Smart Virtual Product Development (SVPD) System to Support Product Inspection Planning in Industry 4.0

Title
Smart Virtual Product Development (SVPD) System to Support Product Inspection Planning in Industry 4.0
Publication Date
2020
Author(s)
Ahmed, Muhammad Bilal
Majeed, Farhat
Sanin, Cesar
( author )
OrcID: https://orcid.org/0000-0001-8515-417X
Email: cmaldon3@une.edu.au
UNE Id une-id:cmaldon3
Szczerbicki, Edward
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Elsevier BV
Place of publication
The Netherlands
DOI
10.1016/j.procs.2020.09.310
UNE publication id
une:1959.11/61790
Abstract

This paper presents the idea of supporting product inspection planning process during the early stages of product life cycle for the experts working on product development. Aim of this research is to assist a collaborative product development process by using Smart Virtual Product Development (SVPD) system, which is based on Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). The proposed system is developed to support three key aspects of industrial product development i.e. design, manufacturing, and product inspection. Therefore, it comprises of three main modules; design knowledge management (DKM), manufacturing capability and process planning (MCAPP), and product inspection planning (PIP). It collects, stores, and uses experiential knowledge from formal decisional events in the form of set of experience (SOE). This research enlightens the working mechanism of the PIP module, and shows how experiential knowledge related to product inspection can be used during the early stages of product development process. This experiential knowledge is extracted and stored from similar products having some common features and functions. First, the basic description and principles of the approach are introduced, then the prototype version of the system is developed and tested for product inspection planning (PIP) module for the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart manufacturing and can play a vital role in Industry 4.0.

Link
Citation
Procedia Computer Science, v.176, p. 2596-2604
ISSN
1877-0509
Start page
2596
End page
2604
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International

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