Multivariate Information in Univariate Control Charts
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Lorenz Braun
Abstract
Statistical Process Control (SPC) has been established in many industries over the last decades. Particularly, the automotive industry including its suppliers of components is responsible for the spread of SPC supported by different norms. By means of process capability indices the fulfilment of requirements with respect to a product is examined, while control charts are used to monitor a process over time by measuring and analyzing continuously the product variables characterizing product quality. This may lead to high costs, which arise mainly as a result of sampling the data. The objective is to recognize and correct changes in quality as soon as possible. This can be achieved by shorter sampling intervals or by an improved analysis of the data. Conditional control charts are a new way of analyzing sample data by using multivariate information provided in classical control charts, which increase the sensibility of control charts.
© Heldermann Verlag
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Artikel in diesem Heft
- Estimation on a GAR(1) Process by the EM Algorithm
- Point and Interval Estimation for the Lifetime Distribution of a k-Unit Parallel System Based on Progressively Type-II Censored Data
- A Note on the Distribution of Bousquet
- A Quality Index for Evaluating the Bank Capital Adequacy According to Basel I and II
- Reliability Test Plans for Series Systems in the Presence of Covariates
- Multivariate Information in Univariate Control Charts
- A Note on the Moments of Random Variables
- A Heuristic Approach for Constrained Redundancy Optimization in Multi-state Systems
- Reliability Computation of Moranda's Geometric Software Reliability Model
- Economic Design of A Modified Variable Sample Size and Sampling Interval Chart
- Gamma Frailty Regression Models in Mixture Distributions
- A Truncated Bivariate t Distribution