Machine Design Knowledge Lab
ABOUT MECHALOGICS
MechaLogics translates and analyzes technical documents, existing CAD/PDF drawings, and mechanism videos. More than 30 years of mechanical-engineering experience is applied to turn source material and customer requirements into information that can be reviewed, traced, and used in practical work.
FROM REQUIREMENT TO DESIGN CRITERIA
01 — Interpret the intent
Separate purpose, required functions, operating conditions, constraints, priorities, and acceptance conditions. Make conflicts and missing assumptions visible before a conclusion is formed.
02 — Structure the design data
Organize requirements, functions, structural groups, components, interfaces, parameters, source evidence, revisions, and decision states as connected records.
03 — Establish the criteria
Select relevant criteria across geometry, materials, manufacturing, assembly, cost, schedule, and risk. State trade-offs and validation conditions.
04 — Control the decision
Keep candidate interpretations open until evidence is sufficient. Accepted, rejected, and HOLD items retain rationale, source, checking result, and unresolved conditions.
05 — Validate the generated output
Check generated translations, analyses, relationship maps, tables, and reports against source material, requirements, units and values, terminology, component and interface relationships, and applicable engineering criteria. Record source location, applied criterion, result, status, and open issue. Classify each conclusion as CONFIRMED, INFERRED, or HOLD.
Requirement
Function
Structural Group
Component / Geometry
→ Validate output: CONFIRMED · INFERRED · HOLD
OUR WORKING PRINCIPLES
Context before wording
Terminology, dimensions, components, interfaces, and operating sequences are interpreted together. No sentence, symbol, or value is treated in isolation.
Evidence before certainty
Confirmed facts, engineering inferences, and unresolved items remain separate. Where the material cannot support a conclusion, the result stays open for confirmation.
Relationships before fragments
Geometry, materials, manufacturing, assembly, cost, and risk influence one another. Reviews follow these relationships rather than disconnected observations.
Reviewable output
Findings include source locations, applied references, checking results, decision status, and open issues so the customer can review how each conclusion was reached.
LONG-TERM DESIGN-OS R&D
Design is managed as an evolving system state—not as a sequence of files.
MechaLogics views design as the controlled transformation of customer intent into a verified system configuration. Requirements, functions, structural groups, interfaces, parameters, knowledge, decisions, evidence, risks, and revisions are linked as one evolving design state. Geometry, drawings, and reports are outputs of that state—not the starting point.
AI supports this process by interpreting and structuring source material, comparing requirements with the current design state, detecting contradictions and missing evidence, maintaining candidate options, and proposing the next checks or actions. AI does not own engineering approval: decisions remain controlled by declared criteria, validators, and human authority.
HOW ENGINEERING KNOWLEDGE IS STRUCTURED FOR AI — Knowledge is not supplied as undifferentiated text. Standards, manuals, equations, design rules, constraints, and validated cases are divided into source-linked Knowledge Entries containing meaning, parameters, units, applicability, exclusions, evidence grade, uncertainty, and revision. Entries are grouped into version-controlled Knowledge Packs and connected through a Knowledge System Map. AI retrieves only the knowledge applicable to the current design state; validators check its use, and only approved feedback becomes a new revision. Unverified output never silently becomes knowledge.
STRUCTURED DESIGN AUTOMATION — Customer intent → requirements and functions → structural groups and interfaces → candidate design state → applicable Knowledge Packs → AI-assisted coordination → analysis and generation tools → validation gates → approved output → revision and trace history. Today’s services use selected parts of this method. The longer-term Design-OS direction connects program status, technical knowledge, design execution, automated generation, validation, and change history in one controlled loop. If evidence is insufficient, the process stops for review rather than inventing a result.
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