1. 12-CRS-0106 REVISED 8 FEB 2013 Data Analytics in Electronics Manufacturing IEEE NSW Section Stefan Mozar

2. 12-CRS-0106 REVISED 8 FEB 2013 2 Overview The aim of this presentation is to show how Data Analytics can be used to make improvements in manufacturing, and the impact that engineering has on the process.

3. 12-CRS-0106 REVISED 8 FEB 2013 Introduction To illustrate the application of data analytics, an example will be use to illustrate an application. Such an example is testing of electronic printed circuit board assemblies (PCA). Board testing is disruptive on the manufacturing flow. Test engineers generally try and test as much as possible to verify a PCA is good. Testing a PCA, typically takes much longer than the assembly process. Thus PCAs are first completely assembled, and tested later. 3

4. 12-CRS-0106 REVISED 8 FEB 2013 Causes of Failure Failure Materials Assembly Design 4

5. 12-CRS-0106 REVISED 8 FEB 2013 How Analytics can Help Industry 4.0 Big Data or Cloud Computing will help predict the possibility to increase productivity, quality and flexibility within the manufacturing industry and thus to understand advantages within the competition. 5

6. 12-CRS-0106 REVISED 8 FEB 2013 Using Analytics 6 Forrester Wave TM

7. 12-CRS-0106 REVISED 8 FEB 2013 The Manufacturing Process 7

8. 12-CRS-0106 REVISED 8 FEB 2013 Results from Manufacturing Field Data Design Data Reliability Safety Pilot Run What are the Data Sources Available? 8

9. 12-CRS-0106 REVISED 8 FEB 2013 Screening with Simulation Monte Carlo Simulation –It can predict production yield –It can isolate design form process –It provides a lot of data –The confidence interval can be stated –No data preprocessing required 9

10. 12-CRS-0106 REVISED 8 FEB 2013 Simulation Steps 1. Develop an equation to calculate tolerances 2. Identify tolerance for each component 3. Include random number generator 4. Run simulation to see if spread falls within range 5. Take further action if required. 10

11. 12-CRS-0106 REVISED 8 FEB 2013 Sample of Monte Carlo Analysis 11

12. 12-CRS-0106 REVISED 8 FEB 2013 The Next Step … 12

13. 12-CRS-0106 REVISED 8 FEB 2013 Additional Statistical Methods A variety of statistical methods can be applied Six Sigma Techniques Optimization Models 13

14. 12-CRS-0106 REVISED 8 FEB 2013 Application to Failure Detection 14

15. 12-CRS-0106 REVISED 8 FEB 2013 Conclusion This method is best suitable for high volume production Be careful as simulation on its own can not detect all potential problems Data Analytics is a game changer which is turning Research & Development work into a data centric discipline. 15

16. 12-CRS-0106 REVISED 8 FEB 2013 Any Questions? 16