Monitoring the Parameters of the Market Model by Linear Profile Procedures

Ho, Linda Lee; Said, Mahmoud El; Kim, Ricardo Wonseuk

doi:10.1515/eqc.2010.006

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…In the early stage, researches mainly focus on parametric linear profiles. Ho et al (2010) proposed to monitor profiles by the slope, intercept and variance of the linear model and identify out-of-control samples by F statistics. Noghondarian and Ghobadi (2012) developed a model in fuzzy linear regression to construct the quality profiles.…”

Section: Introductionmentioning

confidence: 99%

Phase I non-linear profiles monitoring using a modified Hausdorff distance algorithm and clustering analysis

Nie

Liu

et al. 2020

IJQRM

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PurposeThe purpose of this paper is to propose a new non-parametric phase I control chart for the problem of non-linear profile outlier detection.Design/methodology/approachThe proposed non-parametric method is based on a modified Hausdorff distance, which does not require a restrictive assumption on the form of profiles. By obtaining the distance between each profile and the baseline profile, the authors introduced an iterative optimization clustering algorithm to identify outliers by clustering distances.FindingsThe simulation results show that the proposed method can distinguish outliers for structural changes of non-linear profiles. The authors also present a real industrial case example to highlight how practitioners can implement and make use of the proposed control chart in outlier detection applications, and it achieves higher accuracy in the outlier detection of complex profiles.Practical implicationsThe research results of this paper can be applied to any manufacturing or service system whose quality characteristics are characterized by non-linear profiles. This new approach provides quality practitioners a better decision-making tool for non-linear profile outlier detection.Originality/valueDue to the complexity of real-world applications, the non-linear profiles monitoring problem is yet to be addressed. However, the related research still remains rare. And the authors’ proposed non-linear profile control chart, which does not require a restrictive assumption on the form of profiles, shows its applicability and superiority in simulation study and real-world case.

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Section: Introductionmentioning

confidence: 99%