Applying K-harmonic means clustering to the part-machine classification problem

Uenler A., Guengoer Z.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.36, sa.2, ss.1179-1194, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 2
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.eswa.2007.11.048
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1179-1194
  • Anahtar Kelimeler: Cellular manufacturing system, Group technology, K-harmonic means clustering, GROUP TECHNOLOGY, CELL-FORMATION, ALGORITHM, FAMILIES, MATRICES, MODEL
  • Gazi Üniversitesi Adresli: Evet

Özet

Cellular manufacturing system (CMS) is in application of group technology (GT) to the production environment. There arc many advantages of CMS over traditional manufacturing systems like reduction in set up-time, throughput time, etc. The grouping of machine cells and their associated part families so as to minimize the cost of material handling is a major step in CMS and it is called its cell formation (CF) problem. Cell formation is important to the effective performance Of Manufacturing. In this paper, all attempt has been made to effectively apply the K-harmonic means clustering technique to form machine cells and part families simultaneously, which we call K-harmonic means cell formation (KHM-CF). A set of 20 test problems with various sizes drawn from the literature arc used to test the performance of the proposed algorithm. Then, the results are compared with the optimal solution, and the efficacy of the proposed algorithms is discussed. The comparative study shows that the proposed KHM-CF algorithm improves the grouping efficacy for 70%, of the test problems, and gives the same results for 30% of the test problems. (C) 2007 Elsevier Ltd. All rights reserved.