<p>Remanufacturing-as-a-Service promises scalable, lower-cost repair of metal components by coordinating distributed capabilities through a cloud platform. This paper formulates a quantitative, supply-chain optimization of cloud-enabled remanufacturing built on a hybrid additive–subtractive (ASM) repair cost model and evaluates three delivery scenarios: (i) centralized national hubs with hybrid ASM; (ii) collaborations with tier-one local facilities that own separate AM and SM equipment; and (iii) collaborations with tier-two local facilities that provide only partial capability, requiring multi-facility routing. Using a U.S. tooling and machinery case study, this paper quantitatively fuses stepwise ASM repair economics with strategic facility location under an explicit quality–cost trade-off, closing a gap between process modeling and supply-chain design in remanufacturing. Results show that across plausible freights and capital costs, decentralized collaborations remain within 5% of the cost optimum while improving regional responsiveness; longer planning horizons shift the near-optimal set toward 5–8 hubs, rather than a single national site. Sensitivity tests confirm that (a) higher transportation costs and longer horizons favor additional hubs, while (b) tighter accuracy thresholds steer volume to hybrid hubs or vetted tier-one partners. The model provides clear trigger points—based on accuracy targets, capital expenditures, and freight conditions—for deciding when to build new hubs versus contracting with local partners. It offers managers a robust tool to navigate the critical trade-offs between cost efficiency, service reach, and quality.</p>