Variation propagation modeling and analysis at preliminary design phase of multi‐station assembly systems

Abstract

PurposeDimensional variation management is a major challenge in multi‐station sheet metal assembly processes involving complex products such as automotive body and aircraft fuselage assemblies. Very few studies have explored it at a preliminary design phase taking into consideration effects of part deformation on variation propagation, since early design phase involves the development of imprecise design models with scant or incomplete product and process knowledge. The objective of this paper is to present a variation model which can be built into the preliminary design phase taking into consideration all of the existing interactions between flexible parts and tools in multi‐station sheet metal assembly process.Design/methodology/approachThe paper addresses this problem by first, presenting a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; second, determining the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and third, utilizing this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.FindingsThis paper presents a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; determines the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and utilizes this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.Originality/valueA truck cab assembly is presented to demonstrate the advantages of the proposed model over the state‐of‐the‐art approach used in industry for sheet metal assemblies.

Assembly process optimization for reducing the dimensional error of antenna assembly with abundant rivets

“…On one hand, the dimensional issues in the automotive body assemblies are comprehensively studied from the mechanical tolerance analyses to a series of fruits relating to the stream-of-variation analysis (SOVA) (Chase and Greenwood 1988;Ceglarek et al 2004;Cai 2008;Huang et al 2007;Huang and Kong 2008;Wang and Ceglarek 2009), and to the dimensional analyses for self-pierce riveted sheets (Cai et al 2005;Masters et al 2011). Among these researches, many insightful attempts target to more complex dimensional propagations, e.g.…”

“…Among these researches, many insightful attempts target to more complex dimensional propagations, e.g. the three-dimensional (3D) rigid SOVA model (Huang et al 2007), the variation propagation model that considers the joining and releasing schemes especially for the preliminary design (Wang and Ceglarek 2009), the dimensional analysis taking the experimentally tested rivet distortions (Cai et al 2005), and the global finite element (FE) simulation projecting the riveted distortion yielded from the local FE analysis (Masters et al 2011). On the other hand, the mechanical strength and fatigue problems are mainly focused on for the aircraft structure safety that usually takes the local rivet joint as the crucial part Manes et al 2011;Aman et al 2013).…”

Variation modeling of aeronautical thin-walled structures with multi-state riveting

“…Furthermore, they studied of the contact problem of the thin-walled metal structure assemblies, developed a systematic procedure of the non-linear dimensional variation analysis for the thin-walled metal structure assemblies by using the contact finite element method [26]. Wang and Ceglarek [27] represented a beam-based model based on the assumption that only selected critical points/features in the assembly are important to variation. They also deduced a state-of-the-art variation propagation model by integrating the influence of join error on variation propagation and incorporating them into a vector-based model.…”

Object Shape Error Response Using Bayesian 3-D Convolutional Neural Networks for Assembly Systems With Compliant Parts

“…This study was supported by the UK EPSRC project EP/K019368/1: "Self-Resilient Reconfigurable Assembly Systems with Inprocess Quality Improvement", the UKRI open access block grant and the WMG-IIT scholarship. (Corresponding author: Sumit Sinha) been shown to have limitations in their applicability to complex, high dimensional and nonlinear systems [2] as these used linear models between process parameters and measurements of product dimensional quality for both systems with rigid [3] and complaint parts [4]. Ceglarek et al [5] used CAD-based variation patterns and a fault matching technique which combined principal component analysis and pattern similarity for fault diagnosis.…”