SYSTEM AND METHOD FOR INVERSE INFERENCE FOR A MANUFACTURING PROCESS CHAIN

The present disclosure provides a system and method for inverse inference in a chain of manufacturing processes using Bayesian networks is provided. The method generates a composite Bayesian network model for a chain of manufacturing processes from Bayesian network models of the unit processes in th...

Full description

Saved in:
Bibliographic Details
Main Authors BASAVARSU, Gautham Purushottham, SARDESHMUKH, Avadhut Mohanrao, REDDY, Sreedhar Sannareddy, SHAH, Sapankumar Hiteshchandra
Format Patent
LanguageEnglish
Published 30.04.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROL OR REGULATING SYSTEMS IN GENERAL
CONTROLLING
COUNTING
FUNCTIONAL ELEMENTS OF SUCH SYSTEMS
MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS
PHYSICS
REGULATING
Online AccessGet full text

Cover

More Information
Summary:The present disclosure provides a system and method for inverse inference in a chain of manufacturing processes using Bayesian networks is provided. The method generates a composite Bayesian network model for a chain of manufacturing processes from Bayesian network models of the unit processes in the chain. The models of unit processes might have been learned independently in other contexts and stored in a knowledge repository. Models relevant for the current problem context are obtained from the knowledge repository and checked for compatibility using ontological information about their inputs and outputs. The obtained compatible Bayesian network models of unit processes are composed to generate a composite Bayesian network model for the chain. The generated composite Bayesian network model is sampled to perform inverse inference.
Bibliography:Application Number: US201916562858