Schedule Disruptions for Risk Comparisons in Engineering and Enterprise Systems

The systems engineer is challenged with building an understanding and collecting knowledge about the multiple dimensions, functions, and perspectives of systems and allocating resources to improve their design, operations, and other decision making processes. Risk analysis has a role of identifying, assessing and tracking emergent and future conditions that drive the dynamics of systems. However, the literature of comparative risk analysis in the 1990s to the present fell short of its aim that risk analysis could inform resource allocations across domains of health, environment, ecology, workplace safety, engineering, humans and organizations, finance, etc.—yet such span of domains is a distinguishing feature of complex systems. Among others, there was an objection that losses of lives, damages, finances, etc., should not be equated or balanced by multiplicative factors or other mathematical functions. Thus, there remains a gap to use risk analysis to quantify the degrees of concern (or the warranted levels of investment to allay those concerns) across non-comparable entities. Modeling and mathematical disruption theory offers a way that formerly non-comparable sources of risk can be compared, at least in part, by the degree of disruption to the schedules that constitute enterprises and problem domains. This dissertation will model systems in terms of their schedules of elements and, subsequently, quantify and compare the disruptions of the schedules by combinations of emergent and future conditions. The result is a characterization of the disruptions that most and least matter across formerly non-comparable domains. A framework and methodology will consist of (i) a literature review (ii) adopting a system analysis of schedules, (iii) composing disruptions as emergent and future conditions into operations disruptions, perspective disruptions, and time frame disruptions, (iv) testing of the schedules by each of the disruptions, (v) identifying the disruptions that most and least matter to the schedules, (vi) finding implications for information to collect on particular emergent and future conditions in a process of monitoring. The approach supplements the traditional conceptions of risk as (a) probability and severity of adverse effects (Lowrance, 1976), (b) effect of uncertainty on objectives (International Organization for Standardization, 2009), (c) influence of scenarios to priorities (Lambert et al. 2009-2017), etc.), and extends risk analysis to address “the impact of disruption of schedules”. The developed theory and methodology are demonstrated with application to scheduling at a marine container port with disruptions of operations, perspectives, and time frames.