Title: A novel QFD-based analytical guideline approach for painting applicator nozzle selection

Authors: Gustavo Franco Barbosa; Pedro Henrique da Silva Guedes; Sidney Bruce Shiki; Iris Bento da Silva; Guylherme Emmanuel Tagliaferro de Queiroz

Addresses: Mechanical Engineering Department, Federal University of São Carlos, São Carlos, Brazil ' Production Engineering Department, Federal University of São Carlos, São Carlos, Brazil ' Mechanical Engineering Department, Federal University of São Carlos, São Carlos, Brazil ' Mechanical Engineering Department, University of Sao Paulo, São Carlos, Brazil ' Physics Department, University of São Paulo, São Carlos, Brazil

Abstract: This paper proposes a novel quality function deployment (QFD) based analytical guideline, concepted to assist the choice of applicator nozzles for painting systems of any business. The lack of specific guidance methods for this purpose is often the cause of difficulties experienced by industries during the selection of painting applicators. So, an analytical guideline assisted by a customised QFD approach is proposed to analyse all key painting parameters to be assessed and cross-checked with the strategy of a given business. It allows to determine the main technical features that should be considered during the decision process, by a calculation of scores of each painting system. The purpose is to orient the industrial needs related to manufacturing strategies to be used by engineers, managers and project leaders who are in charge of specifying painting systems and making strategic decisions. To attest that, two case studies have been conducted to demonstrate the application of the proposed approach. Thus, this contribution looks for better results in terms of productivity and quality on painting routines, oriented to the company's strategy of costs reduction and adding competitive value to the business. [Submitted: 14 June 2021; Accepted: 3 July 2022]

Keywords: quality function deployment; QFD; analytical guideline; decision process; painting; manufacturing.

DOI: 10.1504/EJIE.2023.131745

European Journal of Industrial Engineering, 2023 Vol.17 No.4, pp.627 - 656

Received: 14 Jul 2021
Accepted: 03 Jul 2022
Published online: 30 Jun 2023 *

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