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

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.

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

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

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!

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)

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)

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

SOLUTION COMPONENTS

Industrial Model – IMPRESS • Flowsheet based language to define a complex production process • Generates effective optimized solutions

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.

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

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

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

Questions &

Discussion