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

2 How to use this presentation
This presentation contains internal links to other slides and external links to websites: Example of a link (text underlined in grey): link to a slide in the presentation or to a website : 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 icon takes the user back to the question statement if a wrong answer has been given Module 8 – Introduction to Process Integration

3 Table of contents Project Summary Module Structure & Purpose Tier I
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 Module 8 – Introduction to Process Integration

4 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 Module 8 – Introduction to Process Integration

5 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 Module 8 – Introduction to Process Integration

6 Project Summary Objectives Participating institutions
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 Module 8 – Introduction to Process Integration

7 PIECE Process integration for Environmental Control in Engineering Curricula Paprican École Polytechnique de Montréal Universidad Autónoma de San Luis Potosí University of Ottawa Universidad de Guanajuato North Carolina State University Instituto Mexicano del Petróleo University of Texas A&M NAMP Program for North American Mobility in Higher Education Module 8 – Introduction to Process Integration

8 This module was created by:
Carlos Alberto Miranda Alvarez Paul Stuart From Host Institution Host director Martin Picon-Nuñez Jean-Martin Brault Module 8 – Introduction to Process Integration

9 What is the structure of this module?
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. Module 8 – Introduction to Process Integration

10 What is the purpose of this module?
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. Module 8 – Introduction to Process Integration

11 Tier I Background Information
Module 8 – Introduction to Process Integration

12 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 Module 8 – Introduction to Process Integration

13 Tier I is broken down into three sections
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. Module 8 – Introduction to Process Integration

14 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 Module 8 – Introduction to Process Integration

15 1.1 Introduction and definition of Process Integration
Module 8 – Introduction to Process Integration

16 .......... but he should. Let’s look at why...
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. Let’s look at why... Module 8 – Introduction to Process Integration

17 A brief history of Process Integration
Introduction and Definition of Process Integration A brief history of Process Integration 1960’s-1970’s 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 1980’s-1990’s Concept expansion from energy to process design 1990’s-2000’s 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… Module 8 – Introduction to Process Integration

18 Modern Process Integration context
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) Module 8 – Introduction to Process Integration

19 Definition of Process Integration
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 Module 8 – Introduction to Process Integration

20 Definition of Process Integration
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.” Module 8 – Introduction to Process Integration

21 Definition of Process Integration
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” Module 8 – Introduction to Process Integration

22 Definition of Process Integration
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.” Module 8 – Introduction to Process Integration

23 Definition of Process Integration
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 Module 8 – Introduction to Process Integration

24 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 Module 8 – Introduction to Process Integration

25 Possible objectives Reducing COSTS POLLUTION ENERGY Increasing
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 Reducing COSTS POLLUTION ENERGY Increasing THROUGHPUT YIELD PROFIT Module 8 – Introduction to Process Integration

26 Real-Time Process Data
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 Module 8 – Introduction to Process Integration

27 Process engineering principles and in-depth process sector knowledge
Introduction and Definition of Process Integration Conclusion Process Integration has evolved from heat recovery methodology in the 80’s 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 Module 8 – Introduction to Process Integration

28 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 Module 8 – Introduction to Process Integration

29 1.2 Overview of Process Integration Tools
Module 8 – Introduction to Process Integration

30 Real Time Optimization Data Treatment and Reconciliation
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 Module 8 – Introduction to Process Integration

31 Real Time Optimization Data Treatment and Reconciliation
Overview of Process Integration Tools Business Model 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 NEXT Module 8 – Introduction to Process Integration

32 Process Simulation Module 8 – Introduction to Process Integration

33 Simulation: “what if” experimentation with a model
Process simulation Simulation: “what if” experimentation with a model Simulation involves performing a series of experiments with a process model PROCESS MODEL Input Output X1, ..., Xn X1, ..., Xm Y1, ..., Yk Y1, ..., Yt A model does not include everything: n>m and k>t “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 Module 8 – Introduction to Process Integration

34 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 Module 8 – Introduction to Process Integration

35 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? ADVANCEMENT of plant operations/ OPERATIONAL SUPPORT OPTIMIZATION OPTIMIZATION of plant operations Online system EDUCATION, TRAINING CONTROL SYSTEM Quasi-online PROCESS DESIGN / ANALYSIS Off-line MODEL Input Output X1, ..., Xm Y1, ..., Yt MODEL (t) Input Output X(t)1, ..., X(t)m Y(t)1, ..., Y(t)t Figure 3 Figure 2 Next Tool Module 8 – Introduction to Process Integration

36 Data Treatment and Reconciliation
Module 8 – Introduction to Process Integration

37 Objectives of Data Treatment
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 Module 8 – Introduction to Process Integration

38 Data Reconciliation 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 Module 8 – Introduction to Process Integration

39 Quantified Performance
Data Treatment & Reconciliation - Benefits DATA RECONCILIATION Measurement Errors? Gross Error Detection Unclosed Balances? Closed Balances Unidentified Losses? Identified Losses Efficiency? Monitored Efficiency Performance? Quantified Performance Next Tool Module 8 – Introduction to Process Integration

40 Pinch Analysis Module 8 – Introduction to Process Integration

41 What is Pinch Analysis? 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 Module 8 – Introduction to Process Integration

42 Features Pinch Analysis 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 Module 8 – Introduction to Process Integration

43 In addition, Pinch Analysis allows you to
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 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 Next Tool Module 8 – Introduction to Process Integration

44 Optimization by Mathematical Programming
Module 8 – Introduction to Process Integration

45 Mathematical Model Optimization of Mathematical Programming
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 Module 8 – Introduction to Process Integration

46 What is Optimization? Optimization of Mathematical Programming
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. Module 8 – Introduction to Process Integration

47 Applications Optimization of Mathematical Programming
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 Module 8 – Introduction to Process Integration

48 Stochastic Search Methods
Module 8 – Introduction to Process Integration

49 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. Module 8 – Introduction to Process Integration

50 There are different types of stochastic algorithms
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 Module 8 – Introduction to Process Integration

51 Life Cycle Analysis (LCA)
Module 8 – Introduction to Process Integration

52 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 Module 8 – Introduction to Process Integration

53 Life Cycle Analysis Extraction and Processing of Raw Materials
Recycling and Disposal as Waste at the end of its useful life Extraction and Processing of Raw Materials Manufacturing Packaging Marketing Use, Reuse and Maintenance of the product Figure 5 Module 8 – Introduction to Process Integration

54 Improves overall environmental performance and compliance
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 Module 8 – Introduction to Process Integration

55 Data-Driven Process Modeling
Module 8 – Introduction to Process Integration

56 Data-Rich but Knowledge-Poor
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. Module 8 – Introduction to Process Integration

57 Theoretical vs. Empirical Model
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 Module 8 – Introduction to Process Integration

58  What is MVA? Benefits Data-Driven Process Modeling
Multivariate Analysis” (> 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 MVA Benefits Explore inter-relationships « What-if » exercises Software sensors Feed-forward control Next Tool Module 8 – Introduction to Process Integration

59 Integrated Process Design & Control
Module 8 – Introduction to Process Integration

60 Context Objectives Integrated Process Control & Control
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 Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

62 Improvement of current dynamics
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 Module 8 – Introduction to Process Integration

63 Real-Time Optimization (RTO)
Module 8 – Introduction to Process Integration

64 Importance of real-time or on-line optimization!
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! Module 8 – Introduction to Process Integration

65 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 Module 8 – Introduction to Process Integration

66 RTO - Schematically Real Time Optimization Business objectives;
Economic data; Product specification RTO - Schematically Reconciliation & gross error detection Updating process model (Steady-statedynamic simulation) Optimization (objective functions) Steady-state detection Cost, process, Environmental & product Data Plant facility Figure 6 Next Tool Module 8 – Introduction to Process Integration

67 Business Model and Supply Chain Modeling (BM-SCM)
Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

69 Data Validation & Reconciliation Cost, Process, Environmental
BM-SCM – Cost, Process, Environmental & Product Data Integrated Business & Process Model Cost, Process, Environmental and Product Data Data Validation & Reconciliation Data Processing Processed P&E Data Data Reconciliation Reconciled The double arrows mean that the data set is consistent throughout the plant facilities Process (P) & Environmental (E) Data Accounting Data Product Market Once the model is built, it can be used to validate and reconcile data Plant Facilities Module 8 – Introduction to Process Integration

70 Integrated Business and Process Model
BM-SCM – Integrated Business & Process Model Cost accounting model Model that deals with the classification, recording, allocation, and summarization of data for the purpose of management decision making and financial reporting Environmental Data Market Data Accounting Data Process Data Product Data Supply Chain (SC) and Env. SC models Click here Integrated Business and Process Model Cost Accounting Model Supply Chain(SC) and Env. SC Models Data Driven Models Process Simulation Models 1st Principles Models Cost, Process, E & P Data Module 8 – Introduction to Process Integration

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 (Waste) 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) Module 8 – Introduction to Process Integration

72 Objectives of the SC and ESC models
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 Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

74 1.3 Around-the-world tour of PI practitioners which focuses on their expertise
Module 8 – Introduction to Process Integration

75 Institutions Companies
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 Module 8 – Introduction to Process Integration

76 Institutions Around-the-world tour of PI Practitioners
North and South America Europe Africa, Middle-East, Asia and Oceania Click on a continent to view institutions from that continent Module 8 – Introduction to Process Integration

77 Institutions-North and South America
Around-the-world tour of PI Practitioners Institutions-North and South America Canada (2) Mexico (1) USA (8) Brazil (1) To view institutions from a particular country, click on the flag of the country of choice Back to World Map Module 8 – Introduction to Process Integration

78 Institutions-Europe Around-the-world tour of PI Practitioners
Belgium (1) Greece (1) Spain (1) Denmark (1) Hungary (1) Sweden (1) Finland (3) Norway (1) Switzerland (1) France (1) Portugal (2) UK (5) Germany (2) Slovenia (1) To view institutions from a particular country, click on the flag of the country of choice Back to World Map Module 8 – Introduction to Process Integration

79 Institutions-Africa, Middle-East, Asia and Oceania
Around-the-world tour of PI Practitioners Institutions-Africa, Middle-East, Asia and Oceania South Africa (1) Israel (1) India (1) Australia (3) To view institutions from a particular country, click on the flag of the country of choice Back to World Map Module 8 – Introduction to Process Integration

80 Back to Americas Institutions
Around-the-world tour of PI Practitioners Canada École Polytechnique de Montréal, Department of Chemical Engineering, Montréal Major Contact: Professor Paul Stuart Web: 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 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 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 NEXT Back to Americas Institutions Module 8 – Introduction to Process Integration

81 Back to Americas Institutions
Around-the-world tour of PI Practitioners Canada University of Ottawa, Department of Chemical Engineering, Ottawa Major Contact: Professor Jules Thibault Web: Brazil Universidade Federal do Rio de Janeiro, Rio de Janeiro Major Contact: Professor Eduardo Mach Queiroz Web: Back to Americas Institutions Module 8 – Introduction to Process Integration

82 Back to Americas Institutions
Around-the-world tour of PI Practitioners Mexico Universidad de Guanajuato, Department of Chemical Engineering, Guanajuato Major Contact: Dr Martín-Picón-Núñez Web: 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 Back to Americas Institutions Module 8 – Introduction to Process Integration

83 Back to Americas Institutions
Around-the-world tour of PI Practitioners USA Carnegie Mellon University, Department of Chemical Engineering, Pittsburgh Major Contact: Professor Ignacio E. Grossmann Web: 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 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 Consortium: CAPD (Centre for Advanced Process Decision-making, founded 1986, 20 members (2001)) including operating companies, engineering & contracting companies, consulting companies and software vendors NEXT Back to Americas Institutions Module 8 – Introduction to Process Integration

84 Back to Americas Institutions
Around-the-world tour of PI Practitioners USA Texas A&M University, Department of Chemical Engineering, College Station Major Contact: Professor Mahmoud M. El-Halwagi Web: and 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 NEXT Back to Americas Institutions Module 8 – Introduction to Process Integration

85 Back to Americas Institutions
Around-the-world tour of PI Practitioners USA Auburn University, Auburn Major Contact: Professor Christopher Roberts Web: Massachusetts Institute of Technology (MIT), Department of Chemical Engineering, Cambridge Major Contact: Professor George Stephanopoulos Web: NEXT Back to Americas Institutions Module 8 – Introduction to Process Integration

86 Back to Americas Institutions
Around-the-world tour of PI Practitioners USA Princeton University, Princeton Major Contact: Professor Christodoulos A. Floudas Web: 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/ NEXT Back to Americas Institutions Module 8 – Introduction to Process Integration

87 Back to Americas Institutions
Around-the-world tour of PI Practitioners USA University of Massachusetts, Amherst Major Contact: Professor J. M. Douglas Web: University of Pennsylvania, Philadelphia Major Contact: Professor Warren D. Seider Web: Back to Americas Institutions Module 8 – Introduction to Process Integration

88 Back to Europe Institutions
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: Denmark Technical University of Denmark, Lyngby Major Contact: Professor Bjørn Qvale Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

89 Back to Europe Institutions
Around-the-world tour of PI Practitioners Finland Åbo Akademi University, Process Design Laboratory, Åbo Major Contact: Professor Tapio Westerlund Web: Lappeenranta University of Technology, Lappeenranta Major Contact: Professor Lars Nyström Web: Helsinki University of Technology, Laboratory of Energy Engineering and Environmental Protection, Helsinki Major Contact: Professor Carl-Johan Fogelholm Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

90 Back to Europe Institutions
Around-the-world tour of PI Practitioners France INPT-ENSIGC, Chemical Engineering Laboratory, Toulouse Major Contact: Professor Xavier Joulia Web: Greece Chemical Process Engineering Research Institute, Hellas Major Contact: Professor I. Vasalos Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

91 Back to Europe Institutions
Around-the-world tour of PI Practitioners Germany Universität Dortmund, Dortmund Major Contact: Professor A. Behr Web: Technische Universität Hamburg, Harburg Major Contact: Professor Günter Gruhn Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

92 Back to Europe Institutions
Around-the-world tour of PI Practitioners Hungary Budapest University of Technology and Economics, Budapest Major Contact: Professor Zsolt Fonyo Web: Norway Norwegian University of Science and Technology, Process Systems Engineering in Trondheim (PROST), Trondheim Major Contact: Professor Sigurd Skogestad Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

93 Back to Europe Institutions
Around-the-world tour of PI Practitioners Portugal Universidade do Porto, Porto Major Contact: Professor Manuel A.N. Coelho Web: Instituto Superior Técnico, Lisboa Major Contact: Professor Clemente Pedro Nunes Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

94 Back to Europe Institutions
Around-the-world tour of PI Practitioners Slovenia University of Maribor, Maribor Major Contact: Professor Peter Glavič Web: Switzerland Swiss Federal Institute of Technology, Lausanne Major Contact: Professor Daniel Favrat Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

95 Back to Europe Institutions
Around-the-world tour of PI Practitioners Spain Universitat Politècnica de Catalunya, Chemical Engineering Department, Barcelona Major Contact: Professor Luis Puigjaner Web: 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 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 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 Back to Europe Institutions Module 8 – Introduction to Process Integration

96 Back to Europe Institutions
Around-the-world tour of PI Practitioners Sweden Chalmers University of Technology, Department of Heat and Power, Göteborg Major Contact: Thore Berntsson Web: 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 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 Industry: Close cooperation with some of the major pulp and paper industry groups, including training courses and consulting Back to Europe Institutions Module 8 – Introduction to Process Integration

97 Back to Europe Institutions
Around-the-world tour of PI Practitioners UK Imperial College, Centre for Process Systems Engineering, London Major Contact: Professor Efstratios N. Pistikopoulos Web: and 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 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 Consortium: Process Systems Engineering (PSE) with 17 members (2003) including operating, engineering & contracting companies, software vendors NEXT Back to Europe Institutions Module 8 – Introduction to Process Integration

98 Back to Europe Institutions
Around-the-world tour of PI Practitioners UK UMIST, Department of Process Integration, Manchester Major Contact: Professor Robin Smith Web: 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 Current research in Process Integration Efficient use of raw materials (including water) Energy efficiency Emissions reduction Efficient use of capital 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 Back to Europe Institutions NEXT Module 8 – Introduction to Process Integration

99 Back to Europe Institutions
Around-the-world tour of PI Practitioners UK University of Edinburgh, Edinburgh Major Contact: Professor Jack W. Ponton Web: University College, London Major Contact: Dr. David Bogle Web: University of Ulster, Coleraine Major Contact: Professor J.T. McMullan Web: Back to Europe Institutions Module 8 – Introduction to Process Integration

100 Back to Asia Institutions
Around-the-world tour of PI Practitioners Israel Technion, Israel Institute of Technology, Haifa Major Contact: Professor Daniel R. Lewin Web: India Indian Institute of Technology, Bombay Major Contact: Dr. Uday V. Shenoy Web: Back to Asia Institutions Module 8 – Introduction to Process Integration

101 Back to Africa Institutions
Around-the-world tour of PI Practitioners South Africa University of the Witwatersrand, Process & Materials Engineering, Johannesburg Major Contact: Professor David Glasser Web: 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 Current research in Process Integration Systems involving reaction, mixing and separation (e.g. reactive distillation) Non-isothermal chemical reactor systems Optimization of dynamic systems Has founded its own consultancy enterprise called Wits Enterprise Back to Africa Institutions Module 8 – Introduction to Process Integration

102 Back to Oceania Institutions
Around-the-world tour of PI Practitioners Australia University of Adelaide, Adelaide Major Contact: Dr. B.K. O'Neill Web: Murdoch University, Rockingham Major Contact: Professor Peter Lee Web: University of Queensland, Brisbane Major Contact: Professor Ian Cameron Web: Back to Oceania Institutions Module 8 – Introduction to Process Integration

103 Companies Around-the-world tour of PI Practitioners
Linnhoff March Limited, Northwich, Cheshire, UK Web: and Linnhoff March is the pioneering company of Pinch Technology and is now a division of KBC Process Technology Limited since 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 NEXT Back to Companies Module 8 – Introduction to Process Integration

104 Companies Around-the-world tour of PI Practitioners
Process Systems Enterprise Limited, London, UK Web: “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 NEXT Back to Companies Module 8 – Introduction to Process Integration

105 Companies Around-the-world tour of PI Practitioners
Industrial and Power Association-National Engineering Laboratory (NEL), UK Web: QuantiSci Limited, UK Web: NEXT Back to Companies Module 8 – Introduction to Process Integration

106 Companies Around-the-world tour of PI Practitioners
American Process Inc., Atlanta, USA Web: “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 NEXT Back to Companies Module 8 – Introduction to Process Integration

107 Companies Around-the-world tour of PI Practitioners
Advanced Process Combinatorics (APC), USA Web: Aspen Technology Inc. (AspenTech), USA Web: and Back to Companies Module 8 – Introduction to Process Integration

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. Module 8 – Introduction to Process Integration

109 QUIZ Module 8 – Introduction to Process Integration

110 Tier I - Quiz Question 1 Where was the concept of Process Integration first developed? Atlanta, USA Guanajuato, Mexico Manchester, UK Montreal, Canada Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

112 Question 3 Tier I - Quiz 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 Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

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 Module 8 – Introduction to Process Integration

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? Solve problems over a long period of time, through processes such as reproduction, mutation, and natural selection Each generation of the program improves upon the quality of the solution (each new generation is better than the previous one) Generate and evaluate thousands of generations in seconds 2 and 3 1 and 2 1 3 2 1,2 and 3 Module 8 – Introduction to Process Integration

117 Question 8 Tier I - Quiz 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 simultaneous analysis of more than five variables Multivariate Analysis methods are used to replace the physical analysis of a process 1 4 1,2 and 4 1,3 and 4 1,2 and 3 All of the above Module 8 – Introduction to Process Integration

118 Question 9 Tier I - Quiz With a Real-Time Optimization system:
The process is optimized directly Up-to date decisions on plant operations and maintenance to maximize plant profitability can be made Decisions can be made before complete information about the data is available It is possible to determine the economically optimal operating regime for a process in the near term 1 1 and 3 2,3 and 4 1,3 and 4 1,2 and 3 All of the above Module 8 – Introduction to Process Integration

119 Answers Tier I - Quiz Question 1 Manchester, UK
Question 2  1,2,4,9 and 10 ;  3,5,6,7 and 8 Question 3 1,3 and 4 Question 4 1,2,3 and 5 Question 5 3 Question 6 2 Question 7 3 Question 8 1,2 and 4 Question 9 2,3 and 4 Module 8 – Introduction to Process Integration


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