Despite its ubiquity in the systems engineering literature, flexibility remains an ambiguous concept. There exist a multitude of definitions, which vary not only by domain, but within domains as well. Furthermore, these definitions often conflict with one another, making it difficult to discern the intended meaning in a given study or to form generalizations across studies. Complicating matters, there is a plethora of related terminology that is often used carelessly and/or interchangeably with flexibility. In this paper, we employ a novel ontological framework for clarifying salient aspects of extant flexibility-related terminology. While it was not possible to distill consensus definitions from the literature, we did identify certain dominant characteristics that enabled us to formulate a set of democratic definitions for flexibility, adaptability, and robustness, as well as recommended definitions for agility and versatility. We believe that the proposed definitions of these key system design principles may provide a baseline for improving analysis and communication among systems engineering practitioners and academics.

For decades, the DoD has employed numerous reporting and monitoring tools for characterizing the acquisition cost estimates of its major programs. These tools have resulted in dozens of studies thoroughly documenting the magnitude and extent of DoD acquisition cost growth. However, little attention has been paid to the behavior of the larger cost component of a system's life cycle cost: Operating and Support (O&S) costs. Consequently, the DoD has little knowledge of how O&S cost estimates behave over time, and virtually no insights regarding their accuracy. In a previous paper, the authors describe an analytical methodology for remedying this deficiency via a study to characterize the historical accuracy of O&S cost estimates. The results of this study are presented here, and indicate there tend to be large errors in DoD O&S cost estimates, and that the accuracy of the estimates improves little over time. However, the results also suggest the possibility of improving the accuracy of these estimates via a stochastically-based predictive cost model.

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Purpose From on-board automotive diagnostics to real-time aircraft state of health, the implementation of health monitoring and management systems are an increasing trend. Further, reductions in operating budgets are forcing many companies and militaries to consider new operating and support environments. Combined with longer service lives for aircraft and other systems, maintenance and operations processes must be reconsidered. The majority of research efforts focus on health monitoring techniques and technologies, leaving others to determine the maintenance and logistics impact on the systems. The paper aims to discuss these issues. Design/methodology/approach This research analyzes the impact of a health monitoring system on a squadron of aircraft. Flight, maintenance and logistics operations are stochastically modeled to determine the impact of program decisions on supply metrics. An arena discrete event simulation is utilized to conduct this research on 20 components on each of the 12 aircraft modeled. Costs and availability are recorded for comparison across three sparing scenarios to include economic order quantity (EOQ) for baseline and health monitoring cases and a just-in-time (JIT) health monitoring set of simulations. Findings Data are presented for EOQ and JIT supply methods. A comparison of health monitoring enabled supply to current methods shows cost savings and availability gains. The different methodologies are compared and discussed as a trade-space for programmatic decisions. Originality/value This work demonstrates the ability of health monitoring systems and condition based maintenance to affect supply ordering decisions. The development of trade-spaces within operating environments is demonstrated along with the ability to conduct cost benefit analyses.