Production did not fail dramatically.
It failed quietly.
The Tactical Droid alerted me to the anomaly with a single line of text, flagged yellow rather than red.
[Efficiency deviation detected: Droid Factory Line 1 operating at 92.6% theoretical throughput.]
An inefficiency of 7.4%.
To an organic administrator, that margin would have been acceptable. To me, it was intolerable.
I halted live production instantly.
"Freeze all non-critical assembly," I ordered.
The Droid Factory's internal arms slowed, then locked in place. Half-assembled B1 units hung in their frames, inert and unfinished. Power consumption dropped by 0.3 MW across the grid.
Silence returned—manufactured, deliberate.
"Explain deviation," I said.
The Tactical Droid projected a layered diagnostic directly into my visual field.
[DROID FACTORY — THROUGHPUT ANALYSIS]
Theoretical Max Throughput:
– 1 B1 unit / 45 seconds
– 80 units/hour per line
Observed Throughput:
– 74.1 units/hour
Loss Sources:
▸ Micro-delays in arm synchronization (2.1%)
▸ Material handoff latency (1.8%)
▸ Thermal regulation cycling (1.3%)
▸ Command confirmation overhead (2.2%)
I focused on the final line.
"Command confirmation overhead?"
"Yes," the Tactical Droid replied. "Each assembly stage requests validation from the central command node to ensure tolerance compliance."
I frowned. "Why?"
"Because you ordered zero-defect manufacturing."
I allowed myself a moment of irritation—not at the Droid, but at myself. Perfection, applied indiscriminately, was as inefficient as negligence.
"Acceptable defect rate for B1 units?" I asked.
The Tactical Droid answered immediately.
"Up to 3.5% performance deviation has negligible battlefield impact. Structural failure probability increases only after 6.8% deviation."
I nodded once.
"Update tolerance thresholds. Accept deviation up to five percent. Remove command confirmation for non-critical joints."
The system responded before the Droid.
[Tolerance parameters updated.]
[Command confirmations removed from 61% of assembly stages.]
I resumed production.
The factory came alive again, arms moving faster now—less hesitation, fewer pauses. The throughput graph climbed smoothly.
[Observed Throughput: 79.3 units/hour.]
Acceptable.
This was the first law of mass production:
Uniformity mattered less than volume.
I expanded the Factory Control Panel.
[MANUFACTURING OVERVIEW]
Active Facilities:
– Droid Factory: 1
– Light Vehicle Factory: 1
– Heavy Vehicle Factory: 1
Aggregate Power Draw:
– Idle: 2.1 MW
– Peak: 6.8 MW
Alloy Consumption Rate (Peak):
– Droids: 95 alloy/hour
– Vehicles: 380 alloy/hour
Net Alloy Production:
– 14,400 alloy/day
The numbers told a clear story.
At current rates, vehicle production—not droids—would become the dominant consumer of refined alloy. That meant factory scheduling mattered more than raw output. If vehicle lines and droid lines peaked simultaneously, stockpiles would deplete rapidly, triggering cascading slowdowns.
"System," I said, "model staggered production cycles."
The panel shifted.
[PRODUCTION SCHEDULING SIMULATION]
Scenario A — Parallel Peaks:
▸ Alloy buffer depletion in 3.2 hours
▸ Forced throttling probability: 74%
Scenario B — Staggered Cycles (30 min offset):
▸ Alloy buffer stable
▸ Forced throttling probability: 9%
Scenario C — Priority Vehicle Production:
▸ Droid backlog accumulation
▸ Tactical readiness reduced by 18%
Scenario B was optimal.
"Implement staggered cycles," I ordered.
[Confirmed.]
The Tactical Droid added, "Recommendation: dedicate separate refinement streams for droid-grade and vehicle-grade alloy."
I raised an eyebrow. "Justify."
"Vehicle armor tolerances require higher density alloy," it said. "Using mixed-grade output increases refinement time by 11%."
Another inefficiency.
"Approved," I said. "Modify refinement nodes accordingly."
The Industrial Processing Layer responded immediately, routing ore flows through newly partitioned refinement paths. Alloy output dipped briefly—then recovered higher than before.
[Net Alloy Output: +6.4%]
The next problem revealed itself as soon as the solution settled.
Heat.
Vehicle assembly produced far more waste heat than projected. The flat world above masked the problem—no wind, no convection, no environmental dissipation. All heat had to go somewhere.
"Thermal saturation forecast," I requested.
[At current production rates, subterranean thermal load will reach critical thresholds in 11.6 hours.]
I clenched my jaw.
Heat was insidious. Unlike power or materials, it accumulated invisibly until systems began to fail without warning.
"Options," I said.
The Tactical Droid responded.
"Option one: reduce production rates. Option two: construct additional heat exchange shafts. Option three: repurpose surface area as thermal radiator."
I dismissed the first immediately.
"Evaluate option three."
A new overlay appeared, mapping the surface above the Headquarters.
[THERMAL DISSIPATION MODEL — SURFACE RADIATORS]
Required Radiator Area:
▸ 1.2 square kilometers
Visibility Risk:
▸ Minimal (no atmospheric distortion detected)
Construction Time:
▸ 18 minutes
The surface was already unnatural. A few more irregularities would not matter.
"Proceed," I said.
The ground several hundred meters from the Headquarters began to shift, unfolding into broad, matte-black panels angled precisely to maximize heat radiation. They did not glow. They did not shimmer.
They simply worked.
Thermal load dropped by 43% within minutes.
Constraint removed.
Replaced, inevitably, by another.
Logistics latency.
The distance between Mining Facilities, Refinement Nodes, Factories, and Storage had been acceptable at small scale. It would not remain so.
"Average material transit time?" I asked.
"42 seconds from mine to refinement," the Tactical Droid replied. "67 seconds from refinement to vehicle factory."
Too slow.
At scale, seconds became hours.
"Design logistics optimization," I ordered. "Priority: throughput, not redundancy."
The Tactical Droid projected several options.
[LOGISTICS OPTIMIZATION OPTIONS]
Option A — Conveyor Speed Increase:
▸ Throughput +15%
▸ Maintenance cost +22%
Option B — Parallel Conveyor Lines:
▸ Throughput +38%
▸ Material cost high
Option C — Autonomous Hauler Droids:
▸ Throughput +52%
▸ Power cost +18%
Option C was tempting—but mobile units introduced new failure modes. Damage. Pathing errors. Command overhead.
Not yet.
"Implement Option B," I decided. "Parallel lines. Keep system simple."
[Confirmed.]
As construction began, I stepped back—physically and cognitively—and examined the system as a whole.
Mining fed refinement. Refinement fed factories. Factories fed storage. Storage fed readiness.
Each link had limits. Each limit could be pushed, but only by introducing cost elsewhere.
This was the second law of mass production:
There was no such thing as free efficiency.
Only trade-offs.
The Tactical Droid spoke again.
"Observation," it said. "Current factory configuration is optimal for standardized units. It will struggle with high-variance designs."
I knew what it was implying.
Advanced droids. Specialized vehicles. Experimental platforms.
Future problems.
"Noted," I said. "When the time comes, we will build factories for complexity—not adapt simple ones."
The Droid inclined its head.
The B1 production counter ticked past 500 total units manufactured since activation. A small number, by galactic standards.
But this was not a galactic factory.
Yet.
I reopened the Status Panel, watching the metrics scroll smoothly, predictably, obediently.
Production stabilized.
Heat managed.
Throughput maximized within current constraints.
Chapter by chapter, equation by equation, the system grew more rigid—and therefore more powerful.
Factories did not win wars.
Factories determined who could afford to fight them.
And I was only beginning to set the price.