Design Methodology of New Furniture Joints

Techniques for self-assembly and disassembly of furniture are predominant mainly in the group of cabinet furniture. The lack of new constructions of furniture joints affects the market development of skeletal furniture intended for self-assembly. These connections should have the following character...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Marcin Podskarbi, Jerzy Smardzewski, Krzysztof Moliński, Marta Molińska-Glura
Formato: article
Lenguaje:EN
Publicado: University of Zagreb, Faculty of Forestry and Wood Technology 2017
Materias:
Acceso en línea:https://doaj.org/article/d95fb07177254c42bde9dd06bbe33a96
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Techniques for self-assembly and disassembly of furniture are predominant mainly in the group of cabinet furniture. The lack of new constructions of furniture joints affects the market development of skeletal furniture intended for self-assembly. These connections should have the following characteristics: be easy to assemble and disassemble, have a minimum number of components, meet aesthetic requirements and be externally invisible. The aim of the study was to develop a methodology for formulating the assumptions for designing a new connection of skeletal furniture. At the outset, the distinguished joint features were presented. Then, assessment criteria were formulated for each feature, with adequate numerical values. On this basis, specific joints and fittings for skeletal furniture were collected and divided into 84 groups. The prepared numerical values were used as the data for statistical analysis. In the first step of the analysis, relationships were characterized between the studied features using the Spearmans rank correlation. On the basis of statistical analysis, the correctness of the obtained classifi cation was confirmed. Based on the analysis of the characteristics of the cluster and Spearmans correlation coefficient values, there was no reason to highlight any qualities as a component of project assumptions. Cluster analysis pointed to differences between groups, as well as groups having similar features. Against this background, a clear design assumption was built.