z-logo
open-access-imgOpen Access
Rule Extraction Required for Manufacturing Process Design
Author(s) -
Jihoon Song,
Jongpil Jeong
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.04.084
Subject(s) - computer science , association rule learning , process (computing) , data mining , cluster analysis , representation (politics) , dimension (graph theory) , rule based system , set (abstract data type) , artificial intelligence , mathematics , politics , political science , pure mathematics , law , programming language , operating system
We propose a method of extracting Main Sub process rules for process design of manufacturing company in 4th industry. In order to extract process design rules, we construct the model as an instance representation model, transform it into data that can utilize the instance data through the dimension reduction algorithm and clustering algorithm, and extract the process information based on the association rule mining algorithm. The process information extracted by the association rule mining algorithm can be used as the main process design rule through vectorization and the part that is difficult to extract can be set as the sub process design rule to design the integrated process rule.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom