zamjenjene decimalne tocke u decimalne zareze

docs/.~lock.ispitni_rezultati.ods#

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+,marockaspark,localhost.localdomain,11.09.2025 12:52,file:///home/marockaspark/.config/libreoffice/4;

docs/ispitni_rezultati.csv

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+Eksperiment,Orijentacija,Visina sloja,Širina ekstruzije,Postotak ispune,Broj slojeva stijenke,A_ekv [mm^2],A_min [mm^2],A_max,Fm kN],Sigma [Mpa],Sigma’,SNR [dB]
+1,Orijentacija 1,0.08,0.4,20.00%,2,100,44.493,,0.778,7.78,17.4858966579012,17.8195919397938
+2,Orijentacija 1,0.08,0.6,55.00%,4,100,87.819,,3.299,32.99,37.5659025951104,30.3676463109069
+3,Orijentacija 1,0.08,0.8,85.00%,6,100,100,,0.794,7.94,7.94,17.9964100485419
+4,Orijentacija 1,0.14,0.4,55.00%,6,100,87.6308,,2.792,27.92,31.8609438690506,28.9183082790225
+5,Orijentacija 1,0.14,0.6,85.00%,2,100,91.5613,,2.468,24.68,26.9546194735112,27.8469031072241
+6,Orijentacija 1,0.14,0.8,20.00%,4,100,93.9905,,2.871,28.71,30.5456402508764,29.1606638499301
+7,Orijentacija 1,0.28,0.4,85.00%,4,100,92.7473,,2.423,24.23,26.1247497231725,27.6870682827501
+8,Orijentacija 1,0.28,0.6,20.00%,6,100,96.3896,,1.891,18.91,19.6182990696092,25.5338305769008
+9,Orijentacija 1,0.28,0.8,55.00%,2,100,79.2649,,2.431,24.31,30.6693126465813,27.7156991768667
+10,Orijentacija 2,0.08,0.4,85.00%,4,100,35.669,,3.398,33.98,95.264795761025,30.6244674906605
+11,Orijentacija 2,0.08,0.6,20.00%,6,100,36.045,,3.218,32.18,89.277292273547,30.1517207952602
+12,Orijentacija 2,0.08,0.8,55.00%,2,100,26.908,,2.768,27.68,102.869035231158,28.8433217156944
+13,Orijentacija 2,0.14,0.4,20.00%,6,100,32.415,,2.472,24.72,76.2609902822767,27.8609693283356
+14,Orijentacija 2,0.14,0.6,55.00%,2,100,24.155,,2.527,25.27,104.616021527634,28.0521048383983
+15,Orijentacija 2,0.14,0.8,85.00%,4,100,42.804,,3.647,36.47,85.2023175404168,31.2387152662756
+16,Orijentacija 2,0.28,0.4,55.00%,4,100,26.909,,2.491,24.91,92.5712586866848,27.9274745507301
+17,Orijentacija 2,0.28,0.6,85.00%,6,100,44.555,,4.111,41.11,92.2679833913141,32.278949535607
+18,Orijentacija 2,0.28,0.8,20.00%,2,100,15.895,,2.263,22.63,142.371815036175,27.0936910790946

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()

docs/taguchi_ancova.py

@@ -0,0 +1,159 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# Taguchi ANOVA + ANCOVA helper
+# Run: python taguchi_ancova.py --input ispitni_rezultati.ods --out results.xlsx --cov A_min A_max
+
+import argparse, sys, unicodedata, math
+from pathlib import Path
+import numpy as np
+import pandas as pd
+
+try:
+    from scipy.stats import f as fdist
+    def f_p_value(F, dfn, dfd): return float(fdist.sf(F, dfn, dfd))
+except Exception:
+    def f_p_value(F, dfn, dfd): return float("nan")
+
+def norm_label(s: str) -> str:
+    s = str(s).strip().lower()
+    s = "".join(c for c in unicodedata.normalize("NFKD", s) if not unicodedata.combining(c))
+    s = s.replace("["," ").replace("]"," ").replace("("," ").replace(")"," ")
+    s = " ".join(s.split())
+    return s
+
+def find_col(df: pd.DataFrame, *candidates):
+    labels = {norm_label(c): c for c in df.columns}
+    for cand in candidates:
+        key = norm_label(cand)
+        if key in labels: return labels[key]
+    for cand in candidates:
+        toks = norm_label(cand).split()
+        for k, orig in labels.items():
+            if all(t in k for t in toks): return orig
+    return None
+
+def taguchi_anova(df: pd.DataFrame, y_col: str, factor_cols):
+    y = pd.to_numeric(df[y_col], errors="coerce")
+    mask = y.notna(); y = y[mask]
+    N = y.shape[0]; mu = float(y.mean()); SST = float(((y - mu) ** 2).sum())
+    rows = []; level_means = {}
+    for f in factor_cols:
+        g = df.loc[mask, f]
+        stats = (pd.DataFrame({"y": y.values, "lvl": g.values}).groupby("lvl", dropna=False)["y"].agg(["mean","count"]).reset_index())
+        SSf = float((stats["count"] * (stats["mean"] - mu) ** 2).sum())
+        a = stats.shape[0]; df_f = max(a-1,0); MSf = SSf/df_f if df_f>0 else float("nan")
+        rows.append({"Faktor": f, "SS": SSf, "df": df_f, "MS": MSf})
+        level_means[f] = dict(zip(stats["lvl"], stats["mean"]))
+    res = pd.DataFrame(rows)
+    SS_factors = float(res["SS"].sum()); df_factors = int(res["df"].sum()); df_total = N-1
+    SS_error = SST - SS_factors; df_error = df_total - df_factors; MS_error = SS_error/df_error if df_error>0 else float("nan")
+    res["F"] = res["MS"] / MS_error if MS_error>0 else float("nan")
+    res["Udio var [%]"] = 100.0*res["SS"]/SST if SST>0 else float("nan")
+    return res, level_means, {"N":N,"mu":mu,"SST":SST,"SS_error":SS_error,"df_error":df_error,"MS_error":MS_error}
+
+def taguchi_yhat(df, y_col, factor_cols, level_means, mu):
+    k = len(factor_cols); yhat = np.zeros(len(df), dtype=float)
+    for f in factor_cols: yhat += df[f].map(level_means[f]).astype(float).values
+    yhat = yhat - (k-1)*mu
+    mask = pd.to_numeric(df[y_col], errors="coerce").notna().values; yhat[~mask] = np.nan
+    return yhat
+
+def simple_linregress(x, y):
+    x = np.asarray(pd.to_numeric(x, errors="coerce"), dtype=float)
+    y = np.asarray(pd.to_numeric(y, errors="coerce"), dtype=float)
+    m = np.isfinite(x) & np.isfinite(y); x=x[m]; y=y[m]; n=len(x)
+    if n<2: return float("nan"), float("nan"), n
+    xb, yb = float(x.mean()), float(y.mean())
+    Sxx = float(((x-xb)**2).sum()); Sxy = float(((x-xb)*(y-yb)).sum())
+    b1 = Sxy/Sxx if Sxx!=0 else float("nan"); b0 = yb - b1*xb if math.isfinite(b1) else float("nan")
+    return b1, b0, n
+
+def ancova_single(e, cov, df_err_old, SST):
+    b1, b0, n_used = simple_linregress(cov, e)
+    cov_num = np.asarray(pd.to_numeric(cov, errors="coerce"), dtype=float)
+    e_hat = b0 + b1*cov_num; e_new = e - e_hat
+    SSE_old = float(np.nansum(e**2)); SSE_new = float(np.nansum(e_new**2)); SS_cov = SSE_old - SSE_new
+    df_err_new = df_err_old - 1; MS_err_new = SSE_new/df_err_new if df_err_new>0 else float("nan")
+    F_cov = (SS_cov/1.0)/MS_err_new if MS_err_new>0 else float("nan"); p = f_p_value(F_cov,1,df_err_new) if math.isfinite(F_cov) else float("nan")
+    dR2 = (SSE_old - SSE_new)/SST if SST>0 else float("nan")
+    return {"b0":b0,"b1":b1,"n_used":n_used,"SSE_old":SSE_old,"SSE_new":SSE_new,"SS_cov":SS_cov,
+            "df_err_old":df_err_old,"df_err_new":df_err_new,"MS_err_new":MS_err_new,"F_cov":F_cov,"p":p,"Delta_R2_vs_SST":dR2}, e_hat, e_new
+
+def main():
+    ap = argparse.ArgumentParser(description="Taguchi ANOVA + ANCOVA (A_min / A_max)")
+    ap.add_argument("--input", required=True); ap.add_argument("--sheet", default=None)
+    ap.add_argument("--out", default="Taguchi_ANCOVA_results.xlsx")
+    ap.add_argument("--cov", nargs="*", default=["A_min"])
+    args = ap.parse_args()
+
+    inp = Path(args.input)
+    if not inp.exists(): print(f"ERROR: Ne postoji {inp}", file=sys.stderr); sys.exit(2)
+    if inp.suffix.lower()==".ods":
+        try: df = pd.read_excel(inp, sheet_name=args.sheet, engine="odf")
+        except Exception as e: print(f"ERROR: .ods ({type(e).__name__}): {e}", file=sys.stderr); sys.exit(2)
+    elif inp.suffix.lower() in (".xlsx",".xls"): df = pd.read_excel(inp, sheet_name=args.sheet)
+    else: df = pd.read_csv(inp)
+
+    y_col = (find_col(df,"Sigma [Mpa]","Sigma [MPa]","sigma","σ") or find_col(df,"Sigma [Mpa]"))
+    if y_col is None:
+        fm = find_col(df,"Fm kN]","Fm [kN]","Force"); aeq = find_col(df,"A_ekv [mm^2]","A ekv","A_ekv")
+        if fm and aeq: df["Sigma [Mpa]"] = pd.to_numeric(df[fm],errors="coerce")*1000/pd.to_numeric(df[aeq],errors="coerce"); y_col="Sigma [Mpa]"
+        else: print("ERROR: σ ni (Fm i A_ekv) nisu pronađeni.", file=sys.stderr); sys.exit(2)
+
+    cand = ["Orijentacija","Visina sloja","Širina ekstruzije","Sirina ekstruzije","Postotak ispune","Broj stijenki","Broj slojeva stijenke"]
+    factors=[]; 
+    for c in cand:
+        col = find_col(df,c); 
+        if col and col not in factors: factors.append(col)
+    if find_col(df,"Broj stijenki") and find_col(df,"Broj slojeva stijenke"):
+        bs = find_col(df,"Broj slojeva stijenke"); 
+        if bs in factors: factors.remove(bs)
+    if not factors: print("ERROR: Faktori nisu pronađeni.", file=sys.stderr); sys.exit(2)
+
+    anova, lvl_means, meta = taguchi_anova(df, y_col, factors)
+    yhat = taguchi_yhat(df, y_col, factors, lvl_means, meta["mu"]); e = pd.to_numeric(df[y_col],errors="coerce").values - yhat
+
+    cov_results={}; per_row = pd.DataFrame({"σ [MPa]":df[y_col], "σ̂ (Taguchi)":yhat, "e":e})
+    names = [c.lower() for c in (args.cov or [])]
+    if ("a_min" in names) or ("a min" in names):
+        amin_col = find_col(df,"A_min [mm^2]","A_min","A min")
+        if amin_col:
+            info, e_hat, e_new = ancova_single(e, df[amin_col], meta["df_error"], meta["SST"])
+            cov_results["A_min"]=info; per_row["A_min"]=df[amin_col]; per_row["ê(A_min)"]=e_hat; per_row["e_new(A_min)"]=e_new
+    if ("a_max" in names) or ("a max" in names):
+        amax_col = find_col(df,"A_max [mm^2]","A_max","A max")
+        if amax_col:
+            info, e_hat, e_new = ancova_single(e, df[amax_col], meta["df_error"], meta["SST"])
+            cov_results["A_max"]=info; per_row["A_max"]=df[amax_col]; per_row["ê(A_max)"]=e_hat; per_row["e_new(A_max)"]=e_new
+
+    MS_err_old = meta["MS_error"]; decisions=[]
+    for nm, info in cov_results.items():
+        keep = (info["MS_err_new"] < MS_err_old) and ( (not math.isnan(info["p"]) and info["p"]<0.05) or math.isnan(info["p"]) )
+        decisions.append({"Kovarijata":nm,"MS_err_old":MS_err_old,"MS_err_new":info["MS_err_new"],"F":info["F_cov"],"p":info["p"],"ΔR²_vs_SST":info["Delta_R2_vs_SST"],"Preporuka_zadrzati":bool(keep)})
+
+    anova_updated = anova.copy()
+    valid = [d for d in decisions if d["MS_err_new"] < MS_err_old]
+    if valid:
+        best = min(valid, key=lambda d: d["MS_err_new"]); ms_new = best["MS_err_new"]
+        anova_updated["F (nakon ANCOVA)"] = anova_updated["MS"] / ms_new
+
+    out = Path(args.out)
+    with pd.ExcelWriter(out, engine="xlsxwriter") as wr:
+        df.to_excel(wr, sheet_name="Raw", index=False); anova.to_excel(wr, sheet_name="ANOVA_Taguchi", index=False)
+        pd.DataFrame([{"N":meta["N"],"mu":meta["mu"],"SST":meta["SST"],"SS_error":meta["SS_error"],"df_error":meta["df_error"],"MS_error":meta["MS_error"]}]).to_excel(wr, sheet_name="Meta", index=False)
+        for f in factors: pd.DataFrame({"Razina":list(lvl_means[f].keys()),"mean σ":list(lvl_means[f].values())}).to_excel(wr, sheet_name=f"Mean_{f}", index=False)
+        if cov_results:
+            for nm, info in cov_results.items(): pd.DataFrame([info]).to_excel(wr, sheet_name=f"ANCOVA_{nm}_info", index=False)
+            per_row.to_excel(wr, sheet_name="ANCOVA_rows", index=False); anova_updated.to_excel(wr, sheet_name="ANOVA_updated", index=False)
+
+    print("ANOVA – glavni učinci:\n", anova.to_string(index=False))
+    if cov_results:
+        print("\nANCOVA – rezultati:")
+        for nm, info in cov_results.items():
+            print(f"  {nm}: F={info['F_cov']:.4g}, p={info['p']:.4g}, MS_err_new={info['MS_err_new']:.4g}, ΔR²={info['Delta_R2_vs_SST']:.4g}")
+        if decisions: 
+            import pandas as pd; print("\nPreporuke:\n", pd.DataFrame(decisions).to_string(index=False))
+        print(f"\nExcel zapisano u: {out}")
+
+if __name__ == "__main__":
+    main()

radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.aux

@@ -1,24 +1,20 @@
 \relax 
 \providecommand \babel@aux [2]{\global \let \babel@toc \@gobbletwo }
 \@nameuse{bbl@beforestart}
-\abx@aux@refcontext{nty/global//global/global/global}
+\abx@aux@refcontext{none/global//global/global/global}
 \providecommand \oddpage@label [2]{}
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-\@writefile{toc}{\contentsline {section}{\numberline {2}Teorijska osnova}{2}{}\protected@file@percent }
+\@writefile{toc}{\contentsline {section}{\numberline {2}FDM aditivna tehnologija}{2}{}\protected@file@percent }
-\newlabel{sec:teorijska_osnova}{{2}{2}{}{section.2}{}}
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-\@writefile{toc}{\contentsline {subsection}{\numberline {2.1}FDM aditivna tehnologija}{2}{}\protected@file@percent }
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-\newlabel{sec:fdm_aditivna_tehnologija}{{2.1}{2}{}{subsection.2.1}{}}
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-\@writefile{toc}{\contentsline {subsection}{\numberline {2.2}Općenito o FDM tehnologiji}{2}{}\protected@file@percent }
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-\newlabel{sec:opcenito_o_fdm_tehnologiji}{{2.2}{2}{}{subsection.2.2}{}}
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-\@writefile{toc}{\contentsline {subsection}{\numberline {2.4}Parametri ispisa}{3}{}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {2.4}Opis relevantnih parametara ispisa}{3}{}\protected@file@percent }
-\newlabel{sec:parametri_ispisa}{{2.4}{3}{}{subsection.2.4}{}}
+\newlabel{subsec:opis_relevantnih_parametara_ispisa}{{2.4}{3}{}{subsection.2.4}{}}
-\@writefile{toc}{\contentsline {subsubsection}{\numberline {2.4.1}Osnovni parametri ispisa}{3}{}\protected@file@percent }
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 \abx@aux@cite{0}{kuznetsov2018strengthPLA}
 \abx@aux@segm{0}{0}{kuznetsov2018strengthPLA}
 \abx@aux@cite{0}{kuznetsov2018strengthPLA}
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-\newlabel{subsubsec:visina_sloja}{{2.5.1}{4}{}{subsubsection.2.5.1}{}}
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+\abx@aux@defaultrefcontext{0}{AzureFilmPLA}{none/global//global/global/global}
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+\gdef \@abspage@last{74}

radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bcf

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radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bcf-SAVE-ERROR

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+    <bcf:citekey order="28" intorder="1">hermann2019extrusionwidth</bcf:citekey>
+    <bcf:citekey order="29" intorder="1">daly2024infillCFPETG</bcf:citekey>
+    <bcf:citekey order="30" intorder="1">bazjanacNauka1</bcf:citekey>
+    <bcf:citekey order="31" intorder="1">bazjanacNauka1</bcf:citekey>
+    <bcf:citekey order="32" intorder="1">cojocaru2025dogbone</bcf:citekey>
+    <bcf:citekey order="33" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="34" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="35" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="36" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="37" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="38" intorder="1">AzureFilmPLA</bcf:citekey>
+    <bcf:citekey order="39" intorder="1">Stamopoulos2020</bcf:citekey>

radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.blg

@@ -1,17 +1,16 @@
 [0] Config.pm:308> INFO - This is Biber 2.20
 [0] Config.pm:311> INFO - Logfile is 'ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.blg'
-[48] biber:342> INFO - === Sat Aug 23, 2025, 14:16:35
+[44] biber:342> INFO - === Thu Sep 18, 2025, 20:01:51
-[59] Biber.pm:420> INFO - Reading 'ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bcf'
+[55] Biber.pm:420> INFO - Reading 'ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bcf'
-[92] Biber.pm:994> INFO - Found 21 citekeys in bib section 0
+[87] Biber.pm:994> INFO - Found 22 citekeys in bib section 0
-[105] Biber.pm:4463> INFO - Processing section 0
+[96] Biber.pm:4463> INFO - Processing section 0
-[110] Biber.pm:4654> INFO - Looking for bibtex file 'literatura.bib' for section 0
+[102] Biber.pm:4654> INFO - Looking for bibtex file 'literatura.bib' for section 0
-[111] bibtex.pm:1713> INFO - LaTeX decoding ...
+[103] bibtex.pm:1713> INFO - LaTeX decoding ...
-[121] bibtex.pm:1519> INFO - Found BibTeX data source 'literatura.bib'
+[111] bibtex.pm:1519> INFO - Found BibTeX data source 'literatura.bib'
-[227] UCollate.pm:68> INFO - Overriding locale 'hr-HR' defaults 'normalization = NFD' with 'normalization = prenormalized'
+[200] UCollate.pm:68> INFO - Overriding locale 'hr-HR' defaults 'normalization = NFD' with 'normalization = prenormalized'
-[227] UCollate.pm:68> INFO - Overriding locale 'hr-HR' defaults 'variable = shifted' with 'variable = non-ignorable'
+[200] UCollate.pm:68> INFO - Overriding locale 'hr-HR' defaults 'variable = shifted' with 'variable = non-ignorable'
-[227] Biber.pm:4283> INFO - Sorting list 'nty/global//global/global/global' of type 'entry' with template 'nty' and locale 'hr-HR'
+[200] Biber.pm:4283> INFO - Sorting list 'none/global//global/global/global' of type 'entry' with template 'none' and locale 'hr-HR'
-[243] bbl.pm:677> INFO - Writing 'ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bbl' with encoding 'UTF-8'
+[210] bbl.pm:677> INFO - Writing 'ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bbl' with encoding 'UTF-8'
-[248] bbl.pm:780> INFO - Output to ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bbl
+[215] bbl.pm:780> INFO - Output to ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.bbl
-[248] Biber.pm:131> WARN - Duplicate entry key: 'kuznetsov2018strengthPLA' in file 'literatura.bib', skipping ...
+[215] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_cMEV/c61ccb34f23828ed7e5b3976dd87481f_7245.utf8, line 1, warning: 1 characters of junk seen at toplevel
-[248] Biber.pm:131> WARN - legacy year field '1963.' in entry 'bazjanacNauka1' is not an integer - this will probably not sort properly.
+[215] Biber.pm:133> INFO - WARNINGS: 1
-[248] Biber.pm:133> INFO - WARNINGS: 2

radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.fdb_latexmk

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+  "ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lot"
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+  "ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.toc"
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radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.fls

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+INPUT ./media/imgs/anova_smik/graf_povrsina_smik.jpg
 INPUT /usr/share/texmf/fonts/tfm/adobe/helvetic/phvrc7t.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4r-0.tfm
+INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4r-0.tfm
 INPUT /usr/share/texmf/fonts/vf/adobe/helvetic/phvrc7t.vf
 INPUT /usr/share/texmf/fonts/tfm/adobe/helvetic/phvr8r.tfm
-INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4r-0.tfm
+INPUT ./ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lof
-INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4r-0.tfm
+INPUT ./ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lof
+INPUT ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lof
+OUTPUT ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lof
+INPUT ./ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lot
+INPUT ./ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lot
+INPUT ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lot
+OUTPUT ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lot
 INPUT /usr/share/texmf/tex/latex/listings/lstlang1.sty
 INPUT /usr/share/texmf/tex/latex/listings/lstlang1.sty
 INPUT /usr/share/texmf/tex/latex/listings/lstlang1.sty
 INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4r-0.tfm
-INPUT /usr/share/texmf/fonts/tfm/adobe/helvetic/phvr7t.tfm
 INPUT /usr/share/texmf/fonts/tfm/public/inconsolata/ot1-zi4b-0.tfm
 INPUT /usr/share/texmf/fonts/vf/adobe/helvetic/phvr7t.vf
 INPUT /usr/share/texmf/fonts/tfm/adobe/helvetic/phvr8r.tfm
@@ -460,11 +583,15 @@ OUTPUT ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.run.xml
 INPUT /usr/share/texmf/fonts/type1/public/inconsolata/Inconsolata-zi4b.pfb
 INPUT /usr/share/texmf/fonts/type1/public/inconsolata/Inconsolata-zi4r.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmex10.pfb
+INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmmi10.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmmi12.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmmi8.pfb
+INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmr10.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmr12.pfb
+INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmr7.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmr8.pfb
 INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmsy10.pfb
+INPUT /usr/share/texmf/fonts/type1/public/amsfonts/cm/cmsy8.pfb
 INPUT /usr/share/texmf/fonts/type1/urw/helvetic/uhvb8a.pfb
 INPUT /usr/share/texmf/fonts/type1/urw/helvetic/uhvbo8a.pfb
 INPUT /usr/share/texmf/fonts/type1/urw/helvetic/uhvr8a.pfb

radno/ispitivanje_cvrstoce_fdm_3d_printanog_uzorka.lof

@@ -0,0 +1,36 @@
+\babel@toc {croatian}{}\relax 
+\contentsline {figure}{\numberline {1}{\ignorespaces Transformacija poprečnog presjeka pojedinog sloja s povećanjem debljine sloja. Oblik sloja prikazan je preko SEM slika.}}{4}{}%
+\contentsline {figure}{\numberline {2}{\ignorespaces Širina ekstruzije pojedinog traga pri izlazu iz mlaznice, kroz paralelne tragove.}}{5}{}%
+\contentsline {figure}{\numberline {3}{\ignorespaces Različiti postotci ispune kod iste vrste ispune.}}{6}{}%
+\contentsline {figure}{\numberline {4}{\ignorespaces 3D model paralelopipeda prikazan u sve tri orijentacije u odnosu na podlogu.}}{9}{}%
+\contentsline {figure}{\numberline {5}{\ignorespaces 3D model paralelopipeda podešenog na 2, 4 i 6 slojeva stijenke.}}{9}{}%
+\contentsline {figure}{\numberline {6}{\ignorespaces Usporedba 100\% (lijevo) i 85\% (desno) postotka ispune, pri širini ekstruzije od 100\%.}}{16}{}%
+\contentsline {figure}{\numberline {7}{\ignorespaces Prikaz rasporeda slojeva u sve tri orijentacije.}}{18}{}%
+\contentsline {figure}{\numberline {8}{\ignorespaces Ispitna epruveta prikazana u sve tri orijentacije bez potpornog materijala.}}{22}{}%
+\contentsline {figure}{\numberline {9}{\ignorespaces Ispitna epruveta prikazana u sve tri orijentacije sa potpornim materijalom u trećoj orijentaciji (desno).}}{22}{}%
+\contentsline {figure}{\numberline {10}{\ignorespaces Prikaz suženja epruvete u presjeku.}}{23}{}%
+\contentsline {figure}{\numberline {11}{\ignorespaces Okvirna geometrija prihvatnog kraja epruvete koji je potrebno izraditi sa 100\% ispune.}}{24}{}%
+\contentsline {figure}{\numberline {12}{\ignorespaces Epruveta pripremljena s 20\% ispune, sa integriranim krajnjim prihvatima s 100\% ispune.}}{24}{}%
+\contentsline {figure}{\numberline {13}{\ignorespaces 3D prikaz epruvete za testiranje na vlak.}}{25}{}%
+\contentsline {figure}{\numberline {14}{\ignorespaces 3D prikaz epruvete za testiranje na smik.}}{25}{}%
+\contentsline {figure}{\numberline {15}{\ignorespaces Skica za dimenzioniranje epruvete za testiranje na smik.}}{26}{}%
+\contentsline {figure}{\numberline {16}{\ignorespaces Skica za dimenzioniranje epruvete za testiranje na vlak.}}{26}{}%
+\contentsline {figure}{\numberline {17}{\ignorespaces Prikaz naprave za smično opterećenje epruvete.}}{29}{}%
+\contentsline {figure}{\numberline {18}{\ignorespaces Prikaz naprave za smično opterećenje epruvete, pripremljene za ispis, u presjeku.}}{30}{}%
+\contentsline {figure}{\numberline {19}{\ignorespaces Prikaz izrađene naprave za smično testiranje sa ispitnim uzorkom.}}{31}{}%
+\contentsline {figure}{\numberline {20}{\ignorespaces Prikaz svih ispitnih uzoraka.}}{33}{}%
+\contentsline {figure}{\numberline {21}{\ignorespaces Primjer graviranog teksta na čelu ispitnog uzorka.}}{34}{}%
+\contentsline {figure}{\numberline {22}{\ignorespaces Primjer vlačnog ispitnog uzorka u kidalici.}}{35}{}%
+\contentsline {figure}{\numberline {23}{\ignorespaces Primjer smičnog ispitnog uzorka u kidalici}}{35}{}%
+\contentsline {figure}{\numberline {24}{\ignorespaces Primjer loma vlačnog ispitnog uzorka.}}{36}{}%
+\contentsline {figure}{\numberline {25}{\ignorespaces Primjer loma simčnog ispitnog uzorka.}}{36}{}%
+\contentsline {figure}{\numberline {26}{\ignorespaces Primjer loma smičnog ispitnog uzorka u napravi.}}{37}{}%
+\contentsline {figure}{\numberline {27}{\ignorespaces 2D prikaz ispune ispitnog uzorka u orijentaciji uspravnog ispisa.}}{38}{}%
+\contentsline {figure}{\numberline {28}{\ignorespaces 2D prikaz ispune ispitnog uzorka u orijentaciji ležećeg ispisa.}}{39}{}%
+\contentsline {figure}{\numberline {29}{\ignorespaces Promjena površine po X i Y osi za presjek na slici \ref {fig:vlak_2d_stojeci}. Izvor: autor.}}{40}{}%
+\contentsline {figure}{\numberline {30}{\ignorespaces Promjena površine po X i Y osi za presjek na slici \ref {fig:vlak_2d_lezeci}. Izvor: autor.}}{40}{}%
+\contentsline {figure}{\numberline {31}{\ignorespaces Udio varijabiliteta svakog faktora i greške.}}{46}{}%
+\contentsline {figure}{\numberline {32}{\ignorespaces Minimalna površina poprečnog presjeka uzorka $A_{\text {min}}$ u odnosu na maksimalnu silu $F_{\text {m}}$ za uzorke s orijentacijom 1.}}{46}{}%
+\contentsline {figure}{\numberline {33}{\ignorespaces Minimalna površina poprečnog presjeka uzorka $A_{\text {min}}$ u odnosu na maksimalnu silu $F_\text {m}$ za uzorke s orijentacijom 2.}}{47}{}%
+\contentsline {figure}{\numberline {34}{\ignorespaces Udio varijabiliteta svakog faktora i greške.}}{52}{}%
+\contentsline {figure}{\numberline {35}{\ignorespaces Korelacija minimalne površine poprečnog presjeka $A_{min}$ i maksimalne postignute sile $F_m$.}}{53}{}%