NDLI: Modeling and optimization of kanban controlled manufacturing system using improved-Group method of data handling

Content Provider	IEEE Xplore Digital Library
Author	Pournasir, M. Jahangir Alam, M. Marthandan, G.
Copyright Year	2011
Description	Author affiliation: Dept. Faculty of Information Technology, Multimedia University, Cyberjaya, Malaysia (Pournasir, M.; Jahangir Alam, M.) \|\| Dept. Faculty of Management, Multimedia University, Cyberjaya, Malaysia (Marthandan, G.)
Abstract	One of the important sub-components in just-in-time (JIT) systems is number of optimal kanabn cards. Although a number of techniques exist for determining the number of kanbans, they have some shortcomings for operationalizing the kanban setting problem. In this paper, intelligent optimization method replace to old technique in kanban system to generate a structure that described the relationship between the operational factors and the number of kanbans with more accurately. We describe how the improved-Group method data handling algorithm can be used to improve the modeling and prediction accuracy when it is applied to kanban setting in just in time system.
Starting Page	321
Ending Page	326
File Size	715020
Page Count	6
File Format	PDF
ISBN	9781467300995
e-ISBN	9781467301022
DOI	10.1109/SCOReD.2011.6148758
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-19
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Kanban Computational modeling Neurons Just-In-Time Group Method Data Handling Genetic Algorithm Polynomials Optimization Testing Genetic algorithms
Content Type	Text
Resource Type	Article

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