Automating Plastic Extrusion Color Control

Eliminating the ‘Black Magic’

Ken Phillips

Market Development Manager

Hunter Associates Laboratories

In Partnership with

PLASTORE, Inc.

Hunter Associates Laboratory Inc.

11491 Sunset Hills Road, Reston, VA 20190-5280

Tel 703.471.6870

sales@hunterlab.com ● www.hunterlab.com

Plastore, Inc

1570 Georgetown Rd, Hudson, OH 44236

Tel 330. 653.3047 ● Toll Free (888) 752 7867

sales@plastore.com ● www.plastore.com

Color Process Automation Technology (cPAT) introduces best practices and solution tools to

help plastics manufacturers achieve greater performance by moving from a philosophy of time-interval

based color QC to a more dynamic approach of continuous monitoring, closed-loop color control, and

automated defect containment. Color process automation technology allows organizations to measure,

analyze, control and document the color of extruded plastic in real-time through the measurement of

Critical Color Process Parameters (CCPP) which affect Critical Color Quality Attributes (CCQA).

A man went to his doctor telling him “Doctor, it hurts when I touch my chin and it hurts when I press on

my sternum, and it even hurts when I palpate my lower left abdomen. The pain radiates throughout my

body every time I touch these areas. What could possibly be wrong with me”? The doctor looked at the

man and said “well, it is simple, you have a broken finger”!

This analogy, though humorous, is used to illustrate the non-humorous way in which one critical but

broken step in a dynamic process can cause systemic pain throughout that process. In business, this is all

too common as variable outcomes cause frustration with customers and employees who routinely

waste time ‘fire fighting’ instead of producing more quality products. A more representative illustration

can be found in color control for plastic extrusion processing.

Today’s plastic extrusion process is a bit of ‘black magic’ when it comes to color control. Readings are

taken every 30 minutes or longer, and adjustments are made based on these static results. This does not

give a close enough view of the process or process stability to know its baseline, what its true variation

is, or how much the process can be improved. The process is not very controllable, predictable or often

times even understandable. And in today’s competitive environment where efficiency is critical, the

pains that can result manifest as high scrap and regrind costs, high labour costs, high material costs,

increased costs of quality and poor customer satisfaction. All of these are a direct result of a broken

color quality control process. A remedy to fix a broken finger would typically include a splint and

possibly some pain medication. A remedy for fixing a broken color quality control process in plastic

extrusion processing should include state of the art Color Process Automation Technology.

Color process automation technology takes the ‘black magic’ out of the process and makes it something

that operators can control, predict and troubleshoot. The result is improvements in efficiency,

productivity and profitability stemming from Quality and Customer Satisfaction improvements, process

and yield improvements, material cost reductions, operator efficiency improvements, and

enhancements to an organizations green initiative and carbon footprint reduction.

Quality and Customer Satisfaction

There is no price that can be put on a customer losing faith in a product or a company. Poor quality, long

lead times, missed deliveries, and returns and rework are all quality costs that can significantly impact

customer satisfaction and bottom line profitability. In plastic extrusion processing, color quality claims

are typically segmented into two categories; manufacturing claims and policy claims. Manufacturing

claims are real color issues where the product shipped out of spec from the factory. Policy claims are

claims in which the product is in color specification, but operator ‘A’ produced product at the high end

of the color specification, typically measured in L* colorimetric value, and operator ‘B’ ran the product

at the low end of the specification, and the customer receives product from both batches. In this case,

the color is within specifications, but noticeably different. Policy claims are the claims that really cost

you, because you did everything ‘right’. You spend the money to do the quality checks and ensure

quality control, but when, in the case of vinyl siding for example, you throw it on the house and two or

three panels or two or three boxes are off color, the product is completely torn off. The initial cost to

assess the complaint can be as much as $3,000, not to mention the $15,000 to $20,000 cost once the

claim is accepted.

Process and yield Improvements

On a perfect day, the average plastics extrusion plant might see 98% efficiency. This number never goes

higher because 2% of material is lost in quality checks, tear offs, nail slots, cutter slugs and other

variables that are part of the process. Most ‘efficient’ plants run at around 94% efficiency. Raising this

yield just 1% can result in a few hundred thousand dollars per year in scrap and other savings. To look at

the big picture, a plant that can raise its efficiency from 94% to 98% can see potential savings in the

millions of dollars. Implementing good color process automation technology can yield improvements of

1.5% to 2%, with improvements in color changeovers of 5%-10%. These improvements are realized with

the most skilled operators, and significantly more with less skilled workers. This is because color process

automation technology forces all operators to do things the same way. It tells them when color is stable

based on predetermined rules they set, when to take a reading, and when to package product. It also

enables automated sorting of saleable product from defective product downstream. And with real-time

process data collection, operations managers can work to a plan. If the data says that at 3,000 pounds

per hour and each color change taking 15 minutes, the result will be 750 pounds of regrind, no more, no

less. This is the number that can be expected. This ability to predict what the color change is going to do

combined with the knowledge that 2% will be scrapped from known process variables gives a plant the

ability plan their events and schedule accordingly, rather than setting hypothetical targets to shoot for in

hopes of achieving them.

Material Savings

The past several years have seen significant plastic price increases, making the job of producing plastics

products challenging to say the least. With oil discovery peaking in the mid-1960s and declining at a rate

of 8% per year, and with the world extracting more oil than it can find and consuming 2% more each

year, there is compelling evidence that the pricing situation will worsen over time. The price of plastics

and resins that use oil feedstocks will continue to trend upward, and moulders must continue to seek

innovative ways to keep costs in check in order to remain competitive. Having a few resin options for

any project can help, and resin buying options in the primary and secondary resin markets can provide

some leverage for price improvement. More direct and predictable solutions that can contribute to

significant cost reductions include using less pigment to color the product, consistently running the

product at the top end of the color specification, and elevating the use of outsourced regrind and

recycled material. Color process automation technology provides the ability to monitor and control the

topcoat as regrind material is increased on the backcoat, ensuring that color quality is not sacrificed as

regrind material use is increased. The result can be a realization in pigment savings of as much as 20 to

30 percent. Added to the savings in pigment use are the savings that can be realized from using recycled

material vs. virgin which can be as much as 40 cents per pound. From an efficiency standpoint, this can

also help to consolidate to a lower number of backcoat colors.

Changes in Workforce Dynamics

Since the 1980’s, reductions in force, retirements, and industry consolidation have made keeping up the

chain of knowledge about plant processes difficult and problematic. The pool of people with the process

and technical knowledge of a plant or even its processes is shrinking. Younger workers do not have the

science, mathematics or mechanical skills, on average that the workers they are replacing had when

they started. The modern operator has evolved into a multi-faceted employee, which has drastically

increased the role’s responsibilities as a “generalist”, solving problems in real time and not specifically

being an expert in merely one section of the process. Today the operator is one of the key members of

the team, and enhancing the efficiency of this role through improved operator response provides a

critical advantage. No longer are operators simply working within their traditional functional boundaries

with established guidelines and procedures to maintain status quo. They are increasingly expected to

leverage their knowledge to make objective real-time decisions, which means they need a deeper

understanding of the various factors that impact their operations and the ability to use that knowledge

to improve planning and problem solving with more proactive measures. The latest color process

automation technologies enable operators to better leverage information in both routine and critical

conditions for optimal decision making, and provides the tools that enable operators to collect, connect,

analyze and act upon vast amounts of real-time operations data supporting a more intelligent and

engaged workforce

Green Initiatives

Manufacturers are getting on board with green initiatives and reviewing their carbon footprint for

improvement. Sustainability however is more than reducing a plants carbon footprint. Properly done,

it’s about creating manufacturing processes that produce the highest profitability over the longest

period of time, taking into consideration costs of materials, labour and energy. More efficient

equipment and control methods in automation can improve the overall equation by reducing the energy

cost per unit of output for any product. But this is not enough. What truly makes a product green is the

amount of recycled material that can be used in it. Recycled product can be challenging to use because

the color is not usually controlled very well, and this will influence the color of a capstock if the capstock

becomes too thin. Color Process Automation Technology can resolve this by automatically varying the

feeder along with the material to keep capstock color in spec as the percent of recycled content on the

backside is increased. Reducing the cost per unit of output combined with the ability to increase the use

of outsourced recycled material can significantly impact an organizations green initiatives while also

helping to improve quality, reduce costs and improve profitability and competitive advantage.

HunterLab and Plastore, Inc. through a strategic partnership have joined forces, lending their expertise

in the fields of color measurement and plastic extrusion processing, to develop cPAT – Color Process

Automation Technology - to specifically address todays color quality and control needs of the plastic

extrusion industry. This new and innovative technology enables companies to achieve the

improvements in efficiencies, productivity and profitability vital to their success and sustainability in

today’s competitive global market.

To learn more about cPAT, visit www.hunterlab.com, or www.plastore.com.

CASE STUDY

QUALITY TOOL – Auto-cut benefit Example

QC picked up a check at 10:30 a.m. and found the color was 1.68 DL. Skid was put on hold and 6 boxes were discarded

QC just happened to pick up at the only time during this run that the color was out of spec (see color scan data)

The color spiked out of spec for 7 five second reads and then went back into spec. range

All color checks were taken on time and if not for QC’s timing this could have been a claim

Auto-cut would have prevented losing 144 pieces of siding, and only lost 12 panels

Eliminates potential color claims from field

Auto Cut Display

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

9:05:01 9:18:30 9:32:21 9:45:10 9:57:30 10:09:15 10:21:30 10:33:45Time

Del

ta L

165

170

175

180

185

190

195

RPM

Delta L High Control Low Control High Spec Low Spec RPM

QUALITY TOOL – Constant Color Checks Ability to continuously monitor for color shifts

Color change line from Light Gray to Medium Gray: Color feeder started at 21.9 and after 6 CF changes it ended up at 20.66, 3hr and 15 min later. This change was done by the cPAT® solution, totally automatic

If operator would have taken a check after color change and began to box product, then waited until his next check 30 min later, there is a high level of certainty that the color would have been far out of the spec range and product would have had to be unboxed and scrapped

4 color feeder changes were made in the first 30 min after product started to be boxed

Medium Gray is a 3.0 ASA color, known for taking a while for color to stabilize after a change

This time appears to change depending on what the previous color was prior to the color change

The cPAT® system constantly monitors color and makes the necessary feeder changes at the

correct times

The cPAT® system eliminates any delayed operator response, and also eliminates a color shift that would go undetected until a color check would be performed at 30 min intervals, having to back track and scrap product

Constant Color Monitor

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

3:34

PM

3:44

PM

3:54

PM

4:04

PM

4:14

PM

4:27

PM

4:37

PM

4:47

PM

4:57

PM

5:07

PM

5:17

PM

5:27

PM

5:37

PM

5:47

PM

5:57

PM

6:07

PM

6:17

PM

6:27

PM

6:37

PM

6:47

PM

Time

Del

ta L

16

17

18

19

20

21

22

23

24

RP

M

DELTA L High Control Low Control High Spec Low Spec RPM

First start BF 21.9

Color drifted dark -

2nd feeder change 21.0

Color w ent light

Color drifted

3rd CF change change 20.24

Color drifted dark

4th CF Change 19.66

Color stable

Color driftimg light

5th CF change 20.24

Color drifting light

6th CF change 20.66

PROCESS TOOL– Recipe Error Why did the run shift light?

Records shows that at 16:38 the co base feeder was changed from 35 to 39 causing the color to go light

This was caused because operator loaded D5 recipe but it was for 3.0 ASA. There was not a .5 recipe. This line did not usually run .5 colors

This explains the color shift and also shows how the cPAT® system brought color back to

nominal making several changes because the increased base feed reduced the regression accuracy causing the CF changes to move the DL* less

Base Change - No Recipe

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

15:30

15:40

15:50

16:00

16:10

16:20

16:30

16:40

16:50

17:00

17:10

17:20

17:31

17:41

17:51

18:01

18:11

18:21

18:31

18:41

18:51

19:01

19:17

Time

Del

ta L

60

70

80

90

100

RP

M

Delta L High Control Low Control High Spec Low Spec RPM

Process Tool – Regression Checks and Correction The regression for this color was off, as you can see by the graph

Recording the feeder changes along with DL* movement will give the actual regression for any concentrate, improving CCS performance. (Assuming Base Feed Rate remains constant)

Can better predict residence time in extruder

Time difference between feeder change and actual start of color shift

Regression Error

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

9:00

9:18

9:36

9:55

10:13

10:31

10:50

11:08

11:26

11:45

12:03

12:21

Time

Del

ta L

15

15.5

16

16.5

17

17.5

RP

M

Delta L RPM

Process Tool – Studying How Db* Controlled Color works Ability to monitor Db* Controlled colors and watch interactions between other functions

Can better train on color control for b* scale colors

Can assist in establishing better adjustments to concentrates

Db* Color Control

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

8:13

AM

8:18

AM

8:23

AM

8:28

AM

8:33

AM

8:39

AM

8:44

AM

8:49

AM

8:54

AM

8:59

AM

9:04

AM

9:09

AM

9:14

AM

9:19

AM

9:24

AM

9:29

AM

9:34

AM

9:39

AM

9:45

AM

9:50

AM

9:55

AM

10:0

0 A

M

10:0

5 A

M

10:1

0 A

M

10:1

5 A

M

10:2

0 A

M

10:2

5 A

M

10:3

0 A

M

10:3

5 A

M

10:4

1 A

M

10:4

6 A

M

10:5

1 A

M

10:5

6 A

M

11:0

1 A

M

11:0

6 A

M

11:1

1 A

M

11:1

6 A

M

11:2

1 A

M

11:2

6 A

M

11:3

1 A

M

11:3

6 A

M

11:4

2 A

M

11:4

7 A

M

11:5

2 A

M

11:5

7 A

M

12:0

2 P

M

12:0

7 P

M

12:1

2 P

M

12:1

7 P

M

12:2

6 P

M

Time

Del

ta L

43.5

44

44.5

45

45.5

46

46.5

47

47.5

48

DELTA L DELTA b RPM

Process Tool – Color Change Tool

Allows all Color Changes to be the same

o Mirrors Current Procedure

o Assists Last Piece Checks

Stability Check

o Improves Color Change Time

o Provides better data for CCS

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

5:51:1

6

5:56:2

1

6:01:2

5

6:06:3

0

6:11:3

5

6:16:4

1

6:21:4

5

6:26:5

1

6:31:5

5

6:37:0

0

6:42:0

5

6:47:1

0

6:52:1

5

6:57:2

0

7:02:2

4

7:07:3

1

7:12:3

5

7:17:4

0

7:22:5

0

7:27:5

6

7:33:0

0

7:38:0

6

7:43:1

5

7:48:2

1

7:53:2

5

7:58:3

0

8:03:3

6

8:08:4

120.5

20.7

20.9

21.1

21.3

21.5

21.7

21.9

22.1

22.3

22.5

22.7

22.9

23.1

23.3

23.5

23.7

23.9

24.1

24.3

24.5

24.7

24.9

Series1 High Control Low Control High Spec Low Spec Series2

Savannah Wicker ASA

Boost

Last good pieceSW color out auto cut

RE entered deltas moved

DL* light

21.09RPM

21.38 RPM

22.09 RPM

20.66 RPM

Start stability check at 7:12:31

New color Granite Gray

entered deltas

DL* went light here because of drain hopper

Changing Base

SYSTEM LOG DATA (example)

System Test - Changing Base

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

9:38:0

2

9:48:5

2

10:01

:03

10:14

:48

10:42

:42

10:55

:57

11:08

:57

11:22

:23

11:43

:22

11:57

:03

12:09

:33

12:21

:18

Time

Del

ta L

80

82

84

86

88

90

92

94

96

98

100

RP

M

DL High Control Low Control High Spec Low Spec RPM

Start X-tore in auto at 9:30 am. Regression for this color is -.25 but set on this run to -.38 to make smaller changes to DL*

At 9:53 changed co base from 200 to DL* w as on the light side but not .210 enough out of .20 reads to make autofeeder change

At 10:06 changed base feed again to 215.

At 10:16 CF Changed from 87 to 91 RPM

At 10:33 CF Changed from 91 to 96 RPM since color w as still too light.

At 11:37 Base Change made color go dark w hich caused system to change Color Feeder

At 11:00 am changed base feed from 215 to 204.