Design of experiments and machine learning with application to industrial experiments

被引:10
|
作者
Fontana, Roberto [1 ]
Molena, Alberto [2 ]
Pegoraro, Luca [2 ]
Salmaso, Luigi [2 ]
机构
[1] Politecn Torino, Dept Math Sci, Turin, Italy
[2] Univ Padua, Dept Management & Engn, Padua, Italy
关键词
Design of Experiments; Machine learning; Active learning; Industrial statistics;
D O I
10.1007/s00362-023-01437-w
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In the context of product innovation, there is an emerging trend to use Machine Learning (ML) models with the support of Design Of Experiments (DOE). The paper aims firstly to review the most suitable designs and ML models to use jointly in an Active Learning (AL) approach; it then reviews ALPERC, a novel AL approach, and proves the validity of this method through a case study on amorphous metallic alloys, where this algorithm is used in combination with a Random Forest model.
引用
收藏
页码:1251 / 1274
页数:24
相关论文
共 50 条
  • [1] Design of experiments and machine learning with application to industrial experiments
    Roberto Fontana
    Alberto Molena
    Luca Pegoraro
    Luigi Salmaso
    Statistical Papers, 2023, 64 : 1251 - 1274
  • [2] Machine learning and design of experiments with an application to product innovation in the chemical industry
    Arboretti, Rosa
    Ceccato, Riccardo
    Pegoraro, Luca
    Salmaso, Luigi
    Housmekerides, Chris
    Spadoni, Luca
    Pierangelo, Elisabetta
    Quaggia, Sara
    Tveit, Catherine
    Vianello, Sebastiano
    JOURNAL OF APPLIED STATISTICS, 2022, 49 (10) : 2674 - 2699
  • [3] Quality improvement and design of experiments - An industrial application
    Gentili, E
    Formentelli, M
    Trovato, G
    AMST'99: ADVANCED MANUFACTURING SYSTEMS AND TECHNOLOGY, 1999, (406): : 825 - 832
  • [4] APPLICATION OF MACHINE LEARNING METHODS IN NEUTRINO EXPERIMENTS
    Yermolenko, R.
    Falko, A.
    Gogota, O.
    Onishchuk, Yu.
    Aushev, V.
    JOURNAL OF PHYSICAL STUDIES, 2024, 28 (03):
  • [5] Double machine learning and design in batch adaptive experiments
    Li, Harrison H.
    Owen, Art B.
    JOURNAL OF CAUSAL INFERENCE, 2024, 12 (01)
  • [6] Discovery Learning Experiments in a New Machine Design Laboratory
    Nagurka, Mark
    Anton, Fernando Rodriguez
    2013 ASEE ANNUAL CONFERENCE, 2013,
  • [7] DESIGN OF EXPERIMENTS IN INDUSTRIAL RESEARCH
    SMALLWOOD, HM
    ANALYTICAL CHEMISTRY, 1947, 19 (12) : 950 - 952
  • [8] DESIGN AND ANALYSIS OF INDUSTRIAL EXPERIMENTS
    MURPHY, TD
    CHEMICAL ENGINEERING, 1977, 84 (12) : 168 - 182
  • [9] Application of design of experiments for industrial paint production process improvement
    Chutima, Parames
    Suksamran, Apisada
    6TH INTERNATIONAL CONFERENCE ON MANUFACTURING, OPTIMIZATION, INDUSTRIAL AND MATERIAL ENGINEERING : MOIME18, 2018, 2044
  • [10] EXPERIMENTS IN MACHINE LEARNING AND THINKING
    KILBURN, T
    GRIMSDALE, RL
    SUMNER, FH
    COMMUNICATIONS OF THE ACM, 1959, 2 (07) : 20 - 21