David R. Jacques

There is an ongoing demand for organizations to become more agile in order to prosper amongst their competitors. Many military organizations have declared a renewed focus towards organizational agility. The goal of this research is to isolate the variables needed to measure organizational agility (OA) in military organizations, allowing for the future development of a suitable method to measure OA without the need to interact with outside organizations. This article begins by providing a suitable and formal definition of organizational agility by exploring and analyzing relevant scholarly literature on the subject. Related terms, such as organizational resiliency, flexibility, robustness, versatility, and adaptability are also explored to examine their definition boundaries and any overlapping areas. Existing methods to measure organizational agility are examined and summarized, and the current limitations to their application are highlighted. Previous studies to find characteristics associated with organizational agility were also examined, and an initial set of 88 organizational agility characteristics was built. Since these included possible redundant or overlapping characteristics, the Q-sort method was employed to discover, analyze, and eliminate redundant items from the dataset, ultimately resulting in 64 unique characteristics. The result is a suitable definition for organization agility applicable to military organizations and a list of potential associated characteristics that summarizes related research to date. This groundwork establishes the foundation to conduct a multi-organization study to further refine the characteristic list and ultimately develop a method to measure organizational agility.

Levels of Automation (LOA) provide a method for describing authority granted to automated system elements to make individual decisions. However, these levels are technology-centric and provide little insight into overall system operation. The current research discusses an alternate classification scheme, referred to as the Level of Human Control Abstraction (LHCA). LHCA is an operator-centric framework that classifies a system’s state based on the required operator inputs. The framework consists of five levels, each requiring less granularity of human control: Direct, Augmented, Parametric, Goal-Oriented, and Mission-Capable. An analysis was conducted of several existing systems. This analysis illustrates the presence of each of these levels of control, and many existing systems support system states which facilitate multiple LHCAs. It is suggested that as the granularity of human control is reduced, the level of required human attention and required cognitive resources decreases. Thus, it is suggested that designing systems that permit the user to select among LHCAs during system control may facilitate human-machine teaming and improve the flexibility of the system.

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.

This report provides findings from research conducted under the RT-18a; Valuing Flexibility project. The primary goal of this research project is to identify, develop, and validate sound quantitative methods, processes, and tools (MPTs) that will enable DoD leadership and program managers to make a convincing case for investments in system flexibility when acquisition decisions are made. The research conducted during the first phase of this project focused on identifying current quantitative MPTs for valuing flexibility in DoD contexts, critically evaluated the theoretical underpinnings of these MPTs, and delivered initial capabilities to value investments in flexibility to handle unforeseen sources of change. The current phase of the project focused in three areas: developing a taxonomy for evaluating MPTs for valuing flexibility in DoD contexts (including an overview of a software implementation), extending existing methods by developing new tools for valuing flexibility through life cycle costs, and using real and illustrative scenarios as examples for applying methods to value flexibility, including a detailed case study of flexibility in Ship Maintenance.

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 inter‐changeably 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. © 2012 Wiley Periodicals, Inc. Syst Eng 16:

The DOD routinely demonstrates its capability to develop phenomenal systems; however, these accomplishments are often tarnished by substantial cost and schedule overruns. While defense policies are continually being revised to address these problems, many believe that a more fundamental source of these overruns is the lack of flexibility in the systems being developed. But providing justification to invest in flexibility is a tough sell, as stakeholders struggle to quantitatively demonstrate the potential return on investment. Therefore, this paper introduces an alternative methodology for valuing the inherent ability of a system or design to accommodate change. The proposed methodology is essentially a modification of the current life cycle model and is premised on the notion that the need for capability changes in a program arise in a stochastic manner that can be incorporated into a continually updated, expected value model presented in terms of total program cost.

This paper developed guidance laws to optimally and autonomously position a relay Micro Aerial Vehicle (MAV) to provide an operator with real-time Intelligence, Surveillance, and Reconnaissance (ISR) by relaying communication and video signals from a rover MAV to the base, thus extending the rover's reach. The ISR system is comprised of two MAVs, the Relay and the Rover, and a Base. The Relay strives to position itself so as to minimize the radio frequency (RF) power required for maintaining communications between the Rover and the Base, while the Rover performs the ISR mission, which may maximize the required RF power. The optimal control of the Relay MAV then entails the solution of a differential game. Applying Pontryagin's Maximum Principle yields a standard, albeit nonlinear, Two-Point Boundary Value Problem (TPBVP). Suboptimal solutions are first obtained as an aid in solving the TPBVP which yields the solution of the differential game. One suboptimal approach is based upon the geometry of the ISR system: The midpoint between the Rover and the Base is the ideal location which minimizes the RF power required, so the Relay heads toward that point—assuming that the Rover is stationary. At the same time, to maximize the rate of required RF power, the Rover moves in the opposite direction of the Relay—assuming the Relay is stationary. These are optimal strategies in the end-game, but it is suboptimal to use them throughout the game. Another suboptimal approach investigated envisions the Rover to remain stationary and solves for the optimal path for the Relay to minimize the RF power requirement. This one-sided optimization problem is analyzed using a Matlab-based optimization program, GPOCS, which uses the Gauss pseudospectral method of discretization. The results from GPOCS corroborated with the geometry-based suboptimal Relay strategy of heading straight toward the midpoint between the Rover and the Base. The suboptimal solutions are readily implementable for real-time operation and are used to facilitate the solutions of the TPBVP.