Adaptive OEE: A FUCOM-TOPSIS Framework for Context-Driven Equipment Effectiveness

Overall Equipment Effectiveness (OEE) is the dominant metric for manufacturing productivity, computed as the multiplicative product of Availability (A), Performance (P), and Quality (Q). Despite its widespread adoption, the classical OEE formula embeds a structural limitation: the three components are treated as equally important regardless of operational context, a fixed-weight assumption that systematically distorts maintenance prioritisation in environments with asymmetric operational priorities. No published framework has formally addressed this limitation through a structured, auditable multi-criteria weighting model. This paper proposes Adaptive OEE, a FUCOM-TOPSIS framework that replaces the fixed A×P×Q product with a context-driven weighting model. FUCOM elicits context-specific weights for A, P and Q from expert judgement using only n−1 pairwise comparisons with guaranteed consistency, while TOPSIS ranks equipment assets under the weighted criteria, producing a closeness coefficient comparable across assets and contexts. Three illustrative case studies covering availability-dominant, performance-dominant, and quality-dominant contexts demonstrate that the classical OEE ranking is not preserved under any weight configuration, with Divergence Index values ranging from 0.667 to 1.333. Divergence is most severe when one component carries strongly asymmetric weight, precisely the condition equal weighting cannot accommodate. The principal contributions are the formalisation of the equal-weighting assumption as a measurement-theoretic deficiency, the replacement of multiplicative aggregation with a weighted distance measure preserving the A/P/Q decomposition, and the introduction of the Divergence Index as a quantitative measure of context-insensitive rank displacement.