TY - GEN
T1 - Architecting systems for optimal lifetime adaptability
AU - Engel, Avner
AU - Reich, Yoram
PY - 2013
Y1 - 2013
N2 - System architecture decisions such as the assignment of components to modules can have a large impact on the system's lifetime adaptability and cost. We broaden systems architecting theory by considering components' option values and interface costs when making the assignment decision. We propose an analytical model to identify the trade-offs between an inexpensive but less adaptable system and an expensive but adaptable one. We demonstrate the model with a realistic example of an Unmanned Air Vehicle (UAV) and use a genetic algorithm to identify an architecture that optimally balances cost and adaptability. Finally, we compensate variations stemming from uncertainties in the input data by means of sensitivity analysis, depicting optimal architectures via lattice charts. By way of example, we demonstrate that optimization provides considerably more cost effective lifetime architectures. In addition, conducting sensitivity analysis combined with lattice charts enable the selection of significantly more robust architectures when the input data is inherently imprecise. The approach received preliminary validation in several real industrial pilot cases.
AB - System architecture decisions such as the assignment of components to modules can have a large impact on the system's lifetime adaptability and cost. We broaden systems architecting theory by considering components' option values and interface costs when making the assignment decision. We propose an analytical model to identify the trade-offs between an inexpensive but less adaptable system and an expensive but adaptable one. We demonstrate the model with a realistic example of an Unmanned Air Vehicle (UAV) and use a genetic algorithm to identify an architecture that optimally balances cost and adaptability. Finally, we compensate variations stemming from uncertainties in the input data by means of sensitivity analysis, depicting optimal architectures via lattice charts. By way of example, we demonstrate that optimization provides considerably more cost effective lifetime architectures. In addition, conducting sensitivity analysis combined with lattice charts enable the selection of significantly more robust architectures when the input data is inherently imprecise. The approach received preliminary validation in several real industrial pilot cases.
KW - Architecture option theory
KW - Design for adaptability
KW - Design structure matrix
KW - Financial options theory
KW - S-curve
KW - Transaction cost theory
UR - http://www.scopus.com/inward/record.url?scp=84897667521&partnerID=8YFLogxK
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:84897667521
SN - 9781904670476
VL - 4 DS75-04
SP - 149
EP - 158
BT - Proceedings of the 19th International Conference on Engineering Design
T2 - 19th International Conference on Engineering Design, ICED 2013
Y2 - 19 August 2013 through 22 August 2013
ER -