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Researchers conduct life testing on objects of interest in an attempt to determine their life distribution as a means of studying their reliability (or survivability). Determining the life distribution of the objects under study helps manufacturers to identify potential faults, and to improve quality. Researchers sometimes conduct accelerated life tests (ALTs) to ensure that failure among the tested units is earlier than what could result under normal operating (or environmental) conditions. Moreover, such experiments allow the experimenters to examine the effects of high levels of one or more stress factors on the lifetimes of experimental units. Examples of stress factors include, but not limited to, cycling rate, dosage, humidity, load, pressure, temperature, vibration, voltage, etc. A special class of ALT is step-stress accelerated life testing. In this type of experiments, the study sample is tested at initial stresses for a given period of time. Afterwards, the levels of the stress factors are increased in agreement with prefixed points of time called stress-change times. In practice, time and resources are limited; thus, any experiment is expected to be constrained to a deadline which is called a termination time. Hence, the observed information may be subjected to Type-I censoring. This study discusses maximum likelihood inferential methods for the parameters of multiple step-stress models from a generalized Birnbaum-Saunders distribution under time constraint alongside other inference-related problems. A couple of general inference frameworks are studied; namely, the observed likelihood (OL) framework, and the expectation-maximization (EM) framework. The last-mentioned framework is considered since there is a possibility that Type-I censored data are obtained. In the first framework, the scoring algorithm is used to get the maximum likelihood estimators (MLEs) for the model parameters. In the second framework, EM-based algorithms are utilized to determine the required MLEs. Obtaining observed information matrices under both frameworks is also discussed. Accordingly, asymptotic and bootstrap-based interval estimators for the model parameters are derived. Model discrimination within the considered generalized Birnbaum-Saunders distribution is carried out by likelihood ratio test as well as by information-based criteria. The discussed step-stress models are illustrated by analyzing three real-life datasets. Accordingly, establishing optimal multiple step-stress test plans based on cost considerations and three optimality criteria is discussed. Since maximum likelihood estimators are obtained by numerical optimization that involves maximizing some objective functions, optimization methods used, and their software implementations in R are discussed. Because of the computational aspects are in focus in this study, the benefits of parallel computing in R, as a high-performance computational approach, are briefly addressed. Numerical examples and Monte Carlo simulations are used to illustrate and to evaluate the methods presented in this thesis. / Thesis / Doctor of Science (PhD)

The thesis is focused on assessment of fatigue behaviour of austempered ductile iron with nodular graphite. Optimal period of transformation was determined based on the best combination of stress and strain characteristics established by tensile test. Cyclic response and low-cycle fatigue life were studied under both stress-control and longitudinal strain-control mode at room temperature. For both modes, shapes of cyclic hardening curves are dependent on stress amplitude. Cyclic deformation curves (CDC) were fitted by power regression function. Results were compared with CDC established by multiple step test in both modes with verification of the influence of cyclic creep (high stress levels, stress-control mode). Experimental data of S-N curves are in agreement with the Manson-Coffin and the Basquin law. Fatigue and cyclic parameters were compared. Fatigue life time in high-cycle fatigue region was determined. Experimental data were fitted by suitable regression functions. Regression parameters and fatigue limit were established by means of each regression function. Experimental data in low- and high-cycle fatigue regions were used to construct S-N curve and to determine relevant parameters. Discontinuity of experimental data was not observed. Low-cycle fatigue behaviour was predicted. Approximation of tolerance bands was realized in high-cycle and both high and low cycle fatigue regions.

The thesis is focused on assessment of fatigue behaviour of austempered ductile iron with nodular graphite. Optimal period of transformation was determined based on the best combination of stress and strain characteristics established by tensile test. Cyclic response and low-cycle fatigue life were studied under both stress-control and longitudinal strain-control mode at room temperature. For both modes, shapes of cyclic hardening curves are dependent on stress amplitude. Cyclic deformation curves (CDC) were fitted by power regression function. Results were compared with CDC established by multiple step test in both modes with verification of the influence of cyclic creep (high stress levels, stress-control mode). Experimental data of S-N curves are in agreement with the Manson-Coffin and the Basquin law. Fatigue and cyclic parameters were compared. Fatigue life time in high-cycle fatigue region was determined. Experimental data were fitted by suitable regression functions. Regression parameters and fatigue limit were established by means of each regression function. Experimental data in low- and high-cycle fatigue regions were used to construct S-N curve and to determine relevant parameters. Discontinuity of experimental data was not observed. Low-cycle fatigue behaviour was predicted. Approximation of tolerance bands was realized in high-cycle and both high and low cycle fatigue regions.