1. Oil-Refinery Planning & Scheduling Optimization
Filippo Focacci
filippo.focacci@decisionbrain.com
Daniel Godard
daniel.godard@decisionbrain.com
Jeff Kelly
jdkelly@industrialgorithms.ca
Alkis Vazacopoulos
alkis@industrialgorithms.com
2. EXPERTISE
Optimization, Supply Chain, and Manufacturing professionals with
international experience in delivering value to customers throughout
innovative optimization solutions.
• Expertise: Production and Process Modeling, Optimization for Planning, Scheduling, Control and
Estimation, Supply Chain Optimization, Optimization Models and Technology, Business Analysis,
Vertical Solution Design and Implementation.
• Thought leadership: 100+ Scientific Publications in Optimization and Supply Chain,
6 Patents, IBM Research Mentorship, IBM Smarter Supply Chain Steering Committee, etc.
• Worked for: Shell, Exxon, Michelin, ArcelorMittal, Danone, Nestle, Genzyme/Sanofi, Honeywell,
IBM, ILOG, SAP R&D, Dash Optimization, Fair Isaac, Verisk, Interthinx.
3. HOW WE CAN HELP
Refinery production planning and scheduling determine when, where, what and how much crude oil to blend,
for example, to effectively meet market demand and efficiently use refinery resources and assets.
Being the last planning process before execution, the ability to make timely, executable and optimal
production planning and scheduling decisions has an important impact on manufacturing flexibility and
efficiency.
• Enables refineries to better manage uncertainty
• Enables refineries to better take advantage of market opportunities (e.g. spot market)
• Enables refineries to better cope with the increasing complexity of production processes
• Enables refineries to improve product quality and reduce manufacturing costs
Refinery Production Planning and Scheduling
Decision
Horizon
Years
Quarters
Months
Weeks
Days
Hours
Strategic
Planning
Primary Distribution
Secondary Distribution
S&OP
Planning
Refinery Planning and Scheduling
Manufacturing Execution System
Business goals
Sales and Marketing
plans
Service level,
Supply Chain costs
OEE
Service level,
Factory Efficiency
4. CURRENT CHALLENGES
Optimize product quality and manufacturing flexibility are the most critical concerns in the
petroleum and petrochemical industries where crude oil is heavier and fuel mix demand changes
over time.
Pain Points:
• Manufacturing processes are complex to schedule
• Effective management of blending and changeovers is critical
• High variability and low schedule attainment impacts supply (crude oil deliveries) and demand (gasoline
and distillates products)
• Difficulties to assess opportunities to insert spot supply and demand
• The manufacturing process changes overtime based on changing supply quality and demand specification
requirements
Solution requirements:
• Sophisticated optimization capabilities able to tackle complex, non-linear and large-scale problems
• To generate plans and schedules that are executable
• To generate plans and schedules that meets market demand while minimizing manufacturing costs
• A user-friendly GUI to help planners driving refinery operational excellence and analyzing refinery
behavior
• A solution that can be adapted to new production processes
5. SHORTCOMINGS OF EXISTING SCHEDULING SOLUTIONS
• All other competitor refinery scheduling systems on the market are simulation-based and involve
trial-and-error search mechanisms performed manually by the end-user.
• Our solution is optimization-based which can also perform simulation easily by either fixing 100%
of the independent or specification variables or it can be run with a partial set of fixed variables.
• Some of the benefits of optimization are to position the decision-making closer to true operating,
manufacturing or processing line of the plant – see the blue line in contrast to the grey line below.
• By moving the grey line (simulation-based) to the red-dashed line (optimization-based) for the
same quantity we can increase quality and for the same quality we can increase quantity – hence
increase profit!
6. COMBINE OPTIMIZATION AND PRECISE MODELING
MODELING
CAPABILITY
OPTIMIZATION CAPABILITY
Poor
Excellent
Excellent
(Ability to generate an
executable schedule)
Simulation
based tools
Heuristic
based tools
First generation
APS tools
Optimization Platform
+
Industrial Models
(Ability to generate a schedule that meets the
business goals of the plant)
7. BENEFITS
• Reduction of quantity and quality target variability
Ability to lower the quality requirements on purchased material
Reduction in cycle stock and safety stock targets
• Improvement in schedule attainment
Improvement in On-Time-Delivery
Improved stability of manufacturing process
• Rapid acceptance and inserting spot supply and demand opportunities
Better capitalize on short-term market opportunities
Better demand management (Smart Available To Promise, Capable To Match)
8. CASE STUDY: CRUDE-OIL BLEND SCHEDULING
Optimized scheduling of crude oil off-loading, storing, blending and
charging meets pipestill feed quantity and quality specifications based
on current information and very short-term anticipated requirements.
Enables
Resource Utilization
Operational Efficiency
Working Capital Reduction
Lower Capital Investment
Holistic View
Consider flowrate, inventory
bounds, operating practices, quality
targets , energy constraints and
costs, maintenance requirements
Energy Cost and Chemical Cost
Maintenance Cost
Plan and Schedule Stability
Enables planners to meet
production goals without
distressing supply, demand or
production.
Pipeline and Shipping penalties
(demurrage)
Distressed Sales of crude oil
Speed & Flexibility
Enables planners to quickly
generate new schedules that
meet production goals.
Spot Demand & Supply
Opportunities
Reduction in Variance
Minimize deviations from quality
targets. Charge the pipestill with
a steady mixture of crude oil.
Lower Quality Requirements for
Crude Oil
Financial
Benefits
Measured ROI Example:
• Refinery: 100,000 bpd
• Saving: 2.85M$/Year
Jeff Kelly, IndustrialALgorithms,
-- Hydrocarbon Processing
9. SOLUTION COMPONENTS
Industrial Model – IMPRESS
• Flowsheet based language to define a complex production process
• Generates effective optimized solutions
10. UNIQUE CAPABILITIES OF IMPRESS
• Production scheduling at its core requires a comprehensive and capacitated flow network to be
constructed detailing the connectivity and capability of the plant.
• We provide a proven and unique topology modeling architecture we call the unit-operation-port-
state superstructure (UOPSS) which can handle the complexity of any integrated refinery. It
inherently understands the need for interconnected convergent and divergent processes with diverse
multi-commodity, multi-resource and multi-echelon requirements.
• We also provide another modeling architecture we call the quantity-logic-quality phenomena
(QLQP) which allows us to accurately represent the following types of variables: flows, holdups,
yields, setups, switchovers, shutdowns, densities, components, properties and conditions. Along
with their constraints, the QLQP provides a modeling framework unlike any other APS system in the
market.
11. SOLUTION COMPONENTS
(IT)
Reporting
Data Integration
Data Modeling
ODM Enterprise IDE
ODM Enterprise
Optimization Server
ODM Enterprise
Client & Planner
Application UI Configuration
(Planners)
Development Deployment
Application UI Customization
Business Use
Custom GUI
Batch process
ODM Enterprise
Data Server(OR)
Industrial Model Design
Enterprise Decision Support Platform – IBM ODM Enterprise
12. APPROACH
Deliverable:
• Recommendation on business improvement projects
• Benefit analysis
• Solution proposal
Proof of Value
Typical Duration:
• 3-6 weeks
Assessment Analysis
Saving Realization
Plan
• Business Case Overview
• Current & Desired Situation
• Success Factors
• Timeline
• Key Findings
• Use Cases
• Benefit Analysis
• Solution and Project Approach
• Resource Charts
• Suggested Next Steps &
Timeline
• Understanding of Business and
Pain Points
• Business Processes
• Identify quick-hit opportunities
• Opportunity prioritization: time,
cost, risk, benefits
13. APPROACH
Deliverable:
• Fully functional solution
Blue-Print
Iterative & Incremental
Implementation
Deployment
• Each iteration must bring
Business Value
• Plan / Do / Check / Act
methodology
• Plan : Detailed Design, KPIs, Data
Required, How to mitigate the top
risks.
• Do : Implement functional
requirements
• Check : Test functional
requirements, measure KPIs
• Act : Tuning
• Training
• Go-Live Support
• Kick-Off
• Hlgh-Level Design : Project
scope, Risks.
Benefit of this approach:
• Incremental build
• Minimize risks
• Go / No Go at each iteration
Implementation
Typical Duration:
• 6-9 months
