Virtual Quality Management Elements in Optimized New Product Development Using Genetic Algorithms

Stefan Bodi, Sorin Popescu, Calin Drageanu and Dorin Popescu
Additional contact information
Stefan Bodi: Technical University of Cluj-Napoca, Romania
Sorin Popescu: Technical University of Cluj-Napoca, Romania
Calin Drageanu: Technical University of Cluj-Napoca, Romania
Dorin Popescu: Technical University of Cluj-Napoca, Romania

from ToKnowPress

Abstract: The contribution of this paper is placed in the field of vQM (virtual Quality Management) supposing the use of software techniques in product and its manufacturing process planning. The research was focused on laying out a framework, which brought together quality techniques used in competitive design (VOCT, AHP, QFD) and mechanisms inspired by biological evolution (genetic algorithms), achieving in the same time customer oriented development and optimization of new product characteristics. Both quality techniques and genetic algorithm were deployed in the virtual environment based on specialized software tools (Qualica, Genesis). The methodology supposes as stages: ‘Acquiring and ranking customer knowledge’ (VOCT and AHP in identifying customer requirements and their degree of importance); ‘Turning requirements into characteristics’ (cascaded QFD is translating successively customer requirements into technical characteristics of product and its components) and ‘Product optimization’ (genetic algorithm optimizes the component characteristics). The genetic algorithm itself contains several constraints derived either from the customer requirements or product functionality. Thus, each component’s shape, size and fitness is determined by the objective function, formulated within the genetic algorithms code. By complying with the above described framework, each component is optimally designed to constitute a product that will best serve customer needs. The proposed methodology is illustrated on the development of furniture industry products that cover diverse design situation. The product optimization and the objective function derived were focused on minimizing the product mass, implicitly its raw material consumption.

Keywords: new product development; information technology; genetic algorithms; virtual quality management (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.toknowpress.net/ISBN/978-961-6914-13-0/papers/ML15-126.pdf full text (application/pdf)
http://www.toknowpress.net/ISBN/978-961-6914-13-0/MakeLearn2015.pdf Conference Programme (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tkp:mklp15:633-642

Access Statistics for this chapter

More chapters in Managing Intellectual Capital and Innovation for Sustainable and Inclusive Society: Managing Intellectual Capital and Innovation; Proceedings of the MakeLearn and TIIM Joint International Conference 2015 from ToKnowPress
Bibliographic data for series maintained by Maks Jezovnik ().