This study builds on an existing structural model developed to examine the influence of
leadership and organizational culture on innovation and satisfaction of engineers in Australian
public sectors (APS). The objective of this study is to increase the understanding of
innovation process with a focus on causal relationships among critical factors. To achieve this
objective, the study develops an assessment approach to help predict creativity and work
meaningfulness of engineers in the APS. Three quantitative analysis methods were sequentially
conducted in this study including correlation analysis, path analysis, and Bayesian
networks. A correlation analysis was conducted to pinpoint the strong association between
key factors studied. Subsequently, path analysis was employed to identify critical pathways
which were accordingly used as a structure to develop Bayesian networks. The findings of
the study revealed practical strategies for promoting (1) transformational leadership and (2)
innovative culture in public sector organizations since these two factors were found to be key
drivers for individual creativity and work meaningfulness of their engineers. This integrated
approach may be used as a decision support tool for managing the innovation process for
engineers in the public sectors.
Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By
identifying combinations of faults in a logical framework it’s possible to define the structure
of the fault tree. The same go with Bayesian networks, but the difference of these probabilistic
tools is in their ability to reasoning under uncertainty. Some typical constraints to the
fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper
shows that information processing has become simple and easy through the use of Bayesian
networks. The study presented showed that updating knowledge and exploiting new knowledge
does not complicate calculations. The contribution is the structural approach of faults
diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are
defined in descending order. The approach presented in this paper has been successfully
applied to turbo compressor, which represent vital equipment in petrochemical plant.
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