Statistical Experimental Design Technique to Determine the Most Effective Process Control Variables for the Control of Flotation Deinking of Office Papers

W J Pauck (M.Sc.)Head of Pulp and Paper Technology

Durban University of TechnologyOct. 2010

PROJECT TEAM

Funding – Forest Products Research (CSIR)Project Manager – Jerome Andrew (CSIR)Researcher – J PauckAcademic supervisors – Dr. Jon Pocock (UKZN) Prof. Richard Venditti (NCSU)Technicians – Hoosain Adam Zamani Myende Nomakhosi Sincuba

Elsie Sibande

Paper Recycling Trends

2010 Expected (1)

Europe 2007 (2) USA 2006 (3)0

10

20

30

40

50

60

70

% U

tiliza

tion

rate

Paper recycling trends have exceeded expectations:

Sources:1. Goettsching & Pakarinen 2000 7: 12-222. European Declaration on Paper Recycling 2006 – 2010. Monitoring Report” 2007)3. 2006 Recovered Paper Annual Statistics

Grade mix of recovered papers in South Africa (Hunt 2008)

SA had a recovery rate of 43% in 2008

(Prasa, 2009)

New legislation (Waste Management Act) will force the use of the remaining unutilized domestic waste!

600 000 tpa recoverable New products

• Increasing variability of waste feed to deinking plants.

• Traditionally - Deinking plants run to set parameters and control the output quality by varying input waste mix.

• Future scenario – – Less flexibility to use waste mix as a control

variable– Will have to use other process parameters to

control.– Greater process flexibility required.

THE PROBLEM

PROCESS WASTE USED PROCESS CONDITIONS

Newsprint deinking

ONP - Old newsprint

OMG - Books and magazines

Alkaline slushing in presence of H2O2, deinking flotation with displector system, washing, dispersion, bleaching

Tissue manufacturing

Mixed office waste:

HL1 – white

HL2 – white & colors

Neutral slushing, multistage deinking without chemicals, dispersion, bleaching

Linerboard and cartonboard manufacture

OCC Slushing, no deinking, cleaning (hydrocyclones), screening, dispersion

Survey of SA industrial practice

Pulper Flotation

1st stage

Washing & thickening

Pulp storage tower

HD cleaner Screen

Fine cleaners

and screens

Disperser

Ink sludge

6

TYPICAL HIGH QUALITY OFFICE PAPER DEINKING PROCESS

Flotation 2nd stage Washing &

thickening

Objectives

• To identify influential process control parameters that could assist in the control of deinking plants.

• Waste paper grades: HL1 and HL2• Pulping – measured brightness (UVincl.) and ERIC

on 170 gsm pulp pads• Flotation - measured brightness (UVincl.) and ERIC

on 170 gsm pulp pads• Washing - Measured brightness (UVincl.) and ERIC

on 60 gsm handsheets, Yield.• Followed a Statistical Experimental Design

procedure to screen the effect of 11 different variables.

LABORATORY DEINKING

Screening Experimental design

• To fully investigate 11 different variables at two levels would require 211 or 2048 experiments.

• Pulping and flotation as per Plackett-Burman experimental design: – 11 factors,– 2 levels, – 12 runs, – reflected – 24 runs eliminates the effect of

interactions.

CONTROL PARAMETERS

TYPICAL LEVELS IN OFFICE PAPER

DEINKING

LEVELS IN LABORATORY

[Low-High]PULPING

% Consistency 16-18 8

pH 7-8 monitored.

%NaOH 0 0 and 0.67

% Sodium silicate 0 0 and 2

%H2O2 0 0 and 1

% Dispersant (%Surfp & %Surff ) 0.085-0.1 0.25 and 0.75

Pulping time (tp mins) 16 5 and 15

Temperature (Tp oC) 50 35 and 50

Chelant 0 0.2

FLOTATIONTemperature (Tf

oC) 40 30 And 45

% Consistency 0.8-1.2 0.8 and 1.3pH 7.5 – 8.0 8 and 10

Hardness (ppm CaCO3) 200 200

Flotation time (tf , mins.) < 5 mins 5 and 20

PULPING FLOTATION A B C D E F G H I J K

RUN NO. %NaOH % Sod Sil %H2O2 % Surf p tp, min Tp, deg C Tf, deg C % cons pH % Surff tf, min1 0.67 0 1 0.25 5 35 45 1.3 10 0 20

2 0.67 2 0 0.75 5 35 30 1.3 10 0.5 5

3 0 2 1 0.25 15 35 30 0.8 10 0.5 20

4 0.67 0 1 0.75 5 50 30 0.8 8 0.5 205 0.67 2 0 0.75 15 35 45 0.8 8 0 206 0.67 2 1 0.25 15 50 30 1.3 8 0 57 0 2 1 0.75 5 50 45 0.8 10 0 5

8 0 0 1 0.75 15 35 45 1.3 8 0.5 59 0 0 0 0.75 15 50 30 1.3 10 0 20

10 0.67 0 0 0.25 15 50 45 0.8 10 0.5 5

11 0 2 0 0.25 5 50 45 1.3 8 0.5 2012 0 0 0 0.25 5 35 30 0.8 8 0 5

13 0 2 0 0.75 15 50 30 0.8 8 0.5 514 0 0 1 0.25 15 50 45 0.8 8 0 2015 0.67 0 0 0.75 5 50 45 1.3 8 0 516 0 2 0 0.25 15 35 45 1.3 10 0 5

17 0 0 1 0.25 5 50 30 1.3 10 0.5 5

18 0 0 0 0.75 5 35 45 0.8 10 0.5 20

19 0.67 0 0 0.25 15 35 30 1.3 8 0.5 2020 0.67 2 0 0.25 5 50 30 0.8 10 0 20

21 0.67 2 1 0.25 5 35 45 0.8 8 0.5 522 0 2 1 0.75 5 35 30 1.3 8 0 2023 0.67 0 1 0.75 15 35 30 0.8 10 0 5

24 0.67 2 1 0.75 15 50 45 1.3 10 0.5 20ΣY+ Sum of outputs, for each experimental factor A to K at the HIGH level

ΣY- Sum of outputs, for each experimental factor A to K at the LOW levelYavg+ Average of ΣY+, for each factor A to K

Yavg- Average of ΣY-, for each factor A to K

EFFECT Net Effect = Yavg+ minus Yavg-, for each factor A to K

LABORATORY DEINKINGLaboratory Hydra Pulper model UEC 2020, Universal Engineering Corporation, India

Flotation Cell model UEC 2026, Universal Engineering Corporation, India

RESULTS Ink removal as a function of flotation time.

Brightness

0 5 10 15 20 2560

65

70

75

80

85

90

95

100

HL1HL2

FLOTATION TIME, tf (mins)

% B

RIG

HTN

ESS

ERIC

0 5 10 15 20 2540

50

60

70

80

90

100

110

120

HL1HL2

FLOTATION TIME, t f (mins)

ERIC

Yield as a function of flotation time

0 5 10 15 20 2570

75

80

85

90

95

100

105

HL1HL2

FLOTATION TIME tf (mins)

YIEL

D %

Effect of processing stage

Brightness ERIC

PULPER FLOATED WASHED 60

65

70

75

80

85

90

95

100

HL1HL2

% B

righ

tnes

s

PULPER FLOATED WASHED 40

50

60

70

80

90

100

110

120

130

140

HL1

HL2

ERIC

CLUSTER PLOTS – BRIGHTNESS VS ERIC

40.0060.00

80.00

100.00

120.00

140.00

160.00

180.0080.00

85.00

90.00

95.00

100.00

105.00

PULPEDFLOATEDWASHED

ERIC

BRIG

HTN

ESS

20.00 40.00 60.00 80.00 100.00 120.00 140.0030.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

PULPEDWASHEDFLOATED

ERIC

BRIG

HTN

ESS

HL1 HL2

RESULTS OF EXPERIMENTAL SCREENING – HL1

tf, min

% Sod Si

l

tp, min

% Surf-

f

% cons

%NaOH

% Surf-

p

%H2O2

Tf, deg

C

[Tp, d

eg C]

[pH]0.00

1.00

2.00

3.00

4.00

5.00

WASHED BRIGHTNESS

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

%NaOH

[Tp, d

eg C]

% cons

tf, min

Tf, deg

C

% Sod Si

l

[tp, m

in]

% Surf-

f

[%H2O2]

[pH]

% Surf-

p0.00

5.00

10.00

15.00

20.00

25.00

WASHED ERIC

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

[%NaO

H]

% cons

% Sod Si

l

[tf, m

in]

[%H2O2]

[pH]

[Tf, d

eg C]

% Surf-

f

[tp, m

in]

% Surf-

p

Tp, d

eg C

0.001.002.003.004.005.006.007.008.00

YIELD

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

RESULTS OF EXPERIMENTAL SCREENING – HL2

Tp, d

eg C

%H2O2

[% Su

rf-p]

[Tf, d

eg C]

% Sod Si

l

[tp, m

in]

% cons

%NaOH

[% Su

rf-f]

[pH]

[tf, m

in]0.001.002.003.004.005.006.007.008.00

WASHED BRIGHTNESS

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

[% co

ns]

tf, min

[% Su

rf-p]

% Sod Si

l

[tp, m

in][pH]

Tp, d

eg C

[%H2O2]

Tf, deg

C

[%NaO

H]

[% Su

rf-f]

0.002.004.006.008.00

10.0012.0014.0016.0018.0020.00

WASHED ERIC

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

[tf, m

in]

% cons pH

% Surf-

p

[%NaO

H]

[Tp, d

eg C]

[% So

d Sil]

tp, min

% Surf-

f

[Tf, d

eg C]

[%H2O2]

0.002.004.006.008.00

10.0012.0014.0016.0018.00

YIELD

24 RUN12 RUN

VARIABLE

NET

EFF

ECT

RANKING OF CONTROL VARIABLES (by magnitude of net effect)

WASHED BRIGHTNESS WASHED ERIC YIELD

FACTOR HL1 HL2 MEAN FACTOR HL1 HL2 MEAN FACTOR HL1 HL2 MEAN

%H2O2 1.0 2.5 1.7 tp, min 6 4 5.0%

consistency 3 4 3.9% Sodium

Silicate 1.6 1.7 1.6 %H2O2 4 4 3.6 % Surf-p 0 3 1.4

Tp, ⁰ C -0.6 3.5 1.5 Tp, ⁰ C 10 -4 3.4 pH -1 4 1.3

tf, min 2.2 -0.2 1.0 pH 3 4 3.3 % Surf-f 0 1 1.0%

consistency 1.1 0.7 0.9 % Surf-p -1 6 2.8 tp, min 0 2 0.7

%NaOH 1.1 0.7 0.9%

consistency -10 9 -0.7% Sodium

Silicate 2 -2 0.3

% Surf-f 1.4 -0.3 0.6 % Surf-f -6 1 -2.3 Tp, ⁰ C 0 -2 -1.0

tp, min 1.5 -1.0 0.2 %NaOH -12 2 -4.7 Tf, ⁰ C -1 -1 -1.2

pH -0.3 -0.2 -0.3 Tf, ⁰ C -7 -3 -4.8 %H2O2 -1 -1 -1.2

Tf, ⁰ C 1.0 -1.9 -0.5% Sodium

Silicate -7 -5 -5.8 %NaOH -4 -2 -3.0

% Surf-p 1.0 -2.4 -0.7 tf, min -8 -8 -7.8 tf, min -2 -8 -5.0Standard Deviation 2.6 2.9

Standard Deviation 10.4 7.7

Standard Deviation 8.6 5.9

CONCLUSION:SELECTION OF EFFECTIVE CONTROL VARIABLES

Brightness ERIC Yield

Waste – HL1 Waste – HL1 Waste – HL1

Waste – HL2 Waste – HL2 Waste – HL2

% H2O2Flotation time Flotation time

% Sodium silicate/NaOH % Sodium silicate/NaOH Flotation consistency

Flotation time Pulping time

Flotation consistency

Color code: Favourable effect Adverse effect

Note: for ERIC a negative correlation is favorable for final properties

• Temperatures (pulping and flotation) have some influence but are not practical control parameters.

• Surfactant addition to float cell has low influence, but addition to pulper had some influence.

• pH generally had a low influence.• The above variables still need to be optimised.

VARIABLES UNSUITABLE FOR CONTROL

• To generate a database of flotation results under all possible process conditions and waste grades.

• To model the deinking process w.r.t. waste inputs and process parameters (using Artificial Neural Networks)

• To use this model to enable mills to proactively react to changing waste conditions.

Further work

THANK YOU

Laboratory procedurePULPING Measure FLOAT Measure WASH &

Measure

•Charge water to pulper.•Add chemicals.•Tear waste and charge to pulper.•Allow to soak 10 mins.•Pre-mix for 30 secs.•Add H2O2 and pulp for specified time.

•Test temperature, consistency, pH.•Form 200 gsm pulp pads (Tappi 218 om-91).•Measure GE brightness and ERIC on Technidyne ColorTouch PC spectrophoto -meter.

•Charge : water, calcium chloride and surfactant.•Adjust pH.•Charge pulp to required consistency.•Agitate and float for required time at 1600rpm.•Transfer contents quantitatively to a bucket.

•Prepare 200 gsm pulp pads and measure brightness, ERIC.•Determine mass and calculate yield.

•Make 60gsm handsheets (Tappi Tappi T 205 sp-95) on Rapid-Koethen former.•Measure brightness, ERIC.

LABORATORY DEINKING: definitions & explanationsBrightness - UVincluded •The illuminant in the spectrophotometer has a UV

component, induces fluorescence in blue region.•Results in higher brightness readings.•Corresponds to what is actually perceived by an observer.

ERIC Measures Effective Residual Ink Concentration. Infrared reluctance at 950nm.

Yield Dry mass fibre out/dry mass paper in x 100

Plackett-Burman design

A non-geometric experimental factorial design in which each main effect is confounded partially with all interactions that do not contain the main effect.

12 run design A 12 run design will allow the screening of 11 different factors.

24 run reflected design A 12 run design reflected, will eliminate the effect of higher order interactions, providing information on the main effects only.