The statistical inference of the multi-component stress-strength parameter, Rs,k, is considered in the three-parameter Weibull
 distribution. The problem is studied in two cases. In the first case, assuming that the stress and strength variables have com
monshape and location parameters but non-common scale parameters, and all these parameters are unknown, the maximum
 likelihood estimation and the Bayesian estimation of the parameter Rs,k are investigated. In this case, as the Bayesian esti
mation does not have a closed form, it is approximated by two methods: Lindley and MCMC. Also, asymptotic confidence
 intervals have been obtained. In the second case, assuming that the stress and strength variables have known common shape
 and location parameters but non-common and unknown scale parameters, the maximum likelihood estimation, the uniformly
 minimum variance unbiased estimators, the exact Bayesian estimation of the parameter Rs,k, and the asymptotic confidence
 interval are calculated. Finally, using Monte Carlo simulation, the performance of different estimators has been compared.