svasta nesto

docs/obrada/ispitni_rezultati.csv

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+Eksperiment,Orijentacija,Visina sloja,Širina ekstruzije,Postotak ispune,Broj slojeva stijenke,A_ekv [mm^2],Fm kN],Sigma [Mpa],SNR [dB]
+1,Orijentacija 1,0.08,0.4 mm,20.00%,2,100,0.778,7.78,17.8195919397938
+2,Orijentacija 1,0.08,0.6 mm,55.00%,4,100,3.299,32.99,30.3676463109069
+3,Orijentacija 1,0.08,0.8 mm,85.00%,6,100,0.794,7.94,17.9964100485419
+4,Orijentacija 1,0.14,0.4 mm,55.00%,6,100,2.792,27.92,28.9183082790225
+5,Orijentacija 1,0.14,0.6 mm,85.00%,2,100,2.468,24.68,27.8469031072241
+6,Orijentacija 1,0.14,0.8 mm,20.00%,4,100,2.871,28.71,29.1606638499301
+7,Orijentacija 1,0.28,0.4 mm,85.00%,4,100,2.423,24.23,27.6870682827501
+8,Orijentacija 1,0.28,0.6 mm,20.00%,6,100,1.891,18.91,25.5338305769008
+9,Orijentacija 1,0.28,0.8 mm,55.00%,2,100,2.431,24.31,27.7156991768667
+10,Orijentacija 2,0.08,0.4 mm,85.00%,4,100,3.398,33.98,30.6244674906605
+11,Orijentacija 2,0.08,0.6 mm,20.00%,6,100,3.218,32.18,30.1517207952602
+12,Orijentacija 2,0.08,0.8 mm,55.00%,2,100,2.768,27.68,28.8433217156944
+13,Orijentacija 2,0.14,0.4 mm,20.00%,6,100,2.472,24.72,27.8609693283356
+14,Orijentacija 2,0.14,0.6 mm,55.00%,2,100,2.527,25.27,28.0521048383983
+15,Orijentacija 2,0.14,0.8 mm,85.00%,4,100,3.647,36.47,31.2387152662756
+16,Orijentacija 2,0.28,0.4 mm,55.00%,4,100,2.491,24.91,27.9274745507301
+17,Orijentacija 2,0.28,0.6 mm,85.00%,6,100,4.111,41.11,32.278949535607
+18,Orijentacija 2,0.28,0.8 mm,20.00%,2,100,2.263,22.63,27.0936910790946

docs/obrada/ispitni_rezultati_taguchi_out/0_raw_with_SNR.csv

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+Eksperiment,Orijentacija,Visina sloja [mm],Širina ekstruzije [mm],Postotak ispune [%],Broj stijenki,A_ekv [mm^2],Fm kN],Sigma [Mpa],SNR [dB],SNR_LB [dB]
+1,Orijentacija 1,0.08,0.4,20.0,2.0,100.0,0.778,7.78,17.8195919397938,17.81959193979378
+2,Orijentacija 1,0.08,0.6,55.0,4.0,100.0,3.299,32.99,30.3676463109069,30.367646310906878
+3,Orijentacija 1,0.08,0.8,85.0,6.0,100.0,0.794,7.94,17.9964100485419,17.996410048541925
+4,Orijentacija 1,0.14,0.4,55.0,6.0,100.0,2.792,27.92,28.9183082790225,28.91830827902247
+5,Orijentacija 1,0.14,0.6,85.0,2.0,100.0,2.468,24.68,27.8469031072241,27.84690310722408
+6,Orijentacija 1,0.14,0.8,20.0,4.0,100.0,2.871,28.71,29.1606638499301,29.16066384993012
+7,Orijentacija 1,0.28,0.4,85.0,4.0,100.0,2.423,24.23,27.6870682827501,27.687068282750126
+8,Orijentacija 1,0.28,0.6,20.0,6.0,100.0,1.891,18.91,25.5338305769008,25.533830576900797
+9,Orijentacija 1,0.28,0.8,55.0,2.0,100.0,2.431,24.31,27.7156991768667,27.715699176866714
+10,Orijentacija 2,0.08,0.4,85.0,4.0,100.0,3.398,33.98,30.6244674906605,30.624467490660535
+11,Orijentacija 2,0.08,0.6,20.0,6.0,100.0,3.218,32.18,30.1517207952602,30.151720795260214
+12,Orijentacija 2,0.08,0.8,55.0,2.0,100.0,2.768,27.68,28.8433217156944,28.843321715694405
+13,Orijentacija 2,0.14,0.4,20.0,6.0,100.0,2.472,24.72,27.8609693283356,27.860969328335564
+14,Orijentacija 2,0.14,0.6,55.0,2.0,100.0,2.527,25.27,28.0521048383983,28.052104838398293
+15,Orijentacija 2,0.14,0.8,85.0,4.0,100.0,3.647,36.47,31.2387152662756,31.238715266275626
+16,Orijentacija 2,0.28,0.4,55.0,4.0,100.0,2.491,24.91,27.9274745507301,27.92747455073013
+17,Orijentacija 2,0.28,0.6,85.0,6.0,100.0,4.111,41.11,32.278949535607,32.27894953560699
+18,Orijentacija 2,0.28,0.8,20.0,2.0,100.0,2.263,22.63,27.0936910790946,27.09369107909457

docs/obrada/ispitni_rezultati_taguchi_out/1_response_means_Sigma.csv

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+Orijentacija,Sigma [Mpa],Delta (max-min),Faktor,Visina sloja [mm],Širina ekstruzije [mm],Postotak ispune [%],Broj stijenki
+Orijentacija 1,21.941111111111113,7.94222222222222,Orijentacija,,,,
+Orijentacija 2,29.883333333333333,7.94222222222222,Orijentacija,,,,
+,23.758333333333336,4.203333333333326,Visina sloja [mm],0.08,,,
+,27.961666666666662,4.203333333333326,Visina sloja [mm],0.14,,,
+,26.016666666666666,4.203333333333326,Visina sloja [mm],0.28,,,
+,23.923333333333332,5.266666666666666,Širina ekstruzije [mm],,0.4,,
+,29.189999999999998,5.266666666666666,Širina ekstruzije [mm],,0.6,,
+,24.623333333333335,5.266666666666666,Širina ekstruzije [mm],,0.8,,
+,22.488333333333333,5.579999999999998,Postotak ispune [%],,,20.0,
+,27.180000000000003,5.579999999999998,Postotak ispune [%],,,55.0,
+,28.06833333333333,5.579999999999998,Postotak ispune [%],,,85.0,
+,22.058333333333334,8.156666666666666,Broj stijenki,,,,2.0
+,30.215,8.156666666666666,Broj stijenki,,,,4.0
+,25.463333333333335,8.156666666666666,Broj stijenki,,,,6.0

docs/obrada/ispitni_rezultati_taguchi_out/2_response_means_SNR.csv

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+Orijentacija,SNR_LB [dB],Delta (max-min),Faktor,Visina sloja [mm],Širina ekstruzije [mm],Postotak ispune [%],Broj stijenki
+Orijentacija 1,25.894013507992987,3.4472547809021563,Orijentacija,,,,
+Orijentacija 2,29.341268288895144,3.4472547809021563,Orijentacija,,,,
+,25.967193050142956,2.879084394721403,Visina sloja [mm],0.08,,,
+,28.84627744486436,2.879084394721403,Visina sloja [mm],0.14,,,
+,28.039452200324888,2.879084394721403,Visina sloja [mm],0.28,,,
+,26.806313311882104,2.232212548834106,Širina ekstruzije [mm],,0.4,,
+,29.03852586071621,2.232212548834106,Širina ekstruzije [mm],,0.6,,
+,27.008083522733894,2.232212548834106,Širina ekstruzije [mm],,0.8,,
+,26.270077928219177,2.3673478837173043,Postotak ispune [%],,,20.0,
+,28.63742581193648,2.3673478837173043,Postotak ispune [%],,,55.0,
+,27.945418955176546,2.3673478837173043,Postotak ispune [%],,,85.0,
+,26.22855197617864,3.272453982363597,Broj stijenki,,,,2.0
+,29.501005958542237,3.272453982363597,Broj stijenki,,,,4.0
+,27.123364760611327,3.272453982363597,Broj stijenki,,,,6.0

docs/obrada/ispitni_rezultati_taguchi_out/3_factor_ranking.csv

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+Faktor,Rang delta (Sigma),Rang delta (SNR)
+Broj stijenki,8.156666666666666,3.272453982363597
+Orijentacija,7.94222222222222,3.4472547809021563
+Postotak ispune [%],5.579999999999998,2.3673478837173043
+Širina ekstruzije [mm],5.266666666666666,2.232212548834106
+Visina sloja [mm],4.203333333333326,2.879084394721403

docs/obrada/ispitni_rezultati_taguchi_out/4_optimal_levels.csv

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+Faktor,Optimalna razina (po S/N)
+Orijentacija,Orijentacija 2
+Visina sloja [mm],0.14
+Širina ekstruzije [mm],0.6
+Postotak ispune [%],55.0
+Broj stijenki,4.0

docs/obrada/ispitni_rezultati_taguchi_out/5_prediction.csv

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+Predikcija,Vrijednost
+Sigma_opt [MPa],40.781111111111116
+SNR_opt [dB],34.893939771178154
+Grand mean Sigma [MPa],25.912222222222223
+Grand mean SNR [dB],27.61764089844407

docs/obrada/ispitni_rezultati_taguchi_out/6_anova_sigma.csv

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+Factor,SS,DOF,MS,Pct_contrib_%
+Orijentacija,283.8550222222221,1,283.8550222222221,23.01723952764538
+Visina sloja [mm],53.10221111111093,2,26.551105555555466,4.305952746663593
+Širina ekstruzije [mm],98.16444444444437,2,49.082222222222185,7.959959676553248
+Postotak ispune [%],107.87454444444445,2,53.93727222222223,8.747332384591576
+Broj stijenki,201.40714444444444,2,100.70357222222222,16.33170500195548
+Error,488.8245444444449,8,61.10306805555561,39.63781066259073

docs/obrada/ispitni_rezultati_taguchi_out/summary.json

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+{
+  "outdir": "ispitni_rezultati_taguchi_out",
+  "factors": [
+    "Orijentacija",
+    "Visina sloja [mm]",
+    "Širina ekstruzije [mm]",
+    "Postotak ispune [%]",
+    "Broj stijenki"
+  ],
+  "opt_levels": {
+    "Orijentacija": "Orijentacija 2",
+    "Visina sloja [mm]": 0.14,
+    "Širina ekstruzije [mm]": 0.6,
+    "Postotak ispune [%]": 55.0,
+    "Broj stijenki": 4.0
+  },
+  "pred_sigma": 40.781111111111116,
+  "grand_mean_sigma": 25.912222222222223
+}

docs/obrada/ispitni_rezultati_taguchi_out/taguchi_results.tex

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+% --- Taguchi rezultati (S = Sigma [MPa], S/N larger-the-better) ---
+
+\subsection{Rezultati Taguchijeve metode}
+
+U skladu s ortogonalnom matricom provedena je analiza s kriterijem \textbf{što-veće-to-bolje}. Za svaku kombinaciju izračunat je S/N omjer \((\mathrm{S/N}=20\log_{10}(\sigma))\) te su određeni glavni učinci po razinama i optimalna kombinacija.
+
+\paragraph{Optimalne razine (po S/N).}
+
+\begin{tabular}{ll}
+\toprule
+Faktor & Optimalna razina (po S/N) \\
+\midrule
+Orijentacija & Orijentacija 2 \\
+Visina sloja [mm] & 0.140000 \\
+Širina ekstruzije [mm] & 0.600000 \\
+Postotak ispune [%] & 55.000000 \\
+Broj stijenki & 4.000000 \\
+\bottomrule
+\end{tabular}
+
+
+\paragraph{Predikcija odziva na optimalnoj kombinaciji.}
+
+\begin{tabular}{lr}
+\toprule
+Predikcija & Vrijednost \\
+\midrule
+Sigma_opt [MPa] & 40.78 \\
+SNR_opt [dB] & 34.89 \\
+Grand mean Sigma [MPa] & 25.91 \\
+Grand mean SNR [dB] & 27.62 \\
+\bottomrule
+\end{tabular}
+
+
+\paragraph{Rang utjecaja faktora.}
+
+\begin{tabular}{lrr}
+\toprule
+Faktor & Rang delta (Sigma) & Rang delta (SNR) \\
+\midrule
+Broj stijenki & 8.157 & 3.272 \\
+Orijentacija & 7.942 & 3.447 \\
+Postotak ispune [%] & 5.580 & 2.367 \\
+Širina ekstruzije [mm] & 5.267 & 2.232 \\
+Visina sloja [mm] & 4.203 & 2.879 \\
+\bottomrule
+\end{tabular}
+
+
+\paragraph{ANOVA (Taguchi).}
+
+\begin{tabular}{lrrrr}
+\toprule
+Factor & SS & DOF & MS & Pct_contrib_% \\
+\midrule
+Orijentacija & 283.855000 & 1 & 283.855000 & 23.017000 \\
+Visina sloja [mm] & 53.102000 & 2 & 26.551000 & 4.306000 \\
+Širina ekstruzije [mm] & 98.164000 & 2 & 49.082000 & 7.960000 \\
+Postotak ispune [%] & 107.875000 & 2 & 53.937000 & 8.747000 \\
+Broj stijenki & 201.407000 & 2 & 100.704000 & 16.332000 \\
+Error & 488.825000 & 8 & 61.103000 & 39.638000 \\
+\bottomrule
+\end{tabular}
+
+
+Napomena: budući da je \(n{=}1\), pogreška (Error) procijenjena je iz preostalih stupnjeva slobode (Taguchi pooling).

docs/obrada/obrada.py

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+
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Taguchi analysis pipeline for FDM experiment (per user's thesis)
+- Reads a CSV with columns similar to:
+  'Eksperiment','Orijentacija','Visina sloja','Širina ekstruzije','Postotak ispune',
+  'Broj slojeva stijenke','A_ekv [mm^2]','Fm kN]','Sigma [Mpa]','SNR [dB]'
+- Cleans units to numeric, recomputes Sigma (optional) and SNR (LB, n=1),
+- Builds response tables (means, Δ), ranks factors, selects optimal levels by SNR,
+- Predicts response at optimal combination (additive model),
+- Runs Taguchi-style ANOVA on Sigma,
+- Saves CSV outputs + main-effects plots + LaTeX snippet.
+Usage:
+    python taguchi_from_csv.py --input ispitni_rezultati.csv --outdir out_tlak
+"""
+import argparse, os, re, json
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+def norm_num(x):
+    if pd.isna(x):
+        return np.nan
+    if isinstance(x, (int, float, np.number)):
+        return float(x)
+    s = str(x).strip()
+    s = s.replace(',', '.')
+    s = s.replace('%','')
+    s = s.replace(' mm','')
+    s = s.replace('MPa','').replace('Mpa','')
+    s = s.replace('kN','').replace('kN]','').replace('[','').replace(']','')
+    try:
+        return float(s)
+    except:
+        return np.nan
+
+def compute_snr_lb(y):
+    # larger-the-better; handles n=1 case
+    y = pd.to_numeric(y, errors='coerce')
+    return 20.0*np.log10(y.clip(lower=1e-12))
+
+def response_table(df, factor, col):
+    t = df.groupby(factor, as_index=False)[col].mean()
+    t["Delta (max-min)"] = t[col].max() - t[col].min()
+    t["Faktor"] = factor
+    return t
+
+def taguchi_anova(df, response, factors):
+    y = df[response].astype(float)
+    mu = y.mean()
+    total_ss = ((y - mu)**2).sum()
+    rows = []
+    dof_used = 0
+    ss_used = 0.0
+    for f in factors:
+        grp = df.groupby(f)[response].agg(['mean','count'])
+        ss_f = (grp['count']*(grp['mean']-mu)**2).sum()
+        dof_f = grp.shape[0]-1
+        rows.append([f, ss_f, dof_f])
+        dof_used += dof_f
+        ss_used += ss_f
+    err_ss = max(total_ss - ss_used, 0.0)
+    err_dof = max(len(df)-1 - dof_used, 0)
+    an = pd.DataFrame(rows, columns=["Factor","SS","DOF"])
+    an["MS"] = an["SS"]/an["DOF"]
+    an["Pct_contrib_%"] = (an["SS"]/total_ss*100.0) if total_ss>0 else np.nan
+    err_row = pd.DataFrame([["Error", err_ss, err_dof, (err_ss/err_dof) if err_dof>0 else np.nan, (err_ss/total_ss*100.0) if total_ss>0 else np.nan]],
+                           columns=["Factor","SS","DOF","MS","Pct_contrib_%"])
+    an = pd.concat([an, err_row], ignore_index=True)
+    return an, mu, total_ss
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--input", required=True, help="Path to CSV with results")
+    ap.add_argument("--outdir", default=None, help="Output directory")
+    ap.add_argument("--response", default="Sigma [Mpa]", help="Response column to analyze (default Sigma [Mpa])")
+    ap.add_argument("--area_col", default="A_ekv [mm^2]", help="Area column if Sigma should be recomputed from Fm/Area")
+    ap.add_argument("--fm_col", default="Fm kN]", help="Force column (kN)")
+    ap.add_argument("--recompute_sigma", action="store_true", help="If set, recompute Sigma = Fm*1000/Area")
+    ap.add_argument("--sn_type", default="LB", choices=["LB"], help="S/N type (only LB supported here)")
+    args = ap.parse_args()
+
+    in_path = args.input
+    outdir = args.outdir or (os.path.splitext(os.path.basename(in_path))[0] + "_taguchi_out")
+    os.makedirs(outdir, exist_ok=True)
+
+    df = pd.read_csv(in_path)
+
+    # Standard column mapping / cleanup for known names
+    rename_map = {
+        "Visina sloja":"Visina sloja [mm]",
+        "Širina ekstruzije":"Širina ekstruzije [mm]",
+        "Postotak ispune":"Postotak ispune [%]",
+        "Broj slojeva stijenke":"Broj stijenki",
+        "Sigma [MPa]":"Sigma [Mpa]",
+        "Fm [kN]":"Fm kN]",
+    }
+    df = df.rename(columns={k:v for k,v in rename_map.items() if k in df.columns})
+
+    # Ensure numeric for relevant columns
+    if "Visina sloja [mm]" in df.columns:
+        df["Visina sloja [mm]"] = df["Visina sloja [mm]"].apply(norm_num)
+    if "Širina ekstruzije [mm]" in df.columns:
+        df["Širina ekstruzije [mm]"] = df["Širina ekstruzije [mm]"].apply(norm_num)
+    if "Postotak ispune [%]" in df.columns:
+        df["Postotak ispune [%]"] = df["Postotak ispune [%]"].apply(norm_num)
+    if "Broj stijenki" in df.columns:
+        df["Broj stijenki"] = df["Broj stijenki"].apply(norm_num)
+    if args.area_col in df.columns:
+        df[args.area_col] = df[args.area_col].apply(norm_num)
+    if args.fm_col in df.columns:
+        df[args.fm_col] = df[args.fm_col].apply(norm_num)
+    if args.response in df.columns:
+        df[args.response] = df[args.response].apply(norm_num)
+
+    # Compute Sigma if asked or missing
+    if args.recompute_sigma or args.response not in df.columns or df[args.response].isna().all():
+        if args.fm_col in df.columns and args.area_col in df.columns:
+            df[args.response] = (df[args.fm_col] * 1000.0) / df[args.area_col]
+        else:
+            raise SystemExit("Cannot recompute Sigma: missing Fm or Area columns")
+
+    # Compute SNR (LB)
+    df["SNR_LB [dB]"] = compute_snr_lb(df[args.response])
+
+    # Save cleaned raw
+    raw_out = os.path.join(outdir, "0_raw_with_SNR.csv")
+    df.to_csv(raw_out, index=False)
+
+    # Factors to analyze (auto detect from known list)
+    candidate_factors = ["Orijentacija","Visina sloja [mm]","Širina ekstruzije [mm]","Postotak ispune [%]","Broj stijenki"]
+    factors = [f for f in candidate_factors if f in df.columns]
+    if len(factors) == 0:
+        raise SystemExit("No known factor columns found. Expected some of: " + ", ".join(candidate_factors))
+
+    # Response tables and deltas
+    resp_mu = pd.concat([response_table(df, f, args.response) for f in factors], ignore_index=True)
+    resp_sn = pd.concat([response_table(df, f, "SNR_LB [dB]") for f in factors], ignore_index=True)
+    resp_mu.to_csv(os.path.join(outdir, "1_response_means_Sigma.csv"), index=False)
+    resp_sn.to_csv(os.path.join(outdir, "2_response_means_SNR.csv"), index=False)
+
+    # Ranking (by Delta)
+    rank_mu = resp_mu.groupby("Faktor")["Delta (max-min)"].max().sort_values(ascending=False).reset_index().rename(columns={"Delta (max-min)":"Rang delta (Sigma)"})
+    rank_sn = resp_sn.groupby("Faktor")["Delta (max-min)"].max().sort_values(ascending=False).reset_index().rename(columns={"Delta (max-min)":"Rang delta (SNR)"})
+    ranking = pd.merge(rank_mu, rank_sn, on="Faktor")
+    ranking.to_csv(os.path.join(outdir, "3_factor_ranking.csv"), index=False)
+
+    # Optimal levels by SNR
+    opt_levels = {f: df.groupby(f)["SNR_LB [dB]"].mean().sort_values(ascending=False).index[0] for f in factors}
+    opt_table = pd.DataFrame({"Faktor": list(opt_levels.keys()), "Optimalna razina (po S/N)": list(opt_levels.values())})
+    opt_table.to_csv(os.path.join(outdir, "4_optimal_levels.csv"), index=False)
+
+    # Prediction at optimal combo (additive model) on response
+    grand_mean = df[args.response].mean()
+    k = len(factors)
+    pred_sigma = sum(df.groupby(f)[args.response].mean().loc[opt_levels[f]] for f in factors) - (k-1)*grand_mean
+    grand_mean_snr = df["SNR_LB [dB]"].mean()
+    pred_snr = sum(df.groupby(f)["SNR_LB [dB]"].mean().loc[opt_levels[f]] for f in factors) - (k-1)*grand_mean_snr
+    pred_df = pd.DataFrame({
+        "Predikcija": ["Sigma_opt [MPa]","SNR_opt [dB]","Grand mean Sigma [MPa]","Grand mean SNR [dB]"],
+        "Vrijednost": [pred_sigma, pred_snr, grand_mean, grand_mean_snr]
+    })
+    pred_df.to_csv(os.path.join(outdir, "5_prediction.csv"), index=False)
+
+    # ANOVA (Taguchi-style) on response
+    anova_df, mu_sigma, totss = taguchi_anova(df, args.response, factors)
+    anova_df.to_csv(os.path.join(outdir, "6_anova_sigma.csv"), index=False)
+
+    # Plots: main effects for SNR
+    for f in factors:
+        means = df.groupby(f)["SNR_LB [dB]"].mean().reset_index()
+        # numeric sort if possible
+        try:
+            means[f] = pd.to_numeric(means[f], errors="ignore")
+            means = means.sort_values(by=f)
+        except:
+            pass
+        plt.figure()
+        plt.plot(means[f], means["SNR_LB [dB]"], marker="o")
+        plt.xlabel(f)
+        plt.ylabel("S/N (LB) [dB]")
+        plt.title(f"Main effect (S/N): {f}")
+        plt.tight_layout()
+        plt.savefig(os.path.join(outdir, f"main_effect_SNR_{f}.png"), dpi=150)
+        plt.close()
+
+    # LaTeX snippet
+    latex_lines = []
+    latex_lines.append(r"% --- Taguchi rezultati (S = Sigma [MPa], S/N larger-the-better) ---")
+    latex_lines.append(r"\subsection{Rezultati Taguchijeve metode}")
+    latex_lines.append(r"U skladu s ortogonalnom matricom provedena je analiza s kriterijem \textbf{što-veće-to-bolje}. Za svaku kombinaciju izračunat je S/N omjer \((\mathrm{S/N}=20\log_{10}(\sigma))\) te su određeni glavni učinci po razinama i optimalna kombinacija.")
+
+    # Optimal levels
+    latex_lines.append(r"\paragraph{Optimalne razine (po S/N).}")
+    latex_lines.append(opt_table.to_latex(index=False, escape=False))
+    # Prediction
+    latex_lines.append(r"\paragraph{Predikcija odziva na optimalnoj kombinaciji.}")
+    latex_lines.append(pred_df.to_latex(index=False, escape=False, float_format='%.2f'))
+    # Ranking
+    latex_lines.append(r"\paragraph{Rang utjecaja faktora.}")
+    latex_lines.append(ranking.to_latex(index=False, escape=False, float_format='%.3f'))
+    # ANOVA
+    an_fmt = anova_df.copy()
+    for c in ["SS","MS","Pct_contrib_%"]:
+        if c in an_fmt.columns:
+            an_fmt[c] = an_fmt[c].astype(float).round(3)
+    latex_lines.append(r"\paragraph{ANOVA (Taguchi).}")
+    latex_lines.append(an_fmt.to_latex(index=False, escape=False))
+    latex_lines.append(r"Napomena: budući da je \(n{=}1\), pogreška (Error) procijenjena je iz preostalih stupnjeva slobode (Taguchi pooling).")
+
+    with open(os.path.join(outdir, "taguchi_results.tex"), "w", encoding="utf-8") as f:
+        f.write("\n\n".join(latex_lines))
+
+    # Small JSON summary
+    summary = {
+        "outdir": outdir,
+        "factors": factors,
+        "opt_levels": opt_levels,
+        "pred_sigma": pred_sigma,
+        "grand_mean_sigma": grand_mean,
+    }
+    with open(os.path.join(outdir, "summary.json"), "w", encoding="utf-8") as f:
+        json.dump(summary, f, ensure_ascii=False, indent=2)
+
+    print("Done. Outputs in:", outdir)
+
+if __name__ == "__main__":
+    main()