Skip to main content
Log in

On Designing Time-Censored Step-Stress Life Test for the Burr Type-XII Distribution

  • Published:
Strength of Materials Aims and scope

This article presents the optimal designing of time step-stress partially accelerated life test (PALT) under censored data from two-parameter Burr type-XII distribution. The maximum likelihood (ML) approach is used to obtain point and interval estimations of the model parameters. Moreover, optimum test plans for time step-stress PALT are optimally developed. The adopted optimality criterion is the minimization of the generalized asymptotic variance of the ML estimators of the model parameters. For illustration, numerical examples are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. M. H. Degroot and P. K. Goel, “Bayesian estimation and optimal designs in partially accelerated life testing,” Nav. Res. Logist. Q., 26, No. 2, 223–235 (1979).

    Article  Google Scholar 

  2. D. S. Bai, S. W. Chung, and Y. R. Chun, “Optimal design of partially accelerated life tests for the lognormal distribution under type I censoring,” Reliab. Eng. Syst. Safe., 40, No. 1, 85–92 (1993).

    Article  Google Scholar 

  3. N. Ahmad and A. Islam, “Optimal accelerated life test designs for Burr type XII distributions under periodic inspection and type I censoring,” Nav. Res. Log., 43, No. 8, 1049–1077 (1996).

    Article  Google Scholar 

  4. A. A. Abdel-Ghaly, E. H. El-Khodary, and A. A. Ismail, “Maximum likelihood estimation and optimal design in step partially accelerated life tests for the Pareto distribution with type-I censoring,” in: Proc. of the 14th Annual Conf. on Statistics and Computer Modeling in Human and Social Sciences, Cairo University (2002), pp. 16–29.

  5. H. M. Aly and A. A. Ismail, “Optimum simple time-step stress plans for partially accelerated life testing with censoring,” Far East J. Theor. Stat., 24, No. 2, 175–200 (2008).

    Google Scholar 

  6. A. M. Abd-Elfattah, A. S. Hassan, and S. G. Nassr, “Estimation in step-stress partially accelerated life tests for the Burr type XII distribution using type I censoring,” Stat. Methodol., 5, No. 6, 502–514 (2008).

    Article  Google Scholar 

  7. A. A. Ismail, “On designing step-stress partially accelerated life tests under failure- censoring scheme,” P. I. Mech. Eng. O - J. Ris., 227, No. 6, 662–670 (2013).

    Google Scholar 

  8. Ali A. Ismail, “On designing constant-stress partially accelerated life tests under time-censoring,” Strength Mater., 46, No. 1, 132–139 (2014).

    Article  Google Scholar 

  9. A. A. Ismail, “Optimum partially accelerated life test plans with progressively type I interval-censored data,” Sequential Anal., 34, No. 2, 135–147 (2015).

    Article  Google Scholar 

  10. Ali A. Ismail, “A. A. Ismail, “Optimum failure-censored step-stress life test plans for the Lomax distribution,” Strength Mater., 48, No. 3, 437–443 (2016).

  11. Ali A. Ismail, “Planning step-stress life tests for the generalized Rayleigh distribution under progressive type-II censoring with binomial removals,” Strength Mater., 49, No. 2, 292–306 (2016).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali A. Ismail.

Additional information

Translated from Problemy Prochnosti, No. 5, pp. 107 – 120, September – October, 2017.

Appendices

Appendix A

Derivation of the second-order partial derivatives:

$$ {\displaystyle \begin{array}{c}\frac{\partial^2\ln L}{\partial^2{\upbeta}^2}=-\frac{n_a}{\upbeta^2}\left(c-1\right)\sum \limits_{i=1}^n{\updelta}_{2i}\left({y}_i-\uptau \right)\frac{\left({y}_i-\uptau \right)}{{\left(\uptau +\upbeta \left({y}_i-\uptau \right)\right)}^2}\\ {}-\left(K+1\right)c\sum \limits_{i=1}^n\left({y}_i-\uptau \right){\updelta}_{2i}\left[\left({y}_i-\uptau \right)\left(c-1\right){A}^{c-2}{\left(1+{A}^c\right)}^{-1}-\left({y}_i-\uptau \right){cA}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\right]\\ {}- kc\left(n-{n}_0\right)\left({Y}_c-\uptau \right)\left[\left(c-1\right)\left({Y}_c-\uptau \right){D}^{c-2}{\left(1+{D}^c\right)}^{-1}-\left({Y}_c-\uptau \right){cD}^{2\left(c-1\right)}{\left(1+{D}^c\right)}^{-2}\right]\\ {}=-\frac{n_a}{\upbeta^2}-\left(c-1\right)\sum \limits_{i=1}^n{\updelta}_{2i}{\left({y}_i-\uptau \right)}^2{A}^{-2}-\left(k+1\right)c\sum \limits_{i=1}^n{\left({y}_i-\uptau \right)}^2{\updelta}_{2i}\left[\left(c-1\right){A}^{c-1}{\left(1+{A}^c\right)}^{-1}-{cA}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\right]\\ {}- kc\left(n-{n}_0\right){\left({Y}_c-\uptau \right)}^2\left[\left(c-1\right){D}^{c-2}{\left(1+{D}^c\right)}^{-1}-{cD}^{2\left(c-1\right)}{\left(1+{D}^c\right)}^{-2}\right],\\ {}\frac{\partial^2\ln L}{\mathrm{\partial \upbeta \partial }c}=\sum \limits_{i=1}^n{\updelta}_{2i}\left({y}_i-\uptau \right){A}^{-1}-k\left({Y}_c-\uptau \right)\left(n-{n}_0\right)\\ {}\times \left[{D}^{c-1}{\left(1+{D}^c\right)}^{-1}+c{\left(1+{D}^c\right)}^{-1}{D}^{c-1}\ln D-{cD}^{c-1}{\left(1+{D}^c\right)}^{-2}{D}^c\ln D\right]\\ {}-\left(k+1\right)\sum \limits_{i=1}^n{\updelta}_{2i}\left({y}_i-\uptau \right)\left[{A}^{c-1}{\left(1+{A}^c\right)}^{-1}+c{\left(1+{A}^c\right)}^{-1}{A}^{c-1}\ln A-{cA}^{c-1}{\left(1+{A}^c\right)}^{-2}{A}^c\ln A\right],\\ {}\frac{\partial^2\ln L}{\mathrm{\partial \upbeta \partial }k}=-c\sum \limits_{i=1}^n{\updelta}_{2i}\left({y}_i-\uptau \right){A}^{c-1}{\left(1+{A}^c\right)}^{-1}-\left({Y}_c-\uptau \right)\left(n-{n}_0\right){cD}^{c-1}{\left(1+{D}^c\right)}^{-1},\\ {}\frac{\partial^2\ln L}{\partial {c}^2}=-\frac{n_0}{c^2}-k\left(n-{n}_0\right)\ln D\left[{\left(1+{D}^c\right)}^{-1}{D}^c\ln D-{\left(1+{D}^c\right)}^{-2}{D}^{2c}\ln D\right]\\ {}-\left(k+1\right)\left[\sum \limits_{i=1}^n{\updelta}_{1i}\ln {y}_i\left\{{\left(1+{y}_i^c\right)}^{-1}{y}_i^c\ln {y}_i-{y}_i^{2c}{\left(1+{y}_i^c\right)}^{-2}\ln {y}_i\right\}\right]\\ {}-\left(k+1\right)\left[\sum \limits_{i=1}^n{\updelta}_{2i}\ln A\left\{{\left(1+{A}^c\right)}^{-1}{A}^c\ln A-{A}^{2c}{\left(1+{A}^c\right)}^{-2}\ln A\right\}\right],\\ {}\frac{\partial^2\ln L}{\partial c\partial k}=-\sum \limits_{i=1}^n{\updelta}_{1i}\ln {y}_i\left\{{\left(1+{y}_i^c\right)}^{-1}{y}_i^c\ln {y}_i\right\}-\sum \limits_{i=1}^n{\updelta}_{2i}\ln A{\left(1+{A}^c\right)}^{-1}{A}^c\ln A-\left(n-{n}_0\right){\left(1+{D}^c\right)}^{-1}{D}^c\ln D,\end{array}} $$

and

$$ \frac{\partial^2\ln L}{\partial {k}^2}=-\frac{n_0}{k^2}. $$

Appendix B

The determinant of F and its partial derivative with respect to τ. The determinant of F can be written as

$$ \left|F\right|={f}_{11}\left({f}_{22}{f}_{33}-{f}_{23}^2\right)-{f}_{12}\left({f}_{12}{f}_{33}-{f}_{13}{f}_{23}\right)+{f}_{13}\left({f}_{12}{f}_{23}-{f}_{13}{f}_{22}\right), $$

and then

$$ {\displaystyle \begin{array}{c}\frac{\partial \left|F\right|}{\mathrm{\partial \uptau }}={f}_{11}\left({f}_{22}^{\prime }{f}_{33}+{f}_{22}{f}_{33}^{\prime }-2{f}_{23}{f}_{23}^{\prime}\right)+{f}_{11}^{\prime}\left({f}_{22}{f}_{33}-{f}_{23}^2\right)\\ {}-{f}_{12}\left({f}_{12}^{\prime }{f}_{33}+{f}_{12}{f}_{33}^{\prime }-{f}_{13}^{\prime }{f}_{23}-{f}_{13}{f}_{23}^{\prime}\right)-{f}_{12}^{\prime}\left({f}_{12}{f}_{33}-{f}_{12}{f}_{23}\right)\\ {}+{f}_{13}\left({f}_{12}^{\prime }{f}_{33}+{f}_{12}{f}_{23}^{\prime }-{f}_{13}^{\prime }{f}_{22}-{f}_{13}{f}_{22}^{\prime}\right)+{f}_{13}^{\prime}\left({f}_{12}{f}_{23}-{f}_{13}{f}_{22}\right),\end{array}} $$

where

$$ {\displaystyle \begin{array}{c}{f}_{11}^{\prime }=\left(c-1\right)\sum \limits_{i=1}^n{\updelta}_{2i}\left[-2\left({y}_i-\uptau \right){A}^{-2}-2{\left({y}_i-\uptau \right)}^2{A}^{-3}\left(1-\upbeta \right)\right]\\ {}+\left(k+1\right)c\sum \limits_{i=1}^n\left(c-1\right){\updelta}_{2i}\left[-2\left({y}_i-\uptau \right){A}^{c-2}{\left(1+{A}^c\right)}^{-1}+{\left({y}_i-\uptau \right)}^2\left(1-\upbeta \right)\left(\left(c-2\right){A}^{c-3}{\left(1+{A}^c\right)}^{-1}\right.\right.\\ {}\left.-{cA}^{2c-3}{\left(1+{A}^c\right)}^{-2}\right]\left(k+1\right)c\sum \limits_{i=1}^nc{\updelta}_{2i}{\left[-2\left({y}_i-\uptau \right){A}^{2\left(c-1\right)}\left(1+{A}^c\right)\right.}^{-2}\\ {}+{\left({y}_i-\uptau \right)}^22\left(1-\upbeta \right)\left(\left(c-1\right){A}^{2c-3}{\left(1+{A}^c\right)}^{-2}\left.\left.-{cA}^{3\left(c-1\right)}{\left(1+{A}^c\right)}^{-3}\right)\right]\right.\\ {}+ kc\left(n-{n}_0\right)\left(c-1\right)\left[-2\left({Y}_c-\uptau \right){D}^{c-2}{\left(1+{D}^c\right)}^{-1}+\left(1-\upbeta \right){\left({Y}_c-\uptau \right)}^2\left(\left(c-2\right){D}^{c-3}{\left(1+{D}^c\right)}^{-1}\right.\right.\\ {}\left.\left.-{cD}^{2c-3}{\left(1+{D}^c\right)}^{-2}\right)\right]-{kc}^2\left(n-{n}_0\right)\left[-2\left({Y}_c-\uptau \right){D}^{2\left(c-1\right)}{\left(1+{D}^c\right)}^{-2}\right.\\ {}+2{\left({Y}_c-\uptau \right)}^2\left(1-\upbeta \right)\left(\left(c-1\right){D}^{2c-3}{\left(1+{D}^c\right)}^{-2}-{D}^{3\left(c-1\right)}\left.\left.c{\left(1+{D}^c\right)}^{-3}\right)\right],\right.\\ {}{f}_{22}^{\prime }=k\left(n-{n}_0\right)\left(1-\upbeta \right)\left[2{D}^{c-1}{\left(1+{D}^c\right)}^{-1}\ln D-c{\left(\ln D\right)}^2\left({D}^{2c-1}{\left(1+{D}^c\right)}^{-2}+{D}^{c-1}\left.{\left(1+{D}^c\right)}^{-1}\right)\right.\right]\\ {}-k\left(n-{n}_0\right)\left(1-\upbeta \right)\left[{D}^{2c-1}{\left(1+{D}^c\right)}^{-2}2\ln D+2c\left(1-\upbeta \right){\left(\ln D\right)}^2\left\{-{D}^{3c-1}{\left(1+{D}^c\right)}^{-3}\right.\right.\\ {}\left.\left.+{D}^{2c-1}{\left(1+{D}^c\right)}^{-2}\right\}\right]+\left(k+1\right)\left(1-\upbeta \right)\sum \limits_{i=1}^n{\updelta}_{2i}\left[2{A}^{c-1}{\left(1+{A}^c\right)}^{-1}\ln A\right.\\ {}+c{\left(\ln A\right)}^2\left.\left\{-{\left(1+{A}^c\right)}^{-2}{A}^{2c-1}+{\left(1+{A}^c\right)}^{-1}\right\}\right]-\left(k+1\right)\left(1-\upbeta \right)\sum \limits_{i=1}^n{\updelta}_{2i}\left[2{A}^{2c-1}{\left(1+{A}^c\right)}^{-2}\ln A\right.\\ {}+2c{\left(\ln A\right)}^2\left\{{\left(1+{A}^c\right)}^{-2}{A}^{2c-1}-{\left(1+{A}^c\right)}^{-3}{A}^{3c-1}\right\},\\ {}{f}_{33}^{\prime }=0,\\ {}{f}_{23}^{\prime }=\sum \limits_{i=1}^n{\updelta}_{2i}\left(1-\upbeta \right)\left[2{A}^{c-1}{\left(1+{A}^c\right)}^{-1}\ln A+c{\left(\ln A\right)}^2{\left(1+{A}^c\right)}^{-1}{A}^{c-1}-{\left(1+{A}^c\right)}^{-1}{A}^{2c-1}\right]\\ {}+\left(n-{n}_0\right)\left(1-\upbeta \right)\left[-{D}^{2c-1}{\left(1+{D}^c\right)}^{-2}c\ln D+{\left(1+{D}^c\right)}^{-1}{D}^{c-1}\left\{c\ln D+1\right\}\right],\\ {}{f}_{12}^{\prime }=\sum \limits_{i=1}^n{\updelta}_{2i}\left[{A}^{-1}+\left(1-\upbeta \right)\left({y}_i-\uptau \right){A}^{-2}\right]+k\left(n-{n}_0\right)\left\{\left(1-\upbeta \right)\left({Y}_c-\uptau \right)\left[{D}^{c-2}\left(c-1\right){\left(1+{D}^c\right)}^{-1}-c{\left(1+{D}^c\right)}^{-1}-c{\left(1+{D}^c\right)}^{-2}{D}^{2\left(c-1\right)}\right]\right.\\ {}-{D}^{c-1}{\left(1+{D}^c\right)}^{-1}-c{\left(1+{D}^c\right)}^{-1}{D}^{c-1}\ln D+c\left({Y}_c-\uptau \right)\left(1-\upbeta \right)\left\{-{D}^{2\left(c-1\right)}c{\left(1+{D}^c\right)}^{-2}\ln D\right.\\ {}+{D}^{c-2}{\left(1+{D}^c\right)}^{-1}\left.\left[1+\left(c-1\right)\ln D\right]\right\}+{c}^{2c-1}{\left(1+{D}^c\right)}^{-2}\ln D\\ {}-c\left(1-\upbeta \right)\left({Y}_c-\uptau \right)\left.\left[{D}^{2c-2}{\left(1+{D}^c\right)}^{-2}-2c{\left(1+{D}^c\right)}^{-3}{D}^{3c-2}\ln D+\left(2c-1\right){\left(1+{D}^c\right)}^{-2}{D}^{2c-2}\ln D\right]\right\}\\ {}+\left(k+1\right)\sum \limits_{i=1}^n{\updelta}_{2i}\left({y}_i-\uptau \right)\left\{\left(1-\upbeta \right)\left[\left(c-1\right){A}^{c-2}{\left(1+{A}^c\right)}^{-1}-{cA}^{2\left(c-1\right)}-{cA}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\right.\right.\\ {}-{c}^2{A}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\ln A+{cA}^{c-2}{\left(1+{A}^c\right)}^{-1}\left(1+\left(c-1\right)\ln A\right)-{cA}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\\ {}+2{c}^2{A}^{3c-2}{\left(1+{A}^c\right)}^{-3}\ln A-c\left(2c-1\right){A}^{2c-2}\left.{\left(1+{A}^c\right)}^{-2}\ln A\right\}\\ {}-\left[{A}^{c-1}{\left(1+{A}^c\right)}^{-1}+c{\left(1+{A}^c\right)}^{-1}{A}^{c-1}\ln A-{cA}^{2c-1}{\left(1+{A}^c\right)}^{-2}\ln A\right],\\ {}{f}_{13}^{\prime}\sum \limits_{i=1}^n{\updelta}_{2i}c\left\{\left({y}_i-\uptau \right)\left(1-\upbeta \right)\left[\left(c-1\right){A}^{c-2}{\left(1+{A}^c\right)}^{-1}-{cA}^{2\left(c-1\right)}{\left(1+{A}^c\right)}^{-2}\right]\right.\\ {}\left.-{A}^{c-1}{\left(1+{A}^c\right)}^{-1}\right\}+\left(n-{n}_0\right)c\left[\left({Y}_c-\uptau \right)\left(1-\upbeta \right)\left[\left(c-1\right){D}^{c-2}{\left(1+{D}^c\right)}^{-1}-{cD}^{2\left(c-1\right)}{\left(1+{D}^c\right)}^{-2}\right]-{D}^{c-1}{\left(1+{D}^c\right)}^{-1}\right].\end{array}} $$

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ismail, A.A., Al-Habardi, K. On Designing Time-Censored Step-Stress Life Test for the Burr Type-XII Distribution. Strength Mater 49, 699–709 (2017). https://doi.org/10.1007/s11223-017-9915-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11223-017-9915-z

Keywords

Navigation