Fig. 1.
ESP32 MQTT Client Connection
Fig. 2.
Online monitoring device deployment on the circular knitting machine Where: (1) The proximity sensor, (2) The yarn feeder sensor, and (3) IoT components
Fig. 3.
MQTT Broker interaction with the machine
Table 1.
Statistical data of measured parameters and the production rate
| n1(rpm) | n2(rpm) | L(mm) | P(kg/h) | |
|---|---|---|---|---|
| Mean | 18.00 | 1174.63 | 2.11 | 6.26 |
| Std | 2.82 | 182.78 | 0.05 | 0.97 |
| Min | 1.00 | 21.00 | 0.68 | 0.11 |
| 25% | 19.00 | 1237.00 | 2.10 | 6.59 |
| 50% | 19.00 | 1238.00 | 2.10 | 6.59 |
| 75% | 19.00 | 1238.00 | 2.13 | 6.59 |
| Max | 21.00 | 1362.00 | 2.68 | 7.26 |
Fig. 4.
Pearson’s correlation matrix
Table 2.
Statistical measure of degrees of multicollinearity
| Independent Parameter | n1&n2 | L&n1 | L&n2 |
|---|---|---|---|
| Ri2 | 0.980 | 0.005 | 0.000 |
| Tolerance | 0.020 | 0.995 | 1.000 |
| VIF | 50.251 | 1.005 | 1.000 |
Fig. 5.
Relation between the production rate and measured parameters
Fig. 6.
Regression hyper-plane for first prediction model
Fig. 7.
Regression hyper-plane for second prediction model