Process / pipelineEngineering methods

Multi-response Control Chart — Multivariate Process Monitoring

A multi-response control chart simultaneously monitors two or more correlated quality characteristics on a single chart, preserving the correlation structure that univariate charts ignore. Built on Hotelling's T² statistic and its time-weighted extensions (MEWMA, MCUSUM), it detects process shifts that would be missed if each response were charted independently. It is the standard tool in manufacturing and service quality when product performance depends on multiple interrelated outputs.

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Sources

  1. Hotelling, H. (1947). Multivariate quality control illustrated by the air testing of sample bombsights. In C. Eisenhart, M. W. Hastay, & W. A. Wallis (Eds.), Techniques of Statistical Analysis (pp. 111–184). McGraw-Hill. link
  2. Lowry, C. A., Woodall, W. H., Champ, C. W., & Rigdon, S. E. (1992). A multivariate exponentially weighted moving average control chart. Technometrics, 34(1), 46–53. DOI: 10.1080/00401706.1992.10484901

Related methods

ScholarGateMulti-response Control Chart (Multi-response Statistical Process Control Chart). Retrieved 2026-06-04 from https://scholargate.app/en/experimental-design/multi-response-control-chart