Research Papers

Change Propagation Analysis in Complex Technical Systems

[+] Author and Article Information
Monica Giffin, Gergana Bounova

Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, MA 02139

Olivier de Weck1

Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, MA 02139deweck@mit.edu

Rene Keller, Claudia Eckert, P. John Clarkson

Engineering Design Centre, University of Cambridge, UK


Corresponding author.

J. Mech. Des 131(8), 081001 (Jul 09, 2009) (14 pages) doi:10.1115/1.3149847 History: Received June 16, 2007; Revised March 24, 2009; Published July 09, 2009

Understanding how and why changes propagate during engineering design is critical because most products and systems emerge from predecessors and not through clean sheet design. This paper examines a large data set from industry including 41,500 change requests that were generated during the design of a complex sensor system spanning a period of 8 years. In particular, the networks of connected parent, child, and sibling changes are resolved over time and mapped to 46 subsystem areas of the sensor system. These change networks are then decomposed into one-, two-, and three-node motifs as the fundamental building blocks of change activity. A statistical analysis suggests that only about half (48.2%) of all proposed changes were actually implemented and that some motifs occur much more frequently than others. Furthermore, a set of indices is developed to help classify areas of the system as acceptors or reflectors of change and a normalized change propagation index shows the relative strength of each area on the absorber-multiplier spectrum between −1 and +1. Multipliers are good candidates for more focused change management. Another interesting finding is the quantitative confirmation of the “ripple” change pattern previously proposed. Unlike the earlier prediction, however, it was found that the peak of cyclical change activity occurred late in the program driven by rework discovered during systems integration and functional testing.

Copyright © 2009 by American Society of Mechanical Engineers
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Figure 1

System block diagram (46 areas)

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Figure 2

Parent-child and sibling change relationships

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Figure 3

Change magnitude distribution

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Figure 4

System structural DSM (ordered 1–46)

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Figure 5

Propagated change versus substituted change

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Figure 6

Overlay of baseline DSM (Fig. 4) with change propagation frequency matrix of actually implemented changes (Table 4)

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Figure 7

Largest change network: 2566 related changes

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Figure 8

Time-lapse analysis (in four increments from top left to lower right) for the fourth largest change network with 87 change requests

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Figure 9

Change network with 11 connected change requests (11-CR) from the larger data set. The initial change request is 32,496 (rejected) in the middle of the graph.

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Figure 10

1-motif change patterns

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Figure 11

Parent-child 2-motif family

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Figure 12

Sibling 2-motif family

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Figure 13

Set of 3-motif change request families

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Figure 14

Expanded PSP family of 3-motif change requests

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Figure 15

Area classification for CRI and CAI (entire data set)

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Figure 16

CPI spectrum between −1 and 1 with areas mapped

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Figure 17

Change propagation tree focused on changes propagating from Area 1 to Area 32 (CPM tool)

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Figure 18

Change requests written over time (number written per month)

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Figure 19

Change patterns predicted in Eckert (2)




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