Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Principal component analysis model for machine-part cell formation
  problem in group technology   In this paper, we consider the problem of forming machine cell in cellular
manufacturing (CM). The major problem in the design of a CM system is to
identify the part families and machine groups and consequently to form
manufacturing cells. The aim of this article is to formulate a multivariate
approach based on a correlation analysis for solving cell formation problem.
The proposed approach is carried out in two phases. In the first phase, the
correlation matrix is used as an original similarity coefficient matrix. In the
second phase, Principal Component Analysis (PCA) is applied to find the
eigenvalues and eigenvectors on the correlation similarity matrix. A scatter
plot analysis as a cluster analysis is applied to make machine groups while
maximizing correlation between elements. A numerical example for the design of
cell structures is provided in order to illustrate the proposed approach. The
results of a comparative study based on multiple performance criteria show that
the present approach is very effective, efficient and practical

27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
1
The categories of this paper are: cs
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess