Enabling model based decision support[1]

Enabling Model-Based Decision Support for Plant
Optimization
An Industry White Paper
Stephen Sarafian, Research & Development, Aspen Technology, Inc.
Ken Dooley, Industry Marketing, Aspen Technology, Inc.

© 2012 Aspen Technology, Inc. AspenTech®, aspenONE®, the aspenONE® logo, the Aspen leaf logo, and OPTIMIZE are trademarks of Aspen Technology, Inc. All rights reserved. All other
trademarks are property of their respective owners. 11-1969-0612

About AspenTech
AspenTech is a leading supplier of software that optimizes process manufacturing—for energy, chemicals,
pharmaceuticals, engineering and construction, power & utilities, mining, pulp and paper, and other mill
products industries that manufacture and produce products from a chemical process. With integrated
aspenONE® solutions, process manufacturers can implement best practices for optimizing their
engineering, manufacturing, and supply chain operations. As a result, AspenTech customers are better
able to increase capacity, improve margins, reduce costs, and become more energy efficient. To see how
the world’s leading process manufacturers rely on AspenTech to achieve their operational excellence
goals, visit www.aspentech.com.

Enabling Model-Based Decision Support for Plant Optimization

Executive Summary
Companies in the process industries worldwide are experiencing increased volatility in their performance while operating
in a challenging and competitive environment. These challenges include: economic uncertainty, global demand shifts,
fluctuating feedstock and production prices, eroding margins and developing and retaining a talent pool. Meeting these
challenges requires making complex business decisions with the agility to adapt to dynamic market conditions. Solutions
that enable the optimization of the decision-making process provide significant value, contributing to the success of
operations and increased profitability.

Decision-support tools have been developed for specific business functions such as process modeling, design, simulation
and optimization, production planning and scheduling, performance monitoring, energy management and more. These
solutions lead to improved decision-making and operating efficiencies. This paper will examine an easy-to-use tool that
extends decision-support capabilities to a wide variety of stakeholders in the design and operation of plant facilities.
Industrial applications implemented by various companies will also be presented to illustrate practical use of this solution.

Excel
Model End Users

Aspen Plus

Model Author
Aspen HYSYS

Figure 1: Aspen Simulation Workbook (ASW) enables Excel users to rapidly run scenarios using the underlying
rigorous models to analyze plant data, monitor performance, and make better decisions.


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Introduction
Improving operations is critical for process plants to remain competitive. Leading companies around the world are using
model-based decision support as an operations best practice to achieve their goals. Some of the benefits include:
• 2-6% improvement in plant capacity
• Up to 10% reduction in energy consumption
• Better product consistency
• Increased safety and reliability
• Labor savings
Model-based decisions are dependent on process simulation models that are developed by users familiar with the
underlying simulation tools. However, many companies fail to leverage models beyond the design process because plant
engineers and operators may not have sufficient knowledge of and experience in the use of the process simulators. On the
other hand, most users are comfortable with Microsoft Excel®. To address this gap, AspenTech offers a solution that easily
links process models with Excel worksheets to enable use of the models by a broader range of users including operations
personnel. Putting models into the hands of operations staff provides them with a decision-support tool based on rigorous
Chemical Engineering principles.

Need for Integrating Simulation Models with Excel
Aspen HYSYS® and Aspen Plus® are industry-leading process simulators that have been proven over decades for
conceptual design, optimization, business planning, asset management and performance monitoring in process industries.
These process simulators feature:
• Best-in-class physical property methods and data
• Comprehensive library of unit operation models
• An efficient workflow for process design, equipment sizing, and preliminary cost estimation
Process simulation models contain valuable information such as plant targets, equipment performance and inferred
properties. However, often there are relatively few users that can manipulate these models to access this valuable
information. Aspen Simulation Workbook (ASW) provides integration between process simulators such as Aspen Plus
and Aspen HYSYS and Microsoft Excel that enables model authors to deploy process models to a wider range of model
users (Figure 1). Model authors follow a simple copy/paste workflow to attach model variables to tables in Excel, enabling
model users to interact with the model using Excel. The ASW tab in Excel provides easy-to-use controls to enhance the
Excel interface with unit operation icons, tables, buttons and other form control actions, resulting in a convenient and
interactive environment for model usage. Models can also be linked to online plant data for monitoring, generating reports
and on-demand decision making.


2


Aspen Simulation Workbook
Aspen Simulation Workbook provides easy and robust integration between AspenTech’s process simulators and Microsoft
Excel, allowing you to rapidly deploy models to a wider range of users without writing a single line of code. During model
building it is important to ensure that the models are robust over a reasonably wide range of conditions. Appropriate
engineering judgment must be applied to keep the model as simple as possible for the intended application or purpose,
resulting in a robust and interactive experience for the casual Excel-based user.

Excel-based Conditional Formatting
Several features of Microsoft Excel are especially convenient to use with Aspen Simulation Workbook. For example, the
“conditional formatting” feature can be used to change the font, background color, and other formatting associated with a
cell based on the value of the data in that cell or based on a user-specified criteria (Figure 2).

Figure 2: Conditional Formatting can be used to make your Aspen Simulation
Workbook model interface more visually appealing and easier to use.

Links to Plant Data
Linking simulation models to plant data within the same Excel sheet allows the model user to:
• Populate simulation cases with measured plant data
• Send simulation results back to the plant information system using tags
• Overlay model predictions with plant data in plots and tables
Plant data tags can be linked to Excel using the standard features of most process historians such as Aspen InfoPlus. 21®.
The tuned models are then used in a predictive mode for what-if studies and other operational improvement scenarios.
ASW provides an easy mechanism for Excel connectivity to plant databases, allowing plant data to be retrieved on
demand and applied to the simulation model (Figure 3).

Plant data tags can be updated each time a process simulation case is run from within Aspen Simulation Workbook. After
the simulation is complete, the tags mapped to model variables are updated with calculation results from the simulation.


3


Figure 3: ASW links simulation models to plant data.

Aspen Plus Aspen HYSYS

Excel ASW

Aspen InfoPlus.21 and
other historians

Scenario Analysis and Performance Monitoring
Aspen Simulation Workbook makes it easy to run hundreds of scenarios through your model to analyze historical data,
analyze process sensitivity, check design cases, evaluate operating conditions, or evaluate a range of feedstocks. The
Scenario feature sets up a table where the user can enter the values of several model inputs (columns) for several cases
(rows). The scenarios are executed sequentially, with key simulation results filling in additional columns. The resulting
table makes it very easy to compare a large number of cases. When used with historical plant data, the Scenario feature
makes it easy to identify changes in plant performance (e.g., changes caused by exchanger fouling over weeks or months),
monitoring equipment, inferring properties, and more.

Workflow Optimization
Workflows can be optimized to easily automate repetitive tasks, such as extracting data from simulations to rapidly
generate reports and charts using Excel (Figure 4).

Figure 4: Results from disparate locations
are consolidated into a single report showing
linked plant historian data.


4


Dynamic Analysis
Aspen Simulation Workbook provides full support for the use of dynamic models (Figure 5). It allows development of
interfaces to batch models or dynamic models of continuous processes, and displays the model results in profile tables or
Excel-based strip charts. Users can interact with the models as they run and see the results in real or faster-than-real time.

Figure 5: Aspen Simulation Workbook supports use of dynamics such as this dynamic crude unit model.

Links to Third-Party Tools
Aspen Simulation Workbook also recognizes the need to link models to third-party tools. Typical applications include
linking models to risk management software, equipment design tools, Monte-Carlo optimization engines, or cost
estimation tools. Aspen Simulation Workbook supports linking your models to these tools using Excel as an integration
environment.

Aspen Simulation Workbook is tightly integrated with the aspenONE® Engineering solutions identified below, enabling
seamless interoperability between AspenTech’s engineering tools and Microsoft Excel.

• Aspen Plus, including Aspen Polymers, Aspen Rate-Based Distillation, and Aspen Plus Dynamics
• Aspen HYSYS, including Aspen HYSYS Dynamics and Aspen HYSYS Upstream
• Aspen HYSYS Petroleum Refining, including reactor calibration environments
• Aspen Custom Modeler® and related products including Aspen Adsorption, Aspen Model Runner, and Aspen
Chromatography (all run modes are supported)
• Aspen Exchanger Design and Rating products including Aspen Shell and Tube Exchanger, Aspen Air Cooled Exchanger,
Aspen Plate Fin Exchanger, Aspen Shell and Tube Mechanical, and Aspen Fired Heater


5


Case Studies
Companies have successfully used ASW to improve plant operations with robust simulation models for improved decision
making, knowledge transfer from experts to less experienced plant personnel, and reduced engineering time through the
automation of complex workflows.

Valero
Valero, a large independent North American refiner, was challenged to achieve optimal performance whenever crudes
were switched. They needed to determine key plant operating targets quickly and achieve faster steady state operation
with a goal to reducing operating costs. An ASW interface driven by an Aspen HYSYS-based model was developed. The
model was made available to operating personnel through an Excel interface, enabling them to make faster and better
decisions. The resulting improvements reduced analysis times for new feedstock and operating scenarios using the power
of modeling. This company was able to get a much better understanding of their crude unit operation and achieve
consistent and improved performance (Figure 6).1

Figure 6: ASW-enabled Excel interface with Aspen HYSYS
improves operations decision-making.

ConocoPhillips
ConocoPhillips needed to develop a business application to optimize their feedstock selection decisions. However, they
had disparate custom models from multiple software programs which their business team was not accustomed to using.
The company decided to implement an Aspen HYSYS-based solution to leverage the power of rigorous models with an
Excel-based interface using Aspen Simulation Workbook. The Excel interface provided a single, easy-to-use environment
with access to input and results (Figure 7). The refinery was able to make rapid, accurate and profitable feedstock
purchase decisions based on the true understanding of current refinery operations, demand and economics.2


6


Aspen Simulation
Workbook

Feed rates and
composition
in Excel R&D yield
validation
model in Excel

Economic/Profitability
Functions in Excel

Fractionation
model in
Aspen HYSYS

Figure 7: A business application to leverage the power of rigorous models with an Excel-based interface using Aspen Simulation Workbook.

Kuraray
Kuraray is a leading Japanese chemical company which needed to optimize their synthetic fiber manufacturing plant.
Kuraray used Aspen Custom Modeler (ACM) to model the fixed bed reactor; this detailed reactor model included
main/side reactions, heat transfer, catalyst deactivation, and fouling. The reactor model was linked to Excel with ASW to
build an off-line decision-support system. The rigorous model was able to simulate dynamic plant performance within
minutes to predict plant conversion and yield, resulting in significantly improved plant operation.

HPCL
HPCL, an Indian refiner, needed to reduce energy in the naphtha stabilizer column, reduce steam consumption, and
maintain the Reid Vapor Pressure (RVP) of the naphtha. Using ASW, engineers created an online plant performance
monitoring application linking their plant real-time database with an Aspen HYSYS model of the plant. Critical plant
values and model results were displayed continuously to operators in both a table and graphical format, providing
guidance to a larger operational staff that was not familiar with Aspen HYSYS and resulting in a significant reduction in
steam consumption and improved product quality.

Turbine Air Systems (TAS)
Turbine Air Systems is a manufacturer of large modular systems for power, industrial and commercial HVAC industries.
They were faced with the challenge of having several complex customized systems which needed a thorough design
analysis; however they only had a few design experts, and this was the limiting factor to their growth. TAS used Aspen
HYSYS models linked to Excel with ASW, enabling even more model users to evaluate projects using standardized designs.
ASW ensured model-based rigorous decision making by non-engineers (model users) with the same high level of
confidence as decisions made by expert model authors. The ASW application, which leveraged existing validated Aspen
HYSYS models, resulted in improved internal operations, better productivity, departmental interactions, distribution of
responsibility, and faster project execution — leading to more projects, more clients, and increased revenue and
profitability.3


7


Summary
Economic uncertainty coupled with changing market dynamics have forced the process industries to take a closer look at
their plant design and operations to cut costs and compete better in an increasingly global environment. Process
industries have already made a significant investment in building detailed process models of their plants. Process
simulation experts can now quickly create Excel access to their models that enable the sharing of information and
knowledge with a wider group of users. ASW extends the value of existing process simulation models from conceptual
engineering to plant operations. ASW saves time and eliminates the need for complex programming while enabling casual
users to make educated decisions by leveraging rigorous simulation models resulting in optimized operations. Numerous
companies have successfully utilized ASW to improve product yield and quality, lower energy consumption, execute
projects faster, save time and labor — ultimately leading to increased profitability.


8


References
1
Schumann, David and Gregory Davis, Valero Energy Company, and Piyush Shah, Aspen Technology, Inc., “Application of
Simulation Models in Operations – A Success Story,” Paper AM-09-23, NPRA Annual Meeting, San Antonio, TX, March
2009.
2
Gislason, Jason, ConocoPhillips, “Using Aspen Simulation Workbook to Make Confident Feedstock Selections,”
AspenTech User Conference, Houston, TX, April 2008.
3
Brown, Duane and Shawn Lee, Turbine Air Systems, and Livia Wiley, Aspen Technology, “Using Aspen Simulation
Workbook to Screen Prospective Business Opportunities,” AspenTech User Conference, Houston, TX, April 2008.

Robertson, Elliott, Burns & McDonnell Engineering, “FEL-2 Optimization of Capital Cost of an NGL Facility Revamp,”
OPTIMIZE 2011 AspenTech Global Conference, Washington, D.C., May 2011.


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Aspen Technology, Inc.
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info@aspentech.com

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© 2012 Aspen Technology, Inc. AspenTech®, aspenONE®, the aspenONE® logo, the Aspen leaf logo, and OPTIMIZE are trademarks of Aspen For a complete list of offices, please visit
Technology, Inc. All rights reserved. All other trademarks are property of their respective owners. 11-1969-0612 www.aspentech.com/locations

Enabling model based decision support[1]

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