Cullet reduction
Attribute cullet to melt, forming or lehr causes and act upstream. Meltrix, Formeon and Seedscan.
Cullet, seeds and stones, energy per tonne, residual stress, first-pass quality or escaped-defect risk. One line, one baseline, one pilot.
Every pilot is scoped to one KPI the plant already measures, with the baseline agreed in writing before shadow mode starts.
Attribute cullet to melt, forming or lehr causes and act upstream. Meltrix, Formeon and Seedscan.
Detect and predict at line speed, attribute to cause, divert flagged ware. Seedscan with Meltrix and Formeon.
Hold chemistry and homogeneity against live signals instead of furnace margin. Meltrix, with Anneon on the lehr.
Read birefringence at the lehr exit and re-shape the cooling curve per product. Anneon.
Thickness, flatness and dimension to grade at rate, validated on the twin. Formeon and Glastwin.
Genealogy on every ware and flagged pieces diverted before stacking. Seedscan and Panebot.
Every Glasent run is an ordered, inspectable sequence. This is scenario_fl2_01 on FL-2 · float line · clear soda-lime: Thickness change FL-2 · 6 mm to 4 mm clear float, residual stress inside spec, zero escaped seeds. It is a worked scenario that shows the shape of a run, not a measured customer result.
Plant Orchestrator · Pulled the 4 mm clear float spec, optical-grade tolerances and the standing energy window from plant MES; locked the target envelope for the run.
Glastwin · Simulated 36 candidate transition recipes across furnace pull, tin-bath ribbon speed and lehr curve; ranked them on seed risk, residual stress and energy per tonne.
Meltrix · Stepped furnace pull toward the new ribbon mass flow while holding melt temperature and fining; chemistry stayed inside the composition window.
Formeon · Raised ribbon speed and re-angled the top rollers to thin the ribbon toward 4 mm; thickness converged inside the design tolerance.
Anneon · Re-shaped the lehr cooling curve for the thinner, faster ribbon so residual stress stays inside spec at the higher speed.
Seedscan · 8 camera, optical and stress stations streaming; a seed cluster flagged at the ribbon edge and attributed to the pull transient, routed to cullet.
Plant Orchestrator · Re-sequenced cut sizes so transition ribbon routes to cullet recovery and good ribbon to the highest-value open order.
Plant Orchestrator · The second pull step exceeded the site autonomy threshold. Held for the glass technologist on shift; approved and written to the audit log.
Panebot · Re-planned pick and stack paths for the thinner panes; plates flagged by Seedscan diverted to cullet, good plates stacked to rack A3.
Plant Orchestrator · Lot released with full genealogy: batch, melt, forming, lehr curve, defect map, stress map and the technologist's approval.
Every tool invocation, argument and result is written to an immutable, human-readable log, and every reasoning step is expandable. Nothing about a run is hidden from the plant.
Plan, thought, action, observation, exactly as the orchestrator would record it.
Move FL-2 from 6 mm to 4 mm clear float with residual stress inside spec and zero escaped seeds.
Simulate the transition on the twin first. Lead with furnace pull so the ribbon mass flow is right before the forming change, then thin the ribbon, then re-shape the lehr curve. Watch the ribbon continuously; hold the second pull step for a human.
The standing recipe changes pull and ribbon speed together. On the twin that produces a fining transient that seeds the ribbon edge. Sequencing the pull step ahead of the forming change and holding fining removes most of it.
twin.simulate(candidates=36) returned recipe #19: pull in two steps, forming change after fining settles, lehr curve re-shaped before belt speed rises.
Recipe #19 scored lowest on seed risk with stress inside spec. Two candidates scored lower on energy but pushed residual stress over the site limit and were discarded.
Execute recipe #19 under autonomy level L3: eleven setpoint writes permitted, the second pull step routed to the glass technologist.
Seed cluster at the ribbon edge at 02:28:41, attributed to the pull transient. cuOpt routed that ribbon to cullet recovery; no flagged plate reached a customer stack.
Scenario run complete. Thickness at 4.0 mm, residual stress inside spec, one approval gate, full genealogy written to the lot record.
Shadow, then assist, then bounded writes. Each stage has an exit condition the plant agrees to before the next one starts.
Connectors to the furnace, forming, lehr, inspection and MES systems for the wedge workflow. The edge node observes and the baseline is measured from the plant's own genealogy.
The agent recommends melt, forming or annealing moves and predicts defects and stress. A technologist approves or corrects each one in the review console; accuracy and ROI are scored against the baseline.
If the plant is satisfied, low-risk forming, annealing or inspection loops move to bounded autonomy inside tag, rate and magnitude limits. Exceptions escalate to a person.
Every figure reproduced from the plant's ware genealogy, with the exclusions listed. The report decides whether a second module or the Plant tier is worth it.
Most sites pick one of these wedges, prove the number, then expand line by line.
Float lines live on thickness, flatness and the lehr curve. Glasent starts on ribbon dimension and residual stress, where off-spec ribbon and breakage at the cutting line are measured every shift.
IS machines form thousands of pieces an hour. Formeon and Seedscan start on gob weight and check detection, with the lehr curve following, where cullet and rejects are counted per section.
Substrate glass is unforgiving on seeds, inclusions and cord. Seedscan and Meltrix start on melt homogeneity and defect attribution, where yield to optical grade is the number.
New compositions and short campaigns make every unproven change expensive. Glastwin and Meltrix start on simulation-first grade changes and energy per tonne.
The arithmetic is the plant's own. Glasent supplies the method and the instrumentation; the pilot supplies the measured result.
A rejected pane or bottle carries the full cost of batch, melting energy, forming and annealing before it is crushed. Attribution is what turns that cost into a setpoint: a seed cluster traced to a pull transient is a furnace move, not a sorting problem.
Melting is the most energy- and carbon-intensive step in the plant, and fixed setpoints carry margin to cover drift nobody is watching. Holding chemistry and homogeneity against live signals lets the plant take that margin back inside the composition window.
A plant does not go from manual to unattended in one step. Glasent makes the level explicit, auditable and reversible at any time, and the first release plan is shadow, then assist, then graduated autonomy.
| Level | What the agent does | What the person does | When |
|---|---|---|---|
| L1 · Shadow and advisory | Observes, predicts and recommends setpoints with its reasoning | Enters every change manually; a baseline is measured | Pilot weeks 1 to 3 |
| L2 · Assist | Proposes a write; it executes on approval | Approves each write in the review console | Pilot weeks 4 to 8 |
| L3 · Bounded | Writes inside tag, rate and magnitude limits on low-risk loops | Approves pull steps, grade releases and anything above threshold | Pilot week 9 onward |
| L4 · Unattended | Runs the approved envelope without prompting | Sets the envelope; reviews the shift record | Planned, after graduated autonomy proves out |
These are the numbers the architecture is built to hit and the pilot is built to measure. None is a customer result yet; every pilot report reproduces its figures from the plant's own ware genealogy.
Two agents will want the same actuator. The orchestrator arbitrates on the run goal, not on who asked first, and the handoff is logged like any other step.
Formeon wants pull held while the ribbon thins, to protect thickness convergence.
Meltrix wants the second pull step now, to settle fining before the seed rate climbs.
Seed risk outranks a short thickness excursion under the run goal "zero escaped seeds". Meltrix wins the actuator, and because the step is above threshold it goes to the technologist.
Actuator returned; Formeon recovers thickness with roller angle instead. Both requests, the score and the reason are in the run record.
Nothing about a Glasent run is implicit. The goal is declared, the plan is simulated on the twin, each step is typed, and the outcome is written to the ware record.
A run starts as a goal, becomes a plan, and executes as a graph of typed steps. The active path is always visible, always logged, always reversible.
Shadow, assist, bounded, then unattended inside an envelope. Each site sets the level per agent, per tag, per shift, and every write above the threshold waits for a named glass technologist.
No customer quotes yet; we are pre-launch. These are the three buyer personas the product is built for and the pain each one describes, in their own terms.
"The furnace has run for years on the same setpoints. The process never has. We find out a melt drifted when the cullet pile grows."
Plant / operations director · ICP persona
"I can tell you why a check appeared from the lehr curve and the gob weight. I cannot be at every line, and the people who could are retiring."
Glass technologist · ICP persona
"A missed seed is a reject. A missed stress fault is a pane that shatters in the field. I need genealogy on every piece, not a spot check."
Quality / reliability engineer · ICP persona
Glasent reads and writes through the furnace, forming, lehr, inspection and MES systems already on the floor. No rip-and-replace, no parallel historian, no new HMI to learn.
Furnace SCADA and PLC, batch-plant weighing, redox and fining instruments
Setpoint reads and guarded writes over OPC UA and Modbus
Float-bath and IS-machine controls, gob-weight and timing systems
Gob, pull, ribbon speed and roller reads; guarded writes
Lehr zone controllers and belt drives
Zone temperature and curve reads; guarded writes
Camera, optical, thermal, polariscope and birefringence stations
Frames, stress maps, defect records, line-speed streams
Orders, grades, lots and ware genealogy
Spec and tolerance reads; genealogy and release writes
Time-series stores and lab information systems
Backfill, replay and lab chemistry
Robot cells, conveyors and stackers via NVIDIA Isaac
Pick, path and stack commands inside the safety envelope
SSO and RBAC via SAML or OIDC; NVIDIA Jetson Orin edge nodes
Named approvers, tag-level roles, sub-100 ms inference
Glasent writes to production equipment. Every capability is scoped, every write is policy-checked, and every action is written to an append-only audit log the plant owns.
| Standard | Scope | Status |
|---|---|---|
| SOC 2 Type I | Cloud control plane | RUNNING Planned in the first six months |
| SOC 2 Type II | Cloud control plane | QUEUED Planned in months six to twelve |
| IEC 62443 | Plant-edge OT security | RUNNING Design-aligned |
| ISO 9001 / IATF 16949 | Quality and genealogy records | SUCCEEDED Record formats supported |
| Container and safety-glass standards | Stress and defect conformance records | SUCCEEDED Record formats supported |
One policy model, one audit trail, one benchmark across every line in every plant, with the composition and forming models kept private to each site.
The questions plant directors and glass technologists ask in the first meeting.
Yes, but only within an explicit tag allow-list with per-tag rate and magnitude limits, and only at the autonomy level your site has set. Every pilot starts in shadow mode, where Glasent predicts and recommends and a person enters everything. Writes come later, after the recommendations have earned it.
Control returns to your existing furnace, forming and lehr systems at their last known-good state. Glasent is a supervisory layer on top of the control system you already run, never a replacement for it, so an outage degrades the plant to its current way of running, not to a stop.
Shadow mode starts on the first day from existing SCADA, forming, lehr and inspection data. Defect and stress prediction improve as site history and labelled outcomes accumulate; the pilot plan sets a baseline period before any recommendation is scored.
Only if you choose cloud training. Compositions, forming recipes and defect libraries are tenant-isolated and never used to train another customer's models. On-prem training and an air-gapped plant edge are available for IP-sensitive producers.
You are, the same as with any control strategy, which is why every write is policy-checked, bounded, logged and reversible, and why anything above your risk threshold waits for a named approver. The audit log records the request, the reasoning, the limits applied and the human decision.
A 90 to 120 day line pilot in three stages: shadow mode to measure the baseline, assist mode where a technologist approves each recommendation, then bounded write-back on low-risk forming, annealing or inspection loops if the plant is satisfied with the results.
Send a historian or inspection extract and the KPI you want moved. The data review tells you in a week whether the pilot is worth running.
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