TY - GEN
T1 - Design refresh planning models for managing obsolescence
AU - Zheng, Liyu
AU - Terpenny, Janis
AU - Sandborn, Peter
AU - Nelson, Raymond
PY - 2012
Y1 - 2012
N2 - Fast moving technologies have caused high-tech components to have shortened life cycles, rendering them obsolete quickly. Obsolescence is a significant problem for systems with operational and support life that are much longer than the procurement lifetimes of their constituent components. Design refresh planning is a strategic way of managing obsolescence. Mathematical models are presented herein to determine the design refresh plan that minimizes total cost. The plan includes guidance on when to execute design refreshes (dates) and what obsolete/non-obsolete system components should be replaced at a specific design refresh. When data uncertainty is considered and obsolescence dates of the components are assumed to follow specific probability distributions, different solutions for executing design refreshes and the probabilities of adopting these solutions can be obtained. The final optimal cost becomes an expected value. An example of an electronic engine control unit (ECU) is included for demonstration of the developed models.
AB - Fast moving technologies have caused high-tech components to have shortened life cycles, rendering them obsolete quickly. Obsolescence is a significant problem for systems with operational and support life that are much longer than the procurement lifetimes of their constituent components. Design refresh planning is a strategic way of managing obsolescence. Mathematical models are presented herein to determine the design refresh plan that minimizes total cost. The plan includes guidance on when to execute design refreshes (dates) and what obsolete/non-obsolete system components should be replaced at a specific design refresh. When data uncertainty is considered and obsolescence dates of the components are assumed to follow specific probability distributions, different solutions for executing design refreshes and the probabilities of adopting these solutions can be obtained. The final optimal cost becomes an expected value. An example of an electronic engine control unit (ECU) is included for demonstration of the developed models.
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U2 - 10.1115/DETC2012-70743
DO - 10.1115/DETC2012-70743
M3 - Conference contribution
AN - SCOPUS:84884603606
SN - 9780791845042
T3 - Proceedings of the ASME Design Engineering Technical Conference
SP - 579
EP - 590
BT - ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012
T2 - ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012
Y2 - 12 August 2012 through 12 August 2012
ER -