TY - JOUR
T1 - Lens injection moulding condition diagnosis and form error analysis using cavity pressure signals based on response surface methodology
AU - Nam, Jung Soo
AU - Baek, Dae Seong
AU - Jo, Hyoung Han
AU - Song, Jun Yeob
AU - Ha, Tae Ho
AU - Lee, Sangwon
N1 - Publisher Copyright:
© IMechE 2015.
PY - 2016/7/1
Y1 - 2016/7/1
N2 - In this article,the condition diagnosis and form error prediction models for lens injection moulding process are developed based on a response surface method by using features extracted from in-process cavity pressure signals. In the lens injection moulding experiments,cavity pressure signals are captured by pressure sensors embedded in a lens mould,and form errors of manufactured lenses are measured afterwards. Then,three features such as filling point,maximum pressure and inflection point pressure are identified from the measured cavity pressure profile,and they are used to formulate the response surface functions for each injection moulding condition. In addition,the response surface functions for the lens form error with the input variables of the above-mentioned three features are also formulated. It is reported that the overall average accuracies for the lens injection moulding condition diagnosis and form error estimation are better than 97% and 80%,respectively,in the actual industrial site.
AB - In this article,the condition diagnosis and form error prediction models for lens injection moulding process are developed based on a response surface method by using features extracted from in-process cavity pressure signals. In the lens injection moulding experiments,cavity pressure signals are captured by pressure sensors embedded in a lens mould,and form errors of manufactured lenses are measured afterwards. Then,three features such as filling point,maximum pressure and inflection point pressure are identified from the measured cavity pressure profile,and they are used to formulate the response surface functions for each injection moulding condition. In addition,the response surface functions for the lens form error with the input variables of the above-mentioned three features are also formulated. It is reported that the overall average accuracies for the lens injection moulding condition diagnosis and form error estimation are better than 97% and 80%,respectively,in the actual industrial site.
KW - condition diagnosis
KW - form error estimation
KW - in-process cavity pressure signal
KW - Lens injection moulding process
KW - response surface methodology
UR - https://www.scopus.com/pages/publications/84983684746
U2 - 10.1177/0954405415572664
DO - 10.1177/0954405415572664
M3 - Article
AN - SCOPUS:84983684746
SN - 0954-4054
VL - 230
SP - 1343
EP - 1350
JO - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
JF - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
IS - 7
ER -