Burn-in is a widely used technique to screen out defective components before they are put into field operation. In this paper, we propose a burn-in policy for the components from a heterogeneous population composed of ordered subpopulations. Assume that components can be minimally repaired when the failure occurs. We consider the total number of minimal repairs observed during burn-in process as a screening rule to remove defective components with poor reliability performance. First, we carry out the probabilistic analysis of the screening policy to show the effectiveness of burn-in. Second, we obtain the optimal burn-in settings which minimize the mean total cost or maximize the probability of passing the mission period. Finally, we give an example to illustrate the proposed model.
KuoWKuoY. Facing the headaches of early failures: a state-of-the-art review of burn-in decisions. Proc IEEE1983; 71(11): 1257–1266.
2.
KuoW. Reliability enhancement through optimal burn-in. IEEE Trans Reliab1984; 33(2): 145–156.
3.
HuangWZhouJNingJ. Optimal burn-in and preventive maintenance modeling with competing failure processes. J Shanghai Jiaotong Univ2015; 20(3): 293–297.
4.
ChaJHBadíaFG. An information-based burn-in procedure for minimally repaired components. Appl Stoch Models Bus Ind2016; 32(4): 511–525.
5.
MosayebiomshiEShemehsavarS. An optimal burn-in policy based on a degradation model. Appl Stoch Models Bus Ind2018; 34(4): 486–498.
6.
HuJSunQYeZS. Sequential degradation-based burn-in test with multiple periodic inspections. Front Eng Manage2021; 8(4): 519–530.
7.
MoritaLHMTomazellaVLFerreiraPH. Optimal burn-in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas. Appl Stoch Models Bus Ind2021; 37(3): 612–627.
8.
KimKOKuoW. Optimal burn-in for maximizing reliability of repairable non-series systems. Eur J Oper Res2009; 193(1): 140–151.
9.
ChaJHFinkelsteinM. Stochastically ordered subpopulations and optimal burn-in procedure. IEEE Trans Reliab2010; 59(4): 635–643.
10.
UlusoySKMazzuchiTAPerlsteinD. Bayesian calculation of optimal burn-in time using the joint criteria of cost and delivered reliability. Qual Reliab Eng Int2010; 27(4): 569–580.
11.
YuanTBaeSJZhuX. A Bayesian approach to degradation-based burn-in optimization for display products exhibiting two-phase degradation patterns. Reliab Eng Syst Saf2016; 155: 55–63.
12.
LyuYZhangYChenK. Optimal multi-objective burn-in policy based on time-transformed Wiener degradation process. IEEE Access2019; 7: 73529–73539.
13.
BlockHWLiYSavitsTH. Initial and final behavior of failure rate functions for mixtures and systems. J Appl Probab2003; 40(3): 721–740.
14.
KlutkeGKiesslerPCWortmanMA. A critical look at the bathtub curve. IEEE Trans Reliab2003; 52(1): 125–129.
15.
ChaJHFinkelsteinM. Burn-in and the performance quality measures in continuous heterogeneous populations. Proc I MechE, Part O: J Risk and Reliability2012; 226(4): 417–425.
16.
TsengSTTangJKuIH. Determination of burn-in parameters and residual life for highly reliable products. Naval Res Logist2003; 50(1): 1–14.
ChaJHFinkelsteinMLevitinG. Optimal warranty policy with inspection for heterogeneous, stochastically degrading items. Eur J Oper Res2021; 289(3): 1142–1152.
19.
XiangYCoitDWFengQ. Optimal burn-in for n-subpopulations with stochastic degradation. In: IEEE international conference on quality, reliability, risk, maintenance, and safety engineering, Xi’an, China, 17–19 June 2011, pp.148–152. New York: IEEE.
20.
XiangYCoitDWFengQ. n Subpopulations experiencing stochastic degradation: reliability modeling, burn-in, and preventive replacement optimization. IIE Trans2013; 45(4): 391–408.
21.
XiangYCoitDWFengQ. Accelerated burn-in and condition-based maintenance for n-subpopulations subject to stochastic degradation. IIE Trans2014; 46(10): 1093–1106.
22.
XiangYCoitDWZhuZ. A multi-objective joint burn-in and imperfect condition-based maintenance model for degradation-based heterogeneous populations. Qual Reliab Eng Int2016; 32(8): 2739–2750.
23.
ChaJH. On a better burn-in procedure. J Appl Probab2000; 37(4): 1099–1103.
24.
JaSSKulkarniVGMitraA. A nonrenewable minimal-repair warranty policy with time-dependent costs. IEEE Trans Reliab2001; 50(4): 346–352.
25.
ChaJH. On optimal burn-in procedures-a generalized model. IEEE Trans Reliab2005; 54(2): 198–206.
26.
LingXLWangMWeiYZ. An optimal screening policy for heterogeneous items with minimal repairs. Commun Stat Theory Methods. Epub ahead of print 20July2023. DOI: 10.1080/03610926.2023.2233150.
27.
AscherHFeingoldH. Repairable systems reliability. New York: Marcel Dekker, 1985.
28.
BrownBLiuBMclntyreS, et al. Reliability evaluation of repairable systems considering component heterogeneity using frailty model. Proc I MechE, Part O: J Risk and Reliability2023; 237(4): 654–670.
29.
ZhaiQYeZSYangJ. Measurement errors in degradation-based burn-in. Reliab Eng Syst Saf2016; 150: 126–135.
30.
ShafieeMChukovaSYunWY. Optimal burn-in and warranty for a product with post-warranty failure penalty. Int J Adv Manuf Technol2014; 70: 297–307.
