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Now, let’s apply stats/PDF/CDF to LSA & LSA-R logistics LRU = Line Replaceable Unit   An LRU required for a 100-hour mission has a constant failure rate of 0.01 failures per hour (so MTBF = 100 hours).   Per the LSA-R, (for simplicity) maintenance swaps are immediate and do not consume mission time. You position/stage (keep) n spares of this LRU at the point of use before the mission starts (so replacements are immediately available)   Let N be the number of LRU failures during the mission.  What distribution models N?  

Let’s switch gears to PBL

Matching: INCOSE concepts to PBL elements

The continuous random variable T is used to model the number of days, t, a mosquito survives after hatching.   The probability that a mosquito survives for more than t days is:

To ensure that an approved Engineering Change Order propagates automatically into updated crew maintenance procedures without manual re-entry, which artifact must be the configuration-controlled ASOT across contractors?

Hypothetical situation: During Test & Evaluation, a deficiency is discovered. How should that flow work to minimize error?

Risk Sensitivity Index – A team runs a Monte Carlo simulation on failure risk for a missile guidance subsystem. The model outputs an estimated risk of failure of 0.0023 with a 95% confidence interval of ±0.0008. What are the lower and upper bounds of the 95% confidence interval? Is this system within a safety requirement that sets the max allowable failure rate at 0.003? [lower]  format – 4 decimals ie, 0.1234 [upper] format – 4 decimals ie, 0.1234 [yes_no]

NFRs are about actions and are measured with explicit metrics.

Consider a fictional topical gel developed to rapidly soothe first-degree sunburn without causing irritation. However, mild skin rashes have been observed in preliminary studies.  This experiment aims to estimate the probability of rash occurrence over time and test whether that hazard rate is within acceptable safety limits. Objective: To statistically determine whether this fictional gel induces a rash at a rate no greater than 1 rash per 200 skin exposure hours, and estimate the probability of rash occurrence over a defined usage period. Assume a significance level = 0.05 Assume hypotheses as: H₀: The rash rate is ≤ 1 per 200 hours H₁: The rash rate is greater than 1 per 200 hours   Experimental Design:   Factor Description Subjects 120 adult volunteers with mild sunburn Application Sites Upper arm or shoulder Frequency Twice daily application for 10 days Exposure Time Estimated 8-hour active duration per application Hazard Measured Occurrence of rash or inflammation near application site * observed total rashes 120   Select all that are true: Hint, you will be using the hazard rate, exposure hours, & expected value.   ——————————– Not needed for solution, but something to keep in mind as an SE Foundations: ISO 24442 – Measurement of UVA protection in vivoISO 24443 – Determination of UVA protection in vitroISO 24440 – Determination of water resistance of sunscreen productsISO 22716 – Cosmetics — Good Manufacturing Practices (GMP)ISO 16128 – Guidelines on Natural and Organic IngredientsISO 11930 – Cosmetics — Microbiology — Evaluation of the antimicrobial protection of a cosmetic product, ensures the product resists microbial growth over its shelf lifeISO 24430 – Cosmetics — Sun protection test methods — In vitro water resistanceConsider interfaces, interactions, policy, and politicsWhat’s keeping the U.S. from allowing better sunscreens? Products sold in Europe, Japan and South Korea offer more protection from the sun. In the U.S., the key ingredients aren’t FDA-approved.https://www.nbcnews.com/health/health-news/us-sunscreen-fda-ingredients-uv-protection-rcna150307 ——————————–  

How can early integration of Human Factors Engineering (HFE) into the INCOSE Technical Process Groups, particularly during Stakeholder Requirements Definition and Architectural Design, influence downstream system performance, usability, and sustainment?