Enhancing the Largest Set Rule for Assembly Line Balancing Through the Concept of Bi-Directional Work Relatedness

Konstantinos N. Genikomsakis; Vassilios D. Tourassis

doi:10.20965/jaciii.2010.p0353

single-jc.php

« previous

JACIII Vol.14 No.4 pp. 353-363

doi: 10.20965/jaciii.2010.p0353

(2010)

Paper:

Views over last 60 days: 835

Enhancing the Largest Set Rule for Assembly Line Balancing Through the Concept of Bi-Directional Work Relatedness

Konstantinos N. Genikomsakis and Vassilios D. Tourassis

Department of Production Engineering and Management, School of Engineering, Democritus University of Thrace, GR-67100, Kimmeria, Xanthi, Greece

Received:

September 16, 2009

Accepted:

January 21, 2010

Published:

May 20, 2010

Keywords:

assembly line balancing, work relatedness

Abstract

The process of optimally assigning the timed tasks required to assemble a product to an ordered sequence of workstations is known as the Assembly Line Balancing (ALB) problem. Typical approaches to ALB assume a strict mathematical posture and mostly treat it as a combinatorial optimization problem with the objective of minimizing the idle time across the workstations, while satisfying precedence constraints. The actual nature of the tasks assigned is seldom taken into consideration. While this approach may yield satisfactory cycle time results on paper, it often leads to inconvenient task assignments in an actual work environment. It has been postulated in the literature that assigning groups of related tasks to the same workstation may lead to assembly lines that exhibit increased robustness in real-world situations at the expense of a slightly increased cycle time. The prototypical example of such an approach, Agrawal’s Largest Set Rule (LSR), utilizes backward work relatedness to assign a set of cohesive tasks to the proper workstation. In this paper, we enhance the performance of the original LSR algorithm through the concept of bi-directional work relatedness, where backward and forward relationships are taken into consideration for task assignments. The proposed concept leads to comparable cycle time and improved work relatedness. Applying this novel concept to a benchmark ALB problem demonstrates the feasibility and applicability of the proposed approach.

Cite this article as:

K. Genikomsakis and V. Tourassis, “Enhancing the Largest Set Rule for Assembly Line Balancing Through the Concept of Bi-Directional Work Relatedness,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.4, pp. 353-363, 2010.

Data files:

References

[1] S. O. Tasan and S. Tunali, “A review of the current applications of genetic algorithms in assembly line balancing,” J. of Intelligent Manufacturing, Vol.19, No.1, pp. 49-69, 2008.
[2] C. Becker and A. Scholl, “A survey on problems and methods in generalized assembly line balancing,” European J. of Operational Research, Vol.168, No.3, pp. 694-715, 2006.
[3] A. Scholl and C. Becker, “State-of-the-art exact and heuristic solution procedures for simple assembly line balancing,” European J. of Operational Research, Vol.168, No.3, pp. 666-693, 2006.
[4] P. K. Agrawal, “The related activity concept in assembly line balancing,” Int. J. of Production Research, Vol.23, No.2, pp. 403-421, 1985.
[5] D. Sly and P. Gopinath, “A Practical Approach to solving Multi-objective Line Balancing Problem,”
Available at: http://www.proplanner.com/Documents/Support/LB/LBTechnical.pdf. Last access: August 2009.
[6] E. Falkenauer, “Line balancing in the real world,” In A. Bouras, B. Gurumoorthy and R. Sudarsan (eds), Proc. of the Int. Conf. on Product Life cycle Management PLM’05, pp. 360-370, Geneva: Inderscience, 2005.
[7] A. Scholl, “Balancing and sequencing of assembly lines,” New York: Physica-Verlag, 1999.
[8] Y. K. Kim, Y. J. Kim, and Y. Kim, “Genetic algorithms for assembly line balancing with various objectives,” Computers and Industrial Engineering, Vol.30, No.3, pp. 397-409, 1996.
[9] T. O. Lee, Y. Kim, and Y. K. Kim, “Two-sided assembly line balancing to maximize work relatedness and slackness,” Computers and Industrial Engineering, Vol.40, No.3, pp. 273-292, 2001.
[10] A. Shtub and E. M. Dar-El, “A methodology for the selection of assembly systems,” Int. J. of Production Research, Vol.27, pp. 175-186, 1989.
[11] S. T. Hackman, M. J. Magazine, and T. S. Wee, “Fast, Effective Algorithms for Simple Assembly Line Balancing Problems,” Operations Research, Vol.37, No.6, pp. 916-924, 1989.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] S. O. Tasan and S. Tunali, “A review of the current applications of genetic algorithms in assembly line balancing,” J. of Intelligent Manufacturing, Vol.19, No.1, pp. 49-69, 2008.

[2] [2] C. Becker and A. Scholl, “A survey on problems and methods in generalized assembly line balancing,” European J. of Operational Research, Vol.168, No.3, pp. 694-715, 2006.

[3] [3] A. Scholl and C. Becker, “State-of-the-art exact and heuristic solution procedures for simple assembly line balancing,” European J. of Operational Research, Vol.168, No.3, pp. 666-693, 2006.

[4] [4] P. K. Agrawal, “The related activity concept in assembly line balancing,” Int. J. of Production Research, Vol.23, No.2, pp. 403-421, 1985.

[5] [5] D. Sly and P. Gopinath, “A Practical Approach to solving Multi-objective Line Balancing Problem,”
Available at: http://www.proplanner.com/Documents/Support/LB/LBTechnical.pdf. Last access: August 2009.

[6] [6] E. Falkenauer, “Line balancing in the real world,” In A. Bouras, B. Gurumoorthy and R. Sudarsan (eds), Proc. of the Int. Conf. on Product Life cycle Management PLM’05, pp. 360-370, Geneva: Inderscience, 2005.

[7] [7] A. Scholl, “Balancing and sequencing of assembly lines,” New York: Physica-Verlag, 1999.

[8] [8] Y. K. Kim, Y. J. Kim, and Y. Kim, “Genetic algorithms for assembly line balancing with various objectives,” Computers and Industrial Engineering, Vol.30, No.3, pp. 397-409, 1996.

[9] [9] T. O. Lee, Y. Kim, and Y. K. Kim, “Two-sided assembly line balancing to maximize work relatedness and slackness,” Computers and Industrial Engineering, Vol.40, No.3, pp. 273-292, 2001.

[10] [10] A. Shtub and E. M. Dar-El, “A methodology for the selection of assembly systems,” Int. J. of Production Research, Vol.27, pp. 175-186, 1989.

[11] [11] S. T. Hackman, M. J. Magazine, and T. S. Wee, “Fast, Effective Algorithms for Simple Assembly Line Balancing Problems,” Operations Research, Vol.37, No.6, pp. 916-924, 1989.