Techkon Launches SmartAnilox to Optimize Anilox Roll Selection and Reduce DeltaE

Techkon is introducing a predictive layer to flexographic color management with the launch of SmartAnilox, a system designed to recommend the optimal anilox roll for achieving the lowest possible deltaE on each color in a print job.

For press operators, the move represents a shift from reactive density adjustments to data-driven color prediction—potentially reducing make-ready times and minimizing costly trial-and-error on press.

From Density Tweaks to Predictive Control

Traditionally, achieving accurate color in flexographic printing has relied heavily on density adjustments and operator experience. Changing anilox rolls—critical components that control ink transfer volume—often involves testing multiple configurations to hit target color values.

SmartAnilox changes that workflow.

Instead of simply adjusting density after printing begins, the system predicts how switching anilox rolls will affect the deltaE—a key metric that measures color deviation from target values.

The predictive engine works by characterizing how density shifts across different anilox roll cell volumes for a specific ink system and substrate combination. Using data gathered from prints or drawdowns across commonly used cell volumes, it models the relationship between ink transfer and color accuracy.

In practical terms, the system calculates the roll that delivers the most accurate color match before the press is fully engaged.

Eliminating Trial-and-Error in the Pressroom

Stephen Rankin, director of product at Techkon USA, framed the launch around a common industry pain point: pressroom uncertainty.

According to Rankin, SmartAnilox identifies the precise roll needed to achieve the lowest deltaE rather than leaving operators to test multiple configurations. The goal is faster color matching and reduced setup waste.

Once initial characterization is complete, SmartAnilox integrates with ChromaQA’s InkCheck graph to automatically display predicted results for all available anilox rolls. Operators can then select the optimal option without manual experimentation.

For converters managing short runs and tight deadlines, shaving even minutes from make-ready can translate into measurable productivity gains.

Why This Matters for Flexographic Printers

Anilox roll selection directly impacts:

•Ink laydown consistency

•Color accuracy

•Substrate compatibility

•Press efficiency

In high-volume packaging environments—particularly in food, beverage and consumer goods—color consistency is not just aesthetic; it is contractual.

SmartAnilox reflects a broader industry trend: embedding predictive analytics into print workflows to increase repeatability and reduce operator dependency.

As packaging designs become more complex and SKU counts rise, digital tools that stabilize color performance may become a competitive differentiator.

Exclusive to ChromaQA 7

SmartAnilox will be available exclusively within ChromaQA 7, Techkon’s flagship color management software, scheduled for release later this month.

By integrating predictive anilox optimization directly into its established color management platform, Techkon is positioning ChromaQA as more than a measurement tool—it becomes a decision-support system.

The Bigger Picture: Data-Driven Printrooms

The introduction of SmartAnilox signals three key shifts in flexographic production:

1. Color Management Is Becoming Predictive

Operators increasingly rely on modeled outcomes rather than manual correction.

2. Efficiency Is Linked to Data

Reducing trial runs lowers waste, downtime and substrate consumption.

3. Pressroom Expertise Is Being Digitally Augmented

Software-driven insights complement—but do not replace—operator experience.

As automation expands across print production, predictive tools like SmartAnilox could help standardize output across facilities and shifts, reducing variability.

In a market where brand color consistency is non-negotiable, eliminating guesswork may be as valuable as increasing press speed.

Source: Based on reporting from Labelsandlabeling.