Industrial statistics: The challenges and the research

David M. Steinberg*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Industrial problems have stimulated an enormous amount of valuable statistical research, from the t-test to advanced statistical tools for quality. Industry continues to generate challenging problems for statistical design, modeling, and analysis. Useful articles are published in our journals, often stimulated by industrial applications. Nonetheless, there is concern that research in industrial statistics is falling well short of its potential for providing interesting problems, that some of the most exciting problems are not getting space in our journals, and that few statisticians working in industry are publishing research. This article endeavors to map out the current state of research in industrial statistics, to describe major issues that need to be addressed, and to discuss whether the research is on target to meet those challenges.

Original languageEnglish
Pages (from-to)45-59
Number of pages15
JournalQuality Engineering
Issue number1
StatePublished - 2 Jan 2016


  • SPC
  • data science
  • design of experiments
  • reliability
  • statistical practice


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