Coatings and Ink Production KPIs: Benchmark Ranges for Yield, First Pass and OEE

Coatings and ink plants run on a handful of KPIs: batch yield, first-pass batch acceptance, dispersion energy, fill-line OEE, changeover time and schedule adherence. Use the ranges below as reference points for spotting a gap worth investigating, not as targets.

Every figure here shows its basis. A superscript number links to a public source in the Sources list at the end, and the sentence states that source's scope, such as its year and the industries it covers. A figure marked no cited source is kept exactly as originally published because no public source stating it was found, so treat it as illustrative.

At a glance

Batch yield

Batch yield is the anchor KPI: net saleable output against theoretical weight-up. Typical wet-product plants run 93 to 96 percent, while world-class operations hold 97 to 98.5 percent no cited source.

For example, the gap between 94 and 98 percent yield on a 3.00 dollar per kg product is 0.12 dollars per kg of pure material loss. On 5,000 metric tons a year, that is 600,000 dollars.

Track the loss by source, not blended, and hold each source to a target. Tank heel alone should sit under 1.2 percent of batch weight no cited source.

How to measure

• Compare net saleable weight with theoretical weight-up for every batch.
• Split the loss by source: tank heel, filter and hose holdup, and fill-line purge.
• Report heel as a share of batch weight.

What moves it

• Tank-heel recovery.
• Filter and hose holdup reduction.
• Disciplined fill-line purge.

Cost a batch from its raw materials and see what yield loss is worth. Coating Batch Cost

First-pass batch acceptance

First-pass batch acceptance measures how many batches meet spec on color, viscosity and density without correction. Typical plants land at 78 to 88 percent first-pass; strong color houses hit 92 to 96 percent no cited source.

Every corrected batch adds 30 to 90 minutes of lab and tank time and burns tint or solvent no cited source.

For example, a 10-point first-pass gain on 40 batches a week is 4 recovered batches. At 30 to 90 minutes per correction, that frees 2 to 6 tank-hours weekly.

How to measure

• Count batches that meet color, viscosity and density spec with no correction.
• Divide by all batches made in the same period.
• Log the correction time and the tint or solvent added on each corrected batch.

What moves it

• Tighter raw-material incoming control.
• Calibrated color instruments with a delta-E target under 1.0 no cited source.
• Locked dispersion procedures.

Track how much tint the corrections burn with the Pigment Usage calculator.

Dispersion energy consistency

Dispersion energy, in kilowatt-hours per ton, tells you whether grind is under control. World-class plants hold energy within plus or minus 5 percent batch to batch, typical plants plus or minus 15 percent no cited source.

Suppose a millbase has a standard of 8.0 kWh per ton. Batches drifting to 10 or 11 signal worn media, wrong tip speed or overcharged solids.

Tight energy control correlates directly with first-pass color, because under-dispersed pigment reads weak and forces tint additions.

How to measure

• Monitor mill power draw and time on every batch.
• Convert them to kilowatt-hours per ton of millbase.
• Flag any run more than 8 percent off the standard energy no cited source.

What moves it

• Media condition, since worn media stretches grind time.
• Correct tip speed for the millbase.
• Solids charged to the recipe, not above it.

Plan grind and mix time with the Mixing Batch Time calculator.

Fill-line OEE

Fill-line OEE separates plants that schedule realistically from those that guess. Availability times performance times quality, measured against nameplate, typically lands at 55 to 68 percent on pail and drum lines^{1, 2}, while well-run lines reach 75 to 82 percent¹.

That evidence comes from packaging lines in general, not pail and drum fillers. In PLC data from 725 consumer packaged goods packaging operations, measured from January to June 2009, the middle half of lines averaged 54.9 percent OEE and the top quarter 82 percent¹. OEE software maker Vorne says most manufacturers score closer to 60 percent². Neither source states the upper end of the typical band.

The biggest loss is availability, dragged down by changeovers and jams; performance loss comes from head misfires and viscosity-driven slow fills. Target changeover under 20 minutes and minor-stop rate under 3 percent of run time no cited source.

Minor stops add up quickly. In the same 2009 packaging data, the average line had about 8.6 stops of 10 minutes or less per hour, a stop roughly every 7 minutes, while best-in-class lines averaged 2.2³.

OEE suits the fill line, which is a discrete operation. The familiar 85 percent world-class OEE figure comes from discrete manufacturing and is not a target for batch process equipment such as mix tanks⁴.

How to measure

• Multiply availability, performance and quality, each measured against nameplate rate.
• Log changeovers and jams as availability losses.
• Count minor stops per hour and as a share of run time.

What moves it

• Faster changeovers.
• Fewer jams and head misfires.
• Viscosity control, so fills run at rated speed.

Compare effective rate with nameplate to see which of the three OEE factors to attack first.

Changeover and cleanout time

Changeover and cleanout time is both a cost and a capacity KPI. Typical color or chemistry changes take 45 to 90 minutes of combined wash, rinse and verification; disciplined plants using sequenced color scheduling and dedicated lines cut this to 20 to 40 minutes no cited source.

For example, a line running 6 to 12 changeovers a day that shaves 25 minutes from each recovers 2.5 to 5 hours of daily capacity.

How to measure

• Time the combined wash, rinse and verification for each change.
• Record the solvent used on each changeover.
• Count changeovers per line per day.

What moves it

• Sequencing light to dark.
• Batching same-chemistry runs together.
• Dedicated lines for the colors that change most often.
• A solvent-per-changeover standard, so operators know when a wash is complete rather than washing to comfort.

Set the wash standard with the Solvent Usage calculator.

Schedule adherence and batch cycle time

Schedule adherence and cycle time round out the operational set. World-class batch plants hit 95 percent or better on-time to schedule with batch cycle variance under 10 percent no cited source.

Typical plants sit at 82 to 90 percent with 20 to 30 percent cycle swing, driven by QC holds and rework no cited source. The lever is decoupling the lab from the tank.

For example, cutting average QC hold from 60 to 30 minutes on 40 batches a week returns roughly 20 tank-hours, more than a full extra shift of output.

How to measure

• Compare each batch's completion with its scheduled time.
• Track batch cycle time and its spread week to week.
• Log QC hold time separately from processing time.

What moves it

• Pulling in-process samples earlier.
• Running color and viscosity tests in parallel.
• Pre-staging raws so weigh-up does not wait.

Estimate batch cycle time and see where the tank hours go. Mixing Batch Time

Put the KPIs on one scorecard

Roll the KPIs into one scorecard so improvements do not cancel out. Chasing fill-line speed while first-pass drops just packs off-spec faster; pushing yield by shrinking purge can leave contaminant in the line and hurt quality.

Weight the scorecard toward the constraint. If tanks limit you, prioritize cycle time and changeover; if the fill line limits you, prioritize OEE.

Cost the effect of yield and tint changes on a formula with the Ink Formulation Cost calculator.

How to build your own baseline

• Review batch yield, first-pass acceptance, dispersion energy, OEE and changeover weekly.
• Write down each KPI's definition and keep it fixed across plants.
• Collect several months of data before you set a target.
• Set each plant a stretch target that closes half the gap to world class within two quarters.
• Record what changed in the process whenever a KPI moves.