learnings from other industries · 2020. 3. 3. · pv average. 2nd international symposium on...

2nd International Symposium on Continuous Manufacturing of PharmaceuticalsImplementation, Technology & Regulatory

Learnings from other industries

See What is Possible


September 26-27, 2016

Speaker Introduction

• Consultant with Emerson Process Management, Systems & Solutions Division

• 38 Years experience with Process Control across all of the Process Industries

• Specialist in advanced regulatory control and multivariable model-predictive control (APC)

• Joined Emerson in 1984

• Previous employer: Olin Corp (1978-1984)

• Education: BSChE from MIT (1978)

E-mail: [email protected]

Lou

Heavner



Agenda

• Process Flow• Continuous vs batch• Refinery description• Quality Parameters

• Crude Comp/Qualities – Material Attributes

• Crude Frac – Critical Process Parameters (CPP)

• Product Comp/Qualities – Critical Quality Attributes (CQA)

• Economic Opportunity• Adaptability to Spot Crudes - Flexibility• Crack Spread Example

• Energy

• Emissions

• Seasonal – Summer gas vs Winter Diesel

• Process Capability – Show me the data (% rejects & why they were rejected)• Analyticals – Reliability of method

• Just because you can measure it…

• Batch vs Continuous Blending• Batch loading vs continuous pipeline

• Enablers

• Control Strategy – MVs, DVs, etc (explain) (Proc Ins vs Proc Outs)

• Summary



Continuous vs Batch

• Continuous• Smaller Capital Investment

• Usually less Working Capital

• Process upset results in small loss of on-spec product• On-the-fly Grade Transitions

• Transition material may not be saleable

• Focus on Regulatory Control (APC)

• Batch• Entire Batch Subject to Rejection

• Each batch has defined recipe

• Focus on Batch Sequence Control (Golden Batch)



Comparative Analysis

Characteristic Refining Pharmaceutical

Process Continuous Batch, Continuous growing interest

Throughput High volume Low volume

Feed Quality Variable, mixture High purity

Product Quality Complex Set of Properties, tight specifications

High purity, consistent

Number of products Few to Many 1 to few per campaign, many formulations

Challenges Variable feedstock, Variable seasonal demand

Regulatory requirements, fit for consumption

Reactor Catalytic Various processes, classical organic chemistry as well as powder processing



Refining Process Flow



Petrochemicals



Quality Parameters

• Feedstock – Crude Qualities (Material Attributes)• Wide Specifications Typical

• Allows Flexibility of Operation

• Fractionator Process – KPIs (Critical Process Parameters)• Continuously Monitored and Controlled

• Economic - Operating (including Optimization)• Regulatory

• Safety

• Environmental

• Products – Product Qualities (Critical Quality Attributes)• Tight and Seasonal Specifications

• Regulatory are achieved in Processing• Economic are achieved in Blending



Typical Gasoline Specification



Agenda






• Energy

• Emissions





• Enablers


• Summary



Economic Margins

Crack Spread is basis for profitability• BBL of Crude• BOE of Products• Utility Cost• Environmental Limits



Factors of Profitability

• Crudes• Heavy vs Light

• Sulfur• Wax

• Disadvantaged

• Products• Reformulated (Geographic Demand)• Low Sulfur• Gasoline vs Heating Oil (Seasonal Demand)

• Utilities and “By-products”

• Planning & Scheduling (Optimization)

• Process Capability• Refinery Size• Refinery Complexity• Refinery Location



Opportunity

• Create the greatest spread between crude and products with the capability of the Refinery• Lowest priced crude that can be refined

• Highest value mix of products



Agenda






• Energy

• Emissions





• Enablers


• Summary



Product Qualities

• On-line vs Off-line analyzers• Reliability

• Sampling Systems

• Validation/Verification

• Inferentials• First Principles vs Empirical

• Validation/Verification



Sequential Vs. Ratio Blending

• Sequential Blending (Batch)• One Component at a time• Economical Method

• Larger piping offset by less instrumentation

• Quality Check at end of blend (Off-line)

• Line Flush required for proper product quality

• Blend Accuracy assured only for completed batches• Off spec Blends can be difficult and

costly to patch

• High Working Inventory (Working Capital)

• In-Line Parallel Metering (Continuous)• In-line or All at same time

• Requires meter and valve for each stream• Smaller diameter Pipes and instruments

• Fewer tanks

• Online Blend Analyzer Required

• Precise control of blending• Instantaneous alarms on blend available

• Blend quality assured on aborted blends



Traceability

• Critical requirement in Pharmaceutical, not so much in other industries• Can be done by Time Segments

• Used for Pipeline Transportation• Multiple Products

• Multiple Producers

• Regulatory Approval requirements will require discussion



Agenda






• Energy

• Emissions





• Enablers


• Summary



Automation - Key Enabler

• Continuous Regulatory Control for minimum Variability• PID Control is the workhorse• On-the-fly grade transitions• On-line analyzers are critical in some cases

• Some but less reliance on QA

• Alarm Management• Process History

• Advanced Control for Constraint Optimization• Multivariable Control• Control of Difficult Dynamics• Inferential Control• Typical Optimization Objectives

• Maximize Production• Maximize Yield• Minimize Utilities

• Statistical Process Control• Multivariate – PCA & PLS



Single Loop Variability

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EFFICIENCY

TIME

TYPICAL CONTROL

CONSTRAINT

PV AVERAGE

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Crude Unit Issues

T-7

Naphtha Stabilizer

Light Naphth

aAtmosTower

T-1

RefluxDrum

Pump-arounds

Naphtha

LGO

HGO

LP Steam Injection

Atmospheric Residue To Vacuum

Column

T-6

T-5

T-4

T-3

T-2

AID86 95%

AIFlash Pt. Density

AI

Cloud Pt. D86 5%

AI

Cloud Pt.

AI

Color

Heavy Naphth

aJet FuelKero

Diesel

HeavyGas Oil

IntermediateGas Oil

Heater

Desalter

Crude OilStripper Columns

Preheat

Preheat

Largest

Unit Energy

Consumption

in Refinery

Frequent

Changes in

Crude Feed

Sets Basic Yield Pattern In The Refinery



Multivariable Problem

• Scope• Process Inputs (Independent)

• Manipulated Variables

• Disturbance Variables (Feed Forward)

• Process Observations (Dependent)• Control Variables

• Constraint Variables

• Challenge• Variable Interaction

• Difficult Dynamics

• Multiple Control Objectives



Control Objectives for Maximum Profit• Maximize throughput when desired

• Minimize off-spec product and lost production on crude switches

• Maximize heater outlet temp when desired• Increases distillation yields• Minimize pass outlet temperature difference

• Maximize high value product yields• Operate at max end point (or initial point) specs• Minimum overflash required to meet GO color

• Minimum pressure• Improves relative volatility• Limited by tower flooding, condenser limit, overhead system valve positions

• Minimize heater excess air• Limited by minimum stack O2 or max CO



Benefit Calculation Example

• Basis:• 23kBPD Crude unit• 10kBPD Vacuum unit

• 2% increase in throughput worth $ 1million annually (if production limited)

• 0.5% increase in distillate yield is worth $0.4 million annually

• 3% energy saving is worth $0.3 million annually

Economic Assumptions

• $ 6/Bbl Refinery incremental throughput margin

• $ 10/Bbl differential between vac resid and HVGO

• Energy – Fuel $5/ mBTU; Steam $10 mBTU



100% position

0% position

0%

po

siti

on

10

0%

po

siti

on

Maximized ThroughputMaximized ProfitMinimized Energy

Constraint Optimization



Example – Cruise Control

• Consider the standard cruise control for an automobile• Control Variable = Speed

• Manipulated Variable – Accelerator pedal

• Enhanced Cruise Control• Control Variable = Speed

• Constraint variable = Fuel Economy (mpg)

• Manipulated Variable – Accelerator

• Manipulated Variable – Brake

• Disturbance Variable – Forward looking slope detection



Example – Cruise Control

• Enhanced Cruise Control w/ Constraint Optimization• Objective 1 – Minimize Operating Cost

• Maximize Control Variable = Speed (up to the target since we don’t want to get a ticket)• Maximize Constraint variable = Fuel Economy (mpg, km/l, etc)• Manipulated Variable – Accelerator• Minimize Manipulated Variable – Brake• Disturbance Variable – Forward looking slope detection

• Objective 2 – Minimize Deviation from Speed Target• Maximize Control Variable = Speed• Constraint variable = Fuel Economy (mpg)• Manipulated Variable – Accelerator• Manipulated Variable – Brake• Disturbance Variable – Forward looking slope detection



Agenda






• Energy

• Emissions





• Enablers


• Summary



Summary

• Parallels between Continuous Industries and Pharmaceuticals• Regulatory Pressure

• Economic Pressure

• Advantages of Continuous Manufacturing• Manufacturing Equipment Cost

• Disturbances Handled on-the-fly

• Challenges of Continuous Manufacturing• Small-scale Production Lots

• Traceability



Questions?

learnings from other industries · 2020. 3. 3. · pv average. 2nd international symposium on...

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