BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20241122T000114Z UID:18A30A76-A076-4301-A446-7B286F7FC92D DTSTART;TZID=America/Los_Angeles:20241114T181500 DTEND;TZID=America/Los_Angeles:20241114T200000 DESCRIPTION:Abstract:\n\nProduct reliability is a function of effective usa ge and applied stress (both operational and environmental) conditions. In real life\, both usage and stress levels are not fixed\, but random variab les\; i.e.\, they are statistically distributed. During engineering life t est design\, people often pick the high percentiles for population usage a nd stress level as the field reference for the sake of conservativeness an d safety margin\, such as 90th percentile\, 95th percentile\, or even 99th percentile. This often yields very ambitious and even unrealistic test sa mple size and/or test duration requirements because the majority (say 90% or higher) of users in the field are assumed to be operating under extreme usage and stress conditions. The question often comes up as to which usag e and stress percentile is the appropriate choice so that the overall popu lation reliability is assured. Is it mean\, median\, or some other percent ile (such as 60%\, 70%\, etc.)? This talk is trying to answer that questio n by introducing the so-called Reliability Equivalence Principle\, and the n presenting the analytical expression of reliability-equivalent reference usage and stress value so that the same reliability target can be achieve d at the population level. Numerical example is given to illustrate the ad vantage of the method for reliability life test design over the traditiona l practice\, especially for a high-reliability product.\n\nCo-sponsored by : SRE Society of Reliability Engineers\n\nSpeaker(s): Frank Sun\n\nRoom: L aural Room\, Bldg: Senior Center\, 550 E Remington Drive\, Sunnyvale Commu nity Center\, Sunnyvale\, California\, United States\, 94087 LOCATION:Room: Laural Room\, Bldg: Senior Center\, 550 E Remington Drive\, Sunnyvale Community Center\, Sunnyvale\, California\, United States\, 9408 7 ORGANIZER:bernhard.hiller@wdc.com SEQUENCE:14 SUMMARY:Reliability-Equivalent Field Reference Usage and Stress Level when Both are Random URL;VALUE=URI:https://events.vtools.ieee.org/m/444146 X-ALT-DESC:Description: <br /><p style="margin: 0in\; text-align: justify\; "><strong><span style="font-size: 10.0pt\; font-family: 'Arial'\,sans-seri f\; color: black\;">Abstract: </span></strong></p>\n<p style="margin: 0in\ ; text-align: justify\;"><span style="font-size: 10.0pt\; font-family: 'Ar ial'\,sans-serif\; color: black\;">Product reliability is a function of ef fective usage and applied stress (both operational and environmental) cond itions. In real life\, both usage and stress levels are not fixed\, but ra ndom variables\; i.e.\, they are statistically distributed. During enginee ring life test design\, people often pick the high percentiles for populat ion usage and stress level as the field reference for the sake of conserva tiveness and safety margin\, such as 90th percentile\, 95th percentile\, o r even 99th percentile. This often yields very ambitious and even unrealis tic test sample size and/or test duration requirements because the majorit y (say 90% or higher) of users in the field are assumed to be operating un der extreme usage and stress conditions. The question often comes up as to which usage and stress percentile is the appropriate choice so that the o verall population reliability is assured. Is it mean\, median\, or some ot her percentile (such as 60%\, 70%\, etc.)?&nbsp\;This talk is trying to an swer that question by introducing the so-called Reliability Equivalence Pr inciple\, and then presenting the analytical expression of reliability-equ ivalent reference usage and stress value so that the same reliability targ et can be achieved at the population level. Numerical example is given to illustrate the advantage of the method for reliability life test design ov er the traditional practice\, especially for a high-reliability product.</ span></p> END:VEVENT END:VCALENDAR