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Ranking
Fuzzy Smart FMEA with DEA (FSFMEA) - Fuzzy FMEA + CCR Data Envelopment Analysis for corrective action prioritization
Risk-based ranking - Fuzzy FMEA (S×O×D under TFN/TrFN) + DEA CCR efficiency scoring for corrective action prioritization
Adesina, K. A., Yazdi, M., Zarei, E., Pouyakian, M.2022doi:10.1007/978-3-030-93352-4_7 ↗
Overview
Efficient FMs (DEA θ*=1) should be prioritized for corrective actions first, as they have lower cost and time requirements. Among efficient FMs, rank by RPN descending. Then handle inefficient FMs by RPN. Note: DEA efficiency here means the FM's corrective action is cost-time efficient - NOT that the FM itself is less risky (higher RPN = higher risk, lower C+T = easier to fix efficiently).
- Output
- priority rank, lower is better
- Data
- Fuzzy (TFN), linguistic expert ratings
- Weights
- Needs a weight source
- Size
- 6+ alternatives, 3 criteria works best
- Used for
- FMEA risk assessment, Safety engineering, Reliability analysis, Corrective action prioritization
How it works
- 1
Her uzman k her FM_i için S, O, D dilsel etiket verir (Very low/Low/Medium/High/Very high). Tables 7.1-7.3 ile TFN veya TrFN'e çevir. Severity: Very high=(0.8,0.9,1), High=(0.5,0.6,0.7,0.8) TrFN, Medium=(0.4,0.5,0.6), Low=(0.2,0.3,0.4,0.5) TrFN, Very low=(0,0.1,0.2). Detectability İNVERTED: Non-detection=(0,0.1,0.2) en kötü.
- 2
Uzmanların yaş/deneyim/eğitim üzerinde pairwise TFN matrisi kur, Buckley 1985 geometrik ortalama yöntemi uygula. Çıktı w_k uzman ağırlıkları, Σw_k=1 (paper §7.2.2.1).
- 3
Her FM_i ve risk faktörü j için Z_i^(j) = Σ_k w_k ⊗ f_ij^(k). TFN/TrFN fuzzy toplama (element-wise). FM8 örneği p.164: (M,M,M,H) uzmanlardan → (0.14+0.18+0.33)·(0.4,0.5,0.5,0.6) + 0.35·(0.7,0.8,0.9) = (0.505,0.505,0.605,0.705).
- 4
TFN için X*=(a1+a2+a3)/3 (Eq.7.5). TrFN için X*=⅓·[(a4+a3)²−a4·a3−(a1+a2)²+a1·a2]/(a4+a3−a1−a2) (Eq.7.6). 1-10 ölçeğine çevir: X_scaled=X*·10. FM8_O örneği: X*=0.587 ≈ 0.6 → scaled 5.87.
- 5
RPN_i = S_i · O_i · D_i (1-10 ölçeğinde crisp). Yüksek RPN = yüksek risk.
- 6
Her FM_i bir DMU. Inputs x_io = (S_i, O_i, D_i, 1/RPN_i) [4 input]; outputs y_ro = (1/C_i, 1/T_i) [2 output]. Dual LP: min θ s.t. Σ_j λ_j·x_ij ≤ θ·x_io, Σ_j λ_j·y_rj ≥ y_ro, λ_j≥0. θ*=1 efficient, θ*<1 inefficient.
- 7
Efficient FMs (θ*=1) ÖNCE - RPN azalan sırada. Sonra inefficient FMs (θ*<1) - RPN azalan sırada. Paper §7.3: efficient={FM3,FM4,FM7,FM9,FM10}, inefficient={FM1,FM2,FM5,FM6,FM8}; final FM9>FM10>FM7>FM4>FM3>FM1>FM8>FM2>FM5>FM6.
Fits when / Look elsewhere when
Fits when
- •Addresses conventional FMEA's 15 documented shortcomings (paper §7.1 list [16]): tie-breaking, weight handling, non-linear D scale, etc.
- •DEA layer adds cost-time aware prioritization beyond pure risk-score (RPN) ranking
- •Buckley FAHP expert weighting handles heterogeneous expert backgrounds (job tenure, education, experience)
- •Mixed TFN/TrFN handling - TFN for symmetric scales (Severity), TrFN for asymmetric/range scales (High includes 7-8)
- •Three published versions (Conventional FMEA / FDFMEA / FSFMEA) provide built-in sensitivity reference (paper Fig.7.2 trend comparison)
Look elsewhere when
- •Cost/time data for corrective actions not available (DEA phase unusable)
- •Fewer than 6 failure modes (DEA unreliable with few DMUs)
- •FMEA context not applicable (method is domain-specific)
Assumptions to verify
- Corrective action cost C and time T are measurable and provided per FM
- DEA CCR assumes constant returns to scale - appropriate for FM efficiency
- Expert group must be heterogeneous for reliable Buckley FAHP weighting
Limitations
- •Paper §7.3 does NOT publish full 10×3 S/O/D matrix per expert - only FM8_O TrFN quartet shown; closed-form reproduction limited to outcome level
- •DEA CCR assumes constant returns to scale - may misrepresent FM efficiency if some FMs have economies of scale in corrective actions
- •Final ranking can override conventional risk priority: paper p.167 acknowledges 'cannot guarantee highest RPN FM will be reduced' (e.g. FM6 highest RPN but least prioritized because cost/time too high)
- •DEA solver dependency: paper uses PIM DEA v3.2 (proprietary); open-source alternatives (pyDEA, scipy.optimize) need adaptation
- •Expert weight elicitation via Buckley FAHP requires separate manifest invocation (chained dependency on FUZZY-AHP)
Edge cases and pitfalls
- •TFN ve TrFN aynı FM agregasyonunda karışık → Eq.7.5 ve Eq.7.6 ayrı uygula (paper FM8 örneği p.164 her ikisini de gösterir)
- •DEA CCR DMU sayısı < 6 (inputs+outputs) → ayrımcılık güç kaybı; rapor edilebilir ama güvenilmez (K.common_pitfalls)
- •Tüm FMs efficient (θ*=1) → DEA discriminative değil, RPN-only ranking'e geri dön
- •RPN=0 → 1/RPN tanımsız, büyük M ile değiştir veya 'no risk' flag
- •TFN'i degenerate TrFN olarak işle (a3=a4): mixed Eq.7.3 toplamı için TFN (l,m,u) → (l,m,m,u) broadcast (FM8 p.164 örtük yapıyor)
- •Aynı RPN ama farklı C/T → DEA kırar (FM9 vs FM10 cost=10.525 same, FM9 time=2.14 vs FM10 time=1.84; combined FM9>FM10 RPN-dominant)
Confusing DEA efficiency (corrective action efficiency) with FM risk level - an efficient FM may still have high RPN.
DEA requires at least as many DMUs (FMs) as the sum of inputs + outputs (4+2=6 minimum FMs for reliable results).
Works with
Commonly takes its weights from
How to cite
Adesina, K. A.; Yazdi, M.; Zarei, E.; Pouyakian, M. (2022). Smart Decision Fuzzy-Based Data Envelopment Model for Failure Modes and Effects Analysis. in: Yazdi M. (ed.), Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis, Studies in Fuzziness and Soft Computing, Vol. 414, Springer, Cham, pp. 151-168 (Chapter 7). https://doi.org/10.1007/978-3-030-93352-4_7
System ID, as it appears in reports and the API
FUZZY-FMEA-DEA