Furnace, forming and lehr equipment
Furnace-control, float, IS-machine and lehr vendors shipping Glasent-ready autonomy on the equipment the plant already buys.
Partners
Autonomy arrives through the people the plant already trusts.
Furnace, forming, lehr and inspection OEMs, glass MES vendors and OT integrators. Glasent adds the autonomy and data layer to what they already supply.
Programme
Four kinds of partner
Glasent adds the autonomy and data layer. It does not resell hardware or replace existing OT systems, which is what makes these partnerships possible.
Inspection equipment
Camera, optical and stress inspection vendors embedding Seedscan-ready sensing, so the plant's inspection stations feed control.
Glass MES and historians
MES and historian vendors where Glasent reads orders, specs and telemetry and writes genealogy and release records back.
Integrators
OT integrators who connect, map tags and run shadow mode with the plant, certified on the platform.
Built for
Flat & architectural
Automotive glazing
Container glass
Display & solar substrates
Specialty & fiber glass
Five glass segments, one plant-edge platform. Design partners wanted in each; none are named here until a pilot is signed.
Commercial
How the partnership works
Straightforward terms, written down before the first joint plant.
- Referral or resale of the Line and Plant tiers, with the partner's integration scope priced separately
- Co-delivery of pilots: the partner connects and maps, Glasent runs shadow, assist and bounded
- No exclusivity on the plant's data. Telemetry, recommendations and outcomes stay the plant's, under the signed data-rights terms
- Certification on connectors, tag models and the autonomy policy before a partner delivers alone
The channel route from the business model is specific: pursue glass-machinery, furnace-control, inspection-equipment and MES partners where Glasent adds the autonomy and data layer rather than reselling their hardware or replacing existing OT systems. That is the only kind of partnership on offer.
Partner status and terms are not yet signed with anyone. This page describes the programme as designed.
Run timeline · scenario
What a partner-delivered run looks like
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.
scenario_fl2_01
FL-2 · float line · clear soda-lime
scenario
SUCCEEDED
-
01
ingest.order
SUCCEEDED
0.9 s
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.
-
02
twin.simulate
SUCCEEDED
41 s
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.
-
03
melt.pull
SUCCEEDED
6 m 20 s
Meltrix · Stepped furnace pull toward the new ribbon mass flow while holding melt temperature and fining; chemistry stayed inside the composition window.
-
04
form.ribbon
SUCCEEDED
4 m 05 s
Formeon · Raised ribbon speed and re-angled the top rollers to thin the ribbon toward 4 mm; thickness converged inside the design tolerance.
-
05
anneal.curve
SUCCEEDED
3 m 12 s
Anneon · Re-shaped the lehr cooling curve for the thinner, faster ribbon so residual stress stays inside spec at the higher speed.
-
06
inspect.ribbon
SUCCEEDED
continuous
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.
-
07
yield.balance
SUCCEEDED
2.4 s
Plant Orchestrator · Re-sequenced cut sizes so transition ribbon routes to cullet recovery and good ribbon to the highest-value open order.
-
08
approve.human
APPROVAL
48 s
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.
-
09
handle.stack
SUCCEEDED
1 m 10 s
Panebot · Re-planned pick and stack paths for the thinner panes; plates flagged by Seedscan diverted to cullet, good plates stacked to rack A3.
-
10
ware.qualify
SUCCEEDED
1 m 02 s
Plant Orchestrator · Lot released with full genealogy: batch, melt, forming, lehr curve, defect map, stress map and the technologist's approval.
Certification
Becoming a certified partner
Four steps, each with something to show.
- 01Technical review
Your connectors, tag models and OT practices against the platform's integration and security requirements.
- 02Joint pilot
One plant, one line, delivered together. You connect and map; Glasent runs shadow to bounded.
- 03Certification
Connectors, tag models and policy work signed off on the joint pilot. You can now deliver the connection phase alone.
- 04Programme
Referral and co-delivery terms, release notes first, and a named engineer for your escalations.
Accelerated computing
Physical AI, at the furnace
A float ribbon never stops and an IS machine forms thousands of pieces an hour. Perception has to be local, deterministic and fast, so Glasent runs GPU inference at the plant edge and keeps training, simulation and optimisation on DGX, HGX and OVX.
Edge perception
4 to 24 synchronised camera, optical, thermal and stress stations per line. Sub-100 ms defect alerts on container lines and sub-500 ms fused stress and flatness decisions on flat glass are the design targets.
Model serving
Defect, stress, time-series drift and process-risk models served across edge and plant servers, with glass-knowledge and reasoning endpoints packaged as NIM services.
Training
Multimodal models fine-tuned on inspection imagery, optical and stress outputs, PLC time series, recipes, gob weight, furnace temperature, pull rate, lehr curves, energy, cullet and final grade. Planned cadence: monthly plant refreshes.
Digital twin
GPU-accelerated furnace CFD, glass-flow and annealing-stress simulation of the as-run line, with 10 to 100 candidate recipes evaluated per grade change.
Synthetic data
50,000 to 250,000 rare seed, stone, cord, inclusion, check and stress scenes per glass family, always validated against real inspection distributions before training use.
Optimisation
Pull-rate constraints, energy windows, cullet routing, forming and annealing sequence and line takt, with RAPIDS for high-volume telemetry ETL.
Fit
Who this works for
And who it does not.
Vendors whose customers ask for autonomy
Equipment and software vendors whose glass-maker customers want the loop closed, not another screen.
Integrators with OT depth
Teams who have mapped furnace, forming and lehr tags before and know what IEC 62443 means on a plant floor.
Resellers of someone else's hardware
Glasent does not resell, and does not partner to resell. The product is software and plant-edge AI.
Dashboard vendors
If the pitch is monitoring, the fit is poor. Glasent exists to act.
Integrations
It speaks plant, not cloud
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
Guardrails
An agent that can move a furnace needs a leash
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.
- Bounded action space. Each agent can only write to an explicit tag allow-list, inside per-tag rate and magnitude limits.
- Policy engine before every write. Autonomy level, shift, product, interlock state and operator presence are all evaluated before a setpoint moves.
- Human-in-the-loop gates. Anything above the site threshold, pull steps, grade releases, safety-adjacent moves, waits for a named approver.
- Immutable audit log. Append-only, hash-chained, exportable, and retained on the plant's own storage.
- Hard fallback. Loss of the edge node, the network or the model returns control to the furnace, forming and lehr systems' last known-good state.
- Tenant and IP isolation. Compositions, forming recipes and defect libraries never cross a customer boundary. On-prem deployment available.
Compliance posture
| 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 |
From the plant floor
The problems we hear
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
Enterprise
Standardise autonomy across the group
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.
- SSO and role-based access down to the tag level
- Group-wide autonomy policy with per-site override and approval chains
- Cross-plant benchmarking on cullet, seeds, energy per tonne and first-pass quality
- VPC, on-prem and air-gapped plant-edge deployment options
- Custom composition, forming and tolerance models per site
- Dedicated deployment engineer and quarterly model review per plant
FAQ
Straight answers
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.
Get started
Bring autonomy to your customers' plants
Tell us what you supply and which plants are asking. The first joint pilot is how every partnership starts.