LOGIC
Industrial infrastructure increasingly depends on algorithmic decision systems. The limiting factor is not computational capability but semantic input consistency. SCY:MO proposes a structured component ontology as a foundational layer for simulation, optimization and AI-native engineering environments.
STRUCTURE
Component specifications are transformed from document-based descriptions into stable datasets. Canonical units, numeric performance curves and consistent parameter semantics enable cross-manufacturer comparability and reduce interpretative engineering risk.
{
"component_class": "pump",
"semantic_version": "0.1",
"units": "SI",
"parameters": {
"flow_nominal_m3h": 120,
"head_nominal_m": 32,
"speed_rpm": 2900
},
"performance_curve": [
{"q":0,"h":38.5},
{"q":60,"h":34.1},
{"q":120,"h":28.6}
]
}SYSTEM
Once component data becomes machine-native, engineering workflows shift from interpretation to synthesis. Simulation models can be constructed as composable physical logic rather than manually curated document abstractions.
CONTACT
SCY:MO is currently in conceptual formation. Collaboration interest from engineers, data architects and industrial system researchers is welcome.