Tier 01 · Deploy firstInspection starts with a qualified local sample; forecasting waits for sales history.1 of 2 cases ready on default inputs
Tier 02 · Follow nextInventory optimisation and digital printing wait for a reliable planning record and workflow.Waiting for planning and workflow inputs
Tier 03 · Emerging pilotsGenerative design and physics-constrained models stay inside bounded validation pilots.Waiting for physical validation route
GFT / Cameroon textile / Digital strategy
A maturity-ranked portfolio for a greenfield garment operation: establish the data spine, test inspection, accumulate history, then expand the applications.
Read the instrument
Pick a tier to read its dependencies, then change which inputs are in hand. A mature method stays on hold until its own data exists. The stack shows programme priorities. It is not a vendor ranking, a completion percentage or a claim of deployment.
Portfolio maturity. Layer size has no quantitative meaning. Filled nodes are cases whose listed inputs are all in hand. Hover or focus a use-case row to trace its plane and required inputs.
Tier one: mature methods, different dependencies
The first tier pairs computer-vision defect detection with demand forecasting. They do not share a start date. Inspection can begin with a bought model and a qualified local image sample. Forecasting must wait for usable sales and order history and a comparison with a simple baseline.
Tier two: operating data and integration
Inventory and supply-chain optimisation follow a reliable planning record. Digital printing and sample reduction require a product workflow that can use their outputs. The aim is to improve a known decision, with the implementation cost and fallback included in the assessment.
Tier three: specialist data, skills and validation
Multi-model design-to-specification and physics-constrained generation sit in the emerging tier of the programme. Evaluate any proposed output against physical and manufacturing requirements. A persuasive image is not a production specification, and a successful demonstration is not an accepted manufacturing process.
1of 6 cases ready with these inputs
Linked rowComputer-vision inspectionNeeds: event capture agreed, local image sample
Define the operating boundary
The programme assumes a greenfield operation with no accumulated production or sales history. Its first digital asset is therefore a dependable record of events. The performance-management design supplies that record. Buying a model can reduce development work, but it does not remove the need to validate local inputs, outputs and operating conditions.
Principle 01Keep product, batch, line, shift and event identities consistent. Define the schema, access rights and correction history before integration. If a vendor changes, the operation should retain the records and definitions needed to interpret its own performance.
Principle 02Assess a supplied capability on representative materials and working conditions. Include difficult examples and the consequences of false decisions. The procurement requirement should specify the evidence that would establish fitness for the proposed use, rather than accept a generic benchmark as local proof.
Principle 03Place model outputs inside the operating review, with uncertainty and a route to challenge them. Define who can release a batch, revise a plan or suspend a model. Automating the observation does not automatically authorise the resulting operational decision.
What the data can support as the operation agesNow: Early on1 of 4 lanes ready to test
Every lane draws on the same record. The record of events is the first asset. Whatever model is bought later, the definitions and correction history stay with the operation.
Inspection and forecasting must pass local tests. A supplied capability earns its place on representative materials and conditions, not on a generic benchmark.
A person releases, revises or suspends. A model output enters the operating review with its uncertainty and a route to challenge it.
Illustrative curve. It shows the order of dependency. It is not a forecast of dates or quantities.
Follow the sequence · Reference signal stage
END-TO-END SIGNAL BUS
The reference architecture connects edge collection, vision, a core store, analytics and the management interface. Its purpose is continuity under variable power and connectivity. Follow the path to see what each layer must preserve. Geometry represents information flow, not measured network speed or installed capacity.
EDGE VISION · FALLBACK READY
The edge layer acquires events and images. Local vision inference avoids making every inspection depend on a distant connection. Keep a manual quality fallback and a record of model identity, confidence and operator review where relevant.
LINK LOST · LOCAL QUEUE
Retain events locally when connectivity fails, then synchronise without duplication. Keep original event times distinct from upload times.
EVENT TIME ≠ UPLOAD TIME
The central store combines quality, production and eventually orders, with explicit handling of missing or corrected records.
ACCOUNTABLE PERSON
Forecasting and optimisation consume validated history. Their outputs return to the same management interface used for operating review. A planning recommendation needs a defined horizon, assumptions and an accountable person before it changes commitments.
Keep provenance attached
The programme annex reproduces external inspection and forecasting claims. They have not been independently reverified for this page and do not share a single evaluation protocol. Treat the figures as context for a validation plan. Local material, defect prevalence, counting rules and commercial conditions can change the result.
Different sources and protocols. Not a measured gain.
Source read-out · Low 60%, high 70%
External literature range reproduced in R29. It is not a local baseline or a directly comparable trial.
Material, defect prevalence and counting rules change this range.
Source
Source read-out · Low above 90%, no upper bound stated
External benchmark in R29. It is not a procurement acceptance threshold by itself.
It needs a local test set before it says anything about a site.
Source
Source read-out · Low 20%, high 50%
External fashion-sector range in R27. No benefit to this venture is assumed.
Product mix, horizon and commercial conditions change the result.
Source
Your marker · your value, not a measurement
Your marker 82%: above the published manual range, below the vision benchmark.
Hover, focus or select a bar to read its source. Drag the marker along the inspection rails.
Warp and Signal
A demonstration shows
It finds the defects in the samples it was shown.
Not acceptance on its own.
The gate needs
A demonstration shows
A smooth line through past sales.
Not acceptance on its own.
The gate needs
A demonstration shows
A persuasive image.
Not acceptance on its own.
The gate needs
The relevant question is whether a capability improves a defined decision under the site’s actual conditions. A camera demonstration, a forecast chart and a generated design each need a different acceptance test. The portfolio keeps these tests separate so maturity in one application cannot stand in for evidence in another.
These are proposed application tiers and architecture layers. No model is represented as deployed at a GFT factory, and no local benefit is inferred from external benchmarks.
Make the design operational
The strategy buys proven capabilities first and keeps data capture under the operation’s control. The work includes integration, operating support and model monitoring. A smaller technical footprint is useful only if the team can keep the record complete and maintain a practical fallback when a service or device fails.
Each gate lays the plane it unlocks. Planes beyond the current gate stay as dashed outlines.
Gate 01 · Unlocks A bought inspection capability, tested locally.
Gate 01
Define source events, storage and correction rules. Select an inspection capability against a local test set and operational requirement. Include normal fabric variation and difficult defects, and check the total review burden created by false alarms before considering a broader rollout.
Prerequisite evidence
Gate 02
Accumulate sales, orders, stockouts and product changes. Compare a candidate model with a simple planning baseline using information available at the time. Separate demand from constrained sales, and keep the cost of excess stock beside the cost of missed demand.
Prerequisite evidence
Gate 03
Bound a design or sampling experiment to a defined product and acceptance requirement. Retain physical validation and specialist review. Measure the complete workflow, including corrections and integration, so an attractive intermediate output does not conceal extra downstream work.
Prerequisite evidence
Test before extending
A passing pilot is a point in time. The routine needs to detect changes in materials, product mix, lighting, cameras, labels and demand patterns. Keep version identity and a safe rollback. A replacement model should meet the same operating requirement and be evaluated before it assumes the role of its predecessor.
Accepted and rejected items sampled on schedule.A change in material or lighting is possible. Sample accepted and rejected items again.Fallback inspection covers the gap.
Sample accepted and rejected items with an agreed review method. Track missed defects and false alarms separately. An aggregate accuracy figure can conceal the failure that matters most commercially, particularly when rare but serious defects are involved.
Error watched by product and horizon.Check by product and horizon whether the recommendation still changes the stock decision.Evaluation windows and exclusions stay explicit.
Evaluate error by product and horizon, and check whether the recommendation changes the inventory decision. Keep evaluation windows and exclusions explicit. A statistical improvement is different from a demonstrated reduction in working capital, waste or missed orders.
Loss of connectivity and device restart exercised.Events stay identifiable.Events held locally, manual fallback active. Reconcile the record before accepting the claim.
Exercise loss of connectivity, device restart and delayed upload. Confirm that events remain identifiable and that the manual fallback is usable. Restore normal service and reconcile the record before accepting a claim that the architecture supports the intended routine.
Illustrative signals. No live readings and no deployed system.
Continue through the programme
Return to the performance design to inspect the data foundation, or to feasibility to reconnect technology to the commercial conditions. Related papers and tools address inspection, cold-start forecasting and edge architecture. Their preparation status is explicit. This strategy describes a proposed sequence and makes no claim of realised performance or guaranteed return.
Ready computer-vision inspectionWaiting demand forecasting (sales and order history, baseline comparison)
Reconnects technology to the commercial conditions before any pilot is scoped.
No paper or instrument in this edition covers generative design. The architecture work shown here describes the capture layer any pilot would rely on.
Proposed sequence only. Not investment, legal or tax advice.