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Costing at the Speed of Light: How Your Concurrent Engineering Design Team can Bootstrap Your Organizations Programmatic Capabilities
What do you do when it is necessary to generate reasonable cost estimates at the earliest Concept Maturity Levels and you have never flown any similar missions before? This paper describes the current and future Team X cost processes and methods, how they are being used to expand our data frontiers and cost modelling capabilities, and how this enables the ability to estimate early and estimate often.
Estimate Early and Estimate Often: How Your Concurrent Engineering Design Team Can Bootstrap Your Organizations Programmatic Capabilities
What do you do when it is necessary to generate reasonable cost estimates at the earliest Concept Maturity Levels and you have never flown any similar missions before? This paper describes the current and future Team X and A-Team cost processes and methods, how they are being used to expand our data frontiers, cost modelling capabilities and how this enables the ability to estimate early and estimate often.
Remote Concurrent Engineering: A-Team Studies in the Virtual World
NASA Jet Propulsion Laboratory’s (JPL’s)Architecture Team (A-Team) has nearly a decade of experiencein maturing early formulation mission and technology conceptsby combining innovative collaborative engineering methodswith cutting-edge subject matter expertise and advancedanalysis tools in an in-person environment. When COVID-19forced JPL’s workforce to work remotely in March 2020, ATeamhad to quickly pivot from an in-person collaborativeenvironment to a remote working environment.Through introspection, careful planning, and considerablepractice, A-Team was able to develop new operating proceduresto effectively continue early formulation studies in a virtualenvironment. A-Team has held over 57 remote studies in the 10months since the start of mandatory telework at JPL in March2020. In the remote setting, A-Team conducts studies in half-daysessions with clients and subject matter experts (SMEs) viavideoconferencing, shared computer screens, and digitalcollaborative tools.The key lesson is that increased staffing and planning is neededto prepare and successfully run remote A-Team studies. RemoteA-Team studies require careful selection of the appropriatetools for security, accessibility, and usability within theNASA/JPL environment. Knowledge capture methods andtemplates need to be thought out and agreed upon in advance asthere is less room for improvising in a remote format. Variouscommunication channels have to be monitored to allow for teamcoordination while maintaining fruitful participant engagementduring a session. In addition, technical backup for all roleswithin the A-Team have to be identified to allow the study tocontinue even if a team member’s connectivity is temporarilyinterrupted. Finally, careful thought has to be put into methodsand processes to create a collaborative environment in a virtualspace such that a group of experts who are only connected viathe internet can experience the creative spark and flow of a greatcollaborative and innovative study.
Remote Concurrent Engineering: A-Team Studies in the Virtual World
No abstract provided
What Makes Hybrid Concurrent Engineering Teams Work and Not Work: A Theoretical Analysis
No abstract provided
The Evolution of Team-X: 25 Years of Concurrent Engineering Design Experience
No abstract provided
Review of a Draft - Avoiding the Impossible: Re-focusing a Non-Feasible Mission 2-Hrs into a 3-Day Engineering Session
Concurrent engineering offers a great many benefits to engineers and mission designers throughout the world of aerospace. The only downside of concurrent engineering, and this is somewhat unavoidable, is that you don’t know the results of a design session until the end when it is completed. Usually, this is not a problem – you wouldn’t start building a spacecraft before the design is finished. However, within mass and cost constrained systems, you may end up with a final design that although technically sound – is not feasible due to mass or cost limits. Employing in-session mass and cost models with flexible inputs that refine their estimates and variance as more detailed information comes in throughout a design session allows major design changes to be made when the probability of breaching a mass or cost cap exceeds a threshold level. This enables mission designers to re-focus the study, and avoid spending 3-days with 15 engineers designing a non-feasible mission. By understanding key correlations and nested relationships within mass or cost, and specifically mass or cost allocations per mission element by mission type, it’s possible to get flexible-input, statistically based mass and cost estimates very early in the design process. Baseline models are seeded using mission characteristics and general parameters (outer planetary orbiter-probe mission, $500M cost cap for example) to provide a rough estimate of the expected mass or cost. As information gets solidified during the session, it gets added to the model and the estimates are updated. Continuing the orbiter-probe mission example, modeling probe heat shield cost as a percent of total probe cost, and probe cost as a percent of total flight system cost, and total flight system cost as a percent of total mission cost allows a design team to roll-up solidified information to estimate the probability of fitting within a mass or cost constraint early in a concurrent design session. When only the heat shield cost is known, the variance of the final estimate is higher, whereas when the full probe gets defined, naturally, the variance of the estimate decreases. A methodology, model, verification and demo implementation for cost limit breach are presented.
True Concurrent Thermal Engineering Integrating CAD Model Building with Finite Element and Finite Difference Methods
Thermal engineering has long been left out of the concurrent engineering environment dominated by CAD (computer aided design) and FEM (finite element method) software. Current tools attempt to force the thermal design process into an environment primarily created to support structural analysis, which results in inappropriate thermal models. As a result, many thermal engineers either build models "by hand" or use geometric user interfaces that are separate from and have little useful connection, if any, to CAD and FEM systems. This paper describes the development of a new thermal design environment called the Thermal Desktop. This system, while fully integrated into a neutral, low cost CAD system, and which utilizes both FEM and FD methods, does not compromise the needs of the thermal engineer. Rather, the features needed for concurrent thermal analysis are specifically addressed by combining traditional parametric surface based radiation and FD based conduction modeling with CAD and FEM methods. The use of flexible and familiar temperature solvers such as SINDA/FLUINT (Systems Improved Numerical Differencing Analyzer/Fluid Integrator) is retained.
Model-Based Engineering Design for Trade Space Exploration throughout the Design Cycle
This paper presents ongoing work to standardize model-based system engineering as a complement to point design development in the conceptual design phase of deep space missions. It summarizes two first steps towards practical application of this capability within the framework of concurrent engineering design teams and their customers. The first step is standard generation of system sensitivities models as the output of concurrent engineering design sessions, representing the local trade space around a point design. A review of the chosen model development process, and the results of three case study examples, demonstrate that a simple update to the concurrent engineering design process can easily capture sensitivities to key requirements. It can serve as a valuable tool to analyze design drivers and uncover breakpoints in the design. The second step is development of rough-order- of-magnitude, broad-range-of-validity design models for rapid exploration of the trade space, before selection of a point design. At least one case study demonstrated the feasibility to generate such models in a concurrent engineering session. The experiment indicated that such a capability could yield valid system-level conclusions for a trade space composed of understood elements. Ongoing efforts are assessing the practicality of developing end-to-end system-level design models for use before even convening the first concurrent engineering session, starting with modeling an end-to-end Mars architecture.
Identification and Classification of Common Risks in Space Science Missions
Due to the highly constrained schedules and budgets that NASA missions must contend with, the identification and management of cost, schedule and risks in the earliest stages of the lifecycle is critical. At the Jet Propulsion Laboratory (JPL) it is the concurrent engineering teams that first address these items in a systematic manner. Foremost of these concurrent engineering teams is Team X. Started in 1995, Team X has carried out over 1000 studies, dramatically reducing the time and cost involved, and has been the model for other concurrent engineering teams both within NASA and throughout the larger aerospace community. The ability to do integrated risk identification and assessment was first introduced into Team X in 2001. Since that time the mission risks identified in each study have been kept in a database. In this paper we will describe how the Team X risk process is evolving highlighting the strengths and weaknesses of the different approaches. The paper will especially focus on the identification and classification of common risks that have arisen during Team X studies of space based science missions.
2020 I.F._Wickizer_New CE Tool for MDC_Final Report
Our team surveyed available products and found no readily-available/U.S. commercial or Agency products which supported our envisioned workflow for the Mission Design Center and the concurrent engineering (CE) process we use. Therefore, we sought to create our own CE tool. Changes in agency policy during the performance period allowed us to shift direction and instead adapt our previous legacy tool (Atlas) to include the collaboration features we sorely needed. Atlas relied upon databases for its back-end data management. Poseidon, the work proposed under this effort, was also intended to leverage from that previous back end (in part). However, in May 2021, EUSO announced that “SBU/CUI Information Can Now Be Shared/Stored Within O365 Without Encryption.” Consequently, we made the decision to use O365 in place of our back end. This change provides for version history, collaborative simultaneous editing, and other collaboration tools agency-wide that were previously unavailable with the old database architecture. The new Atlas O365 has more flexibility and capability for users. It’s now easier for users to switch between using the tool for concurrent engineering and individual subsystem engineering. A version was delivered for concurrent engineering of small satellite missions; so far, it has been used successfully on the Aeolus MDC study. Atlas O365 will facilitate the design and assessment of Small Satellite Missions at low Concept Maturity Level at Ames. Feasibility assessments on mission concepts still at a low CML permit strategic planning and decision-making efforts at the center level about which concepts should be pursued and proposed.