Research Article | OPEN ACCESS
Assembly Line Efficiency Measurement and Line Balancing-A Case Study on Automobile Cluster Assembly Line
S. Sathish and A.R. Lakshmanan
Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India
Research Journal of Applied Sciences, Engineering and Technology 2015 8:651-654
Received: November 7, 2014 | Accepted: December 18, 2014 | Published: March 15, 2015
Abstract
Factors which affect the performance of assembly lines are difficult to be assessed and solved by mathematical model. This study attempts a practical solution to the stochastic Automobile Instrument cluster assembly line balancing problem. The factors influencing the assembly time in manufacturing systems are analysed, the precedence diagram model for the above assembly line is built and the effects of factors on the line balancing problem are considered. Lastly, the balancing results of the deterministic model are compared to the real world data from industries for the effective usage of the altered model.
Keywords:
Assembly line balancing techniques, automobile instrument cluster assembly line, kilbridge wester method, stochastic factors,
References
-
Amen, M., 2000. An exact method for cost-oriented assembly line balancing. Int. J. Prod. Econ., 64: 187-195.
CrossRef -
Baybars, I., 1986. A survey of exact algorithms for the simple assembly line balancing problem. Manage. Sci., 32: 909-932.
CrossRef -
Brudaru, O., 2010. Dynamic segregative genetic algorithm for assembly lines balancing. Proceeding of 12th International Symposium on Date of Conference on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC).
CrossRef -
Everitt, B.S., 1974. Cluster Analysis. 1st Edn., John Wiley and Sons, New York.
-
Khouja, M., D.E. Booth, M. Suh and J.K., Mahaney Jr., 2000. Statistical procedures for task assignment and robot selection in assembly cells. Int. J. Comp. Integ. M., 13(2): 95-106.
CrossRef -
Levitin, G., J. Rubinovitz and B. Shnits, 2004. A genetic algorithm for robotic assembly line balancing. Eur. J. Oper. Res., 168(3): 811-825.
CrossRef -
Mahalanobis, P.C., 1936. On the generalized distance in statistics. P. Natl. Inst. Sci. India, 12: 49-55.
-
Mahto, D. and A. Kumar, 2012. An Empirical investigation of assembly line balancing techniques and optimized implementation approach for efficiency improvements. Global J. Res. Eng. Mech. Mech. Eng., 12(3).
-
Roher, M.W., 2000. Seeing is believing: The importance of visualization in manufacturing simulation. Proceeding of Winter Simulation Conference. Orlando, FL, U.S.A., 1: 1211-1216.
-
Rosenberg, O. and H. Ziegler, 1992. A comparison of heuristic algorithms for cost-oriented assembly line balancing. Z. Oper. Res., 36: 477-495.
CrossRef -
Schaefer, D., C. Borgmann and D. Sheffter, 2001. Factory planning and the potential of virtual reality. Proceeding of AVRII and CONVR. Gothenburg, Sweden, October 4th-5th 2001.
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
![](http://www.maxwellsci.com/images/RJASET-maxw.jpg) |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
![Submit Manuscript](../images/sub.jpg) |
Information |
|
|
|
Sales & Services |
|
|
|