Engineering design under uncertainty is an established field. Attempts to extricate the human decision maker from the process generally do not succeed. Surprisingly, even the determination of system parameters and their admissible values needs as many interventional steps from human designers and operators, as the selection of final attributes of the system that the human end user is expected to only interact and be concerned with. In this light, it becomes important to consider the mathematical models that would explain and model the decision making behavior of human beings. Concerningly, this behavior has been seen to violate common sense probability axioms. In this paper, we propose an earnest look at the mathematics of quantum mechanical theory in modeling and manipulating the uncertainties involved in engineering systems. We propose that the state of a system be modeled as a point in an abstract complex vector space as in quantum mechanics. Additionally, at a given point in time it can be interpreted as a superposition of multiple pure states. This change in perspective allows explanation of many commonly observed behaviors, least of which is the inconsistencies in defining what constitutes the failure of a system. We present our approach in the context of reliability engineering as it sees some of the most prevalent use of uncertainty modeling and propagation techniques. However, the implications on design and design theory are also evident. Some motivating examples are provided and directions for future work are identified.

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