In some statistical process control applications, the quality of the product is characterized by the combination of both correlated variable and attributes quality characteristics. In this paper, we propose a novel control scheme based on the combination of two multi-layer perceptron neural networks for simultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attr...

Software process assessments have been used to verify the conformance with quality reference models or standards, usually in a context of software process improvement programs. Most of these assessments are concerned with just one specific model or standard. However, organizations could be interested in more than one model, being necessary to offer an integrated assessment that allows evaluate ...

Mixtures provide a useful approach for relaxing parametric assumptions. Discrete mixture models induce clusters, typically with the same cluster allocation for each parameter in multivariate cases. As a more flexible approach that facilitates sparse nonparametric modeling of multivariate random effects distributions, this article proposes a kernel partition process (KPP) in which the cluster al...

The concept of process capability was proposed in early 1970 with the introduction of ‘capability ratio’ by Juran, a world known quality expert. Thereafter almost 40 years have been passed and many indices such as Cp, Cpk and Cpm were developed for measuring process performance. However, many researchers, for example, Kotz and Johnson [1-2] raised concerns about the application of the diversifi...

Due to the rapid change of technology along with advanced data-collection systems, the simultaneous monitoring of two or more quality characteristics (or variables) is necessary. Multivariate Statistical Process Control (SPC) charts are able to effectively detect process disturbances. However, when a disturbance in a multivariate process is triggered by a multivariate SPC chart, process personn...

In market globalization environment, the enterprises need respond to customer requirement and increasing customer satisfaction. The enterprises need to be fine appropriate approach that can help to achieve their goal. This encouraged many enterprises to adopt either Six Sigma for improving process throughout process interaction and problem solving or Lean for wastes reduction in processes. Howe...

Data-based procedures for monitoring the operating performance of a PV system are proposed in this article. The only information required to apply is availability measurements, which routinely on-line collected via sensors. Here, kernel-based machine learning methods, including support vector regression (SVR) and Gaussian process (GPR), used model multivariate data from fault detection because ...

A d-dimensional α-stable random vector is determined by a spectral measure Γ (a finite Borel measure on Sd=unit sphere in R) and a shift vector μ ∈ R, e.g. Samorodnitsky and Taqqu (1994). The notation X ∼ Sα,d(Γ, μ) will be used to denote such a stable random vector. Until recently, there has been little understanding of what multivariate stable distributions look like, nor any methods for work...

This thesis presents contributions within the field of process capability analysis. Process capability analysis deals with how to assess the capability of processes. Based on process capability analysis one can determine how the process performs relative to its product requirements or specifications. An important part within process capability analysis is the use of process capability indices. ...