TY - JOUR
T1 - Degradation-based burn-in with preventive maintenance
AU - Ye, Zhi-Sheng
AU - Shen, Yan
AU - Xie, Min
PY - 2012/9/1
Y1 - 2012/9/1
N2 - As many products are becoming increasingly more reliable, traditional lifetime-based burn-in approaches that try to fail defective units during the test require a long burn-in duration, and thus are not effective. Therefore, we promote the degradation-based burn-in approach that bases the screening decision on the degradation level of a burnt-in unit. Motivated by the infant mortality faced by many Micro-Electro-Mechanical Systems (MEMSs), this study develops two degradation-based joint burn-in and maintenance models under the age and the block based maintenances, respectively. We assume that the product population comprises a weak and a normal subpopulations. Degradation of the product follows Wiener processes with linear drift, while the weak and the normal subpopulations possess distinct drift parameters. The objective of joint burn-in and maintenance decisions is to minimize the long run average cost per unit time during field use by properly choosing the burn-in settings and the preventive replacement intervals. An example using the MEMS devices demonstrates effectiveness of these two models. © 2012 Elsevier B.V. All rights reserved.
AB - As many products are becoming increasingly more reliable, traditional lifetime-based burn-in approaches that try to fail defective units during the test require a long burn-in duration, and thus are not effective. Therefore, we promote the degradation-based burn-in approach that bases the screening decision on the degradation level of a burnt-in unit. Motivated by the infant mortality faced by many Micro-Electro-Mechanical Systems (MEMSs), this study develops two degradation-based joint burn-in and maintenance models under the age and the block based maintenances, respectively. We assume that the product population comprises a weak and a normal subpopulations. Degradation of the product follows Wiener processes with linear drift, while the weak and the normal subpopulations possess distinct drift parameters. The objective of joint burn-in and maintenance decisions is to minimize the long run average cost per unit time during field use by properly choosing the burn-in settings and the preventive replacement intervals. An example using the MEMS devices demonstrates effectiveness of these two models. © 2012 Elsevier B.V. All rights reserved.
KW - Burn-in
KW - Degradation
KW - Long run average cost
KW - Preventive replacement
KW - Wiener process
UR - http://www.scopus.com/inward/record.url?scp=84861093941&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84861093941&origin=recordpage
U2 - 10.1016/j.ejor.2012.03.028
DO - 10.1016/j.ejor.2012.03.028
M3 - RGC 21 - Publication in refereed journal
SN - 0377-2217
VL - 221
SP - 360
EP - 367
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -