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

1. What to do when you don’t have a clue. Terry A. Ring Chemical Engineering University of Utah

2. 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 Al2O3 H2O Shaft Kiln 1800C Dryer 200C Hot Gas Hot

3. 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.

4. 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?

5. 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

6. Fm (x,t) – Cumulative Mass Distribution P. Somasundaran and D. Feustenau

7. 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

8. 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

9. 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.

10. 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

11. Comparison I Design of Experiments Traditional Experimentation Tests Theory Develop a new Theory End up with a mathematical understanding of experimental results • 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

12. 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

13. 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 54= 625 experiments 2 experiments/day ~ 1 yr work • 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

14. 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 = [ΣRi (+) – ΣRi (-) ]/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 X22 + E33 X32 + … +E12 X1X2 + E13 X1X3 + E23 X2X3 + … +E123 X1X2 X3

15. Response Surface Map Bleaching Cotton • Effects (PVs) • % NaOH • %H2O2 • Temp • Time • Responses • Reflectance • Fluidity • > 6 to be useful

16. 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 X22 + 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

17. 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

18. 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