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A DECISION THEORY APPROACH TO SUPPORT ACTION PLANS IN COOKER HOODS MANUFACTURING

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MARCH 2019   -  Volume: 94 -  Pages: 203-208

DOI:

https://doi.org/10.6036/8890

Authors:

PAOLO CICCONI - LEONARDO POSTACCHINI - NICOLA BERGANTINO - GIANLUCA CAPUZZI - ANNA COSTANZA RUSSO - ROBERTO RAFFAELI - MICHELE GERMANI

Disciplines:

  • Computer Sciences (SISTEMA DE CONTROL DE PRODUCCIÓN )
  • Industrial technology (INGENIERIA DE PROCESOS )

Downloads:   277

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Received Date :   3 July 2018

Reviewing Date :   4 July 2018

Accepted Date :   8 October 2018


Key words:
Knowledge Base, Bayesian Network, Industry 4.0, Cooker Hoods, Base de conocimientos, Red Bayesiana, Industria 4.0, Campanas de cocina
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

Nowadays, Knowledge-Based systems are widespread decision-making tools applied in product design and manufacturing planning. The series production requires agile and rapid decision-making methods to support actions in manufacturing lines. Therefore, agent-based tools are necessary to support the detection, diagnosis, and correction of accidental production faults. The context of Industry 4.0 has been enhancing the integration of sensors in manufacturing lines to monitor production and analyze failures. The motivation of the proposed research is to study and validate decision theory methods to be applied in smart manufacturing. This paper shows a Knowledge-Based approach to support action decision-making processes by a Bayesian network model. The proposed method aims at solving production problems detected in the manufacturing process. In particular, the focus is on the automatic production of cooker hoods. A case study describes how the approach can be applied in the real-time control actions, after a problem in quality is detected.

Keywords: Knowledge Base, Bayesian Network, Industry 4.0, Cooker Hoods.

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