Methods for Using Manpower to Assess USAF Strategic Risk

With limited personnel resource funding availability, senior US Air Force (USAF) decision makers struggle to base enterprise resource allocation from rigorous analytical traceability. There are over 240 career fields in the USAF spanning 12 enterprises. Each enterprise develops annual risk assessments by distinctive core capabilities. A core capability (e.g. Research and Development) is an enabling function necessary for the USAF to perform its mission as part of the Department of Defense (DOD). Assessing risk at the core capability is a good start to assessing risk, but is still not comprehensiveness enough. One of the twelve enterprises has linked its task structure to Program Element Codes (PECs). Planners and programmers use amount of funding per PEC to assess tasks needed to address a desired capability. For the first time, a linkage between core functions, core capabilities, PECs, tasks and manpower has been developed. We now can provide an objective nomenclatured way to compute personnel risk. All resources planned are not programmed (i.e. resource allocated and budgeted); the delta between the two translate into capability gaps and a level of strategic risk. A USAF career field risk demonstration is performed using normal, sigmoid and Euclidean-norm functions. Understanding potential personnel shortfalls at the career field level should better inform core capability analysis, and thus increase credibility and defensibility of strategic risk assessment

Simulation Of Modeling Sortie Generation Process In TURAF

Simulation is a useful technique for engineers and operations researchers. One of the primary advantages of simulation models is that they are able to provide users with practical feedback when analyzing real-world systems. This thesis builds a discrete event simulation of the sortıe generatıon process, to help decision makers in performing analyses regarding quantity of manpower, bottlenecks in supply and maintenance activities; as well as utilization of maintenance manpower, cost and number of sorties produced in a specific time. We only model one aircraft system with four Line Replacement Units (LRU), but any system and its LRUs can be included in our simulation. Our analysis focuses on eight Measures of Effectiveness (MOE) from our simulation. The final simulation provides a reasonable representation of many, but not all, characteristics of the sortie generation process. It is a preliminary simulation tool for further research on the sortie generation process in the Turkish Air Force, and provides decision-makers with the ability to analyze the sortie generation process in support of future decisions

Annual Report 2014

This report highlights salient features and activities across the spectrum of NPS research activities conducted on behalf of both Navy and Marine Corps topic sponsors during the 2014 fiscal year. Each of the 90 research projects’ executive summary included herein outlines key results. While most of the summaries detail final results, some projects have multi-year project lengths and, therefore, progress to date is reported

Air Force Institute of Technology Research Report 2011

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Riverine sustainment 2012

Student Integrated ProjectIncludes supplementary materialThis technical report analyzed the Navy's proposed Riverine Force (RF) structure and capabilities for 2012. The Riverine Sustainment 2012 Team (RST) examined the cost and performance of systems of systems which increased RF sustainment in logistically barren environments. RF sustainment was decomposed into its functional areas of supply, repair, and force protection. The functional and physical architectures were developed in parallel and were used to construct an operational architecture for the RF. The RST used mathematical, agent-based and queuing models to analyze various supply, repair and force protection system alternatives. Extraction of modeling data revealed several key insights. Waterborne heavy lift connectors such as the LCU-2000 are vital in the re-supply of the RF when it is operating up river in a non-permissive environment. Airborne heavy lift connectors such as the MV-22 were ineffective and dominated by the waterborne variants in the same environment. Increase in manpower and facilities did appreciable add to the operational availability of the RF. Mean supply response time was the biggest factor effecting operational availability and should be kept below 24 hours to maintain operational availability rates above 80%. Current mortar defenses proposed by the RF are insufficient.N

Leverage AI to Learn, Optimize, and Wargame (LAILOW) for Strategic Laydown and Dispersal (SLD) of the USN Operating Forces

NPS NRP Technical ReportThe SECNAV disperses Navy forces in a deliberate manner to support DoD guidance, policy and budget. The current SLD process is labor intensive, takes too long, and needs AI. The research questions are: - How does the Navy weight competing demands for naval forces between the CCMDs to determine an optimal dispersal of operating forces? - How does the Navy optimize force laydown to maximize force development (Fd) and force generation (Fg) efficiency? We propose LAILOW to address the questions. LAILOW was derived from the ONR funded project and focuses on deep analytics of machine learning, optimization, and wargame. Learn: When there are data, data mining, machine learning, and predictive algorithms are used to analyze data. Historical Phased Force Deployment Data (TPFDDs) and SLD Report Cards data among others, one can learn patterns of what decisions were made and how they are executed with in the past. Optimize: Patterns from learn are used to optimize future SLD plans. A SLD plan may include how many homeports, home bases, hubs, and shore posture locations (Fd) and staffs (Fg). The optimization can be overwhelming. LAILOW uses integrated Soar reinforcement learning (Soar-RL) and coevolutionary algorithms. Soar-RL maps a total SLD plan to individual ones used in excursion modeling and what if analysis. Wargame: There might be no or rare data for new warfighting requirements and capabilities. This motivates wargame simulations. A SLD plan can include state variables or problems (e.g., future global and theater posture, threat characteristics), which is only observed, sensed, and cannot be changed. Control variables are solutions (e.g., a SLD plan). LAILOW sets up a wargame between state and control variables. Problems and solutions coevolve based on evolutionary principles of selection, mutation, and crossover.N3/N5 - Plans & StrategyThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Restoring Confidence: A Qualitative Study of the Experience of Interim Commanding Officers in U.S. Navy Operational Units

Commanding officers in the United States Navy are entrusted by law with absolute authority, responsibility, and accountability. Despite a rigorous selection process, some commanding officers are relieved of command every year. In many cases, these commanding officers are replaced by interim commanding officers, leaders selected to fill the job for short periods of time. There is a gap in leadership literature about the phenomenon of interim command leadership in the Navy. This study investigated interim commanding officers\u27 experiences of taking command following the deliberate removal of the unit\u27s previous commanding officer. A review of current literature on the subjects of command at sea, leadership, organizational culture, and leading planned change in organizations was conducted to develop a basis for understanding existing theories about challenges facing incoming leaders, effective leadership behaviors to generate change within an organization, and recommended strategies for effecting organizational change. A qualitative research methodology was used to provide rich detail about the experiences of interim commanding officers and to develop theories grounded in the data. Eleven former Navy interim commanding officers were interviewed to obtain data to answer the following research questions: (1) What were the experiences and leadership challenges faced by interim commanding officers? (2) Which experiences, if any, differed from their first command tour? (3) What observations were made by interim commanding officers about the organizational culture and morale of the wardroom upon their arrival and departure from the unit? (4) Which leadership behaviors and strategies, if any, did interim commanding officers find useful to change the organizational culture and morale of the wardroom? The findings suggested that: (a) interim commanding officers experienced a higher degree of confidence entering the assignment than on their first command tour, (b) the unknown and not knowing who among the crew they could trust were challenges, (c) effects on the wardroom varied with severity of the incident, the crew\u27s perceived association with the event, and remoteness factors, and (d) that by modeling desired behaviors and focusing on communication, interim commanding officers restored confidence in leadership and mission readiness to the wardroom, the crew and external stakeholders

A System Dynamics Model For Manpower And Technology Implementation Trade-off And Cost Estimation

The U.S. Navy has been confronted with budget cuts and constraints during recent years. This reduction in budget compels the U.S. Navy to limit the number of manpower and personnel to control costs. Reducing the total ownership cost (TOC) has become a major topic of interest for the Navy as plans are made for current and future fleets. According to the U.S. Government Accountability Office (GAO, 2003), manpower is the most influential component of determining the life cycle cost of a ship. The vast majority of the TOC is comprised of operating and support (O&S) costs which account for approximately 65 percent of the TOC. Manpower and personnel costs account for approximately 50 percent of O&S costs. This research focused on tradeoff analysis and cost estimation between manpower and new technology implementation. Utilizing concepts from System Dynamics Modeling (SDM), System Dynamics Causal Loop diagrams (CLD) were built to identify major factors when implementing new technology, and then stocks and flows diagrams were developed to estimate manpower cost associated with new technology implementation. The SDM base model reflected an 18 months period for technology implementation, and then compared different technology implementation for different scenarios. This model had been tested by the public data from Department of the Navy (DoN) Budget estimates. The objective of this research was to develop a SDM to estimate manpower cost and technology tradeoff analysis associated with different technology implementations. This research will assist Navy decision makers and program managers when objectively considering the impacts of iii technology selection on manpower and associated TOC, and will provide managers with a better understanding of hidden costs associated with new technology adoption. Recommendations were made for future study in manpower cost estimation of ship systems. In future studies, one particular type of data should be located to test the model for a specific manpower configuration

Evaluation of the HARDMAN comparability methodology for manpower, personnel and training

The methodology evaluation and recommendation are part of an effort to improve Hardware versus Manpower (HARDMAN) methodology for projecting manpower, personnel, and training (MPT) to support new acquisition. Several different validity tests are employed to evaluate the methodology. The methodology conforms fairly well with both the MPT user needs and other accepted manpower modeling techniques. Audits of three completed HARDMAN applications reveal only a small number of potential problem areas compared to the total number of issues investigated. The reliability study results conform well with the problem areas uncovered through the audits. The results of the accuracy studies suggest that the manpower life-cycle cost component is only marginally sensitive to changes in other related cost variables. Even with some minor problems, the methodology seem sound and has good near term utility to the Army. Recommendations are provided to firm up the problem areas revealed through the evaluation

ANALYSIS OF MARKOV CHAIN MONTE CARLO METHODS IN MULTI-INDENTURE INVENTORY OPTIMIZATION

U.S. Navy aircraft are required to meet minimum operational availability targets, while minimizing spare parts procurement costs. The current optimization model written by Salmeron and Buss, uses marginal analysis, as described by Sherbrooke, to determine optimal sparing policies for this highly complex multi-indenture model. The literature lacks alternative optimization methodologies for such a problem, so we propose an alternative approach utilizing simulated annealing (SA), a Markov Chain Monte Carlo algorithm. We present three SA approaches tested in three case studies of varying size and complexity. Our initial findings show that in very simple problems, SA is easily capable of outperforming marginal analysis; however, problems with more complexity have large optimality gaps. This is likely because the SA Markov chain is unable to effectively explore the multi-indenture structure of the problem. We implement a method to account for this structure that intelligently builds initial feasible solutions using an epsilon-greedy approach to marginal analysis. This approach produces better results than NAVARM in more than half of the trials on problems of moderate complexity. We also implement a novel method for calculating operational availability that may allow full scale problems to be optimized more efficiently.NAVSUP WSSLieutenant Commander, United States NavyApproved for public release. Distribution is unlimited