Optimal process design in selective assembly when components with smaller variance are manufactured at three shifted means

Abstract

Selective assembly is an effective approach for improving the quality of a product that is composed of two mating components, when the quality characteristic of the product is the clearance between the mating components. In this approach, the components are sorted into several groups according to their dimensions, and the product is assembled by randomly selecting mating components from corresponding groups. A number of previous studies focused on equal width partitioning schemes, in which the dimensional distributions of the two components are partitioned so that all groups have equal widths. When there is a large difference between the variances of the two component dimensions, equal width partitioning will result in a large number of surplus components due to differences between the numbers of components in corresponding groups. Some authors have proposed a method of manufacturing the component with smaller variance at three shifted means to cope with this difficulty. In the present paper, an optimal manufacturing mean design that minimises the number of surplus components is derived. It is shown that the use of the optimal design considerably reduces the number of surplus components compared with using another previously proposed manufacturing mean design and the no-shift design.

Optimization of selective assembly and adaptive manufacturing by means of cyber-physical system based matching

“…Regarding this issue, various statistical methods have been developed to find optimal binning strategies, e.g. by Mease et al [2], Matsuura et al [3] or Kannan et al [6]. Fang et al [7] propose methods based on classes with equal probabilities.…”

“…of crankshafts, pistons or electric drive rotors) [2][3][4], the requirements to the product quality in more and more cases approach the technological limits of the potential manufacturing processes. In particular, for assemblies with very small tolerances, the manufacturing processes of the components are either not capable of guaranteeing the required precision or only at very high cost.…”

“…Schmitt et al [16] developed a self-optimization method for the adaption of manufacturing parameters in a process chain. Arai [17], Codellani et al [3] and Kayasa et al [18] developed process models to analyze various effects of production systems with selective assembly and adaptive manufacturing such as machine reliability or work in progress. While most of the approaches are restricted to the matching of only two components, some also deal with three ones, e.g.…”

An approach to minimizing surplus parts in selective assembly with genetic algorithm

“…According to the independent event probability formula given in equation (10), the total assembly success rate of the product with multiple dimension chains is given in equation (11) …”

Straight-Build Assembly Optimization: A Method to Minimize Stage-by-Stage Eccentricity Error in the Assembly of Axisymmetric Rigid Components (Two-Dimensional Case Study)

“…Based on the measurement data, correction is applied in the assembly using tooling adjustment. Another approach of assembling two components based on measurement data of the components known as "selective assembly" is studied by various researchers [21][22][23][24], Selective assembly can only be applied to high volume assembly products, where mating components are measured and the measurement data collected. The measurement data are then divided into groups.…”