Predictive Signatures for Lunar Manufacturing Systems

Lunar manufacturing concepts combine in-situ resources, autonomous equipment, constrained maintenance, environmental exposure, and delayed terrestrial supervision. These conditions make changes in system response potentially important even when monitored values remain within specified limits. This conceptual paper defines a predictive signature as a persistent and repeatable change in an input-response relationship that appears across one or more physical or control domains and may justify a bounded operational response. The construct does not predict failure time, estimate remaining useful life, or establish that a critical transition will occur. Instead, it organizes candidate evidence that system behavior may be departing from a validated operating regime. The paper differentiates predictive signatures from anomaly detection, prognostics and health management, structural health monitoring, and generic early-warning indicators. It then proposes operational definitions, structural, thermal, and dynamic signature classes, an evidence-to-response pathway, and validation criteria that address persistence, repeatability, contextual comparability, cross-domain coherence, confounding influences, and uncertainty. Lunar manufacturing literature supports the relevance of environmental and process variability, but no lunar operational dataset currently validates the proposed construct. Accordingly, the framework should guide hypothesis formation, instrumentation, simulation, and ground-based testing rather than serve as an operationally qualified decision rule. The paper concludes with a staged research agenda for establishing detectability, discrimination, lead time, and response utility before deployment.