Foretak Global
Project Proteus

The industrial economics of Proteus

The $100
cost model.

Designing backward from cost—from mine to finished aircraft.

The central question is not whether a prototype can be assembled for approximately $100. It is whether a standardized American production system could eventually manufacture useful common-core aircraft near that recurring unit cost at very high volume.

The cost is a system

No silver bullet.
Many compounding gains.

Product architecture, scale, automation, yield, supply-chain depth, energy, tooling, capital utilization and purchasing power must reinforce one another.

01

Product architecture and BOM simplification

Every unnecessary part adds more than its purchase price. It adds handling, inventory, inspection, assembly time, failure opportunities and supplier complexity. Proteus is designed backward from the target by reducing unique parts, fasteners, interfaces and manual adjustment.

02

Economies of scale

A component made at 10,000 units a year has different economics at one million or ten million. Volume can justify dedicated tooling, automated production, longer supplier agreements, lower setup cost per unit and stronger purchasing terms.

03

Learning curves

Cost can fall as cumulative production grows. Processes stabilize, scrap declines, suppliers automate, layouts improve and engineering changes become less frequent. Volume changes conversion cost as well as fixed-cost allocation.

Commonality changes the economics

50,000 missions.
One common core.

Modular Open Systems Approach principles allow a common airframe, avionics architecture, power system, wiring standard, software environment and module interface to serve multiple configurations. Mission-specific differentiation happens later through standardized modules and software.

20,000Surveillance
15,000Communications
10,000Mapping
5,000Electronic support

50,000Common cores, configured late

Automation and the dark factory

Reduce repetitive minutes—not American ambition.

Robotic handling, automated dispensing, machine vision, standardized fixtures, autonomous material movement, digital quality records and automated testing can reduce repetitive labor per aircraft. Human work moves toward engineering, maintenance, software, tooling, quality analysis, cybersecurity and process improvement.

Yield is a hidden cost driver

90% yield means 1.11 attempts per good unit.

Poor yield consumes extra material, labor, machine time, energy, inspection and factory capacity. For an extremely low-cost product, high yield is not merely a quality objective. It is part of the cost architecture.

The upstream reality

Domestic extraction matters.
Competitive conversion matters more.

Batteries and electronics

Domestic lithium helps only when refining, cathode and anode processing, cell production, formation, pack assembly, testing and recycling are also competitive. The same logic applies to copper, magnets, semiconductors, PCB materials, aluminum, graphite, polymers and composites.

Energy

Final assembly is relatively light manufacturing. Mineral refining, chemical conversion, metals production, battery cells, carbon materials, semiconductors and industrial gases can be far more energy intensive. Energy policy reaches the cost target through every upstream component.

Mining

An ore body is not yet a supply chain. The analysis follows each input through concentration, refining, processing, components, subassemblies, factory and finished aircraft. The objective is not merely domestic extraction. It is competitive domestic conversion.

MineConcentrationRefiningProcessingComponentSubassemblyFactoryAircraft

The mathematical model

Every assumption gets a line.

The workbook can contain hundreds or thousands of components and manufacturing processes. Each line accounts for material, conversion, quantity, yield, energy, labor, machine time, logistics, tooling, supplier premiums and learning effects.

Component-level cost

Ci(Q) = ni / Yi × [(MiIm + Ci0(Q / Q0i)bᵢ)Si + EiPE + LiPL/3600 + TiPM/3600 + Fi + Ki/Ni − Ri]

Finished-unit cost

CProteus = Σ Ci + Cassembly + Ctest + Cpackaging + Cfactory/Q + CNRE/N + Coverhead + Cwarranty

nᵢQuantity of component or process i per aircraft
YᵢProcess yield
MᵢMaterial cost
IₘMaterial-price index
Cᵢ⁰Baseline conversion or purchase cost
Q / Q₀ᵢProduction-volume ratio
bᵢLearning-curve exponent
SᵢSupplier or domestic-content factor
EᵢPₑEnergy use × energy price
LᵢPₗ / 3600Labor seconds × labor rate
TᵢPₘ / 3600Machine seconds × machine rate
FᵢFreight and logistics
Kᵢ / NᵢTooling amortization
RᵢRecovery, recycling or residual credit

Four production scales

Volume changes the problem.

0110,000per year

Industrial pilot

High fixed cost per unit, limited tooling amortization and substantially more manual activity.

02100,000per year

Dedicated production

Purpose-built tooling, stronger purchasing power and targeted automation begin to make sense.

031,000,000per year

Mass production

Dedicated suppliers, automated assembly, tooling amortization and strong learning effects emerge.

0410,000,000per year

Industrial mobilization

Capacity, upstream supply, yield, energy, logistics, reliability and uptime become the central constraints.

The credibility test

The $100 target is a constraint—not a claim.

The current figure is a design and industrialization target, not a claim that a complete domestically manufactured Proteus aircraft can presently be purchased for exactly $100. Every component, process, supplier assumption, labor requirement, energy input, factory investment, yield rate and learning effect must earn its place inside the constraint.

If the technically useful minimum is $118, improve the architecture or change the target.

If $85 is possible at scale, reinvest the margin in capability, reliability or resilience.

The purpose is not to force the spreadsheet to prove the thesis. It is to force the thesis to survive the spreadsheet.