Reflection – Learning Launch

Challenge  I am a mechanical engineer of my organization’s PECVD (Plasma-Enhanced Chemical Vapor  Deposition) group. Recently one of our big challenges is to qualify a new potential supplier for  manufacturing one plastic part for us. The project involves supplier engineers, buyers, financing  department and business management. We work very closely and have many meetings and  discussion around this topic. The biggest challenge of this project was lack of supporting data to  prove that the 2nd source supplier candidate can make reliable and strong part for our future  systems. We want good mechanical properties as current supplier (1st supplier) but we want  reduce cost with local suppliers and different raw material source. We need to convince upper  executives that the parts of potential supplier are reliable and good to sell to our customers.

Selection  The target is simple and clear. We need to provide solid supporting materials to managers to  make them believe what we think, so we choose learning launch tool. Basically, it means we  need to do small and cheap experiments to a quickly test on our ideas or prototypes.

Application  In this case, we need acquire some samples from our suppliers to test our assumption: the part  they made is good enough. It is very impressive that, in the video, Rene Ten points our  judgements are all basically guesses. I totally agree with that statement. We need data and test  result to support the hypotheses, not just “I think” and move the project to next phase. It’s  dangerous to send our parts to customers without any qualification data. If the quality is not  good enough, the flaws may cause machine shut down and lose a lot of money for schedule  delay and scrap useless wafers. Even worse, in high energy plasma condition, bad quality parts  may cause operator injury and death.

Fortunately, we have some samples from our potential supplier and send them to trustable 3rd  party test center to investigate the material properties. Next, to make sure the data is reliable  and worth comparison with 1st suppliers’, we asked them to follow ASTM standards for all our  samples.

Insight  By using the learning launch tool, our team validated the assumptions and made conclusion that  the parts they made is very reliable and good to be test in a large scope. Next, we plan to do  another bigger test: put the whole part in our process chamber, then borrow one chamber from  one of our customer in the future and working with our customers’ process engineers. With  these supporting materials and collected data, I believe we can convince our managers to use  the parts for customers and save a bunch of money for our company.

Approach  It’s our first time to try this design thinking activities, we may come across some errors during  the process. However, I still believe this is a great experience for all of us, especially engineers.  Also, next time with similar project, we can implement this technique in early state to boost our  qualification process and convince people to collect data as soon as possible.


Reflection – Learning Launch Challenge I am a mechanical engineer of my organization ’s PECVD ( Plasma - Enhanced Chemical Vapor Deposition ) group . Recently one of our big challenges is to qualify a new potential supplier for manufacturing one plastic part for us . The project involves supplier engineers , buyers , financing department and business management . We work very closely and have many meetings and discussion around this topic . The biggest challenge of this project was lack of supporting data to prove that the 2nd source supplier candidate can make reliable and strong part for our future systems . We want good mechanical properties as current supplier ( 1st supplier ) but we want reduce cost with local suppliers and different raw material source . We need to convince upper executives that the parts of potential supplier are reliable and good to sell to our customers . Selection The target is simple and clear . We need to provide solid supporting materials to managers to make them believe what we think , so we choose learning launch tool . Basically , it means we need to do small and cheap experiments to a quickly test on our ideas or prototypes . Application In this case , we need acquire some samples from our suppliers to test our assumption : the part they made is good enough . It is very impressive that , in the video , Rene Ten points our judgements are all basically guesses . I totally agree with that statement . We need data and test result to support the hypotheses , not just “ I think ” and move the project to next phase . It ’s dangerous to send our parts to customers without any qualification data . If the quality is not good enough , the flaws may cause machine shut down and lose a lot of money for schedule delay and scrap useless wafers . Even worse , in high energy plasma condition , bad quality parts may cause operator injury and death . Fortunately , we have some samples from our potential supplier and send them to trustable 3rd party test center to investigate the material properties . Next , to make sure the data is reliable and worth comparison with 1st suppliers ’ , we asked them to follow ASTM standards for all our samples . Insight By using the learning launch tool , our team validated the assumptions and made conclusion that the parts they made is very reliable and good to be test in a large scope . Next , we plan to do another bigger test : put the whole part in our process chamber , then borrow one chamber from one of our customer in the future and working with our customers ’ process engineers . With these supporting materials and collected data , I believe we can convince our managers to use the parts for customers and save a bunch of money for our company . Approach It ’s our first time to try this design thinking activities , we may come across some errors during the process . However , I still believe this is a great experience for all of us , especially engineers . Also , next time with similar project , we can implement this technique in early state to boost our qualification process and convince people to collect data as soon as possible .