کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
7541710 1489051 2018 67 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
Variable selection methods in multivariate statistical process control: A systematic literature review
ترجمه فارسی عنوان
روش های انتخاب متغیر در کنترل چند متغیره آماری: یک بررسی ادبی سیستماتیک
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کلمات کلیدی
انتخاب متغیر، کنترل فرآیند آماری چند متغیره، نظارت بر روند صنعتی، مجموعه داده های با ابعاد بزرگ،
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
چکیده انگلیسی
Technological advances led to increasingly larger industrial quality-related datasets calling for process monitoring methods able to handle them. In such context, the application of variable selection (VS) in quality control methods emerges as a promising research topic. This review aims at presenting the current state-of-the-art of the integration of VS in multivariate statistical process control (MSPC) methods. Proposals aligned with the objective were identified, classified according to VS approach, and briefly presented. Research on the topic has considerably increased in the past five years. Thirty methods were identified and categorized in 10 clusters, according to the objective of improvement in MSPC and the step of process monitoring they were aimed to improve. The majority of the propositions were either targeted at exclusively monitoring potential out-of-control variables or improving the monitoring of in-control variables. MSPC improvements were centered in principal component analysis (PCA) projection methods, while VS was mainly carried out using the Least Absolute Shrinkage and Selection Operator (LASSO) method and genetic algorithms. Fault isolation was the most addressed step in process monitoring. We close the paper proposing five topics for future research, exploring the opportunities identified in the literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 115, January 2018, Pages 603-619
نویسندگان
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