  This article deals with Part family formation problem which is believed to be
moderately complicated to be solved in polynomial time in the vicinity of Group
Technology (GT). In the past literature researchers investigated that the part
family formation techniques are principally based on production flow analysis
(PFA) which usually considers operational requirements, sequences and time.
Part Coding Analysis (PCA) is merely considered in GT which is believed to be
the proficient method to identify the part families. PCA classifies parts by
allotting them to different families based on their resemblances in: (1) design
characteristics such as shape and size, and/or (2) manufacturing
characteristics (machining requirements). A novel approach based on simulated
annealing namely SAPFOCS is adopted in this study to develop effective part
families exploiting the PCA technique. Thereafter Taguchi's orthogonal design
method is employed to solve the critical issues on the subject of parameters
selection for the proposed metaheuristic algorithm. The adopted technique is
therefore tested on 5 different datasets of size 5 {\times} 9 to 27 {\times} 9
and the obtained results are compared with C-Linkage clustering technique. The
experimental results reported that the proposed metaheuristic algorithm is
extremely effective in terms of the quality of the solution obtained and has
outperformed C-Linkage algorithm in most instances.
