What to do when you don’t have a clue.

Terry A. RingChemical Engineering

University of Utah

First Job• MS ChE at UC Berkeley, BS ChE Clarkson– Well Educated in traditional unit operations

• 1st Project Develop Mass and Energy Balance for Alumina from clay Acid Leach process using a computer before ASPEN exists

• 2nd Project Al2O3 Nodules

Dryer

200C

Shaft Kiln

1800CHot Hot Gas

H2OAl2O3

2nd Project• Rotating Pan Nodulizer for Al2O3

– Control Pellet Size– Minimize Dust Generated– Minimize water Used– Minimize additives Used– Minimize Pore Volume

• Process Variables– Pan (1 m pilot, 5 m plant)

• RPM of Pan• Pan Angle• Spray Configuration• Alumina feed point• Ratio of Alumina to water fed

– Conveyor Dryer• Drying Temperature• Airflow

– Shaft Kiln• Sintering Temperature• Holding Time

• Project finished in 6 mo.

Project 3

• Found Synergism between additives– Decreased time/energy needed to sinter by ½– Lowered Operating costs to produce

• US Patent 4,045,234 “Process For Producing High Density Sintered Alumina”

• $1 million (1974 $s) in fuel savings ($4.83 million 2013 $s)• How much was I paid for this work?

Getting Started

• Call Plant and Talk to Engineer– Did not really know much– Relies on Operator to run Pan Nodulizer

• Call Plant and Talk to Operator– Everything controls Everything

• Call Technician who rate the Pilot Plant– Water and pan angle and RPM control nodule size

• Literature Search– 1 paper - P. Somasundaran and D. Feustenau– 1 PhD thesis - P. Somasundaran and D. Feustenau

Fm (x,t) – Cumulative Mass Distribution

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P. Somasundaran and D. Feustenau

What to do?

• Short Time for the Project – 6 months• No ChE Background that is useful!• No literature that is useful!• No people to help!

• So complain at lunch to fellow employees

Design of Experiments

• Lunch Companion– I think you might try statistically designed

experiments or design of experiments– We had a consultant come to talk about this two

years before you joined the company.– I do not know much about what the consultant

said.• Corporate Librarian Saved Me

Other Names

• Statistically Designed Experiments• Design of Experiments• Factorial Design of Experiments• ANOVA– Analysis of variance : A mathematical process for

separating the variability of a group of observations into assignable causes and setting up various significance tests.

Comparison I

Design of Experiments Traditional Experimentation• Tests

– Theory– Correlation

• Develop a new – Theory– Correlation

• End up with a mathematical understanding of experimental results based on process variables

Comparison I

Design of Experiments• Determines if Process Variables are

important (significant ) – compared to experimental errors

• Develops a mathematical relationship for experimental results based upon process variables– No Theory is developed or tested

• Allows Predictions of Results for all process variables within ranges used in experimentation

• Allows Process Optimizations• Understand the requirements on

processing conditions needed to meet production specifications

Traditional Experimentation• Tests Theory• Develop a new Theory• End up with a mathematical

understanding of experimental results

How is this approach different?

Design of Experiments Traditional Experimentation• Do a series of experiments

changing one variable at a time• 5 Process Variables (PV)

• RPM of Pan• Pan Angle• Spray Configuration• Alumina feed point• Ratio of Alumina to water fed

• 4 different values for PV• Number of Experiments

– 5^4= 625 experiments– 2 experiments/day ~ 1 yr work

How is this approach different?

Design of Experiments• Do a series of experiments

changing all variables at the same time

• 5 Process Variables (PV)• RPM of Pan• Pan Angle• Spray Configuration• Alumina feed point• Ratio of Alumina to water fed

• 2 levels for PV plus multiples of center point

• Number of Experiments– 25+1= 64 experiments– 2 experiments/day ~ 1 month work

Traditional Experimentation• Do a series of experiments

changing one variable at a time• 5 Process Variables (PV)

• RPM of Pan• Pan Angle• Spray Configuration• Alumina feed point• Ratio of Alumina to water fed

• 4 different values for PV• Number of Experiments

– 54= 625 experiments– 2 experiments/day ~ 1 yr work

Different Nomenclature

• Effects of PVs– Process Variables

• RPM of Pan• Pan Angle• Spray Configuration• Alumina feed point• Ratio of Alumina to water fed

• Scaled PVs ( -1 to +1)– original X value and converts to (X − a)/b, where a = (Xh + XL)/2 and b = (Xh−XL)/2

• Effect Ei = [Σ Ri (+) – Σ Ri (-) ]/N• Responses, R’s

– Diameter of Nodules– Water Content of Nodules– Pore Volume– Dust in Dryer– Sintering Temperature

• Variance (StDEV2)• Software

– Stat-ease, MiniTab• Response Surface • Ri = E1 X1 + E2 X2 + E3 X3+ …

+E11 X12 + E22 X2

2 + E33 X32 + …

+E12 X1 X2 + E13 X1 X3 + E23 X2 X3 + …

+E123 X1 X2 X3

Response Surface Map Bleaching Cotton

• Effects (PVs)– % NaOH– %H2O2

– Temp– Time

• Responses– Reflectance– Fluidity

• > 6 to be useful

Steps for DOE• Identify process variables

– Often more PVs than you initially think are important• Identify the range for each process variable

– High– Low

• Scale Process Variables• Set up experimental matrix

• (+,-,-), (+,+,-),(+,-,+), (+,+,+)

• Randomize Experiments• Identify Responses to be measured for each process variable• Run Experiments• Analyze Experimental results using ANOVA• Compare responses to experimental uncertainty (F-test)

– Remove insignificant process variables

• Calculate Response mathematics Ri = E1 X1 + E2 X2 + E3 X3+ … +E11 X12 + E22 X2

2 + E33 X32 + …

+E12 X1 X2 + E13 X1 X3 + E23 X2 X3 + … +E123 X1 X2 X3

• Use for Process Optimization• Use for 6-sigma

– Identify the range that a PV can vary and keep product within specification

Nodulizer Results

• Nodule Diameter– Important Effects (in order of importance)• Water to alumina ratio• RPM• Pan angle

• Dust Production– Important Effects (in order of importance)• Water to alumina ratio• Additive concentration• RPM

Results

• Sintered Density– Important Effects• Sintering Time• Pan RPM• Water to alumina ratio• Additives

• Water Control is Critical• IR water sensor and control system story