Research Papers: Design for Manufacture and the Life Cycle

Determining Granularity of Changeable Manufacturing Systems Using Changeable Design Structure Matrix and Cladistics

[+] Author and Article Information
Tarek AlGeddawy

Mechanical and Industrial Engineering,
University of Minnesota Duluth,
1305 Ordean Court,
Duluth, MN 55812
e-mail: geddawy@d.umn.edu

Hoda ElMaraghy

Intelligent Manufacturing Systems Center,
University of Windsor,
2285 Wyandotte West,
Windsor, ON N9B 1K3, Canada
e-mail: hae@uwindsor.ca

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received December 27, 2013; final manuscript received December 26, 2014; published online February 6, 2015. Assoc. Editor: Rikard Söderberg.

J. Mech. Des 137(4), 041702 (Apr 01, 2015) (12 pages) Paper No: MD-13-1592; doi: 10.1115/1.4029515 History: Received December 27, 2013; Revised December 26, 2014; Online February 06, 2015

Changeable manufacturing systems offer a high level of adaptability and agility in response to product and market changes. They are characterized by modularity and scalability, which are derivatives of system granularity. Determining the best granularity level of a changeable system helps maximize its ability to change throughout its planned utilization horizon. A new model and two case studies are presented to show: (1) new changeability design structure matrix (CDSM) to express all planned system configurations, (2) cladistics analysis to hierarchically cluster CDSM into component modules, and (3) new granularity index (GI) to determine the best system granularity level which balances the merits of manufacturing system modularity with integration.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Fig. 1

Granularity levels of an automobile (modified from Ref. [28])

Grahic Jump Location
Fig. 2

Cladistics analysis of a group of work-pieces

Grahic Jump Location
Fig. 3

IDEF0 representation of the SCA model

Grahic Jump Location
Fig. 4

The four DSM scenarios of two components in a changeable manufacturing system

Grahic Jump Location
Fig. 5

The generation of a CDSM from system configuration DSMs

Grahic Jump Location
Fig. 6

The effect of importance of integration versus segregation and existence of system components on GI

Grahic Jump Location
Fig. 7

The required configurations of the studied reconfigurable machine-tool and the corresponding CDSM analysis

Grahic Jump Location
Fig. 8

Cladistic and changeability analysis of the machine-tool

Grahic Jump Location
Fig. 9

Generic structure of an iFactory station

Grahic Jump Location
Fig. 10

The families of products produced by each iFactory system configuration

Grahic Jump Location
Fig. 11

The four anticipated system configurations of the iFactory

Grahic Jump Location
Fig. 12

Graph representation of the four planned iFactory configurations

Grahic Jump Location
Fig. 13

DSM representation of four iFactory configurations and the aggregated CDSM

Grahic Jump Location
Fig. 14

The cladogram resulting from cladistics analysis of the CDSM

Grahic Jump Location
Fig. 15

The suggested integrated system module for a better system changeability

Grahic Jump Location
Fig. 16

The four anticipated iFactory configurations using the recommended integrated module (9)

Grahic Jump Location
Fig. 17

Different granularity levels effect on GI




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In