REDI Manufacturing TraceLab v2.8.1

POC-aligned pre-shipment simulation: receiving → MREDI generation → device build → module assembly → parametric testing → OQC → final disposition. The conventional path fragments data across enterprise systems. REDI1C carries compact module lineage, validator-node timestamps, summarized test results, and disposition in one evolving item-bound record.

1. Manufacturing lifecycle flow

Smartphone-Manufacturing station flow. Lifecycle after shipment is intentionally excluded.

2. Traceability capture comparison

Left: enterprise systems. Right: REDI1C item-bound state.

Conventional System

IQC, assembly, test, QA, and disposition systems each store their own fragment. Test stations store raw XML parametric files locally.
No conventional records yet. Start the demo.

REDI System

One REDI1C string evolves as validator nodes append module references, lineage, test summaries, timestamps, and disposition.
Evolving REDI1C string
No REDI record yet. Start the demo.
Module lineage summary from REDI f(x)
ModuleVendorOEM PartCurrent MREDIPrev MREDIsReworkTest Result

3. Lifecycle Traceability System Overhead

Illustrative system overhead only: cloud databases, servers, APIs, storage, maintenance, and reconciliation labor. Not product manufacturing cost.
Conventional system overhead / unit
$0.00
Cloud DBs, APIs, servers, storage, IT support
REDI system overhead / unit
$0.00
Validator nodes, encode/decode, compact storage
Conventional memory / unit
0.00 KB
Raw XML-heavy records
REDI memory / unit
0.000 KB
Compact summary + lineage
Conventional overhead represents the cost of operating traceability infrastructure: cloud databases, online servers, API connections between MES/ERP/test/QA systems, dashboard maintenance, storage of raw test files, IT/admin support, technician scanning effort, and engineering time spent reconciling missing or mismatched records. REDI overhead represents validator-node software, REDI encode/decode operations, checksum validation, compact storage, and lightweight synchronization.

4. REDI-Derived Yield and Consumption Analytics

Derived from REDI item-bound lineage, test outcomes, and disposition records. Values update using the unit count from the Scalability Calculator below.
Interpretation
This analytics view is REDI-derived. The same analytics can exist in a conventional environment, but only after reconciling multiple system records. REDI makes the lineage and disposition logic directly available from decoded item-bound records and the row-wise REDI ledger.
MetricValue
ModuleVendorUsedReworkFailures

5. Scalability Calculator

Choose the number of units. This updates both the scalability table and the REDI-derived analytics section above.
Uses the accumulated system-overhead assumptions from the current simulated flow. Run all stations for a full-flow estimate.
Metric Conventional REDI Difference

6. Lifecycle event timeline

Every station contributes a system update and/or a REDI validator-node update.
No events yet.