AI on the Press Does Not Automatically Reduce Labor. Organize Handover Data First

AI on the press can still increase handover costs because it can answer questions, but it cannot fill in the context missing from unorganized shop-floor data

When I assess this kind of implementation, I first use the "Mai Strategy Three-Gate Print Submission Framework" to check whether the next shift can follow the alarm, changeover, and setup records and carry out the work

Dantex Group, the supplier of Pico-series UV inkjet label-printing equipment, showcased PAL, or Pico Adaptive Logic, a system built into the machine interface that supports operation and troubleshooting in everyday language, at LOUPE Americas 2026, a printing equipment and technology showcase, for UV inkjet, or ultraviolet-curable inkjet, label presses

PAL integrates the PicoPilot and PicoCenta operator interfaces, answers operation and maintenance questions by voice, and proactively flags anomalies when it detects them. The event was held in Chicago from September 15 to 17 at booth 6415, and PAL is expected to launch in early 2027

Dantex aims to shorten response times and improve uptime, or productive operating time, but whether it actually saves labor still depends on whether the incident records can support the next shift, customer service, quoting, and delivery scheduling

Handover data needs to connect conditions, actions, and results. Simply writing "There was an anomaly" helps neither operators nor AI

An SOP, or standard operating procedure, does not need to start as a thick manual. First, make sure someone who was not there can repeat a changeover using the data

・Alarm log: record the alarm message, material, and machine status, then add the response and result

・Changeover SOP: arrange plate removal, cleaning, plate mounting, machine setup, test printing, and release points in a fixed sequence

・Artwork revision handoff: keep the version number, client-approved file, locations changed, and known risks in one record

・Delivery updates: mark which anomalies affect what was promised in the quote, the delivery date, and the wording used by customer service

PAL is expected to be integrated with PicoPilot and PicoCenta. The prepress team's filenames, version numbers, and machine records should follow the same naming convention too. Otherwise, no matter how good the interface is, operators will still have to go back and ask someone

These three need separate roles. First put the veteran operator's experience into an SOP. Then let AI handle search, reminders, and first-pass troubleshooting. When the proof or equipment condition does not match, on-site judgment takes priority

・Veteran operator's rule of thumb: fastest for handling exceptions, but when that person is away, the experience stops there

・Paper SOP: works well for fixed changeovers, but a new alarm can leave people searching for the right response

・AI assistance: can find answers in natural language, meaning questions phrased like everyday speech, and proactively flag anomalies, but it is limited by the knowledge base and the completeness of the records

Dantex worked with 42 Technology, a product design and innovation consultancy in Cambridge, UK, to put complex equipment operation into the interface. PAL is expected to join PicoCare, a service and support plan, and be fitted to new Pico machines starting in 2027

Print plants should organize their data before evaluating the interface

Designers should write the questions the machine will raise into the handoff package. That cuts down on prepress back-and-forth

I use the "Mai Strategy Three-Gate Print Submission Framework" to close the gaps between design, prepress, and the production line

・1. Specification gate: spell out the size, bleed, the image area extending beyond the trim line, color mode, linked images, fonts, and finishing locations

・2. Version gate: keep a version number for every revision. Even if the client changes only one phone number, mark the difference. Use one clearly defined handoff point for the approved file and the print-ready file

・3. Feedback gate: write the proofing result, machine anomaly, reason for the revision, and final settings used back into the handover record

I most often remind the final-artwork team that changing one small character is still a version change. When the filename, PDF, and approval record differ, the press floor ends up with the previous version, and customer service and delivery schedules get scrambled after that

Before bringing in AI, run a pilot on one machine or one high-frequency changeover task. That exposes data gaps without throwing the entire plant's workflow into disorder at once

Start small

・1. Recreate the handover with the most recent alarm or changeover record, then check whether the next shift can finish the job using the data

・2. Record where people repeat questions, wait for maintenance replies, rebuild files, or ask customer service for more information

・3. Write the revised SOP, response results, and version rules back into the record, then decide whether to scale up

PAL's technical knowledge base is still being expanded ahead of its formal launch in early 2027. Dantex has also said that customer data protection will be at the center of its future development

If the team does not have enough time to organize everything, ask the Mai Strategy Knowledge Academy consulting team to inventory the handover fields first, then bring in the tool

・Whether AI saves labor depends first on whether shop-floor experience can be turned into searchable records

・A changeover SOP must cover conditions, actions, and results. A rule of thumb cannot serve as the process on its own

・A designer's handoff includes more than artwork files. It also needs the version, specifications, and known risks

・Machine support, customer-service reports, and delivery commitments should all draw from the same handover record

On the print manufacturing side, start by organizing records for a single machine or high-frequency task. On the design side, put version details and prepress conditions into the files. Teams bringing in AI need to build answer sources, permissions, and human review into the workflow. If a SaaS, or a model for delivering software services over the internet, team only builds a chat interface, its value will hit a wall on the shop floor very quickly. It can connect to quotes, delivery dates, and customer service only when data can be searched, written back, and traced

・Dantex Unveils the PAL AI Operator Support System at LOUPE Americas 2026