How to use data from connected devices for derivation of mission profiles
Abstract
Enrico and Fred discuss the value of using real-world usage data to define mission profiles, advocating for a shift from deterministic to stochastic approaches. They touch on the impact of environmental conditions, the risk of selection bias in data analysis, and weigh the cost-benefit of using connected devices to improve design and reliability decisions.
Key Points
Topics include:
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Importance of Evaluating Real Usage for Mission Profiles
- Emphasized the need to base mission profiles on real-world usage rather than assumptions or specifications.
- Highlighted how inaccurate assumptions can lead to over- or under-designed components.
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Shift from Deterministic to Stochastic Approaches
- Discussed the limitations of deterministic methods that rely on fixed worst-case values.
- Advocated for using statistical distributions to represent real-world variability in loads and conditions.
- Stochastic modeling helps in better understanding risk and optimizing designs.
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Environmental Conditions Matter
- Explored how temperature, humidity, and other environmental factors significantly influence component reliability.
- Real usage data helps reveal operating conditions that differ from lab environments.
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Selection Bias in Data Collection
- Talked about the risk of drawing conclusions from biased datasets e.g., focusing only on failed products or a non-representative user group.
- Stressed the importance of capturing a broad and representative sample for analysis.
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Cost-Benefit of Connected Devices
- Evaluated the investment in IoT-enabled devices for capturing usage and environmental data.
- Weighed the upfront cost of connectivity and data management against long-term savings through better product design, reduced warranty costs, and predictive maintenance.
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Show Notes
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