Yazar "Kahraman, Cengiz" için listeleme
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Design of Fuzzy (u)over-tilde Control Charts
Şentürk, Sevil; Erginel, Nihal; Kaya, İhsan; Kahraman, Cengiz (Old City Publishing Inc, 2011)When expressing any data in linguistic terms related to a quality characteristic, traditional statistical techniques are insufficient to capture the vagueness in the data. Linguistic data can be transformed into numerical ... -
Design of Fuzzy u Control Charts
When expressing any data in linguistic terms related to a quality characteristic, traditional statistical techniques are insufficient to capture the vagueness in the data. Linguistic data can be transformed into numerical ... -
Evaluating the Packing Process in Food Industry Using Fuzzy X ~ and S ~ Control Charts
Erginel, Nihal; Şentürk, Sevil; Kahraman, Cengiz; Kaya, İhsan (Atlantis Press, 2011)The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement ... -
Evaluating the packing process in food industry using fuzzy and [stilde] control charts
The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement ... -
Fuzzy exponentially weighted moving average control chart for univariate data with a real case application
Şentürk, Sevil; Erginel, Nihal; Kaya, İhsan; Kahraman, Cengiz (Elsevier Science BV, 2014)Statistical process control (SPC) is an approach to evaluate processes whether they are in statistical control or not. For this aim, control charts are generally used. Since sample data may include uncertainties coming ... -
Fuzzy Statistical Process Control Techniques in Production Systems
Kahraman, Cengiz; Gülbay, Murat; Erginel, Nihal; Şentürk, Sevil (Springer-Verlag Berlin, 2010)Crisp Shewhart control charts monitor and evaluate a process as "in control" or "out of control" whereas the fuzzy control charts do it by using suitable linguistic or fuzzy numbers by offering flexibility for control ...
