NDLI: A new linguistic based algorithm for creating manufacturing cell

Content Provider	Springer Nature Link
Author	Roy, Nirghar Mostafaeipour, Ali
Copyright Year	2014
Abstract	This paper presents a new approach for modeling formation of machine groups and the associated parts families using a linguistic model. The method outlines a hierarchical approach for deciding the number of clusters/machine groups. The solution is improved further by utilizing a genetic algorithm with the objective of decreasing actual job-shop inter-cell distance moved. A unique feature of the proposed method is that it recognizes the operation sequence of manufacturing the parts specified in the process sheets. The concept of null machine is introduced in the linguistic model to calculate the dissimilarity among parts. The movement of parts can be either flow type or random job-shop type for the discrete manufacturing shop, required to be partitioned. Back flow/tracking are minimized. The flexibility of changing number of machine groups is also built-in the model. The model has been found useful and flexible enough to solve any realistic discrete manufacturing system and is found to work comfortably in medium to large job shop situations when the machine part incidence matrix shows sparse density.
Starting Page	133
Ending Page	138
Page Count	6
File Format	PDF
ISSN	19552513
Journal	International Journal on Interactive Design and Manufacturing (IJIDeM)
Volume Number	8
Issue Number	2
e-ISSN	19552505
Language	English
Publisher	Springer Paris
Publisher Date	2014-04-05
Publisher Place	Paris
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Linguistic Algorithm Manufacturing cell Group technology Levenshtein Engineering Engineering Design Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design Electronics and Microelectronics, Instrumentation Industrial Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Modeling and Simulation

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