Please use this identifier to cite or link to this item: https://repositorio.ufrn.br/jspui/handle/123456789/25454
Title: Mixed two- and four-level experimental designs for interchangeable parts with different degrees of assembly difficulty
Authors: Vivacqua, Carla A.
Ho, Linda Lee
Pinho, André L.S.
Keywords: Hard-to-change factor;Minimum setup;Prototype testing;Regular design;Restricted randomization;Split-plot fractional factorial design
Issue Date: Aug-2017
Publisher: International journal of quality & reliability management
Citation: VIVACQUA, Carla A.; HO, Linda Lee ; PINHO, André L. S. . Mixed two- and four-level experimental designs for interchangeable parts with different degrees of assembly difficulty. International Journal Of Quality and reliability management, v. 34, p. 1152-1166, 2017. Disponível em: <http://www.emeraldinsight.com/doi/full/10.1108/IJQRM-01-2016-0006>. Acesso em: 04 dez. 2017
Portuguese Abstract: Purpose – The purpose of this paper is to show how to properly use the method of replacement to construct mixed two- and four-level minimum setup split-plot type designs to accommodate the presence of hard-to-assemble parts. Design/methodology/approach – Split-plot type designs are economical approaches in industrial experimentation. These types of designs are particularly useful for situations involving interchangeable parts with different degrees of assembly difficulties. Methodologies for designing and analyzing such experiments have advanced lately, especially for two-level designs. Practical needs may require the inclusion of factors with more than two levels. Here, the authors consider an experiment to improve the performance of a Baja car including two- and four-level factors. Findings – The authors find that the direct use of the existing minimum setup maximum aberration (MSMA) catalogs for two-level split-plot type designs may lead to inappropriate designs (e.g. low resolution). The existing method of replacement for searching exclusive sets of the form (α, β, αβ) available in the literature is suitable for completely randomized designs, but it may not provide efficient plans for designs with restricted randomization. Originality/value – The authors provide a general framework for the practitioners and have extended the algorithm to find out the number of generators and the number of base factor at
URI: https://repositorio.ufrn.br/jspui/handle/123456789/25454
Appears in Collections:CCET - DEST - Artigos publicados em periódicos

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