A comparative study on evaluating air quality of taiwan using various multivariate process capability indices

Pan Jeh-Nan, Lai Sheng-Chen, Lee Chun-Yi

Research output: Contribution to journalArticle

Abstract

With the advent of high-technology era, the problems of the air, water and land pollution have led to the crisis of global ecosystems, e.g., greenhouse effect, human respiratory system damage and plants damage. In order to further prevent the deterioration of environmental system and achieve global sustainability, major organizations and corporations around the world are starting to systematically review the environmental performance of their supplies based on the regulations stipulated by Environmental Protection Agency of each country. Therefore, how to monitor environmental performance becomes an important research issue. The multivariate process capability index established by Niverthi and Dey (2000) is based on the assumption of normality. However, the air pollution data may not follow normal distribution. In this paper, a novel RND index using percentile estimation as well as Taguchi's quadratic loss function is developed to relieve the normal assumption. Applying the concept of coverage probability, the results of our comparative study indicate that RND index can correctly reflect the actual air quality. Finally, a computer program using R language is developed to simplify the calculation of the RND index, and a numerical example further demonstrates that our proposed RND index can facilitate the early detection of air pollution in Taiwan.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalJournal of Quality
Volume16
Issue number1
Publication statusPublished - 2009 Apr 27

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

Fingerprint Dive into the research topics of 'A comparative study on evaluating air quality of taiwan using various multivariate process capability indices'. Together they form a unique fingerprint.

  • Cite this