Not having Forge
has a measurable cost.

Without Forge

2–4 hours to identify and dispatch

• ↓Operator calls supervisor to report fault
• ↓Supervisor manually logs ticket in CMMS
• ↓Technician identifies subsystem from symptom description
• ↓Technician searches shared drive for the right schematic — version unknown
• ↓Technician calls stores to check part availability
• ↓Wrong part ordered — machine waits for reorder
• ↓Fault recurs 3 weeks later — treated as a new event

Average fault-to-production time: 2–4 hours. Estimated repeat rate: 1 in 3 corrective repairs.

With Forge

8 seconds to work order. 47 minutes to production.

• ↓Sensor breach logged by ForgeMachine — subsystem identified from PLC I/O map
• ↓ForgeOps classifies fault and dispatches corrective WO automatically
• ↓Work order arrives pre-filled: machine ID, subsystem, sensor readings, timestamp
• ↓Correct schematic attached before technician reaches the machine
• ↓Parts check run against live ERP stock — PO raised only if needed
• ↓Post-repair sensor data captured — machine cleared by data, not signature
• ↓Fault record closed. Component history updated. Recurrence monitored.

Fault-to-WO: 8 seconds. Machine down for 47 minutes. No manual steps.

Without Forge

Each repair treated as a first occurrence

• ↓Three technicians raise three separate WOs for the same fault over 6 weeks
• ↓Each WO is closed independently — no cross-WO pattern detection
• ↓No engineering notification triggered — failure looks isolated
• ↓Root cause is never investigated
• ↓Fourth occurrence damages a secondary component
• ↓Repair cost doubles — unplanned engineering escalation required
• ↓No training record created for the failure mode

Average chronic failure: 4–8 repairs before root cause is addressed. Engineering involvement: zero.

With Forge

Fourth occurrence triggers root cause investigation automatically

• ↓ForgeMaint flags recurring fault — configurable window (default: 45 days)
• ↓Engineering brief opened in ForgeCAD with full fault history pre-loaded
• ↓ForgeKnowledge surfaces: what changed on this machine in the last 60 days
• ↓Engineer identifies root cause — lubrication interval extended 3 weeks prior
• ↓Design fix issued. ForgeMachine updates maintenance procedure automatically.
• ↓Training record created for the failure category
• ↓Same fault has not recurred.

Pattern identified at occurrence four. Root cause resolved. Training gap closed.

Without Forge

Change notification by email — some machines missed

• ↓Engineer releases new drawing revision via PLM
• ↓Engineer sends email to floor supervisor with the change
• ↓Supervisor updates one of three affected machines
• ↓Two machines run the old NC program
• ↓Parts produced to the wrong tolerance
• ↓NCR raised — customer parts scrapped
• ↓Root cause traced to an email nobody forwarded

Engineering changes that reach all affected machines: 60–70%. NCR rate from missed changes: measurable.

With Forge

Design change propagates to all three machines before the next run

• ↓Engineer releases revision in ForgeCAD — change event published to ForgeHub
• ↓All three machines running the part are identified automatically
• ↓NC programs for all three machines flagged as stale — tool offsets recalculated
• ↓Maintenance inspection procedure updated to reflect new tolerance
• ↓Pending PO flagged if bar stock may be insufficient for the new dimension
• ↓Compliance change record created automatically — AS9100 requirements met
• ↓No email. No forwarding. No missed machines.

Engineering changes that reach all affected machines: 100%. Manual change communication: zero.

Without Forge

Wrong part. Wrong vendor. Manual every time.

• ↓Technician identifies replacement part from paper manual or memory
• ↓Part number checked against stores inventory — manually
• ↓Stores doesn't have it — technician calls procurement
• ↓Procurement searches vendor catalogue for the part number
• ↓PO raised manually — standard lead time applies
• ↓Machine waits for the part
• ↓Part arrives — sometimes it's the wrong spec

Part identification errors: 10–20% of unplanned repairs. Average PO-to-delivery: 3–5 days.

With Forge

Correct part, correct vendor, PO raised before the technician starts

• ↓ForgeMachine identifies the failed component from the I/O map
• ↓ForgeProcure checks ERP on-hand stock — automatically
• ↓If stock is sufficient: no PO raised, stores notified
• ↓If stock is below reorder threshold: draft PO raised against approved vendor
• ↓PO is pre-filled with correct part number, specification, and quantity
• ↓Part is on order before the technician begins the repair
• ↓Post-repair: component history updated with the replacement record

Part identification errors: zero — part number sourced from machine graph. PO raised in parallel with repair.

Without Forge

Same fault. Different technician. Different outcome.

• ↓Four different technicians repair the same fault over 14 months
• ↓Each one diagnoses differently — none of them fix the root cause
• ↓No cross-technician pattern analysis runs — each repair looks independent
• ↓Training records are updated manually — often not updated at all
• ↓Skills gap on hydraulic pressure faults is invisible until it causes a failure
• ↓Manager escalates to engineering only after the machine causes a production loss
• ↓Engineering identifies a training gap that has existed for over a year

Average time to identify a skills gap through repeat failures: 12–18 months.

With Forge

Skills gap identified at occurrence four — before the machine causes a loss

• ↓ForgeMaint detects: three different technicians, three different diagnoses, zero first-time fixes
• ↓Workforce intelligence flag raised: training gap on fault category — hydraulic pressure
• ↓Engineering brief opened with all repair histories and sensor readings attached
• ↓Root cause identified at the design level — hydraulic accumulator pre-charge drift
• ↓Training record updated for the fault category
• ↓Technicians notified of new diagnosis procedure — proactively
• ↓Same fault pattern has not recurred across any technician

Skills gap identified at occurrence four. Training record created automatically.