industrial algorithms marketing presentation

INDUSTRIAL ALGORITHMS BETTER DECISION-MAKING AND

DATA-MINING

FOR INDUSTRIAL PROBLEMS

Jeff Kelly & Alkis Vazacopoulos, November 2012

1/18/2013

1 Copyright, Industrial Algorithms LLC

Our mission and who we are?

Our mission is to provide efficient solutions to solve complex APS (Advanced Planning and Scheduling) problems.

Who we are:

Jeff Kelly: 25-years of both production & process modeling & optimization for planning, scheduling, control & estimation (PSCE) problems in the process industries, worked in Shell, Exxon, Honeywell, consulted for more than 30 companies

Alkis Vazacopoulos: 25-years of solving production planning and scheduling in process, printing & publishing, consumers goods, etc, worked for Dash Optimization, Fair Isaac, Verisk and consulted for more than 100 companies.

1/18/2013

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Copyright, Industrial Algorithms LLC

What verticals do we serve?

Energy Power

and Utility

Systems

(continuous)

Specialty

Chemicals,

Food &

Beverage,

Pharma

(batch and

continuous)

Mining,

Metals &

Minerals

Pulp & Paper

and Meat

Processing

(batch and

dimensional)

Petroleum

Refining

Oil & Gas

Petro-

chemicals

(continuous

and batch)

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We solve problems that deal with the

following decisions:

Quantity

How much to produce?

What is the batch-size?

Quality

How to blend specific products

to satisfy certain levels of

quality?

Logic

What machines to use?

How to sequence the jobs to

minimize setup costs?

Time

When to produce?

How to respect past decisions &

future orders?

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We solve these types of problems

Our system can model and solve

problems which are a mix of both

planning & scheduling

decision-making.

We introduce nonlinear

optimization in large-scale

planning and scheduling

problems and

solve problems involving

quantity, quality & logic.

We properly manage complexity in

problems that would normally be

considered as uncertainty by other

vendors.

We use data-mining techniques to

support the solving of problems

that incorporate control,

feedback, and maintainability

issues.

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What products do we provide:

IMPRESS: Industrial Modeling & Presolving System is our proprietary modeling platform.

You can model, solve, interface and interact with any supply-chain, production-chain, demand-chain and/or value-chain optimization problem.

IMPRESS so far has been applied in:

Production Planning

Plant Scheduling

Pipeline & Marine Shipping

Energy Management

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Why are we unique?

IMPRESS is flowsheet-based (i.e., a figurative language).

This means that the modeling is inherently network or superstructure “aware” with equipment-to-equipment, resource-to-resource, activity-to-activity, etc. as explicit language constructs or objects.

It also means that all of the effort of generating the sparse A matrix in the LP, MILP and NLP is done automatically by automatically creating all of the sets, parameters, variables and constraints when the model is configured using our proprietary and comprehensive library of sub-models.

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How do we model the Superstructure?

Unit-Operation 1 Unit-Operation 2

Port-State 1

Port-State 2

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How do we model the Superstructure

Configure versus Code: Draw the flowsheet of connected industrial objects and the

sets, parameters, variables, constraints & derivatives are automatically created.

User, custom or adhoc sub-models can also be coded when required.

Unit-Operation 1 Unit-Operation 2

Port-State 1

Port-State 2

charge, batch & lot-sizing,

input-output yields,

stream flow bounding,

min/max run-lengths & cycle-times,

sequence-dependent setups,

certification delays,

density, composition & property limits,

nonlinear & discontinuous formulas,

economic, environmental & efficiency

objectives, etc.

Why we are better?

We can solve more complex

problems, that involve quantity,

logic and quality decision

variables.

We have a technology to provide

industrial modeling & solving

for large-scale optimization

problems without coding the

algebra.

Improved economics & increased

efficiency through faster & better

solutions which are robust &

reliable.

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IMPRESS is an intuitive

& easy to use modeling

environment.

What is our focus?

Allegoric

(Sets, Lists,

Network, Flowsheet)

Algebraic

(Variables, Constraints)

Analytic

(Parameters,

Formulas, Functions)

Algorithmic

(Modeling, Solving)

To manage the modeling & solving aspects or

details of any industrial problem.

How do you configure problems?

Problems are configured either:

Interfacing with our flat-file Industrial Modeling Language

(IML) or

Interactively with our Industrial Programming Language

(IPL) using a programming language such as C, C++, C#,

Java, Python, etc.

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What Math Programming and Solvers

we use?

Supply-chain planning and scheduling

optimization problems,

Logistics modeling and solving is

required utilizing Mixed-Integer Linear

Programming (MILP).

Production-chain planning and

scheduling optimization problems,

both Logistics and Quality

optimization models are solved using

an integrated and innovative

combination of both MILP and

Nonlinear Programming (NLP).

We currently have bindings to several linear

and nonlinear programming solvers such as

COINMP, GLPK, LPSOLVE, SCIP, XPRESS,

XPRESS-SLP, CONOPT, IPOPT,

KNITRO & SLPQP.

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Jet Fuel Supply Chain IMF - Example

One oil-refinery producing different grades of jet

fuel and one airport terminal storing Jet-A, Jet-A1

and Jet-B with a railroad in between.

Logistics details such as the input-output or yield

modeling of the refinery and the round-trip times of

the tank-cars (similar to batch-processes with cycle-

time) are modeled & solved as a MILP.

Jet Fuel Supply Chain IMF - Flowsheet

Fast Moving Consumer Goods IMF

Two materials produced in bulk-unit produces

eighteen different packaged materials in pack-unit.

Sequence-dependent switchovers with

setup/setdown times & “repetitive” maintenance

cleanouts on bulk-unit with material families.

Due to the slow & fast nature of the bulk & pack-

units we perform “novel” hybrid planning &

scheduling i.e., bulk-unit is scheduled & pack-unit is

planned to reduce solve time (“planuling”).


Bulk-Line

Pack-Line

Sequence-Dependent

Switchovers

Forecasted & Firm

Future Demand Orders

Time Horizon: 60 time-periods w/ day periods.

Continuous Variables = 10,000

Binary Variables = 5,000

Constraints = 20,000

Time to First Good Solution = 10 to 30-seconds

Time to Provably Optimal = 1 to 10-hours due to

sequence-dependent switchovers.

Solver: Xpress

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Cogeneration (Steam/Power) IMF

Two multi-fuel steam boilers with three modes for

different operating regions and standby.

One steam turbogenerator to produce electrical

power from high-pressure steam.

One electrical power header with import & export

of power to plant.


Fuel Header

Water Pump

Boiler1 w/ 3 Modes Boiler2 w/ 3 Modes

HP Steam Header

MP Steam Header

Power Header

Steam

Turbogenerator

Blowdown

Pressure Reducing

Valve

Time Horizon: 168 time-periods w/ hour periods.

Continuous Variables = 5,000

Binary Variables = 1,000

Constraints = 7,500

Time to First Good Solution = 5 to 30-seconds

Time to Provably Optimal = 5 to 15-minutes.

Solver: Xpress

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Power Generation IMF

Three thermal-plants and two hydro-plants with and

without water storage.

Three nodes or buses with voltage phase angle

inputs where each bus obeys Kirchhoff’s current and

voltage laws.

One time-varying demand load located on bus #3.

Power Generation IMF

Thermal & Hydro Plants

Three Buses/Nodes

1st & 2nd Kirchhoff Laws

Varying Demand Load

Voltage Phase Angles

SubsTance flow ANalysis (STAN) IMF

Large-scale data reconciliation and regression is performed to compute observability, redundancy and variability estimates.

Substances are any material or meta/sub-material (concentrations) which need to be traced within the flowsheet or network to track their movements based on flow and composition measurements over time.

STAN is a software development from TUVienna using IA’s IMPRESS solver called SECQPE (successive equality-constrained QP engine).

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1/18/2013 Copyright, Industrial Algorithms LLC

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SubsTance flow ANalysis (STAN) IMF

Other uses of IMPRESS …

First-principles or rigorous process modeling to manage difficult but high-valued bottlenecks.

On-line process/production monitoring to compare model predictions with plant actuals in real-time.

Large-scale nonlinear optimization to solve industrial scale problems where there is a large portion of linear constraints and a smaller portion of nonlinear constraints with multilinear cross-product terms (x1*x2) using successive linear & quadratic programming.

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How do we engage?

We first consult to determine how we can improve

the profit and performance of the problem as a

whole.

Then, depending on the benefit areas and apparent

bottlenecks, a tailored and incremental solution is

implemented which focuses on both improving

economics and increasing efficiency whilst being

transparent and usable.

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How do we engage?

Using our Industrial Modeling Frameworks (IMF):

These are preconfigured solutions that we can

adopt to your specific problems.

We have IMFs in the following areas:

Production Planning

Plant Scheduling

Pipeline & Marine Shipping

Energy Management

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For a demonstration of our IMFs

& IMPRESS, please Contact

Alkis Vazacopoulos

Industrial Algorithms LLC

Mobile: 201-256-7323

[email protected]

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industrial algorithms marketing presentation

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