Abstract
To assure product quality, an early warning and inspection system to predict the variation (trend) of a product's quality (i.e. the product thickness) in the manufacturing process is necessary. Here, a manual online measurement of a production line installed with an online automatic warning system that will prevent manually accumulated errors from occurring is presented. Using this system, a quality trend profile will be made. The abnormal trend distribution will be obtained by randomly selecting the period of the quality trend profile and translating it into a time distribution bar chart. The monitoring online system will be pre-warned via the abnormal trend distribution. A product's thickness can be obtained using a linear variable differential transformer (LVDT). The analogue signal will be transmitted to the AD converter of the PLC's analogue input channel. The digital signal will be transmitted from the series port to the remote PC via the web control unit. A profile of the product's thickness measured by the LVDT will be monitored online and dynamically exhibited in the web-based remote system by using an embedded Javascript, an HTML, and a web control unit. The upper/lower thresholds will be preset in the product thickness' profile. In addition, the quality monitoring system will be pre-warned via the time distribution bar chart when the abnormal trend distribution occurs. Consequently, the web-base monitoring system can be extended to remotely connect to all the LVDT devices.
| Original language | English |
|---|---|
| Title of host publication | Materials, Mechatronics and Automation II |
| Pages | 120-127 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2013 Oct 4 |
| Event | 2013 International Conference on Materials, Mechatronics and Automation, ICMMA 2013 - , Singapore Duration: 2013 Apr 21 → 2013 Apr 22 |
Publication series
| Name | Advanced Materials Research |
|---|---|
| Volume | 740 |
| ISSN (Print) | 1022-6680 |
Other
| Other | 2013 International Conference on Materials, Mechatronics and Automation, ICMMA 2013 |
|---|---|
| Country | Singapore |
| Period | 13-04-21 → 13-04-22 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Engineering(all)
Cite this
}
A quality monitoring online system using an early warning abnormal trend distribution : A thickness measurement case study using a LVDT. / Chuo, Po Chou; Huang, Yi-Cheng; Chiu, Min Chie; Cheng, Ho Chih.
Materials, Mechatronics and Automation II. 2013. p. 120-127 (Advanced Materials Research; Vol. 740).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A quality monitoring online system using an early warning abnormal trend distribution
T2 - A thickness measurement case study using a LVDT
AU - Chuo, Po Chou
AU - Huang, Yi-Cheng
AU - Chiu, Min Chie
AU - Cheng, Ho Chih
PY - 2013/10/4
Y1 - 2013/10/4
N2 - To assure product quality, an early warning and inspection system to predict the variation (trend) of a product's quality (i.e. the product thickness) in the manufacturing process is necessary. Here, a manual online measurement of a production line installed with an online automatic warning system that will prevent manually accumulated errors from occurring is presented. Using this system, a quality trend profile will be made. The abnormal trend distribution will be obtained by randomly selecting the period of the quality trend profile and translating it into a time distribution bar chart. The monitoring online system will be pre-warned via the abnormal trend distribution. A product's thickness can be obtained using a linear variable differential transformer (LVDT). The analogue signal will be transmitted to the AD converter of the PLC's analogue input channel. The digital signal will be transmitted from the series port to the remote PC via the web control unit. A profile of the product's thickness measured by the LVDT will be monitored online and dynamically exhibited in the web-based remote system by using an embedded Javascript, an HTML, and a web control unit. The upper/lower thresholds will be preset in the product thickness' profile. In addition, the quality monitoring system will be pre-warned via the time distribution bar chart when the abnormal trend distribution occurs. Consequently, the web-base monitoring system can be extended to remotely connect to all the LVDT devices.
AB - To assure product quality, an early warning and inspection system to predict the variation (trend) of a product's quality (i.e. the product thickness) in the manufacturing process is necessary. Here, a manual online measurement of a production line installed with an online automatic warning system that will prevent manually accumulated errors from occurring is presented. Using this system, a quality trend profile will be made. The abnormal trend distribution will be obtained by randomly selecting the period of the quality trend profile and translating it into a time distribution bar chart. The monitoring online system will be pre-warned via the abnormal trend distribution. A product's thickness can be obtained using a linear variable differential transformer (LVDT). The analogue signal will be transmitted to the AD converter of the PLC's analogue input channel. The digital signal will be transmitted from the series port to the remote PC via the web control unit. A profile of the product's thickness measured by the LVDT will be monitored online and dynamically exhibited in the web-based remote system by using an embedded Javascript, an HTML, and a web control unit. The upper/lower thresholds will be preset in the product thickness' profile. In addition, the quality monitoring system will be pre-warned via the time distribution bar chart when the abnormal trend distribution occurs. Consequently, the web-base monitoring system can be extended to remotely connect to all the LVDT devices.
UR - http://www.scopus.com/inward/record.url?scp=84884735384&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84884735384&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMR.740.120
DO - 10.4028/www.scientific.net/AMR.740.120
M3 - Conference contribution
SN - 9783037857472
T3 - Advanced Materials Research
SP - 120
EP - 127
BT - Materials, Mechatronics and Automation II
ER -