Statistical Process Control

Statistical Process Control is a quality management methodology that uses statistical techniques to monitor and control process behavior by analyzing variation in process data, thereby distinguishing common-cause from special-cause variation to maintain and improve process performance.

6.2K

Publications

327.4K

Citations

8.4K

Authors

2.5K

Institutions

Publications per year

2017–2026

1.5K

Authors

8.4K

  1. WH
    William H. Woodall

    Virginia Tech, United States

    95 publications · 11.4K citations

    54

    h-index

  2. DC
    Douglas C. Montgomery

    Arizona State University, United States

    74 publications · 17.2K citations

    45

    h-index

  3. MR
    Marion R. Reynolds

    Virginia Tech, United States

    63 publications · 5.6K citations

    42

    h-index

  4. PC
    Philippe Castagliola

    Nantes Université, France

    121 publications · 4.6K citations

    40

    h-index

  5. MR
    Muhammad Riaz

    King Fahd University of Petroleum and Minerals, Saudi Arabia

    142 publications · 4.9K citations

    39

    h-index

1–5 of 8.4K

Venues

  1. Journal of Quality Technology

    385 publications · 36.3K citations

    102

    h-index

  2. Technometrics

    287 publications · 45.9K citations

    101

    h-index

  3. Quality and Reliability Engineering International

    599 publications · 19.7K citations

    63

    h-index

  4. International Journal of Production Research

    229 publications · 9.6K citations

    54

    h-index

  5. IIE Transactions

    125 publications · 6.4K citations

    48

    h-index

1–5