institute of Technology, Bombay
Major Contact Dr. Uday V. Shenoy
Web http//www.che.iitb.ac.in/
Back to Asia Institutions
101
Around-the-world tour of PI Practitioners
South Africa
University of the Witwatersrand, Process
Materials Engineering, Johannesburg
Major Contact Professor David Glasser
Web http//www.procmat.wits.ac.za/
Research areas recognized as the major research
group in the development of the Attainable Region
(AR) method for Reactor and Process Synthesis.
The Attainable Region concept has been expanded
to systems where mass transfer, heat transfer and
separation take place. In its generalized form
(reaction, mixing, separation, heat transfer and
mass transfer), the Attainable Region concept
provides a Synthesis tool that will provide
targets for "optimal" designs against which more
practical solutions can be judged
Has founded its own consultancy enterprise called
Wits Enterprise http//www.enterprise.wits.ac.za/

• Current research in Process Integration
• Systems involving reaction, mixing and
  separation (e.g. reactive distillation)
• Non-isothermal chemical reactor systems
• Optimization of dynamic systems

Back to Africa Institutions
102
Around-the-world tour of PI Practitioners
Australia
University of Adelaide, Adelaide
Major Contact Dr. B.K. O'Neill
Web http//www.chemeng.adelaide.edu.au/
Murdoch University, Rockingham
Major Contact Professor Peter Lee
Web http//wwweng.murdoch.edu.au/engindex.html
University of Queensland, Brisbane
Major Contact Professor Ian Cameron
Web http//www.cheque.uq.edu.au/
Back to Oceania Institutions
103
Around-the-world tour of PI Practitioners
Companies
Linnhoff March Limited, Northwich, Cheshire, UK
Web http//www.linnhoffmarch.com/ and
http//www.kbcat.com/
Linnhoff March is the pioneering company of Pinch
Technology and is now a division of KBC Process
Technology Limited since 2002. KBC Advanced
Technologies is the leading independent process
engineering consultancy, improving operational
efficiency and profitability in the hydrocarbon
processing industry worldwide

• List of Services in the area of Process
  Integration
• Project execution and consulting
• Software development and support
• Training assistance
• Typical Projects 1200 assignments over 18 years

• PI Technologies
• Pinch Technology (analysis and HEN Design,Total
  Site Analysis)
• Water Pinch for wastewater minimization
• Combined thermal and hydraulic analysis of
  distillation columns PI software extensively
  proven state-of-the-art software including
  SuperTarget, PinchExpress, WaterTarget and Steam97

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104
Around-the-world tour of PI Practitioners
Companies
Process Systems Enterprise Limited, London, UK
Web http//www.psenterprise.com
Process Systems Enterprise Limited (PSE) is a
provider of advanced model-based technology and
services to the process industries. These
technologies address pressing needs in
fast-growing engineering and automation market
segments of the chemicals, petrochemicals, oil
gas, pulp paper, power, fine chemicals, food,
pharmaceuticals and biotech industries.

• List of Services in the area of Process
  Integration
• Dynamic process modeling
• Dynamic optimization
• Enterprise modeling
• Extensive training for all its products

• PI Technologies
• gPROMS, for general PROcess Modeling System ?
  Steady-state and dynamic process simulation,
  optimization (MINLP) and parameter estimation
  software, packaged for different users
• Model Enterprise ? supply chain modeling and
  execution environment
• Model Care ? business model

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105
Around-the-world tour of PI Practitioners
Companies
Industrial and Power Association-National
Engineering Laboratory (NEL), UK
Web http//www.ipa-scotland.org.uk/home.asp
QuantiSci Limited, UK
Web http//www.quantisci.co.uk/
NEXT
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106
Around-the-world tour of PI Practitioners
Companies
American Process Inc., Atlanta, USA
Web http//www.americanprocess.com
Founded in 1994, American Process Inc is the
premier consulting engineering specialist firm
dedicated to energy cost minimization in pulp and
paper and other industries. Our success is
largely due to offering custom tailored solutions
for our customers, understanding that each mill
is a unique operation, thereby optimizing the
potential for savings

• List of Services in the area of Process
  Integration
• Energy Targeting Using Pinch Analysis
• Simulation modeling
• Linear optimization
• Over 150 studies completed

• PI Technologies
• PARIS (Production Analysis for Rate and
  Inventories Strategies) ? Decision-Making tool
  for optimizing pulp and paper mill operations)
• O-Pinch (Operational Pinch)
• SPARTA ? real-time steam and power cost
  optimizer
• Water Close ? water pinch

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107
Around-the-world tour of PI Practitioners
Companies
Advanced Process Combinatorics (APC), USA
Web http//www.combination.com
Aspen Technology Inc. (AspenTech), USA
Web http//www.aspentech.com and
http//www.hyprotech.com
Back to Companies
108
End of Tier I

• This is the end of Tier I. At this point, we
  assume that you have done all the reading. Some
  of this information might still seem confusing
  but remember that we are still trying to set all
  the pieces in the Process Integration puzzle.
• Prior to advancing to Tier II, a short multiple
  choice quiz will follow.

109
QUIZ
110
Tier I - Quiz
Question 1
Where was the concept of Process Integration
first developed?
Atlanta, USA
Guanajuato, Mexico
Manchester, UK
Montreal, Canada
111
Tier I - Quiz
Question 2
Using PI techniques and methods allows you to
observe different variations in a process, a
plant or a company. Use each one of the following
and indicate if they would be reduced or
increased in a Process Integration context.
1. Costs 2. Pollution 3. Throughput 4.
Energy Use 5. Yield 6. Profit 7. Data
Use 8. Production Volume 9. Water Use 10.
Operating Problems
? 1,4,6,7 and 9 ? 2,3,5,8 and 10
? 2,3,6,8 and 10 ? 1,4,5,7 and 9
? 1,2,4,9 and 10 ? 3,5,6,7 and 8
? 3,4,5,7 and 8 ? 1,2,6,9 and 10
112
Tier I - Quiz
Question 3

• Which of the following statements are false?
• Steady-state simulations enable the process
  engineer to study strategies for start-up and
  shut down
• In the process industry, we find two levels of
  models models of unit operations and plant
  models
• A model can represent exactly what goes on in a
  process
• Generally, dynamic simulations are used to
  estimate the sizes and costs of process units

1 and 2
2 and 3
1 and 3
3 and 4
2 and 4
1,3 and 4
1,2 and 3
All of the above
113
Tier I - Quiz
Question 4

• What are plant measurements usually corrupted by?
• Random power supply fluctuations
• Ambient conditions
• Sensor miscalibration
• Computer calculation capacity and speed
• Hostile process environment
• Sampling frequency

1,2 and 3
1,3 and 6
1,2 and 5
2,3,5 and 6
2 and 4
1,2,3 and 4
1,2,3 and 5
All of the above
114
Tier I - Quiz
Question 5

• What was Pinch Analysis originally conceived for?
• Oil refinery emissions reduction
• Capital investment and operating costs savings
• Heat Exchanger Network design
• Better use of hydrogen in refineries
• Utility Network design

2 and 3
3 and 4
1
3
2
1,2,3 and 4
1,2,3 and 5
All of the above
115
Tier I - Quiz
Question 6

• What does an objective function represent in an
  optimization problem?
• Interactions among variables
• Performance criteria
• Parameters
• Mass and energy balances
• Equalities or inequalities

2 and 3
3 and 4
1
3
2
1,2,3 and 4
1,2,3 and 5
All of the above
116
Tier I - Quiz
Question 7
The entire research area of Genetic Algorithms
was inspired by Darwin's theory of natural
selection and survival of the fittest. Unlike
natural evolution, a Genetic Algorithm program is
usually able to do what?

1. Solve problems over a long period of time,
   through processes such as reproduction, mutation,
   and natural selection
2. Each generation of the program improves upon the
   quality of the solution (each new generation is
   better than the previous one)
3. Generate and evaluate thousands of generations in
   seconds

2 and 3
1 and 2
1
3
2
1,2 and 3
117
Tier I - Quiz
Question 8

• Which of the following statements are false?
• The need for capital investment savings has led
  to the creation of data-mining techniques
• A black-box model using the plant process data
  directly takes the process fundamentals into
  account
• Multivariate analysis is defined as the
  simult