DSFB Structural Semiotics Engine for Semiconductor Process Control - A Deterministic Augmentation Layer for Typed Residual Interpretation for Fault Detection and Run-to-Run Variation in Advanced Manufacturing

DSFB does not compete with SPC, EWMA, or FDC — it augments them. Those systemscontinue to operate unchanged. DSFB reads the residual streams they already produceand returns a typed, deterministic, human-readable interpretation of what the residualsmean structurally. On the SECOM public benchmark under a fixed Stage III read-onlyprotocol, this augmentation collapses 28,607 raw boundary episodes into 71 policy-governedReview/Escalate episodes while preserving 104/104 labeled failure events. Episode precisionrises from a raw-boundary proxy of 0.36% to 80.3% — a 220.8× improvement in operatorrelevance. The upstream SPC and EWMA systems are not modified, replaced, or disabled.If DSFB is removed, upstream behavior is unchanged.Semiconductor process monitoring already produces dense residual streams through sta-tistical process control (SPC), run-to-run and advanced process control (APC), and faultdetection and classification (FDC) systems, but operational action is still dominated byscalar alarms that suppress temporal structure. This paper studies the DSFB StructuralSemiotics Engine as a deterministic augmentation layer over those existing residual streams.It does not propose a replacement controller or a new fab-wide monitoring stack. Instead,it maps residual trajectories into explicit objects — residual sign, admissibility envelope,grammar state, and provenance-aware motif entries — so that slow drift, boundary ap-proach, and structural excursion can be represented in a typed and inspectable form.The paper makes a bounded claim. It shows how deterministic intermediate representa-tions can support auditability arguments and operator review, and how the DSFB formalobjects can be instantiated using semiconductor observables such as innovation residuals,control limits, and specification windows. It does not prove SEMI standards compliance,completed qualification, universal superiority over SPC/EWMA/FDC/ML baselines, orphysical chamber-mechanism attribution from public data alone.The empirical evidence is Stage III public-data evidence on the SECOM dataset and its cur-rent Rust companion implementation. Under the fixed operator-facing protocol, DSFB isevaluated strictly as a read-only downstream layer over residuals already produced by exist-ing SPC/EWMA/FDC-style monitoring. In the selected SECOM configuration, the policy-governed DSFB layer preserves 104/104 labeled failure events while reducing investigation-worthy Review/Escalate decisions from 10,554 to 3,854 (63.5%) and collapsing raw bound-ary episodes from 28,607 to 71 (99.75%). Episode precision rises from a raw-boundaryprecision proxy of 0.36% to 80.3% (220.8x). The bounded empirical claim is thereforeoperator-facing: DSFB does not alter upstream control logic, thresholds, or actuation, butit converts a large residual review surface into a small set of structured, human-readableepisodes.