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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White
Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White
Faculty Publications
The Air Force software development environment is experiencing a paradigm shift. The 2019 Defense Innovation Board concluded that speed and cycle time must become the most important software metrics if the US military is to maintain its advantage over adversaries.1 This article proposes utilizing a cost-of-delay (CoD) framework to prioritize projects toward optimizing readiness. Cost-of-delay is defined as the economic impact resulting from a delaying product delivery or, said another way, opportunity cost. In principle, CoD assesses the negative impacts resulting from changes to the priority of a project.
Integrating Cost As A Decision Variable In Wargames, Joshua N. Reese, Jonathan D. Ritschel, Brent T. Langhals, Ryan D. Engle
Integrating Cost As A Decision Variable In Wargames, Joshua N. Reese, Jonathan D. Ritschel, Brent T. Langhals, Ryan D. Engle
Faculty Publications
The US military can no longer afford to be reactive, leaving critical cost analyses to the months and years following operations or full-scale conflicts. By leveraging cost in wargaming as part of the Joint planning process, DOD can provide Congress and the American taxpayers a range of potential costs associated with various military engagements that reflect fiscal and operational realities.
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Faculty Publications
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …
A Case For Open Mission Systems In Dod Aircraft Avionics, Michael J. Brown, R. David Fass, Jonathan D. Ritschel
A Case For Open Mission Systems In Dod Aircraft Avionics, Michael J. Brown, R. David Fass, Jonathan D. Ritschel
Faculty Publications
The DOD is adopting open mission systems (OMS) as the future in the military aviation environment. OMS proponents promise reduced costs and truncated schedules through increased competition in the marketplace and reduced coding efforts. To the best of our knowledge, no studies have examined the success of these open architectures in the DOD. Therefore, we investigate costs and schedule for a recent DOD avionics OMS demonstration platform in comparison to 13 historically analogous programs.
The Impact Of Learning Curve Model Selection And Criteria For Cost Estimation Accuracy In The Dod, Candace Honious, Brandon Johnson, John J. Elshaw, A. B. Badiru
The Impact Of Learning Curve Model Selection And Criteria For Cost Estimation Accuracy In The Dod, Candace Honious, Brandon Johnson, John J. Elshaw, A. B. Badiru
Faculty Publications
The first part of this manuscript examines the impact of configuration changes to the learning curve when implemented during production. This research is a study on the impact to the learning curve slope when production is continuous but a configuration change occurs. Analysis discovered the learning curve slope after a configuration change is different from the stable learning curve slope pre-configuration change. The newly configured units were statistically different from previous units. This supports that the new configuration should be estimated with a new learning curve equation. The research also discovered the post-configuration slope is always steeper than the stable …