Open AccessCapacity Analysis of Cable Insulation Crosslinking Production Process Based on IoT Big Data
Author(s) -
ZhenHui Lv,
LongJiang Bian,
Mingjun Feng,
Jinli Zhang
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2237/1/012028
Subject(s) - control chart , statistical process control , computer science , univariate , multivariate statistics , process (computing) , autocorrelation , \bar x and r chart , process control , statistics , data mining , ewma chart , mathematics , machine learning , operating system
In the cable insulation crosslinking production process, the process quality is determined by multiple processes and multiple related process variables, and there are complex autocorrelation and cross-correlation among these process variables. In this paper, different process variables are studied. By implementing statistical process control on a univariate, single value control chart (I) and moving range control chart ( M ¯ R ) are drawn, and process capability C P is analyzed to find variables with weak process capability for improvement. At the same time, based on the background of the continuous development of the Internet of Things and big data technology, this paper evaluates the complex autocorrelation and cross-correlation between the overall process variables, adopts the multivariate statistical process control technology, and combines the multivariate HOTELLING T 2 control chart and MEWMA control chart to reflect the statistical characteristics of multiple variables, thus avoiding misjudgment or omission of process quality monitoring model. By studying the setting of cable production process parameters and quality standards, combined with the application of complete multivariate statistical process control (MSPC) around the evaluation results, process, and technical requirements, this research can provide effective guidance for the cable insulation crosslinking production process