Case Study
Flexible Deployment of a Commercial Earth Imaging CubeSat Constellation
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Key Idea Description
Performance Optimization in commercial Earth imaging through flexible deployment of a CubeSat constellation. This study employs a system model and real options analysis to manage uncertainties in market demand and technological conditions. By adopting a flexible satellite launch strategy responsive to realized demand, the research demonstrates how such an approach can maximize net present value (NPV) and operational efficiency while mitigating risks associated with rigid deployment strategies.
- Broad Area: Satellite Imaging, Space Systems Engineering, Strategic Flexibility, Commercial Space Operations.
- Main issues of case: Addressing the high costs and risks of CubeSat constellation deployment, managing variable demand for satellite imagery, and optimizing investment decisions under uncertain conditions.
- Main analytic topics: Real Options Analysis, Monte Carlo Simulation, Demand Forecasting, Cost-Benefit Analysis.
Insights
- Flexible Launch Strategy Benefits: Adopting a flexible CubeSat deployment strategy allows for adjustments based on market demand and technological advancements, significantly enhancing operational efficiency and profitability. This flexibility results in better resource allocation and reduces the risks associated with over-commitment to a fixed deployment plan.
- Increased NPV and Risk Mitigation: The use of real options analysis in planning CubeSat constellations shows a notable increase in net present value (NPV). By responding to actual demand and market conditions, the strategy minimizes financial risks and optimizes investment returns, ensuring a more resilient and adaptable commercial satellite imaging operation.
Training
Relevant lectures:
- Paradigm change in engineering systems and planning
- How to optimise design and decision-making under uncertainty
- How to manage the design process
Gallery
Abstract
This paper investigates the strategic decisions that make for a successful commercial remote sensing constellation. A system model is developed to capture the impact of architectural and business decisions, along with external economic and technical uncertainties, which impact the success of the venture, as measured by Net Present Value (NPV).
The system model is implemented for two architectural approaches. The first is a “rigid strategy” where business decisions and cost commitments are made at the outset of the project, when best guesses for the realization of uncertain parameters are required.
The second architectural approach is a “flexible strategy” which leverages the physically and temporally distributed deployment of a small satellite constellation to make responsive decisions as the future unfolds and uncertainties are better understood.
It is shown that employing flexible strategies can yield up to 30% increases in average NPV, nearly double maximum expected NPV, and improve Value at Risk (VAR) figures by as much 60% over a rigid strategy. This work confirms that commercial success of a remote-sensing constellation is as dependent on technical decisions as on the realization of an uncertain future. Thus, the most prudent course of action is to understand these uncertainties and adopt a reactive and flexible deployment strategy.
Summary
Introduction:
The report examines the deployment of a commercial Earth imaging CubeSat constellation. The project applies principles from Engineering Systems Analysis for Design, including engineering for uncertainty, flexibility in product design, and cost/revenue analysis.
Problem Context:
The development and deployment of a CubeSat constellation is characterized by high costs, technical overhead, and long timelines for generating revenue. The success of such ventures is influenced by uncertain external factors like demand for satellite imagery and launch costs.
System Model:
A system model was created to simulate the interactions of technical, managerial, and external conditions affecting the profitability of the CubeSat constellation. The base case assumes perfect knowledge of the future, while subsequent analyses introduce uncertainty to observe its impact on Net Present Value (NPV).
Key Findings:
- Base Case Analysis: Assuming perfect conditions, the static base case showed a high NPV. However, introducing uncertainties like demand fluctuation and satellite lifetime significantly reduced expected NPV.
- Flexible Strategies: The study explored flexible strategies to enhance system responsiveness to demand. Conditional satellite launches based on realized demand trends showed potential for improved financial outcomes.
Flexibility Options:
- Conditional Satellite Launches: Adjusting the number of satellite launches based on real-time demand can maximize revenue and minimize risks associated with over- or under-deployment.
- High-Reliability CubeSats: Investing in higher reliability CubeSats can mitigate the risk of early satellite failures, ensuring sustained operational capacity.
Base Case:
- Deterministic Case: With 2 spacecraft, the baseline scenario estimates the removal of 793 fragments, a program risk score of 1 out of 5, and total spending of $2.38 billion.
- Uncertainty Case: Introducing budget variability (+/- 22%) and removal rate uncertainty (+/- 30%) results in an average removal of 745 fragments and spending of $2.39 billion. Program risk increases due to potential budget overruns.
Flexible Designs:
To mitigate uncertainties and exploit opportunities, two flexible options are proposed:
- Add Spacecraft: Build and launch additional ADR spacecraft if budget conditions allow.
- Helper Cubesats: Deploy small cubesats to assist in debris capture, increasing capture success probability from 60% to 95%.
Conclusion
Incorporating flexibility into the design and deployment strategy of CubeSat constellations can significantly enhance their economic viability. By adopting responsive and adaptive strategies, companies can better manage uncertainties and improve the chances of financial success in the competitive and uncertain space economy.