The Estimation of Product Standard Time by Artificial Neural Networks in the Molding Industry

Table 1

The premeasured train and the test values of the ANNs.

Volume	Weight	Process number	Cylinder hole number	Arrival status	Standard time
310000	118	14	4	good	1094.0
265000	110	14	3	good	896.0
…	…	…	…	…	…
…	…	…	…	…	…
…	…	…	…	…	…
115000	34	6	0	good	369.7
120000	37	6	0	good	389.7^*
112000	33	6	0	good	379.3^*
98000	41	6	0	good	378.0^*
13500	25	7	0	good	365.0^*
14000	23	7	0	good	377.3^*
14000	23	7	0	good	374.0^*
13500	30	7	0	bad	380.3^*
12000	28	7	0	good	368.0^*
17000	34	7	0	good	354.0^*
11000	18	8	0	moderate	430.0^*
18000	22	6	0	moderate	354.0
…	…	…	…	…	…
…	…	…	…	…	…
…	…	…	…	…	…
16500	8	5	0	good	245.0
480	8	3	0	bad	83.0
3200	9	5	0	good	293.0
4000	14	7	0	moderate	418.0
4000	18	7	0	moderate	425.0

^∗Randomly selected 10 standard times are used as test values.