IOT & RELIABILITY PRACTICAL EXAMPLES AND GOOD PRACTICES. Voy Grohman, PhD VP, Firmware Engineering, ID-Systems. IoT Workshop PHM2017

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1 IOT & RELIABILITY PRACTICAL EXAMPLES AND GOOD PRACTICES Voy Grohman, PhD VP, Firmware Engineering, ID-Systems IoT Workshop PHM2017 1

2 Reliability Needs in Industry How important is quality/reliability? Every Boards and CEO will say it is paramount Their actions may tell you a different story! Motivation? It is all about business! 2

3 Reliability Comparison Who has better reliability/quality? Automaker that has ranked in bottom 1/3 in terms of quality for the past 6+ years*, with less than 1/3 of their vehicles recommended by CR Large domestic HVAC manufacturer with less than 1% warranty return rate in 2 years Medium size domestic IoT service company with 60% annual product refurbish rate * - Excludes 2014 data 3

4 Automaker % 50% 40% US Market Share (%) 30% 20% Automaker % of models recommended % of all vehicle models recommended 10% 0% Sources: Bureau of Economic Analysis (BEA), official sales data, CR 4

5 What s The Point? There is no engineering discipline closer tied to business than reliability! You have to know the business well to be successful! 5

6 Predicting Battery Life Example Goal: Predict the battery life of a product in the field Battery life is measured in days of operation Presented data has been normalized (target = 5) 10+ years of development of the battery model Years of testing and development, $$$ spent Design and manufacturing test verification Close quality monitoring and reliable partners 6

7 Predicting Battery Life Example 40.0% frequency 35.0% 30.0% 25.0% Days of battery life operation (scaled) 20.0% 15.0% 10.0% 5.0% 0.0%

8 Predicting Battery Life Example Device Analysis Bring sample devices that failed in the field Put them through rigorous testing and verification to find the failure cause except they do not fail their battery life is 10% higher than model predicts Why? 8

9 IoT Promise IoT tools will not: Magically solve your product issues by themselves IoT tools will: Help you find your product issues so you can remedy them Help you learn about your customer Help you learn the market product operates in IoT is a platform for quality improvement 9

10 Best Companies Companies with highest product quality and reliability: Know their markets extremely well and they design, test and verify in their markets well Have made a strategic decision to invest in quality Design for quality from ground up 10

11 All Failures are NOT Created Equal If the failure is not noticeable to the customer, it has small business impact All failures matter to engineers, but not all failures matter to business 11

12 Product and Process Design Has to incorporate all key quality concepts: understand the customer and the market design specifically for that market know your reliability target (how many 9s?) 12

13 Product and Process Design Development process to take advantage of modern design techniques: focus on correct design principles hold correct design reviews automatic regression testing extended engineering diagnostics correct field diagnostics proper data reviews proper return and warranty analysis 13

14 Return Analysis Significance of No Trouble Found Issues Found MHW EHW FW NTF Business NTF Other NTF Other what are these? 14

15 Today s Biggest IoT Mistakes Collect too much data Collect too little data Collect poor quality data Don't spend enough effort on analyzing data Insufficient understanding of customer market for reliability and prognostics 15

16 IoT Product Improvement Cycle Product (Re)- Launch New Firmware Field Data Collection (New HW Tweak) Data Analysis 16

17 Current Trends Use IoT to learn about the market Use better market knowledge to improve product and quality of prognostics Improve quality of data (better components => better methodology) Automatic data analysis (AI) 17

18 Summary Quality is a process that starts and ends with the customer and their market IoT is a unique platform to help you learn about it in depth 18

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