Statistical estimation of variation transmission model in a manufacturing process

被引:0
|
作者
José Antonio Heredia
Matias Gras
机构
[1] Universitat Jaume I,ESID Department
[2] Keraben,undefined
来源
The International Journal of Advanced Manufacturing Technology | 2011年 / 52卷
关键词
Manufacturing process; Quality control; Statistical modelling; Statistical process control; Variation transmission; Variance components;
D O I
暂无
中图分类号
学科分类号
摘要
This article describes a method for obtaining a variation transmission model in a multi-stage manufacturing process in situations in which the characteristic that defines the quality of the product is an independent variable which variation is the consequence of the one generated and transmitted through the different process stages. The method uses regression analysis to obtain models that relate the quality characteristic to process variables, statistical process control techniques to estimate the variance of the variables and the analysis of variance to estimate the variance components from the observed data and to verify that data come from a stable process. This method can be applied to processes where the quality characteristics are different at each stage (a usual situation in chemical processes) and in cases where not all the process variables can be measured directly. The model also includes the measurement errors both of the quality characteristic and of the process variables. The new proposed approach has been applied to validate its suitability in a ceramic tiles manufacturing process.
引用
收藏
页码:789 / 795
页数:6
相关论文
共 50 条
  • [21] Statistical process control for multistage manufacturing and service operations: A review
    Tsung, Fugee
    Li, Yanting
    Jin, Ming
    2006 IEEE INTERNATIONAL CONFERENCE ON SERVICE OPERATIONS AND LOGISTICS, AND INFORMATICS (SOLI 2006), PROCEEDINGS, 2006, : 752 - +
  • [22] An integrated model for statistical and vision monitoring in manufacturing transitions
    Nembhard, HB
    Ferrier, NJ
    Osswald, TA
    Sanz-Uribe, JR
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2003, 19 (06) : 461 - 476
  • [23] Opportunistic maintenance integrated model for a two-stage manufacturing process
    Hasan Rasay
    Farnoosh Naderkhani
    Fariba Azizi
    The International Journal of Advanced Manufacturing Technology, 2022, 119 : 8173 - 8191
  • [24] Opportunistic maintenance integrated model for a two-stage manufacturing process
    Rasay, Hasan
    Naderkhani, Farnoosh
    Azizi, Fariba
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2022, 119 (11-12) : 8173 - 8191
  • [25] Integrated statistical process control and engineering process control for a manufacturing process with multiple tools and multiple products
    Lee, Shui-Pin
    Wong, David Shan-Hill
    Sun, Cheng-I
    Chen, Wun-Hwa
    Jang, Shi-Shang
    JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING, 2015, 32 (03) : 174 - 185
  • [26] Economic optimal model integrating statistical process control and preventive maintenance
    Huang Dan
    Zhu Haiping
    Yin Hui
    Deng Yuhao
    Tian Zhipeng
    2016 IEEE INTERNATIONAL CONFERENCE OF ONLINE ANALYSIS AND COMPUTING SCIENCE (ICOACS), 2016, : 218 - 224
  • [27] Evolution of process capability in a manufacturing process
    Sousa, Sergio
    Rodrigues, Nuno
    Nunes, Eusebio
    JOURNAL OF MANAGEMENT ANALYTICS, 2018, 5 (02) : 95 - 115
  • [28] A systematic review of statistical process control implementation in the food manufacturing industry
    Lim, Sarina Abdul Halim
    Antony, Jiju
    Arshed, Norin
    Albliwi, Saja
    TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE, 2017, 28 (1-2) : 176 - 189
  • [29] A review of statistical process control techniques for short run manufacturing systems
    DelCastillo, E
    Grayson, JM
    Montgomery, DC
    Runger, GC
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1996, 25 (11) : 2723 - 2737
  • [30] Application of Statistical Process Control (SPC) in Manufacturing Industry in a Developing Country
    Madanhire, Ignatio
    Mbohwa, Charles
    13TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING - DECOUPLING GROWTH FROM RESOURCE USE, 2016, 40 : 580 - 583