Role of Process Integration in
Process Systems Engineering
Ignacio E. Grossmann
Center for Advanced Process Decision-making (CAPD)
Department of Chemical Engineering
Carnegie Mellon University
Pittsburgh, PA 15213, U.S.A.
International Process Integration
Jubilee Conference
Gothenburg, Sweden
March 18, 2013
What is the impact of Chemical Engineering
on Process Systems Engineering?
What is the impact of Process Systems Engineering
on Process Integration?
Trends in Chemical Engineering
(Last decade)
Bioengineering area :
- Perceived as “hot” area: most new faculty in bio area
- Many new Biomedical Engineering Depts
Job market biomedical engineers?
Many U.S. departments (~50%) were renamed as:
Chemical and Biomolecular Engineering
(e.g. Cornell, U. Penn., Illinois, Georgia Tech)
Chemical and Biological Engineering
(e.g. Colorado, Northwestern, Notre Dame, Wisconsin)
 Nanotechnology is other “hot” area
Trends in Chemical Engineering
(Last decade)
 Increasing emphasis on Science in Chemical Eng.
Departments
- Many professors are not chemical engineers
and do not regard AIChE/IChemE as
their primary organization
- Has increased multidisciplinary approach
- Decreased emphasis on chemical engineering
fundamentals
- Process Design(Process Integration) courses
largely outsourced to retired industry people
- Process Control no longer required at many
U.S. universities
Other examples trends in Chemical Engineering
- Netherlands has now only two chemical engineering departments:
Delft, Eindhoven; no Chaired Process Systems Eng. Professors
- Houston, the capital city of Oil & Gas and Chemical Industry
in US has only ONE Process Systems Engineering Professor
U. Houston: Michael Nikolaou; Rice University: NONE
- Many faculty members in US do not publish anymore
in chemical engineering journals
Trends in Publications
Move from Engineering to Science
Impact factors ~2.2
Impact factors ~30
AIChE J: Top Accepted Articles by
Country of Origin
Country
Total
% of
Submissions
United States
73
13.32%
China
Canada
France
Spain
Germany
India
Netherlands
Japan
United
Kingdom
Australia
Taiwan
Sweden
Belgium
Korea,
Republic of
South Africa
157
32
16
16
10
51
9
17
28.65%
5.84%
2.92%
2.92%
1.82%
9.31%
1.64%
3.10%
17
3.10%
12
10
5
3
2.19%
1.82%
0.91%
0.55%
6
1.09%
3
0.55%
October 30, 2012
US/Canada: 20%
Europe: 16%
China: 30%
India: 10%
Japan, Taiwan, Korea: 7%
Articles Accepted Dec. 15, 2011 through Oct. 23, 2012
7
Dow concerned about big-push to Bio
Dow requires critical scientific & engineering skills75-100 PhD/year
•
•
Chemistry, Materials Science, Chemical Engineering, Mechanical Engineering
Dow Solar, Energy Storage Materials, Lightweight Materials, Electronic Materials
US Chemical Engineering & Chemistry Departments are chasing biotechnologies
31% of the Chemical Engineering Departments in the US added “bio” to their names in 20yrs
“Bio-Tsuname”: Funding New Faculty Research Teaching Students Workforce
Percentage of Faculty with “bio”
Related Research Interests:
Number of Published Articles
2K
1K
3K
0K
Biodiesel + Cellulosic Ethanol +
Bioengineering
Reactor Design +
Transp. Phenomena
+ Fluid Dynamics
Northwestern
U
Illinois
UT
Austin
UC
Santa
Barbara
Caltech
58%
Berkeley
Georgia
Tech
Top Strategic Universities
•
•
Dow Has to Influence the
Scientific Funding Environment
AS THE BIGGEST US EMPLOYER IN THE
CHEMICAL INDUSTRY DOW HAS TO:
• Partner with strategic universities to:
• Work on problems relevant to Dow
(e.g. PSE/Process Integration)
• Develop talent with the skills needed
• Influence the “Influencers”
Commit to Long Term Funding
$25 million/year for next 10 yr in US
$10 million/year for next 10 yr outside US
9
“Dow will invest in
fundamental research
at US Universities”
FUNDI NG THE FUNDAM ENTALS
Do w Ch e m i ca l co m m i t s $2 5 0 m i l l i o n t o US
u n i v e r si t i e s t o r e i n f o r ce b a si c R& D
New emphasis: energy and sustainability
Growing World Energy Demand
Most Energy Growth in Developing Nations
Sheppard, Socolow (2007)
Energy and sustainability likely to swing pendulum
against bio and nano areas in Chemical Engineering
Trends in Process Systems Engineering
Motivation
1. Balance between “commodity” industry vs.
“new emerging” technologies
Value preservation vs. Value creation
2. Use of fossil fuels vs. renewable energy technologies
and environmental impact
3. Global supply chains and their optimization
Research Challenges in Process Systems Engineering?
Expanding the Scope of Process Systems Engineering
(Grossmann & Westerberg, 2000; Marquardt et al, 1998)
What is science base for PSE?
Process Knowledge => Conceptual design=> Process Integration
Numerical analysis => Simulation => Performance process-product
Mathematical Programming => Optimization => Synthesis/design
Systems and Control Theory => Process Control => Manufacture
Computer Science => Advanced Info./Computing => Efficient
problem solving
Management Science => Operations/Business
=> Supply chain
Research Challenges in PSE
I. Product and Process Design
II. Energy and Sustainability
III. Enterprise-wide Optimization
I.
Product and Process Design:
from “Bulk” to “Molecular” Processing
George Stephanopoulos (2004)
XA
XB
XC
XD
XE
XF
XG
XH
Macro-Processing:
Batch or Continuous Chemical Plants
XD
XE
XF
XG
XH
Micro-Processing:
Plant-on-a-Chip
Molecular-Processing:
The Cell
Metabolites
DNA
RNA
Protein
De Novo Protein Design
Define target template
Backbone coordinates for N,Ca,C,O
and possibly Ca-Cb vectors from PDB
Human b-Defensin-2
hbd-2 (PDB: 1fqq)
Approach
In silico sequence selection => MILP
Fold specificity => Global optimization
(Chris Floudas, Princeton)
Design folded protein
Which amino acid sequences will
stabilize this target structure ?
Full sequence design
Combinatorial complexity
-Backbone length : n
-Amino acids per position : m
mn possible sequences
=> New improved inhibitors
(Klapeis, Floudas, Lambris, Morikis, 2004)
Metabolic Networks: Inverse Problem
(Ghosh, Domach, Grossmann, 2004)
Find reaction pathway
(linear combination of
extreme points for fluxes)
that minimizes squared
deviation from NMR spectra
for given selection of
measured metabolites
MILP for all extreme points
Global optimization inverse problem
Venkat Venkatasubramanian
Multi-Scale
Model
Quantum Mechanics
Kinetics
Heat Transfer FEA
Mechanics FEA
Part Design CAD
/CAM
Integrated Design of
Formulated Rubber Parts
Gani et al. (2012)
II. Energy and Sustainability
Environmental impact
oa
l
C
po
w
H
yd
ro
G
as
er
d
W
in
ar
uc
le
lta
vo
ot
o
Ph
Bi
om
as
N
ics
1000
900
800
700
600
500
400
300
200
100
0
s
CO2 eq. (g/kWh)
Renewables: Carbon footprint various Energy Options
Adisa Azapagic (2012)
Carnegie Mellon
20
Depletion of fossil fuels?
Oil Reserves
Year 2000
Total: 1105 thousand million barrels
6,20%
Year 2010
Total: 1383 thousand million barrels
3,60%
5,40%
8,50%
Middle East
3,30%
25% increase!
9,50%
S. & Cent. America
9,70%
Europe & Eurasia
10,10%
Africa
8,90%
63,10%
54,40%
North America
Asia Pacific
17,30%
 Discovery of New Large Oil and Gas Reserves
 New technologies for Offshore oil exploration and production
*Statistical Review of World Energy (June, 2011)
Carnegie Mellon
21
Depletion of fossil fuels?
Growth in Shale Gas
In 2035 close to 50% from Shale Gas
Carnegie Mellon
Horizontal drilling
Hydraulic fracking
Northeast: from 0.3 trillion scft 2009
to 5.8 trillion scft
2035
22
Water scarcity
Two-thirds of the world population will face water stress by year 2025
Carnegie Mellon
23
Biorefinery
Bioethanol, FT-diesel and hydrogen from switchgrass
Martin, Grossmann (2012)
Biodiesel from cooking oil or algae oil
24
Carnegie Mellon
Conceptual Design Strategy
for Energy and Water Optimization
Energy optimization
Issue: fermentation reactions at modest temperatures
=> No source of heat at high temperature as in petrochemicals
Multieffect distillation followed by heat integration process streams
Water optimization
Issue: cost contribution is currently still very small
(freshwater contribution < 0. 1%)
=> Total cost optimization is unlikely to promote water conservation
Optimal process water networks for minimum energy consumption
25
Carnegie Mellon
Scope of Advanced Process Systems Engineering Tools
Energy consumption corn-based process
Author (year)
Energy consumption
(Btu/gal)
Pimentel (2001)
75,118
Keeney and DeLuca (1992)
48,470
Wang et al. (1999)
40,850
Shapouri et al. (2002)
51,779
Wang et al (2007)
38,323
From Karrupiah et al (2007)
24,918 Btu/gal vs 38,323 Btu/gal
Why? Multieffect distillation
and heat integration
Water consumption corn-based process
Author (year)
Water consumption
( gal/gal ethanol)
Gallager (2005) First
plants
11
Philips (1998)
5.8
MATP (2008)
Old plants in 2006
4.6
MATP (2008)
New plants
3.4
From Martin and Grossmann (2010)
1.5 gal water/gal ethanol vs 3.4
Why? Integrated process network
with reuse and recycle
26
Carnegie Mellon
Optimal Development of Oil Fields (deepwater)
Offshore field having several reservoirs (oil, gas, water)
facilities
Gupta, Grossmann (2011)
Decisions:
Number and capacity of FPSO facilities
Installation schedule for facilities
Number of sub-seawells to drill
Oil/gas production profile over time
Objective:
Maximize the Net Present Value
(NPV) of the project
wells
Reservoirs
FPSO (Floating Production Storage Offloading)
MINLP model
- Nonlinear reservoir behavior
- Three components (oil, water, gas)
- Lead times for FPSO construction
- FPSO Capacity expansion
- Well Drilling Schedule
Example
Optimal NPV = $30.946 billion
Total Oil/Gas
Production
20 Year Time Horizon
10 Fields
3 FPSOs
23 Wells
3 Yr lead time FPSO
1 Yr lead time expansion
FPSO-3
FPSO-2
FPSO-1
Yr 1
Yr 2
Field-6
Field-1
Field-3
Field-5
Yr5
Yr4
Yr7
Field-4
Yr7
Field-2
Yr5
Field-7
450
400
350
300
250
200
150
100
50
0
Yr5
fpso1
fpso2
fpso3
t1
t2
t3
t4
t5
t6
t7
t8
t9
t10
t11
t12
t13
t14
t15
t16
t17
t18
t19
t20
x (kstb/d)
Oil Flowrate
1 2
3 4
5 6
7 8
Yr 1
9 10Time
11 12 13 14 15 16 17 18 19 20
Yr7
Field-8
Yr6
Field-9
Yr4
Field-10
Yr4
III. Enterprise-wide Optimization
Beyond the plant level/ Integration with business operations
Wellhead
Trade &
Schedule
Crude and
Other
Feedstocks
Trade & Transfer of Terminal
Transfer of Refinery
Loading
Crude and Optimization Schedule Products
from
Products
Feedstocks
Refinery
to Refinery
to Terminal
Dennis Houston (ExxonMobil)
Discovery
Targets
Hits
Leads
Candidate
2-5 yrs
Market
Development
Preclinical
Development
Phase 1
0.5 - 2 yrs 1 - 2 yrs
Phase 2a/b
Phase 3
1.5 - 3.5 yrs 2.5 - 4 yrs
Colin Gardner (Transform Pharmaceuticals)
Pump
Submission& Lifecycle
Approval
Management
0.5-2 yrs
10-20 yrs
Optimization
Production Planning for Parallel BatchEnterprise
Reactors
Erdirik, Grossmann (2007)
Materials:
F1
Raw materials, Intermediates, Finished products
Unit ratios (lbs of needed material per lb of material
produced)
F2
Production Site:
F3
•
Reactors:
– Products it can produce
– Batch sizes for each product
– Batch process time for each product (hr)
– Operating costs ($/hr) for each material
– Sequence dependent change-over times
=> Lost capacity
(hrs per transition for each material pair)
– Time the reactor is available during a given
month (hrs)
Customers:
A
Reaction 1
STORAGE
INTERMEDIATE
STORAGE
Reaction 2
B
STORAGE
Reaction 3
C
STORAGE
F4
due date
due date
due date
Monthly forecasted demands for desired products
Price paid for each product
week 1
week 2
week t 30
Design of Responsive Chemical Supply Chains under Uncertainty
Network Structure at Location Map
You, Grossmann (2009)
31
Optimal Planning of Sustainable Chemical Supply Chains
Guillen, Grossmann (2007)
Markets
l=1,…,L
Warehouses
k=1,…,K
Plants
j=1,…,J
t
WH klp
Suppliers
Technology 1
PUjpt
PL jkpt
Q
Wijpt
Technology I
INVkpt
Life Cycle Analysis
DMKlpt
Q
CWHkt
CPLijt
Technology 1
Technology I
Pareto-Optimal Solutions
Bicriterion optimization
Max Net Present Value
Min Environmental Impact
Eco-Indicator 99 for LCA
(Health, Ecosystem, Resources)
Uncertainty in emissions
China, September 2007
Parametric programming
32
Energy Supply Chain Model
Floudas et al., 2011)
Hybrid Coal, Biomass, and Natural Gas to Liquids Systems
Coal availabilities from database
Grid points of candidate facility locations
Transportation fuel
demand
Biomass availabilities from database
Water supply
Carbon dioxide
sequestration
capacities
Energy Supply Chain
Optimization Model
Natural gas availabilities from database
CBGTL plant
parameters
Transportation
infrastructure
33
Network Layout
MILP: 105,000 binary variables, 3,311,000 continuous
62,000 constraints.
Overall cost: $18.93/GJ LHV
($95.11/bbl crude oil)
130 facilities selected (9 small, 74 medium, 47 large)
50% reduction in emissions
34
Concluding Remarks
Major challenges in Process Systems Engineering
Product and Process Design
Energy and Sustainability
Enterprise-wide Optimization
+
Fundamentals of Process Systems Engineering
Modeling
Optimization
Process Synthesis/Process Integration
Process Operations
Process Control
Challenge of Process Systems/Process Integration community:
Communicate importance of area to rest of Chemical Engineering
Driven by Industrial Needs!!
35