ColorMetrix User Group 2004

ColorMetrixUser Group

2004

Keynote presentation by Howard Nelson Ed.D

ColorMetrix 4th Annual User Group Meeting

August 8-10, 2004 • Las Vegas, Nevada

Print Measurement as Historical Eras

Decades in which projects were initiated (and perhaps continue to evolve)

Provides us with an overview of where we came from, so we might be able to predict where technology will take us next

50 Years of Print Quality Verification

Measurement of printing through print characteristics

Print consistency controlPrint quality control

LTF

Began researching lithographic technology during WW II for the US War Department

Began to research and consult for private industry after the War

Became GATF in the 1960’s

Historically Speaking

The 1950’s were the research era Introduction of the scientific approach to

problem-solving LTF began to publish their findings in the

“popular trade-press” First densitometers became available

Historically…

1960’s were the developmental era Web offset printing grabbed the market-

share for most impressions Densitometers became widely used GATF pioneered print characteristic

identification and calculation

Historically

1970’s were the standardization era SNAP - 1970 - 1972 SWOP - 1976 - 1980 Color proofing systems introduced Print measurement investigates

ink/paper/chemistry relationships

Historically

1980’s were a consolidation era CEPS systems improve halftone control Color proofing systems improved First Spectrophotometers available Print measurement data feeds back to

improve prepress accuracy

Historically

1990’s were the era of verification No-proof editorial Spectrophotometers become generally

available ColorMetrix Technology LLC Press “Fingerprinting” for process control

Press Fingerprinting

Five rules of Press Fingerprinting Simulate production Choose a test form Run the form Measure the sheets and collect data Feedback to prepress

A step beyond??

Print Control Measurements

Solid Ink Density Dot Area Gain (at the 50% dot value)Print Contrast% Trap (for Wet Ink Trap)3/C Neutral Gray BalanceHue Error and Grayness Error

Solid Ink Density

Makeready aimpoint for color approvalPrint consistency targetBasis reading for other calculationsOne of the main image contrast

indicators

Dot Area Gain

Image contrast indicator

Print Contrast

How well the press/ink/paper combination is able to render shadow detail by differentiating between shadow area tone values

Wet Ink Trap

Control of secondary (RGB) colors

Verification Fingerprinting

Monitoring “Sheet Contrast” At a given Solid Ink Coverage, print

contrast characteristics shouldn’t vary• C=1.30, M=1.40, Y=1.05, K=1.60• DG=20%, PC=40%, Trap

Fingerprinting to verify press components are functional

Press Component Life

Like aircraft component parts, press parts are rated for useful life Plates & blankets by # of impressions Rollers by # of operating hours Even cylinder bearers are rated TBOoR

components

Verification Fingerprinting

Run test form under “Press New” conditions

Discover and monitor TBOoR for press parts

Re-run test form to verify need for replacement

Watch sheet contrast for clues

Scanable Press Test Form

The scanable presstest form

Scanable Form Components

Two-tier standard color bar

Scanable color bar

Scanable Form Components

Scanable ICC color profile

Scanable Form Components

Scanable Tone Ramps

Scanable Form Components

Scanable GrayBalance Ramps

Scanable Form Components

Scanable Total Ink Coverage Ramps

ColorMetrix

Collects and displays graphic dataDisplays Run with VOC tolerancesProcess TrendingColor hexagonPress fingerprintingData sharing with other programs

Historically Speaking

2000 - 2010 may be the era of SPC Use of statistics to identify problems Use of statistics to monitor runs Using statistics to predict outcomes

Six Sigma Data Analysis

Specifies the amount of variation experienced compared to the specs

Greater process predictability Lowers costs by minimizing waste and rework

Isolates special cause variation from common cause variation

Descriptive Statistics

Mean The average of the data as collected

Standard Deviation The value of one sigma

Run Chart

Note the value of each individual point Observe trends during the run

Runs up and down vs expected runs Observe the P-Value

P-Value for Clustering, P < .05 = Special Cause P-Value for Mixtures, P > .95 = Special Cause

I-MR Chart

Individual Value of each data point of the run Mean, UNPL, LNPL

Moving Range of the differences in value during the run Average range, UNPL, LNPL

Process Capability Analysis

The Cp index Ratio of the spec limits to the width of the process Cp = 2 means the process is stable Cp ≤ 1 means the process is unstable

The Cpk index Ratio of the process width to the spec width including

centering of the spec on the process Cpk > 1 means the process is capable of meeting spec Cpk = 1 or less means the process is incapable of meeting

spec

Differences in Process Capability

Some Words of Thanks

Colormetrix Technologies LLC Jim Raffel, Mike Litcher, Mike Woods

E. I. DuPont de NemoursGATF / PIA and Gretag-MacBethFlint Ink Corp.

Jeff Gilbert, Craig Stone