Live plate status board
Every plate's current state across imaging, washout, drying, finishing, QC, and ship — refreshed off floor activity, not manual updates.
Live status for every job and every plate — from artwork intake through imaging, finishing, QC, and ship. No more whiteboards, no more 'let me check with the floor', no more missed press dates.
Most job-tracking and project-management tools assume work moves in a straight line: ticket opens, ticket closes. Flexo prepress doesn't work that way. A job becomes one to twelve plates. Plates merge into gangs. Gangs split back into customer POs. Each plate has its own state, its own imaging slot, its own QC pass.
One incoming job ticket spawns multiple plates, each at a different stage of imaging, washout, finishing, and QC. Generic trackers force you to model this as sub-tasks — which immediately drifts from the floor reality.
When small jobs share imaging area for yield, the plate has one physical state but multiple owners. Service-ticket tools have no concept of this — so allocation and status both end up in someone's head.
CSRs need a customer-facing view. The floor needs a press-date view. Owners need a margin view. Generic trackers give one timeline view and ask you to filter — instead of modeling the three audiences natively.
Miss a press date and the converter's line stops. Flexo prepress lives or dies on the ship-by date, and generic project tools don't surface plates at risk until the deadline has slipped.
Flexoworks tracks plates, not tickets. Every plate carries its own job ID and live state through imaging, washout, drying, finishing, QC, and outbound shipping — with gang allocation, customer visibility, and at-risk press-date alerts modeled in. The tracker speaks the language of the shop floor.
Status that's accurate to the floor — not a CSR's best guess from a 9 AM whiteboard read.
Every plate's current state across imaging, washout, drying, finishing, QC, and ship — refreshed off floor activity, not manual updates.
One job spawns N plates; gangs roll up plates across customer POs. Status rolls up and down the hierarchy without anyone reconciling it by hand.
Every job carries the converter's press date. Plates falling behind imaging or finishing throughput trigger early alerts — not late discoveries.
QC failures, washout issues, distortion-factor recuts, and rush re-images flag against the originating job so CSRs and shop leads see the problem before the customer does.
Every plate logs its QC checks — depth measurement, anilox compatibility, screening verification — against the original spec, audit-ready for the customer.
How many plates moved through each station yesterday, last week, last month — by imager, by operator, by plate type. Floor capacity decisions on real data.
Flexoworks doesn't try to replace the imaging side. It reads imaging events out of your existing workflow engine, attaches them to the job and plate records, and presents the views your team actually needs.
Your existing workflow engine handles RIPping, screening, step-and-repeat, CDI imaging control, and washout. Imaging events feed into Flexoworks.
Imaging events plus finishing, QC, and ship events combine into one live plate timeline. CSRs, shop leads, and customers each get the view they need.
Live customer-facing status pulled from floor reality. Stops the call-the-floor relay and gives CSRs a status they can quote without checking.
Plates by station, plates at risk, plates blocked. Press-date-driven prioritization replaces the daily whiteboard scrum.
Optional customer portal lets brands and converters see their own job status — without your CSRs becoming the lookup layer.
Job-tracking is only useful when it reflects what's actually happening on the floor and gets the right status to the right person. Flexoworks pulls imaging events from your workflow engine and pushes status updates to the channels customers actually watch.
Bring a real job in flight. We'll show you the live status board, the press-date risk view, the customer portal, and what the CSR sees when a brand calls — all on your data.