At the end of your life, you will never regret not having passed one more test, not winning one more
Idea Transcript
SIGN IN SIGN UP
Bayesian models and stochastic processes applied to CSP sampling plans for quality control in production in series and by lots Full Text: Authors:
PDF
Get this Article
Tools and Resources Buy this Article Recommend the ACM DL
Rodrigo Barbosa Correa Universidad del Norte, Barranquilla, Colombia Carlos D. Paternina-Arboleda Universidad del Norte, Barranquilla, Colombia Diana G. Ramírez Ríos Universidad del Norte, Barranquilla, Colombia
Save to Binder Export Formats: BibTeX EndNote ACM Ref Upcoming Conference: WSC '18 Share:
|
Contact Us | Switch to single page view (no tabs) Abstract
Authors
References
Cited By
Index Terms
Publication
Reviews
Comments
Table of Contents
Nowadays, businesses consider that their methods are perfect, this means, that by having available a department of analysis and statistic control of the process, everything that the inspector or the inspection tools decides are considered to be correct, with not even a minimum of error involved. Yet, if they considered the principles of uncertainty of Heisenberg, in which he believes that the uncertainty associated to the observation, does not contradict the existence of laws that govern the behavior of the particles in the universe, not even the capacity of the scientists to discover those laws, which will be seen as precise predictions, which can be substituted by the calculations of probabilities. This investigation focuses on the study of CSP sampling plans for acceptance with Bayesian and Markovian revisions, in the processes of production in series and by lots, that support the quality activities and reduction of costs by inspection.