A Methodological Approach to Knowledge-Based Engineering Systems for Manufacturing

Mele, Mattia (2020) A Methodological Approach to Knowledge-Based Engineering Systems for Manufacturing, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Meccanica e scienze avanzate dell'ingegneria, 32 Ciclo. DOI 10.6092/unibo/amsdottorato/9237.
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Abstract

A survey of implementations of the knowledge-based engineering approach in different technological sectors is presented. The main objectives and techniques of examined applications are pointed out to illustrate the trends and peculiarities for a number of manufacturing field. Existing methods for the development of these engineering systems are then examined in order to identify critical aspects when applied to manufacturing. A new methodological approach is proposed to overcome some specific limitations that emerged from the above-mentioned survey. The aim is to provide an innovative method for the implementation of knowledge-based engineering applications in the field of industrial production. As a starting point, the field of application of the system is defined using a spatial representation. The conceptual design phase is carried out with the aid of a matrix structure containing the most relevant elements of the system and their relations. In particular, objectives, descriptors, inputs and actions are defined and qualified using categorical attributes. The proposed method is then applied to three case studies with different locations in the applicability space. All the relevant elements of the detailed implementation of these systems are described. The relations with assumptions made during the design are highlighted to validate the effectiveness of the proposed method. The adoption of case studies with notably different applications also reveals the versatility in the application of the method.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Mele, Mattia
Supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Knowledge Based Systems ; Intelligent Manufacturing ; Sustainable Manufacturing ; Computer Aided Engineering ; Computer Aided Manufacturing
URN:NBN
DOI
10.6092/unibo/amsdottorato/9237
Data di discussione
17 Marzo 2020
URI

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