Session
Session VII: Educational Programs - Research & Academia
Location
Salt Palace Convention Center, Salt Lake City, UT
Abstract
Cost estimation is a key element in the planning and execution of CubeSat mission, as it helps ensure that resources are used efficiently and that mission objectives remain aligned with technical and operational constraints. A solid technical baseline - one that clearly describes the system’s characteristics - is essential for developing reliable cost estimates and for establishing a shared understanding of the project among stakeholders. This paper presents the cost estimation process used at the ITA Space Center for CubeSat platforms. The method follows a structured, eight-step approach adapted from NASA and ESA standards. The steps begin with receiving the stakeholder's request and understanding the project’s purpose. Next, a Work Breakdown Structure (WBS) is defined or obtained. In the third step, technical project information is gathered or reviewed. The fourth step involves building the cost model based on the chosen methodology. Step five focuses on collecting supporting data, which is followed by the actual cost estimation in step six. The seventh step addresses the analysis of risks and uncertainties. Finally, in the eighth step, the cost estimate is revised after design reviews to incorporate updates and changes. The paper focuses specifically on Step 3, where the technical baseline is defined. This step involves collecting and verifying project data, identifying system characteristics, and tracking technical milestones. This part of the process is particularly important for improving the accuracy and consistency of cost projections, especially for research and educational missions. To build this baseline, parameters such as satellite mass, mission type and duration, orbital profile, propulsion needs, power requirements, data rate, and attitude control specifications are collected. The parameters are selected and refined through discussions with subject-matter experts to reflect the specific needs of the CubeSats developed at ITA. An important aspect of this process is the close collaboration between the estimation team and the technical leaders. This ensures that the information used for cost modeling is up to date and reflects the actual system configuration. Additionally, the process considers the interdependencies between subsystems and external constraints, such as launcher compatibility and payload objectives, to improve overall estimate quality. The approach is illustrated through its application to SPORT; a space weather CubeSat developed at the ITA Space Center. The case study shows how Step 3 contributes to a more reliable cost estimate by grounding it in realistic and well-documented technical assumptions. This paper aims to contribute to the improvement of cost estimation practices for CubeSats and other small satellite missions, offering a process that is structured yet flexible enough to be adapted to projects with similar technical and operational characteristics.
Document Type
Event
A Proposed Process to Define and Collect Project Information for Cost Estimation of CubeSat Platforms
Salt Palace Convention Center, Salt Lake City, UT
Cost estimation is a key element in the planning and execution of CubeSat mission, as it helps ensure that resources are used efficiently and that mission objectives remain aligned with technical and operational constraints. A solid technical baseline - one that clearly describes the system’s characteristics - is essential for developing reliable cost estimates and for establishing a shared understanding of the project among stakeholders. This paper presents the cost estimation process used at the ITA Space Center for CubeSat platforms. The method follows a structured, eight-step approach adapted from NASA and ESA standards. The steps begin with receiving the stakeholder's request and understanding the project’s purpose. Next, a Work Breakdown Structure (WBS) is defined or obtained. In the third step, technical project information is gathered or reviewed. The fourth step involves building the cost model based on the chosen methodology. Step five focuses on collecting supporting data, which is followed by the actual cost estimation in step six. The seventh step addresses the analysis of risks and uncertainties. Finally, in the eighth step, the cost estimate is revised after design reviews to incorporate updates and changes. The paper focuses specifically on Step 3, where the technical baseline is defined. This step involves collecting and verifying project data, identifying system characteristics, and tracking technical milestones. This part of the process is particularly important for improving the accuracy and consistency of cost projections, especially for research and educational missions. To build this baseline, parameters such as satellite mass, mission type and duration, orbital profile, propulsion needs, power requirements, data rate, and attitude control specifications are collected. The parameters are selected and refined through discussions with subject-matter experts to reflect the specific needs of the CubeSats developed at ITA. An important aspect of this process is the close collaboration between the estimation team and the technical leaders. This ensures that the information used for cost modeling is up to date and reflects the actual system configuration. Additionally, the process considers the interdependencies between subsystems and external constraints, such as launcher compatibility and payload objectives, to improve overall estimate quality. The approach is illustrated through its application to SPORT; a space weather CubeSat developed at the ITA Space Center. The case study shows how Step 3 contributes to a more reliable cost estimate by grounding it in realistic and well-documented technical assumptions. This paper aims to contribute to the improvement of cost estimation practices for CubeSats and other small satellite missions, offering a process that is structured yet flexible enough to be adapted to projects with similar technical and operational characteristics.
