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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.
Hihn, Jairus↗
Concurrent Engineering Working Group White Paper Distributed Collaborative Design: The Next Step in Aerospace Concurrent Engineering
As aerospace missions grow larger and more technically complex in the face of ever tighter budgets, it will become increasingly important to use concurrent engineering methods in the development of early conceptual designs because of their ability to facilitate rapid assessments and trades of performance, cost and schedule. To successfully accomplish these complex missions with limited funding, it is essential to effectively leverage the strengths of individuals and teams across government, industry, academia, and international agencies by increased cooperation between organizations. As a result, the existing concurrent engineering teams will need to increasingly engage in distributed collaborative concurrent design. The purpose of this white paper is to identify a near-term vision for the future of distributed collaborative concurrent engineering design for aerospace missions as well as discuss the challenges to achieving that vision. The white paper also documents the advantages of creating a working group to investigate how to engage the expertise of different teams in joint design sessions while enabling organizations to maintain their organizations competitive advantage.
Hihn, Jairus↗
Characterizing Distributed Concurrent Engineering Teams: A Descriptive Framework for Aerospace Concurrent Engineering Design Teams
As aerospace missions grow larger and more technically complex in the face of ever tighter budgets, it will become increasingly important to use concurrent engineering methods in the development of early conceptual designs because of their ability to facilitate rapid assessments and trades in a cost-efficient manner. To successfully accomplish these complex missions with limited funding, it is also essential to effectively leverage the strengths of individuals and teams across government, industry, academia, and international agencies by increased cooperation between organizations. As a result, the existing concurrent engineering teams will need to increasingly engage in distributed collaborative concurrent design. This paper is an extension of a recent white paper written by the Concurrent Engineering Working Group, which details the unique challenges of distributed collaborative concurrent engineering. This paper includes a short history of aerospace concurrent engineering, and defines the terms 'concurrent', 'collaborative' and 'distributed' in the context of aerospace concurrent engineering. In addition, a model for the levels of complexity of concurrent engineering teams is presented to provide a way to conceptualize information and data flow within these types of teams.
Concept Design↗
An Exploration of Mission Concepts That Could Utilize Small RPS
The NASA Radioisotope Power Systems (RPS) Program Mission Analysis Team at the Jet Propulsion Laboratory (JPL) requested a JPL Innovation Foundry Architecture Team (A-Team) study to assess mission pull for small RPS (1 mWe - 40 We) in order to inform the RPS Program Office on what future power system developments should be focused on. The A-Team is JPL’s concurrent engineering design team for science definition and early mission concept development, targeting concept maturation levels of 1 through 3. The requested small RPS study was tasked to identify the architecture space of potential small RPS missions, and suggest power levels that could enable or enhance potential future small spacecraft missions. This paper describes the collaborative engineering processes that the A-Team and Mission Analysis Team used to reach results quickly and the findings to inform the RPS Program about mission concept power requirements on RPS for small missions.
Bairstow, Brian K.↗
A New Concurrent Engineering Tool for the New Mission Design Center at NASA Ames Research Center
The NASA Ames Mission Design Center (MDC) has undergone a significant transformation process in recent years, culminating in becoming a true Concurrent Engineering Center. The underlying goal of this transformation is to better serve the Ames PI community in a cost-effective and rapidly-responsive way, providing quality products pivotal to the decision-making proposal strategy of our center. The four pillars of the change focus on four areas: personnel, physical places, tools, and training. Personnel: the MDC switched from using a dedicated pool of engineers—mostly entry-level career—for a matrixed approach with more experienced Subject Matter Experts, usually involved in spaceflight projects. These SMEs get detailed to the MDC for the duration of the study on a part-time or full-time basis. Physical places: The physical aspect pertains mostly to the layout of the new Engineering building and the dedicated concurrent engineering layout to foster collaboration. The current plan includes a dedicated space for concurrent engineering sessions as well as dedicated project rooms for concept studies. Tool: the MDC team is developing a new in-house concurrent engineering tool to facilitate concurrent engineering sessions. The team leveraged the many lessons learned and insight gained from using the current concurrent engineering tool, in use since 2007. SMEs have been involved throughout its design and development, ensuring accuracy and providing validity to the implementation approach. This new tool is database-driven and allows a team to work concurrently on the same model of a mission concept. “Workspaces” are provided for each of the traditional spacecraft mission design disciplines, including cost accounting and systems engineering. There are multiple tiers of fidelity available within each workspace, which can be completed parametrically or independently from the other disciplines as needed or synchronously with the other disciplines. A “commit” step synchronizes a workspace with the mission database and identifies any potential conflicts, along with the user who entered the conflicting data. A Mission Summary workspace enables a Study Lead to run an effective CE session, displaying key graphics, workspace status information, and technical and monetary budget information. This new CE tool will be undergoing Beta Testing with its primary user base and a limited Parts database in the summer of 2020. The team plans to release the first fully operational version in December 2020. Training: working in early concept development and maturation for a space mission requires a unique mindset and being comfortable with uncertainties in an environment where requirements are not yet fully developed, and where changes and trade-offs happen at a high tempo. The MDC started a weekly training program to ensure a common knowledge base on how do develop and mature early concept studies, as well as how to operate in a concurrent engineering environment. In conclusion, the MDC transformation will provide the overall PI community focused on cost-effective small satellite scientific missions with a powerful tool to address and mature early concepts more effectively and efficiently.
David Mauro↗
Spreadsheets in Team X: Preserving Order in an Inherently Chaotic Environment
JPL is NASA's prime center for deep space missions. In response to the need to reduce the cost and time to complete early concept studies and proposals JPL created the first concurrent engineering team in the aerospace industry: Team X. Started in 1995, Team X has carried out over 800 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. Since its inception, the software backbone of this highly successful design team - engaged in examining some of NASA's cutting edge concepts - has been the unassuming spreadsheet. Over the years the Team X spreadsheet-based tools have evolved from simple standalone engineering models into a networked spreadsheet intensive system with real time parameter updating. Recent new capabilities include stochastic cost estimation and a graphical drag and drop block diagram that automatically populates the related spreadsheet parameters of cost, mass and power. This paper describes how the spreadsheet functions within Team X: its history, architecture, current capabilities, enabling strengths and persistent weaknesses. In addition, the verification methods and institutional oversight that have evolved as the Team X products became increasingly critical to Laboratory success are also discussed.
concurrent engineering↗
A Concurrent Design Approach for Designing Space Telescopes and Instruments
At the Project Design Center at the Jet Propulsion Laboratory, a concurrent design environment is under development for supporting development and analysis of space instruments and telescopes in the early, conceptual design phases.
Concurrent↗
Computational simulation of concurrent engineering for aerospace propulsion systems
Results are summarized of an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulations methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties - fundamental in developing such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering for propulsion systems and systems in general. Benefits and facets needing early attention in the development are outlined.
Chamis, C. C.↗
Computational simulation for concurrent engineering of aerospace propulsion systems
Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.
Chamis, C. C.↗
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.
Zusack, Steven↗
Control-structure-thermal interactions in analysis of lunar telescopes
The lunar telescope project was an excellent model for the CSTI study because a telescope is a very sensitive instrument, and thermal expansion or mechanical vibration of the mirror assemblies will rapidly degrade the resolution of the device. Consequently, the interactions are strongly coupled. The lunar surface experiences very large temperature variations that range from approximately -180 C to over 100 C. Although the optical assemblies of the telescopes will be well insulated, the temperature of the mirrors will inevitably fluctuate in a similar cycle, but of much smaller magnitude. In order to obtain images of high quality and clarity, allowable thermal deformations of any point on a mirror must be less than 1 micron. Initial estimates indicate that this corresponds to a temperature variation of much less than 1 deg through the thickness of the mirror. Therefore, a lunar telescope design will most probably include active thermal control, a means of controlling the shape of the mirrors, or a combination of both systems. Historically, the design of a complex vehicle was primarily a sequential process in which the basic structure was defined without concurrent detailed analyses or other subsystems. The basic configuration was then passed to the different teams responsible for each subsystem, and their task was to produce a workable solution without requiring major alterations to any principal components or subsystems. Consequently, the final design of the vehicle was not always the most efficient, owing to the fact that each subsystem design was partially constrained by the previous work. This procedure was necessary at the time because the analysis process was extremely time-consuming and had to be started over with each significant alteration of the vehicle. With recent advances in the power and capacity of small computers, and the parallel development of powerful software in structural, thermal, and control system analysis, it is now possible to produce very detailed analyses of intermediate designs in a much shorter period of time. The subsystems can thus be designed concurrently, and alterations in the overall design can be quickly adopted into each analysis; the design becomes an iterative process in which it is much easier to experiment with new ideas, configurations, and components. Concurrent engineering has the potential to produce efficient, highly capable designs because the effect of one subystem on another can be assessed in much more detail at a very early point in the program. The research program consisted of several tasks: scale a prototype telescope assembly to a 1 m aperture, develop a model of the telescope assembly by using finite element (FEM) codes that are available on site, determine structural deflections of the mirror surfaces due to the temperature variations, develop a prototype control system to maintain the proper shape of the optical elements, and most important of all, demonstrate the concurrent engineering approach with this example. In addition, the software used for the finite element models and thermal analysis was relatively new within the Program Development Office and had yet to be applied to systems this large or complex; understanding the software and modifying it for use with this project was also required. The I-DEAS software by Structural Dynamics Research Corporation (SDRC) was used to build the finite element models, and TMG developed by Maya Heat Transfer Technologies, Ltd. (which runs as an I-DEAS module) was used for the thermal model calculations. All control system development was accomplished with MATRIX(sub X) by Integrated Systems, Inc.
Thompson, Roger C.↗
NASA Tech Briefs: What Does a Microbial Ecologist Do?
Dr. Leslie Bebout works as a microbial ecologist in the Exobiology Branch at NASA's Moffett Field, CA-‐based Ames Research Center. She and her colleagues study the complexities of carbon, nitrogen and hydrogen cycling in early Earth and Mars analog microbial systems. They concurrently are using this systems biology approach to work with engineers to design systems geared to optimize the use of water, light and nutrient resources relevant both to the development of new green technologies and space exploration capabilities.
Garud, Sumedha↗
Early Formulation Model-centric Engineering on NASA's Europa Mission Concept Study
The proposed Jupiter Europa Orbiter and Jupiter Ganymede Orbiter missions were formulated using current state-of-the-art MBSE facilities: - JPL's TeamX, Rapid Mission Architecting - ESA's Concurrent Design Facility - APL's ACE Concurrent Engineering Facility. When JEO became an official "pre-project" in Sep 2010, we had already developed a strong partnership with JPL's Integrated Model Centric Engineering (IMCE) initiative; decided to apply Architecting and SysML-based MBSE from the beginning, begun laying these foundations to support work in Phase A. Release of Planetary Science Decadal Survey and FY12 President's Budget in March 2011 changed the landscape. JEO reverted to being a pre-phase A study. A conscious choice was made to continue application of MBSE on the Europa Study, refocused for early formulation. This presentation describes the approach, results, and lessons.
early formulation↗
Integrating post-manufacturing issues into design and manufacturing decisions
An investigation is conducted on research into some of the fundamental issues underlying the design for manufacturing, service and recycling that affect engineering decisions early in the conceptual design phase of mechanical systems. The investigation focuses on a system-based approach to material selection, manufacturing methods and assembly processes related to overall product requirements, performance and life-cycle costs. Particular emphasis is placed on concurrent engineering decision support for post-manufacturing issues such as serviceability, recyclability, and product retirement.
Eubanks, Charles F.↗
Opportunity for early science return by the Artemis Program
The purpose of the Artemis Program is to gather vital scientific and engineering data by conducting robotic exploration missions on the lunar surface both prior to and concurrent with human missions. The Artemis Program includes rapid, near-term development of a variety of small experimental and operational payloads, a low-cost capacity to deliver these payloads to any location on the lunar surface, and the analysis of the data returned. The Artemis Program will provide opportunities to improve the understanding of lunar geosciences, to demonstrate the Moon's unique capacity as an astronomical platform to study the universe, to conduct scientific and technology development experiments, and to prepare for and complement human missions.
Meyer, Charles↗
Quality Function Deployment for Large Systems
Quality Function Deployment (QFD) is typically applied to small subsystems. This paper describes efforts to extend QFD to large scale systems. It links QFD to the system engineering process, the concurrent engineering process, the robust design process, and the costing process. The effect is to generate a tightly linked project management process of high dimensionality which flushes out issues early to provide a high quality, low cost, and, hence, competitive product. A pre-QFD matrix linking customers to customer desires is described.
Dean, Edwin B.↗
Exploring the Science Trade Space with the JPL Innovation Foundry A-Team
The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts with a group called the Architecture Team (A-Team). The A-Team combines innovative collaborative methods and facilitated sessions with subject matter experts and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an ATeam study. In these studies, Concept Maturity Levels (CML) are used to group methods. These levels include idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for exploring the science objectives, feasibility, and scope will be described including use of a new technique for understanding the most compelling science, called a Science Return Diagram (SRD). In the process of developing the SRD, gradients in the science trade space are uncovered along with their implications for implementation and mission architecture. Special attention is paid towards developing complete investigations, establishing a series of logical claims that lead to the natural selection of a measurement approach. Over 20 science-focused A-Team studies have used these techniques to help science teams refine their mission objectives, make implementation decisions and reveal the mission concept’s most compelling science. This paper will describe the A-Team process for exploring the mission concept's science trade space and the Science Return Diagram technique.In June of 2011 a new collaborative engineering approach forearly concept formulation began in the JPL InnovationFoundry [1], six months later becoming the “A-Team” [2].Responding to a need for exploring mission architecturelevel trades [3], the A-Team precedes Team X [4,5] in asequence of concurrent engineering teams at JPL that can beused to mature a concept from a “cocktail napkin” level ideato a complete mission point design. The A-Team efficientlyexplores the science, implementation, and programmatictrade space in early concept formulation. Small, facilitatedgroups of experts generate innovative ideas, quantitativelyassess feasibility, and discover key sensitivities in the tradespace through collaborative analysis and use of advancedmethods and tools. The A-Team process builds off theexperience within JPL and other recent approaches to earlyconcept formulation [6] including best practices of the JPLInnovation Foundry, Project Systems Engineering &Formulation Section, Team Eureka and the Rapid MissionArchitecture Team[7].The A-Team is a focal point for innovative formulationapproaches and people within JPL. It relies on a largebackground of study resources, creative thinkers and “greybeard” scrutinizers, advanced tools, and subject matterexperts with both breadth and depth in experience andexpertise that are all available at JPL. The A-Team isdesigned to be a rapid and efficient process takingapproximately 6 weeks (the entire process can be as short asjust a few days or as long as up to three months) and costingthe equivalent of a work-month of a full-time employee orless. Studies begin with detailed planning and client reviewfollowed by study sessions, analysis work, and reporting.The staffing on each study is customized to the study goalsand objectives, and it is addressed early in the A-Teamprocess. Sessions are generally half-day or whole-day eventsand conducted over a series of days with focused agendas thatare moderated by a trained facilitator. Preliminary results andknowledge capture are available within hours of each session,and a final report is generally available two weeks later.One of the biggest challenges facing early conceptdevelopment is understanding the gradient in science returnversus various available mission scenarios and payload options. Often times, major areas of scientific inquiry havealready been prioritized by science groups, including throughthe National Research Council’s Decadal Studies inAstronomy, Planetary, and Earth Science. Yet science teamscontinue to struggle, especially in competitive missionsolicitations, to capture the right amount of scope that’sachievable within the cost constraints of the opportunity.Often the desire to completely and comprehensively study ascience area in just one mission (after all, true missionopportunities are rare) drives teams to take on too much,providing requirements that are unachievable within theresources of the opportunity without inducing unacceptableimplementation risk. Alternatively, science teams can seekto reduce risk by using an established instrument, but havenot thought through the traceability and key aspects of thescience question to justify its use. Both scenarios lead to badassumptions at the beginning of the concept development thatcan then ripple through implementation option choices,potentially preventing what would have been a good scienceinvestigation from being selected.The purpose of this paper is first to provide some additionalbackground and summary of the A-Team process, tools,people, and facilities. We then focus on the A-Teammethodology for overcoming the barriers of defining thescience scope well at the early concept development stage.This includes understanding the science story andtraceability, and then examining the gradient in science returnversus key characteristics of observables, developing theright payload and mission requirement specification throughexamining the science and implementation trade space.
Ziemer, John K.↗