Research Article
A Novel Method for Evaluating Dredging Productivity Using a Data Envelopment Analysis-Based Technique
Table 7
Daily dredging productivity by the proposed method.
| Work day | Input | Output | Daily dredging productivity | Hydraulic excavator (SL-330) | Hydraulic excavator (320B) | Daily trucks | Daily dredging (M3) | 1 input result | 3 input result |
| 1 | 2 | 7 | 79 | 1086 | 0.239 | 0.494 | 2 | 1 | 8 | 175 | 2936 | 0.543 | 0.603 | 3 | 1 | 8 | 385 | 6804 | 0.934 | 0.942 | 4 | 2 | 7 | 235 | 4147 | 0.698 | 0.762 | 5 | 2 | 7 | 178 | 3811 | 0.701 | 0.794 | 6 | 2 | 7 | 194 | 3763 | 0.675 | 0.756 | 7 | 2 | 7 | 353 | 6135 | 0.877 | 0.906 | 8 | 1 | 8 | 142 | 2087 | 0.408 | 0.529 | 9 | 1 | 8 | 194 | 4203 | 0.754 | 0.782 | 10 | 2 | 7 | 203 | 4565 | 0.807 | 0.898 | 11 | 2 | 7 | 292 | 4857 | 0.753 | 0.798 | 12 | 2 | 7 | 292 | 5280 | 0.818 | 0.868 | 13 | 2 | 7 | 193 | 3288 | 0.590 | 0.662 | 14 | 1 | 8 | 193 | 5367 | 0.964 | 1.000 | 15 | 1 | 8 | 296 | 5078 | 0.783 | 0.798 | 16 | 2 | 7 | 267 | 4569 | 0.733 | 0.787 | 17 | 2 | 7 | 275 | 4636 | 0.736 | 0.787 | 18 | 2 | 7 | 277 | 4650 | 0.736 | 0.786 | 19 | 2 | 7 | 302 | 5173 | 0.791 | 0.835 | 20 | 1 | 8 | 351 | 6055 | 0.867 | 0.878 | 21 | 2 | 7 | 427 | 7397 | 0.966 | 0.972 | 22 | 2 | 7 | 443 | 7741 | 0.992 | 0.994 | 23 | 2 | 7 | 409 | 7164 | 0.955 | 0.968 | 24 | 1 | 8 | 310 | 5431 | 0.821 | 0.836 | 25 | 2 | 7 | 333 | 5835 | 0.856 | 0.891 | 26 | 2 | 7 | 359 | 6290 | 0.892 | 0.920 | 27 | 2 | 7 | 443 | 7751 | 0.993 | 0.995 | 28 | 1 | 8 | 343 | 6007 | 0.869 | 0.881 | 29 | 1 | 8 | 403 | 7062 | 0.948 | 0.955 | 30 | 2 | 7 | 412 | 7210 | 0.958 | 0.969 | 31 | 2 | 7 | 423 | 7396 | 0.970 | 0.978 | 32 | 2 | 7 | 372 | 6510 | 0.908 | 0.932 | 33 | 2 | 7 | 421 | 7375 | 0.970 | 0.978 | 34 | 1 | 8 | 423 | 7410 | 0.972 | 0.976 | 35 | 2 | 7 | 422 | 7384 | 0.970 | 0.978 | 36 | 2 | 7 | 435 | 7620 | 0.986 | 0.99 | 37 | 2 | 7 | 437 | 7627 | 0.984 | 0.988 | 38 | 1 | 8 | 449 | 7841 | 0.998 | 1.000 | 39 | 2 | 7 | 449 | 7847 | 0.999 | 0.999 | 40 | 2 | 7 | 450 | 7866 | 1.000 | 1.000 | 41 | 2 | 7 | 434 | 7592 | 0.983 | 0.988 | 42 | 2 | 7 | 436 | 7625 | 0.985 | 0.989 | 43 | 1 | 8 | 426 | 7452 | 0.974 | 0.978 | 44 | 2 | 7 | 431 | 7540 | 0.980 | 0.985 | 45 | 2 | 7 | 440 | 7708 | 0.991 | 0.994 | 46 | 2 | 7 | 437 | 7643 | 0.986 | 0.990 | 47 | 1 | 8 | 383 | 6703 | 0.922 | 0.931 | 48 | 1 | 8 | 433 | 7580 | 0.983 | 0.986 | 49 | 1 | 8 | 436 | 7634 | 0.986 | 0.989 | 50 | 2 | 7 | 443 | 7754 | 0.994 | 0.996 | 51 | 2 | 7 | 435 | 7616 | 0.985 | 0.989 | 52 | 1 | 8 | 437 | 7643 | 0.986 | 0.989 | 53 | 2 | 7 | 433 | 7577 | 0.982 | 0.987 | 54 | 2 | 7 | 431 | 6754 | 0.878 | 0.883 | 55 | 2 | 7 | 443 | 7746 | 0.993 | 0.995 | 56 | 2 | 7 | 447 | 7752 | 0.989 | 0.990 | 57 | 1 | 8 | 10 | 400 | 0.102 | 0.360 | 58 | 1 | 8 | 10 | 400 | 0.102 | 0.360 | 59 | 2 | 7 | 303 | 5298 | 0.809 | 0.853 | 60 | 2 | 7 | 129 | 2266 | 0.453 | 0.632 | 61 | 2 | 7 | 40 | 686 | 0.163 | 0.617 | 62 | 2 | 7 | 252 | 5177 | 0.849 | 0.919 | 63 | 1 | 8 | 380 | 6651 | 0.919 | 0.927 | 64 | 1 | 8 | 355 | 6212 | 0.885 | 0.896 | 65 | 2 | 7 | 303 | 5298 | 0.809 | 0.853 | 66 | 2 | 7 | 129 | 2266 | 0.453 | 0.632 |
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