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Computing shadow prices with multiple Lagrange multipliers
A two-stage solution approach for plastic injection machines scheduling problem
1. | Eskisehir Osmangazi University, Department of Industrial Engineering, Meselik Campus, 26040, Eskisehir, Turkey |
2. | Eskisehir Technical University, Department of Industrial Engineering, Iki Eylul Campus, 26555, Eskisehir, Turkey |
One of the most common plastic manufacturing methods is injection molding. In injection molding process, scheduling of plastic injection machines is very difficult because of the complex nature of the problem. For example, similar plastic parts should be produced sequentially to prevent long setup times. On the other hand, to produce a plastic part, its mold should be fixed on an injection machine. Machine eligibility restrictions should be considered because a mold can be usually fixed on a subset of the injection machines. Some plastic parts which have same shapes but different colors are used same mold so these parts can only be scheduled simultaneously if their mold has copies, otherwise resource constraints should be considered. In this study, a multi-objective mathematical model is proposed for parallel machine scheduling problem to minimize makespan, total tardiness, and total waiting time. Since NP-hard nature of problem, this paper presents a two-stage mathematical model and a two-stage solution approach. In the first stage of mathematical model, jobs are assigned to the machines and each machine is scheduled separately in the second stage. The integrated model and two-stage mathematical model are scalarized by using goal programming, compromise programming and Lexicographic Weighted Tchebycheff programming methods. To solve large-scale problems in a short time, a two-stage solution approach is also proposed. In the first stage of this approach, jobs are assigned to machines and scheduled by using proposed simulated annealing algorithm. In the second stage of the approach, starting time, completion time and waiting time of the jobs are calculated by using a mathematical model. The performance of the methods is demonstrated on randomly generated test problems.
References:
[1] |
M. Afzalirad and M. Shafipour,
Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions, Journal Of Intelligent Manufacturing, 29 (2018), 423-437.
doi: 10.1007/s10845-015-1117-6. |
[2] |
E. Akyol Ozer and T. Sarac,
MIP models and a matheuristic algorithm for an identical parallel machine scheduling problem under multiple copies of shared resources constraints, TOP, 27 (2019), 94-124.
doi: 10.1007/s11750-018-00494-x. |
[3] |
O. Alagoz and M. Azizoglu,
Rescheduling of identical parallel machines under machine eligibility constraints, European Journal of Operational Research, 149 (2003), 523-532.
doi: 10.1016/S0377-2217(02)00499-X. |
[4] |
A. Baykasoglu and F. Ozsoydan,
Dynamic scheduling of parallel heat treatment furnaces: A case study at a manufacturing system, Journal of Manufacturing Systems, 46 (2018), 152-162.
doi: 10.1016/j.jmsy.2017.12.005. |
[5] |
G. Bektur and T. Sarac,
A Mathematical Model and Heuristic Algorithms for an Unrelated Parallel Machine Scheduling Problem with Sequence-Dependent Setup Times, Machine Eligibility Restrictions and a Common Server, Computers & Operations Research, 103 (2019), 46-63.
doi: 10.1016/j.cor.2018.10.010. |
[6] |
I. A. Chaudhry and P. R. Drake,
Minimizing total tardiness for the machine scheduling and worker assignment problems in identical parallel machines using genetic algorithms, International Journal of Advanced Manufacturing Technology, 42 (2009), 581-594.
doi: 10.1007/s00170-008-1617-z. |
[7] |
S. G. Dastidar and R. Nagi,
Scheduling injection molding operations with multiple resource constraints and sequence dependent setup times and costs, Computers & Operations Research, 32 (2005), 2987-3005.
doi: 10.1016/j.cor.2004.04.012. |
[8] |
R. Driessel and L. Moench, Scheduling jobs on parallel machines with sequence dependent setup times precedence constraints and ready times using variable neighborhood search, International Conference on Computers and Industrial Engineering, (2009), 273–278.
doi: 10.1109/ICCIE.2009.5223515. |
[9] |
E. B. Edis and C. Oguz,
Parallel machine scheduling with flexible resources, Computers & Industrial Engineering, 63 (2012), 433-447.
doi: 10.1016/j.cie.2012.03.018. |
[10] |
E.B. Edis and I. Ozkarahan,
A combined integer/constraint programming approach to a resource constrained parallel machine scheduling problem with machine eligibility restrictions, Engineering Optimization, 43 (2011), 135-157.
doi: 10.1080/03052151003759117. |
[11] |
E. B. Edis and I. Ozkarahan,
Solution approaches for a real-life resource-constrained parallel machine scheduling problem, International Journal of Advanced Manufacturing Technology, 58 (2012), 1141-1153.
doi: 10.1007/s00170-011-3454-8. |
[12] |
A. Ezugwu and F. Akutsah,
An Improved Firefly Algorithm for the Unrelated Parallel Machines Scheduling Problem With Sequence-Dependent Setup Times, IEEE ACCESS, 6 (2018), 54459-54478.
doi: 10.1109/ACCESS.2018.2872110. |
[13] |
B. Gacias, C. Artigues and P. Lopez,
Parallel machine scheduling with precedence constraints and setup times, Computers & Operations Research, 37 (2010), 2141-2151.
doi: 10.1016/j.cor.2010.03.003. |
[14] |
R. Gokhale and M. Mathirajan, Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flow time in automobile gear manufacturing, International Journal of Advanced Manufacturing Technology, 60 (2012), 1099-1110. Google Scholar |
[15] |
T. Keskinturk, M. B. Yildirim and M. Barut,
An ant colony optimization algorithm for load balancing in parallel machines with sequence-dependent setup times, Computers & Operations Research, 39 (2012), 1225-1235.
doi: 10.1016/j.cor.2010.12.003. |
[16] |
K. Li, Y. Shia, S. Yanga and B. Cheng,
Parallel machine scheduling problem to minimize the makespan with resource dependent processing times, Applied Soft Computing, 11 (2011), 5551-5557.
doi: 10.1016/j.asoc.2011.05.005. |
[17] |
X. Li, H. Chehade, F. Yalaoui and L. Amodeo, Fuzzy logic controller based multi-objective meta-heuristics to solve parallel machines scheduling problem, Journal of Multiple-Valued Logic and Soft Computing, 18 (2012), 617-636. Google Scholar |
[18] |
S. W. Lin, Z. J. Lee, K. C. Ying and C. C. Lu,
Minimization of maximum lateness on parallel machines with sequence-dependent setup times and job release dates, Computers & Operations Research, 38 (2011), 809-815.
doi: 10.1016/j.cor.2010.09.020. |
[19] |
M. Liu and C. Wu,
Scheduling algorithm based on evolutionary computing in identical parallel machine production line, Robotics and Computer Integrated Manufacturing, 19 (2003), 401-407.
doi: 10.1016/S0736-5845(03)00041-3. |
[20] |
T. Park, T. Lee and C. O. Kim,
Due-date scheduling on parallel machines with job splitting and sequence-dependent major/minor setup times, International Journal of Advanced Manufacturing Technology, 59 (2012), 325-333.
doi: 10.1007/s00170-011-3489-x. |
[21] |
R. Ruiz and C. A. Romano,
Scheduling unrelated parallel machines with resource-assignable sequence-dependent setup times, International Journal of Advanced Manufacturing Technology, 57 (2011), 777-794.
doi: 10.1007/s00170-011-3318-2. |
[22] |
T. Sarac and A. Sipahioglu, Plastik enjeksiyon makinalarinin Çizelgelenmesi problemi, Journal of Industrial Engineering, 20 (2009), 2-14. Google Scholar |
[23] |
L. Su, W. Y. Chang and F. D. Chou, Minimizing maximum lateness on identical parallel machines with flexible resources and machine eligibility constraints, International Journal of Advanced Manufacturing Technology, 56 (2011), 1195.
doi: 10.1007/s00170-011-3236-3. |
[24] |
I. T. Tanev, T. Uozumi and Y. Morotome,
Hybrid evolutionary algorithm-based real-world flexible job shop scheduling problem: Application service provider approach, Applied Soft Computing, 5 (2004), 87-100.
doi: 10.1016/j.asoc.2004.03.013. |
[25] |
A. K. Turker and C. Sel, A Hybrid approach on single server parallel machines scheduling problem with sequence dependent setup times, Journal of the Faculty of Engineering and Architecture of Gazi University, 26 (2011), 731-740. Google Scholar |
[26] |
Y. Unlu and S. J. Mason,
Evaluation of mixed integer programming formulations for non-preemptive parallel machine scheduling problems, Computers & Industrial Engineering, 58 (2010), 785-800.
doi: 10.1016/j.cie.2010.02.012. |
show all references
References:
[1] |
M. Afzalirad and M. Shafipour,
Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions, Journal Of Intelligent Manufacturing, 29 (2018), 423-437.
doi: 10.1007/s10845-015-1117-6. |
[2] |
E. Akyol Ozer and T. Sarac,
MIP models and a matheuristic algorithm for an identical parallel machine scheduling problem under multiple copies of shared resources constraints, TOP, 27 (2019), 94-124.
doi: 10.1007/s11750-018-00494-x. |
[3] |
O. Alagoz and M. Azizoglu,
Rescheduling of identical parallel machines under machine eligibility constraints, European Journal of Operational Research, 149 (2003), 523-532.
doi: 10.1016/S0377-2217(02)00499-X. |
[4] |
A. Baykasoglu and F. Ozsoydan,
Dynamic scheduling of parallel heat treatment furnaces: A case study at a manufacturing system, Journal of Manufacturing Systems, 46 (2018), 152-162.
doi: 10.1016/j.jmsy.2017.12.005. |
[5] |
G. Bektur and T. Sarac,
A Mathematical Model and Heuristic Algorithms for an Unrelated Parallel Machine Scheduling Problem with Sequence-Dependent Setup Times, Machine Eligibility Restrictions and a Common Server, Computers & Operations Research, 103 (2019), 46-63.
doi: 10.1016/j.cor.2018.10.010. |
[6] |
I. A. Chaudhry and P. R. Drake,
Minimizing total tardiness for the machine scheduling and worker assignment problems in identical parallel machines using genetic algorithms, International Journal of Advanced Manufacturing Technology, 42 (2009), 581-594.
doi: 10.1007/s00170-008-1617-z. |
[7] |
S. G. Dastidar and R. Nagi,
Scheduling injection molding operations with multiple resource constraints and sequence dependent setup times and costs, Computers & Operations Research, 32 (2005), 2987-3005.
doi: 10.1016/j.cor.2004.04.012. |
[8] |
R. Driessel and L. Moench, Scheduling jobs on parallel machines with sequence dependent setup times precedence constraints and ready times using variable neighborhood search, International Conference on Computers and Industrial Engineering, (2009), 273–278.
doi: 10.1109/ICCIE.2009.5223515. |
[9] |
E. B. Edis and C. Oguz,
Parallel machine scheduling with flexible resources, Computers & Industrial Engineering, 63 (2012), 433-447.
doi: 10.1016/j.cie.2012.03.018. |
[10] |
E.B. Edis and I. Ozkarahan,
A combined integer/constraint programming approach to a resource constrained parallel machine scheduling problem with machine eligibility restrictions, Engineering Optimization, 43 (2011), 135-157.
doi: 10.1080/03052151003759117. |
[11] |
E. B. Edis and I. Ozkarahan,
Solution approaches for a real-life resource-constrained parallel machine scheduling problem, International Journal of Advanced Manufacturing Technology, 58 (2012), 1141-1153.
doi: 10.1007/s00170-011-3454-8. |
[12] |
A. Ezugwu and F. Akutsah,
An Improved Firefly Algorithm for the Unrelated Parallel Machines Scheduling Problem With Sequence-Dependent Setup Times, IEEE ACCESS, 6 (2018), 54459-54478.
doi: 10.1109/ACCESS.2018.2872110. |
[13] |
B. Gacias, C. Artigues and P. Lopez,
Parallel machine scheduling with precedence constraints and setup times, Computers & Operations Research, 37 (2010), 2141-2151.
doi: 10.1016/j.cor.2010.03.003. |
[14] |
R. Gokhale and M. Mathirajan, Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flow time in automobile gear manufacturing, International Journal of Advanced Manufacturing Technology, 60 (2012), 1099-1110. Google Scholar |
[15] |
T. Keskinturk, M. B. Yildirim and M. Barut,
An ant colony optimization algorithm for load balancing in parallel machines with sequence-dependent setup times, Computers & Operations Research, 39 (2012), 1225-1235.
doi: 10.1016/j.cor.2010.12.003. |
[16] |
K. Li, Y. Shia, S. Yanga and B. Cheng,
Parallel machine scheduling problem to minimize the makespan with resource dependent processing times, Applied Soft Computing, 11 (2011), 5551-5557.
doi: 10.1016/j.asoc.2011.05.005. |
[17] |
X. Li, H. Chehade, F. Yalaoui and L. Amodeo, Fuzzy logic controller based multi-objective meta-heuristics to solve parallel machines scheduling problem, Journal of Multiple-Valued Logic and Soft Computing, 18 (2012), 617-636. Google Scholar |
[18] |
S. W. Lin, Z. J. Lee, K. C. Ying and C. C. Lu,
Minimization of maximum lateness on parallel machines with sequence-dependent setup times and job release dates, Computers & Operations Research, 38 (2011), 809-815.
doi: 10.1016/j.cor.2010.09.020. |
[19] |
M. Liu and C. Wu,
Scheduling algorithm based on evolutionary computing in identical parallel machine production line, Robotics and Computer Integrated Manufacturing, 19 (2003), 401-407.
doi: 10.1016/S0736-5845(03)00041-3. |
[20] |
T. Park, T. Lee and C. O. Kim,
Due-date scheduling on parallel machines with job splitting and sequence-dependent major/minor setup times, International Journal of Advanced Manufacturing Technology, 59 (2012), 325-333.
doi: 10.1007/s00170-011-3489-x. |
[21] |
R. Ruiz and C. A. Romano,
Scheduling unrelated parallel machines with resource-assignable sequence-dependent setup times, International Journal of Advanced Manufacturing Technology, 57 (2011), 777-794.
doi: 10.1007/s00170-011-3318-2. |
[22] |
T. Sarac and A. Sipahioglu, Plastik enjeksiyon makinalarinin Çizelgelenmesi problemi, Journal of Industrial Engineering, 20 (2009), 2-14. Google Scholar |
[23] |
L. Su, W. Y. Chang and F. D. Chou, Minimizing maximum lateness on identical parallel machines with flexible resources and machine eligibility constraints, International Journal of Advanced Manufacturing Technology, 56 (2011), 1195.
doi: 10.1007/s00170-011-3236-3. |
[24] |
I. T. Tanev, T. Uozumi and Y. Morotome,
Hybrid evolutionary algorithm-based real-world flexible job shop scheduling problem: Application service provider approach, Applied Soft Computing, 5 (2004), 87-100.
doi: 10.1016/j.asoc.2004.03.013. |
[25] |
A. K. Turker and C. Sel, A Hybrid approach on single server parallel machines scheduling problem with sequence dependent setup times, Journal of the Faculty of Engineering and Architecture of Gazi University, 26 (2011), 731-740. Google Scholar |
[26] |
Y. Unlu and S. J. Mason,
Evaluation of mixed integer programming formulations for non-preemptive parallel machine scheduling problems, Computers & Industrial Engineering, 58 (2010), 785-800.
doi: 10.1016/j.cie.2010.02.012. |


Ref. | Solution Methods | |||
[24] | Resource | Number of Tardy Jobs | Hybrid evolutionary algorithm | |
[8] | Variable neighborhood search | |||
[7] | Resource, |
Inventory holding, backlogging and setup time | Work center based decomposition approach | |
[15] | Average relative percentage of imbalance | GA and ant colony optimization | ||
[16] | 0-1 MIP model and GA with a fuzzy logic controller | |||
[18] | Maximum tardiness( |
Greedy Algorithm | ||
[25] | A hybrid GA and tabu search approach | |||
[3] | Optimizing Algorithm | |||
[23] | A network flow mathematical programming model and a heuristic approach | |||
[17] | Simulated annealing algorithm | |||
[11] | Resource, |
Integer programming and constraint programming model | ||
[21] | Resource |
Mixed integer programming model | ||
[11] | Resource, |
Integer programming, constraint programming model | ||
[10] | Resource, |
A Combined Integer/Constraint Programming Approach | ||
[9] | Resource | Integer programming, constraint programming model | ||
[1] | An integer programming model, GA | |||
[12] | Firefly algorithm | |||
[4] | Energy consumption and annual income | A multi-start and constructive search algorithm | ||
[2] | Resource, |
MIP models and a matheuristic algorithm |
Ref. | Solution Methods | |||
[24] | Resource | Number of Tardy Jobs | Hybrid evolutionary algorithm | |
[8] | Variable neighborhood search | |||
[7] | Resource, |
Inventory holding, backlogging and setup time | Work center based decomposition approach | |
[15] | Average relative percentage of imbalance | GA and ant colony optimization | ||
[16] | 0-1 MIP model and GA with a fuzzy logic controller | |||
[18] | Maximum tardiness( |
Greedy Algorithm | ||
[25] | A hybrid GA and tabu search approach | |||
[3] | Optimizing Algorithm | |||
[23] | A network flow mathematical programming model and a heuristic approach | |||
[17] | Simulated annealing algorithm | |||
[11] | Resource, |
Integer programming and constraint programming model | ||
[21] | Resource |
Mixed integer programming model | ||
[11] | Resource, |
Integer programming, constraint programming model | ||
[10] | Resource, |
A Combined Integer/Constraint Programming Approach | ||
[9] | Resource | Integer programming, constraint programming model | ||
[1] | An integer programming model, GA | |||
[12] | Firefly algorithm | |||
[4] | Energy consumption and annual income | A multi-start and constructive search algorithm | ||
[2] | Resource, |
MIP models and a matheuristic algorithm |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-WGP | 384 | 273 | 326 | 394 | 346 | 335 | 318 | 280 | |
299 | 99 | 296 | 564 | 116 | 295 | 232 | 102 | ||
4 | 7 | 3 | 0 | 0 | 0 | 0 | 0 | ||
0.1 | 0.07 | 0.09 | 0.24 | 0.07 | 0.08 | 0.11 | 0.05 | ||
196 | 181 | 299 | 880 | 153 | 175 | 82 | 95 | ||
M0-CP | 384 | 273 | 343 | 388 | 326 | 383 | 328 | 280 | |
299 | 99 | 281 | 506 | 157 | 258 | 222 | 102 | ||
4 | 7 | 3 | 87 | 14 | 0 | 16 | 0 | ||
0.1 | 0.07 | 0.09 | 0.29 | 0.09 | 0.08 | 0.15 | 0.05 | ||
322 | 73 | 212 | 522 | 111 | 183 | 85 | 74 | ||
M0-LWT | 384 | 273 | 343 | 388 | 326 | 383 | 328 | 280 | |
299 | 99 | 281 | 506 | 157 | 258 | 222 | 102 | ||
4 | 7 | 3 | 87 | 14 | 0 | 16 | 0 | ||
0.1 | 0.07 | 0.09 | 0.29 | 0.09 | 0.08 | 0.15 | 0.05 | ||
343 | 97 | 323 | 996 | 186 | 194 | 284 | 119 | ||
M1-M2-WGP | 423 | 313 | 345 | 433 | 331 | 335 | 310 | 266 | |
465 | 130 | 333 | 796 | 291 | 295 | 485 | 141 | ||
0 | 0 | 0 | 114 | 0 | 0 | 0 | 0 | ||
0.14 | 0.09 | 0.10 | 0.42 | 0.11 | 0.08 | 0.19 | 0.05 | ||
1 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | ||
M1-M2-CP | 450 | 320 | 345 | 393 | 380 | 335 | 350 | 351 | |
636 | 144 | 333 | 701 | 237 | 295 | 479 | 208 | ||
0 | 7 | 0 | 167 | 0 | 0 | 0 | 13 | ||
0.19 | 0.1 | 0.1 | 0.42 | 0.11 | 0.08 | 0.19 | 0.1 | ||
2 | 1 | 0 | 2 | 1 | 1 | 1 | 1 | ||
M1-M2-LWT | 450 | 320 | 345 | 393 | 390 | 335 | 350 | 351 | |
636 | 144 | 333 | 701 | 237 | 295 | 479 | 208 | ||
0 | 7 | 0 | 167 | 10 | 0 | 0 | 13 | ||
0.19 | 0.1 | 0.1 | 0.42 | 0.12 | 0.08 | 0.19 | 0.1 | ||
8 | 3 | 6 | 14 | 4 | 3 | 5 | 3 | ||
SA-M3 | 473 | 320 | 411 | 366 | 402 | 383 | 328 | 295 | |
456 | 82 | 349 | 717 | 335 | 258 | 222 | 99 | ||
90 | 16 | 37 | 112 | 127 | 0 | 16 | 0 | ||
0.19 | 0.08 | 0.13 | 0.37 | 0.25 | 0.08 | 0.15 | 0.05 | ||
13 | 12 | 13 | 13 | 12 | 12 | 12 | 13 |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-WGP | 384 | 273 | 326 | 394 | 346 | 335 | 318 | 280 | |
299 | 99 | 296 | 564 | 116 | 295 | 232 | 102 | ||
4 | 7 | 3 | 0 | 0 | 0 | 0 | 0 | ||
0.1 | 0.07 | 0.09 | 0.24 | 0.07 | 0.08 | 0.11 | 0.05 | ||
196 | 181 | 299 | 880 | 153 | 175 | 82 | 95 | ||
M0-CP | 384 | 273 | 343 | 388 | 326 | 383 | 328 | 280 | |
299 | 99 | 281 | 506 | 157 | 258 | 222 | 102 | ||
4 | 7 | 3 | 87 | 14 | 0 | 16 | 0 | ||
0.1 | 0.07 | 0.09 | 0.29 | 0.09 | 0.08 | 0.15 | 0.05 | ||
322 | 73 | 212 | 522 | 111 | 183 | 85 | 74 | ||
M0-LWT | 384 | 273 | 343 | 388 | 326 | 383 | 328 | 280 | |
299 | 99 | 281 | 506 | 157 | 258 | 222 | 102 | ||
4 | 7 | 3 | 87 | 14 | 0 | 16 | 0 | ||
0.1 | 0.07 | 0.09 | 0.29 | 0.09 | 0.08 | 0.15 | 0.05 | ||
343 | 97 | 323 | 996 | 186 | 194 | 284 | 119 | ||
M1-M2-WGP | 423 | 313 | 345 | 433 | 331 | 335 | 310 | 266 | |
465 | 130 | 333 | 796 | 291 | 295 | 485 | 141 | ||
0 | 0 | 0 | 114 | 0 | 0 | 0 | 0 | ||
0.14 | 0.09 | 0.10 | 0.42 | 0.11 | 0.08 | 0.19 | 0.05 | ||
1 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | ||
M1-M2-CP | 450 | 320 | 345 | 393 | 380 | 335 | 350 | 351 | |
636 | 144 | 333 | 701 | 237 | 295 | 479 | 208 | ||
0 | 7 | 0 | 167 | 0 | 0 | 0 | 13 | ||
0.19 | 0.1 | 0.1 | 0.42 | 0.11 | 0.08 | 0.19 | 0.1 | ||
2 | 1 | 0 | 2 | 1 | 1 | 1 | 1 | ||
M1-M2-LWT | 450 | 320 | 345 | 393 | 390 | 335 | 350 | 351 | |
636 | 144 | 333 | 701 | 237 | 295 | 479 | 208 | ||
0 | 7 | 0 | 167 | 10 | 0 | 0 | 13 | ||
0.19 | 0.1 | 0.1 | 0.42 | 0.12 | 0.08 | 0.19 | 0.1 | ||
8 | 3 | 6 | 14 | 4 | 3 | 5 | 3 | ||
SA-M3 | 473 | 320 | 411 | 366 | 402 | 383 | 328 | 295 | |
456 | 82 | 349 | 717 | 335 | 258 | 222 | 99 | ||
90 | 16 | 37 | 112 | 127 | 0 | 16 | 0 | ||
0.19 | 0.08 | 0.13 | 0.37 | 0.25 | 0.08 | 0.15 | 0.05 | ||
13 | 12 | 13 | 13 | 12 | 12 | 12 | 13 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | 296 | 331 | 391 | 239 | 154 | 283 | 183 | 262 | |
311 | 325 | 393 | 135 | 191 | 331 | 124 | 117 | ||
2 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | ||
0.08 | 0.13 | 0.14 | 0.06 | 0.06 | 0.08 | 0.07 | 0.04 | ||
618 | 2211 | 1774 | 337 | 415 | 497 | 439 | 246 | ||
M0-CP | 296 | 331 | 370 | 198 | 154 | 283 | 143 | 262 | |
311 | 325 | 326 | 122 | 191 | 331 | 94 | 117 | ||
2 | 0 | 70 | 24 | 0 | 0 | 17 | 0 | ||
0.08 | 0.13 | 0.15 | 0.06 | 0.06 | 0.08 | 0.08 | 0.04 | ||
691 | 1227 | 1414 | 401 | 403 | 539 | 252 | 169 | ||
M0-LWT | 296 | 331 | 370 | 198 | 154 | 283 | 143 | 262 | |
311 | 325 | 326 | 122 | 191 | 331 | 94 | 117 | ||
2 | 0 | 70 | 24 | 0 | 0 | 17 | 0 | ||
0.08 | 0.13 | 0.15 | 0.06 | 0.06 | 0.08 | 0.08 | 0.04 | ||
1045 | 1231 | 1980 | 354 | 402 | 876 | 298 | 108 | ||
M1-M2-WGP | 341 | 492 | 409 | 286 | 223 | 282 | 243 | 295 | |
495 | 870 | 428 | 344 | 431 | 500 | 295 | 342 | ||
14 | 327 | 155 | 8 | 0 | 0 | 0 | 0 | ||
0.12 | 0.58 | 0.23 | 0.13 | 0.14 | 0.12 | 0.15 | 0.09 | ||
1 | 2 | 0 | 1 | 1 | 1 | 1 | 1 | ||
M1-M2-CP | 334 | 411 | 470 | 297 | 230 | 345 | 189 | 530 | |
488 | 791 | 567 | 263 | 430 | 600 | 273 | 1073 | ||
7 | 274 | 305 | 89 | 0 | 7 | 21 | 0 | ||
0.11 | 0.5 | 0.34 | 0.16 | 0.14 | 0.15 | 0.16 | 0.26 | ||
1 | 1 | 1 | 1 | 0 | 0 | 0 | 24 | ||
M1-M2-LWT | 341 | 411 | 470 | 297 | 230 | 338 | 189 | 295 | |
495 | 791 | 567 | 263 | 430 | 600 | 273 | 344 | ||
14 | 274 | 305 | 89 | 0 | 0 | 21 | 0 | ||
0.12 | 0.5 | 0.34 | 0.16 | 0.14 | 0.15 | 0.16 | 0.09 | ||
2 | 6 | 3 | 3 | 2 | 2 | 2 | 1 | ||
SA-M3 | 369 | 416 | 469 | 253 | 185 | 336 | 143 | 309 | |
317 | 571 | 639 | 128 | 186 | 407 | 94 | 116 | ||
50 | 282 | 304 | 80 | 44 | 85 | 17 | 0 | ||
0.11 | 0.46 | 0.36 | 0.11 | 0.16 | 0.18 | 0.08 | 0.05 | ||
12 | 14 | 12 | 13 | 12 | 14 | 14 | 13 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | 296 | 331 | 391 | 239 | 154 | 283 | 183 | 262 | |
311 | 325 | 393 | 135 | 191 | 331 | 124 | 117 | ||
2 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | ||
0.08 | 0.13 | 0.14 | 0.06 | 0.06 | 0.08 | 0.07 | 0.04 | ||
618 | 2211 | 1774 | 337 | 415 | 497 | 439 | 246 | ||
M0-CP | 296 | 331 | 370 | 198 | 154 | 283 | 143 | 262 | |
311 | 325 | 326 | 122 | 191 | 331 | 94 | 117 | ||
2 | 0 | 70 | 24 | 0 | 0 | 17 | 0 | ||
0.08 | 0.13 | 0.15 | 0.06 | 0.06 | 0.08 | 0.08 | 0.04 | ||
691 | 1227 | 1414 | 401 | 403 | 539 | 252 | 169 | ||
M0-LWT | 296 | 331 | 370 | 198 | 154 | 283 | 143 | 262 | |
311 | 325 | 326 | 122 | 191 | 331 | 94 | 117 | ||
2 | 0 | 70 | 24 | 0 | 0 | 17 | 0 | ||
0.08 | 0.13 | 0.15 | 0.06 | 0.06 | 0.08 | 0.08 | 0.04 | ||
1045 | 1231 | 1980 | 354 | 402 | 876 | 298 | 108 | ||
M1-M2-WGP | 341 | 492 | 409 | 286 | 223 | 282 | 243 | 295 | |
495 | 870 | 428 | 344 | 431 | 500 | 295 | 342 | ||
14 | 327 | 155 | 8 | 0 | 0 | 0 | 0 | ||
0.12 | 0.58 | 0.23 | 0.13 | 0.14 | 0.12 | 0.15 | 0.09 | ||
1 | 2 | 0 | 1 | 1 | 1 | 1 | 1 | ||
M1-M2-CP | 334 | 411 | 470 | 297 | 230 | 345 | 189 | 530 | |
488 | 791 | 567 | 263 | 430 | 600 | 273 | 1073 | ||
7 | 274 | 305 | 89 | 0 | 7 | 21 | 0 | ||
0.11 | 0.5 | 0.34 | 0.16 | 0.14 | 0.15 | 0.16 | 0.26 | ||
1 | 1 | 1 | 1 | 0 | 0 | 0 | 24 | ||
M1-M2-LWT | 341 | 411 | 470 | 297 | 230 | 338 | 189 | 295 | |
495 | 791 | 567 | 263 | 430 | 600 | 273 | 344 | ||
14 | 274 | 305 | 89 | 0 | 0 | 21 | 0 | ||
0.12 | 0.5 | 0.34 | 0.16 | 0.14 | 0.15 | 0.16 | 0.09 | ||
2 | 6 | 3 | 3 | 2 | 2 | 2 | 1 | ||
SA-M3 | 369 | 416 | 469 | 253 | 185 | 336 | 143 | 309 | |
317 | 571 | 639 | 128 | 186 | 407 | 94 | 116 | ||
50 | 282 | 304 | 80 | 44 | 85 | 17 | 0 | ||
0.11 | 0.46 | 0.36 | 0.11 | 0.16 | 0.18 | 0.08 | 0.05 | ||
12 | 14 | 12 | 13 | 12 | 14 | 14 | 13 |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-GP | 2365 | 2135 | 1928 | 2115 | 1574 | 1805 | - | 1817 | |
22190 | 20719 | 15318 | 19944 | 4590 | 8989 | - | 10340 | ||
396 | 94 | 130 | 124 | 0 | 0 | - | 0 | ||
0.27 | 0.23 | 0.19 | 0.28 | 0.07 | 0.11 | - | 0.12 | ||
M0-CP | 2358 | 2274 | 1965 | 1625 | 1491 | 1772 | 1656 | 1821 | |
18290 | 17933 | 15682 | 14654 | 4761 | 5670 | 8345 | 9159 | ||
280 | 416 | 364 | 301 | 18 | 56 | 0 | 78 | ||
0.23 | 0.25 | 0.22 | 0.22 | 0.07 | 0.08 | 0.10 | 0.12 | ||
M0-LWT | 5776 | 8558 | 7284 | 2547 | 2764 | 5648 | 2013 | 4304 | |
21808 | 33944 | 26740 | 56966 | 7363 | 16720 | 19845 | 14963 | ||
577 | 1458 | 657 | 1070 | 91 | 240 | 0 | 420 | ||
0.43 | 0.74 | 0.56 | 0.80 | 0.16 | 0.37 | 0.22 | 0.33 | ||
M1-M2-WGP | 2077 | 2022 | 1779 | 1771 | 1447 | 1789 | 1474 | 1463 | |
21191 | 19565 | 17681 | 16175 | 4779 | 15204 | 5719 | 13613 | ||
76 | 178 | 4 | 198 | 0 | 0 | 0 | 12 | ||
0.22 | 0.23 | 0.19 | 0.23 | 0.06 | 0.16 | 0.07 | 0.14 | ||
M1-M2-CP | 1979 | 1992 | 1865 | 1546 | 1467 | 1635 | 1440 | 1663 | |
15322 | 20602 | 14408 | 13934 | 3348 | 6396 | 4255 | 7751 | ||
467 | 128 | 185 | 306 | 0 | 2 | 0 | 186 | ||
0.21 | 0.23 | 0.18 | 0.21 | 0.05 | 0.08 | 0.05 | 0.12 | ||
M1-M2-LWT | 5232 | 5076 | 6301 | 5395 | 2624 | 3838 | 3360 | 2862 | |
19227 | 18025 | 22470 | 18168 | 6768 | 11926 | 10643 | 8291 | ||
593 | 489 | 349 | 382 | 83 | 13 | 0 | 41 | ||
0.38 | 0.37 | 0.45 | 0.43 | 0.14 | 0.22 | 0.19 | 0.15 | ||
SA-M3 | 1819 | 1561 | 1623 | 1346 | 1473 | 1621 | 1399 | 1776 | |
8153 | 5314 | 3941 | 4380 | 2609 | 1347 | 2687 | 3086 | ||
479 | 82 | 137 | 290 | 0 | 0 | 0 | 357 | ||
0.14 | 0.07 | 0.07 | 0.1 | 0.04 | 0.03 | 0.04 | 0.08 | ||
36 | 32 | 38 | 40 | 30 | 31 | 36 | 36 |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-GP | 2365 | 2135 | 1928 | 2115 | 1574 | 1805 | - | 1817 | |
22190 | 20719 | 15318 | 19944 | 4590 | 8989 | - | 10340 | ||
396 | 94 | 130 | 124 | 0 | 0 | - | 0 | ||
0.27 | 0.23 | 0.19 | 0.28 | 0.07 | 0.11 | - | 0.12 | ||
M0-CP | 2358 | 2274 | 1965 | 1625 | 1491 | 1772 | 1656 | 1821 | |
18290 | 17933 | 15682 | 14654 | 4761 | 5670 | 8345 | 9159 | ||
280 | 416 | 364 | 301 | 18 | 56 | 0 | 78 | ||
0.23 | 0.25 | 0.22 | 0.22 | 0.07 | 0.08 | 0.10 | 0.12 | ||
M0-LWT | 5776 | 8558 | 7284 | 2547 | 2764 | 5648 | 2013 | 4304 | |
21808 | 33944 | 26740 | 56966 | 7363 | 16720 | 19845 | 14963 | ||
577 | 1458 | 657 | 1070 | 91 | 240 | 0 | 420 | ||
0.43 | 0.74 | 0.56 | 0.80 | 0.16 | 0.37 | 0.22 | 0.33 | ||
M1-M2-WGP | 2077 | 2022 | 1779 | 1771 | 1447 | 1789 | 1474 | 1463 | |
21191 | 19565 | 17681 | 16175 | 4779 | 15204 | 5719 | 13613 | ||
76 | 178 | 4 | 198 | 0 | 0 | 0 | 12 | ||
0.22 | 0.23 | 0.19 | 0.23 | 0.06 | 0.16 | 0.07 | 0.14 | ||
M1-M2-CP | 1979 | 1992 | 1865 | 1546 | 1467 | 1635 | 1440 | 1663 | |
15322 | 20602 | 14408 | 13934 | 3348 | 6396 | 4255 | 7751 | ||
467 | 128 | 185 | 306 | 0 | 2 | 0 | 186 | ||
0.21 | 0.23 | 0.18 | 0.21 | 0.05 | 0.08 | 0.05 | 0.12 | ||
M1-M2-LWT | 5232 | 5076 | 6301 | 5395 | 2624 | 3838 | 3360 | 2862 | |
19227 | 18025 | 22470 | 18168 | 6768 | 11926 | 10643 | 8291 | ||
593 | 489 | 349 | 382 | 83 | 13 | 0 | 41 | ||
0.38 | 0.37 | 0.45 | 0.43 | 0.14 | 0.22 | 0.19 | 0.15 | ||
SA-M3 | 1819 | 1561 | 1623 | 1346 | 1473 | 1621 | 1399 | 1776 | |
8153 | 5314 | 3941 | 4380 | 2609 | 1347 | 2687 | 3086 | ||
479 | 82 | 137 | 290 | 0 | 0 | 0 | 357 | ||
0.14 | 0.07 | 0.07 | 0.1 | 0.04 | 0.03 | 0.04 | 0.08 | ||
36 | 32 | 38 | 40 | 30 | 31 | 36 | 36 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | 1539 | 1896 | 1515 | - | 645 | 709 | - | 1336 | |
17499 | 25024 | 19640 | - | 3198 | 4627 | - | 14430 | ||
1092 | 1396 | 3426 | - | 0 | 3 | - | 1094 | ||
0.27 | 0.43 | 0.51 | - | 0.03 | 0.05 | - | 0.29 | ||
M0-CP | 1487 | 2179 | 1515 | 1798 | 756 | 784 | 815 | 1219 | |
18635 | 24170 | 19422 | 20895 | 3262 | 3674 | 6330 | 10974 | ||
1530 | 2531 | 3777 | 1862 | 66 | 7 | 94 | 869 | ||
0.31 | 0.55 | 0.54 | 0.43 | 0.04 | 0.05 | 0.08 | 0.23 | ||
M0-LWT | 4093 | 6059 | 10466 | 16743 | 1002 | 1947 | 1726 | 3677 | |
17052 | 23743 | 44256 | 70611 | 3124 | 7355 | 6522 | 14022 | ||
1434 | 1912 | 3808 | 5674 | 156 | 333 | 126 | 830 | ||
0.38 | 0.62 | 1.0 | 1.0 | 0.06 | 0.16 | 0.12 | 0.33 | ||
M1-M2-WGP | 1261 | 1608 | 1205 | 1136 | 598 | 578 | 528 | 633 | |
11303 | 15041 | 12840 | 10871 | 2202 | 4029 | 2336 | 3878 | ||
1350 | 2117 | 1138 | 1645 | 0 | 3 | 2 | 6 | ||
0.23 | 0.41 | 0.23 | 0.29 | 0.02 | 0.04 | 0.02 | 0.04 | ||
M1-M2-CP | 1278 | 1674 | 1217 | 1069 | 627 | 619 | 531 | 712 | |
11048 | 16595 | 12358 | 9831 | 2197 | 2454 | 1988 | 3554 | ||
1486 | 2512 | 1140 | 1795 | 92 | 50 | 5 | 190 | ||
0.25 | 0.47 | 0.23 | 0.3 | 0.04 | 0.04 | 0.02 | 0.06 | ||
M1-M2-LWT | 4806 | 8617 | 4168 | 5018 | 841 | 906 | 727 | 1253 | |
20346 | 34350 | 16584 | 20148 | 2316 | 2578 | 1798 | 3606 | ||
1711 | 2793 | 1427 | 1619 | 11 | 10 | 56 | 79 | ||
0.46 | 0.91 | 0.39 | 0.51 | 0.03 | 0.04 | 0.04 | 0.07 | ||
SA-M3 | 1249 | 1807 | 1047 | 977 | 876 | 651 | 639 | 738 | |
9711 | 14617 | 6886 | 5216 | 2845 | 1635 | 1121 | 1539 | ||
1941 | 2752 | 1318 | 1327 | 315 | 28 | 39 | 457 | ||
0.27 | 0.48 | 0.20 | 0.21 | 0.08 | 0.03 | 0.03 | 0.08 | ||
231 | 232 | 198 | 235 | 34 | 33 | 37 | 38 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | 1539 | 1896 | 1515 | - | 645 | 709 | - | 1336 | |
17499 | 25024 | 19640 | - | 3198 | 4627 | - | 14430 | ||
1092 | 1396 | 3426 | - | 0 | 3 | - | 1094 | ||
0.27 | 0.43 | 0.51 | - | 0.03 | 0.05 | - | 0.29 | ||
M0-CP | 1487 | 2179 | 1515 | 1798 | 756 | 784 | 815 | 1219 | |
18635 | 24170 | 19422 | 20895 | 3262 | 3674 | 6330 | 10974 | ||
1530 | 2531 | 3777 | 1862 | 66 | 7 | 94 | 869 | ||
0.31 | 0.55 | 0.54 | 0.43 | 0.04 | 0.05 | 0.08 | 0.23 | ||
M0-LWT | 4093 | 6059 | 10466 | 16743 | 1002 | 1947 | 1726 | 3677 | |
17052 | 23743 | 44256 | 70611 | 3124 | 7355 | 6522 | 14022 | ||
1434 | 1912 | 3808 | 5674 | 156 | 333 | 126 | 830 | ||
0.38 | 0.62 | 1.0 | 1.0 | 0.06 | 0.16 | 0.12 | 0.33 | ||
M1-M2-WGP | 1261 | 1608 | 1205 | 1136 | 598 | 578 | 528 | 633 | |
11303 | 15041 | 12840 | 10871 | 2202 | 4029 | 2336 | 3878 | ||
1350 | 2117 | 1138 | 1645 | 0 | 3 | 2 | 6 | ||
0.23 | 0.41 | 0.23 | 0.29 | 0.02 | 0.04 | 0.02 | 0.04 | ||
M1-M2-CP | 1278 | 1674 | 1217 | 1069 | 627 | 619 | 531 | 712 | |
11048 | 16595 | 12358 | 9831 | 2197 | 2454 | 1988 | 3554 | ||
1486 | 2512 | 1140 | 1795 | 92 | 50 | 5 | 190 | ||
0.25 | 0.47 | 0.23 | 0.3 | 0.04 | 0.04 | 0.02 | 0.06 | ||
M1-M2-LWT | 4806 | 8617 | 4168 | 5018 | 841 | 906 | 727 | 1253 | |
20346 | 34350 | 16584 | 20148 | 2316 | 2578 | 1798 | 3606 | ||
1711 | 2793 | 1427 | 1619 | 11 | 10 | 56 | 79 | ||
0.46 | 0.91 | 0.39 | 0.51 | 0.03 | 0.04 | 0.04 | 0.07 | ||
SA-M3 | 1249 | 1807 | 1047 | 977 | 876 | 651 | 639 | 738 | |
9711 | 14617 | 6886 | 5216 | 2845 | 1635 | 1121 | 1539 | ||
1941 | 2752 | 1318 | 1327 | 315 | 28 | 39 | 457 | ||
0.27 | 0.48 | 0.20 | 0.21 | 0.08 | 0.03 | 0.03 | 0.08 | ||
231 | 232 | 198 | 235 | 34 | 33 | 37 | 38 |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-WGP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-CP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-LWT | 5499 | 7943 | - | - | 5224 | 5683 | - | - | |
371810 | 394667 | - | - | 394518 | 388008 | - | - | ||
1399 | 5206 | - | - | 942 | 1450 | - | - | ||
0.71 | 0.89 | - | - | 0.72 | 0.76 | - | - | ||
M1-M2-WGP | 5737 | 8535 | 6578 | 6779 | 5073 | 5495 | 5340 | 5873 | |
133487 | 275567 | 218122 | 226738 | 114247 | 154587 | 1222567 | 151816 | ||
1928 | 6108 | 3476 | 3618 | 310 | 1371 | 64 | 1643 | ||
0.35 | 0.75 | 0.55 | 0.53 | 0.24 | 0.39 | 0.23 | 0.4 | ||
M1-M2-CP | - | - | - | - | 5196 | - | - | 6133 | |
- | - | - | - | 122797 | - | - | 148961 | ||
- | - | - | - | 847 | - | - | 1784 | ||
- | - | - | - | 0.29 | - | - | 0.41 | ||
M1-M2-LWT | 4975 | 7435 | 5715 | - | - | 5068 | 5098 | 6142 | |
371810 | 394667 | 381471 | - | - | 388008 | 405443 | 393012 | ||
797 | 3158 | 1725 | - | - | 999 | 336 | 1841 | ||
0.67 | 0.80 | 0.72 | - | - | 0.72 | 0.66 | 0.79 | ||
SA-M3 | 3536 | 4105 | 3452 | 3849 | 3124 | 3530 | 4285 | 4252 | |
18409 | 24746 | 26997 | 23597 | 15347 | 20652 | 9298 | 26957 | ||
192 | 158 | 241 | 86 | 0 | 173 | 0 | 108 | ||
0.05 | 0.07 | 0.07 | 0.06 | 0.04 | 0.06 | 0.04 | 0.07 | ||
66 | 70 | 72 | 82 | 64 | 65 | 74 | 68 |
Test No | 1-1 | 2-1 | 3-1 | 4-1 | 5-1 | 6-1 | 7-1 | 8-1 | |
M0-WGP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-CP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-LWT | 5499 | 7943 | - | - | 5224 | 5683 | - | - | |
371810 | 394667 | - | - | 394518 | 388008 | - | - | ||
1399 | 5206 | - | - | 942 | 1450 | - | - | ||
0.71 | 0.89 | - | - | 0.72 | 0.76 | - | - | ||
M1-M2-WGP | 5737 | 8535 | 6578 | 6779 | 5073 | 5495 | 5340 | 5873 | |
133487 | 275567 | 218122 | 226738 | 114247 | 154587 | 1222567 | 151816 | ||
1928 | 6108 | 3476 | 3618 | 310 | 1371 | 64 | 1643 | ||
0.35 | 0.75 | 0.55 | 0.53 | 0.24 | 0.39 | 0.23 | 0.4 | ||
M1-M2-CP | - | - | - | - | 5196 | - | - | 6133 | |
- | - | - | - | 122797 | - | - | 148961 | ||
- | - | - | - | 847 | - | - | 1784 | ||
- | - | - | - | 0.29 | - | - | 0.41 | ||
M1-M2-LWT | 4975 | 7435 | 5715 | - | - | 5068 | 5098 | 6142 | |
371810 | 394667 | 381471 | - | - | 388008 | 405443 | 393012 | ||
797 | 3158 | 1725 | - | - | 999 | 336 | 1841 | ||
0.67 | 0.80 | 0.72 | - | - | 0.72 | 0.66 | 0.79 | ||
SA-M3 | 3536 | 4105 | 3452 | 3849 | 3124 | 3530 | 4285 | 4252 | |
18409 | 24746 | 26997 | 23597 | 15347 | 20652 | 9298 | 26957 | ||
192 | 158 | 241 | 86 | 0 | 173 | 0 | 108 | ||
0.05 | 0.07 | 0.07 | 0.06 | 0.04 | 0.06 | 0.04 | 0.07 | ||
66 | 70 | 72 | 82 | 64 | 65 | 74 | 68 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-CP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-LWT | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M1-M2-WGP | 1865 | 4259 | 1637 | 4430 | 1048 | 578 | 1093 | 1744 | |
49222 | 144672 | 38766 | 156241 | 15984 | 4029 | 17236 | 399726 | ||
3562 | 17320 | 2274 | 22013 | 1 | 3 | 0 | 2472 | ||
0.24 | 0.95 | 0.15 | 1.0 | 0.03 | 0.04 | 0.03 | 0.25 | ||
M1-M2-CP | 1862 | 4431 | 2063 | 4710 | 1415 | 2107 | 1291 | 2050 | |
56691 | 158564 | 59000 | 186431 | 25063 | 41366 | 21170 | 42777 | ||
3674 | 19700 | 4637 | 22460 | 1388 | 1930 | 125 | 1954 | ||
0.25 | 1.0 | 0.27 | 1.0 | 0.12 | 0.20 | 0.04 | 0.22 | ||
M1-M2-LWT | 11668 | - | 13751 | - | 2141 | 16990 | 2203 | 14119 | |
123224 | - | 142194 | - | 15990 | 178534 | 17515 | 140421 | ||
3611 | - | 4665 | - | 0 | 3370 | 71 | 2534 | ||
0.48 | - | 0.54 | - | 0.04 | 0.66 | 0.05 | 0.57 | ||
SA-M3 | 1617 | 4096 | 1443 | 3695 | 1113 | 1746 | 1095 | 1350 | |
25013 | 109062 | 18602 | 93653 | 3156 | 11361 | 5052 | 9681 | ||
2138 | 15728 | 2054 | 13899 | 0 | 1535 | 88 | 878 | ||
0.14 | 0.84 | 0.11 | 0.70 | 0.01 | 0.13 | 0.02 | 0.09 | ||
90 | 276 | 275 | 267 | 72 | 173 | 69 | 277 |
Test No | 9-1 | 10-1 | 11-1 | 12-1 | 13-1 | 14-1 | 15-1 | 16-1 | |
M0-WGP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-CP | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M0-LWT | - | - | - | - | - | - | - | - | |
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
- | - | - | - | - | - | - | - | ||
M1-M2-WGP | 1865 | 4259 | 1637 | 4430 | 1048 | 578 | 1093 | 1744 | |
49222 | 144672 | 38766 | 156241 | 15984 | 4029 | 17236 | 399726 | ||
3562 | 17320 | 2274 | 22013 | 1 | 3 | 0 | 2472 | ||
0.24 | 0.95 | 0.15 | 1.0 | 0.03 | 0.04 | 0.03 | 0.25 | ||
M1-M2-CP | 1862 | 4431 | 2063 | 4710 | 1415 | 2107 | 1291 | 2050 | |
56691 | 158564 | 59000 | 186431 | 25063 | 41366 | 21170 | 42777 | ||
3674 | 19700 | 4637 | 22460 | 1388 | 1930 | 125 | 1954 | ||
0.25 | 1.0 | 0.27 | 1.0 | 0.12 | 0.20 | 0.04 | 0.22 | ||
M1-M2-LWT | 11668 | - | 13751 | - | 2141 | 16990 | 2203 | 14119 | |
123224 | - | 142194 | - | 15990 | 178534 | 17515 | 140421 | ||
3611 | - | 4665 | - | 0 | 3370 | 71 | 2534 | ||
0.48 | - | 0.54 | - | 0.04 | 0.66 | 0.05 | 0.57 | ||
SA-M3 | 1617 | 4096 | 1443 | 3695 | 1113 | 1746 | 1095 | 1350 | |
25013 | 109062 | 18602 | 93653 | 3156 | 11361 | 5052 | 9681 | ||
2138 | 15728 | 2054 | 13899 | 0 | 1535 | 88 | 878 | ||
0.14 | 0.84 | 0.11 | 0.70 | 0.01 | 0.13 | 0.02 | 0.09 | ||
90 | 276 | 275 | 267 | 72 | 173 | 69 | 277 |
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