Challenge : I work as an engineer in the process development of a medical device for a manufacturing   company . The medical device was previously manufactured by another production plant , and the   manufacturing company I work for is being asked to manufacture the same device almost identical as   the one that already exists in the market .   After process development activities , the process is not giving   expected results , and there was a high scrap rate due to quality issues of the devices being built . Quality   issues are related mainly to one specific process step , the cutting step , it seems the designed tool to do   it was not working as intended and the yield of that step was unacceptably low . The cutting step uses a   cutting die where the pieces being built are pressed with a manually operated press , the pressure   applied to the piece against the die produces the sample to be cut in the desired form , however the   variability in pressure was producing pieces with irregular edges . 

 Selection : The tool I chose was learning launch , I executed small , quick , and cheap experiments to test   an idea to improve the cutting process . I chose it since I think it was applicable for the kind of challenge I   was being exposed , I needed to learn and improve through observation . 

 Application : I had an idea of a pneumatic cutting press to standardize the process , instead of manual   cutting press that was being used .   To start with my learning launch I built a cutting die that could be   used with a pneumatic press we already had in the facility , basically the sample would be placed in the   cutting die to be pressed against it , cutting the sample into the desired form . The idea was to have a   stable pressure of cutting and to produce acceptable samples each time . I involved 3 assemblers , which   would work as my “ customers ” since they will be the ones using the press and involved two engineers   more from different areas : one from manufacturing department and one from occupational health .   These engineers helped me mitigate my confirmation bias , as Heller mentioned . 

 I let assemblers and engineers to use the press meanwhile I started the observation phase . The samples   built with that press were subjected to the quality criteria test , unfortunately , samples failed the test .   The yield was improving but was not higher than 50 % . This means I was getting disconfirming data . So ,   the next step I took was to pivot : We improve the die by attaching some fasteners that were already   used in the device , this idea was given by one of the assemblers after noticing the key problem was the   piece moved when the pressure was going to be applied . After that improvement , we performed the   test again and got a 100 % yield . I think the tool was applied effectively , since even though it did not   worked the first time , I learned from one of the stakeholders and the process was improved   tremendously thank to this . 

 Insight : The insight I got was from involving assemblers and learning from them . I realized the solution   did not had to be fancy looking or a big design breakthrough , it could be something as simple as using   materials you already have available . Specifically , I got to understand that executing these kinds of   experiments with different groups is key to understand the bigger picture of the problem , and of course   to came up with the best solution to it . 

 Approach : I would use the same tool again next time , the tool helped me to understand the key problem   in the process by observation of the applied experiments , and more importantly by the involvement of   different groups in the execution of those experiments . However , considering the useful insight I got   from the assemblers , next time , I would involve assemblers since the beginning of the process   development and use a tool like mind mapping to involve more stakeholders and their ideas . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Challenge : I work as an engineer in the process development of a medical device for a manufacturing   company . The medical device was previously manufactured by another production plant , and the   manufacturing company I work for is being asked to manufacture the same device almost identical as   the one that already exists in the market .   After process development activities , the process is not giving   expected results , and there was a high scrap rate due to quality issues of the devices being built . Quality   issues are related mainly to one specific process step , the cutting step , it seems the designed tool to do   it was not working as intended and the yield of that step was unacceptably low . The cutting step uses a   cutting die where the pieces being built are pressed with a manually operated press , the pressure   applied to the piece against the die produces the sample to be cut in the desired form , however the   variability in pressure was producing pieces with irregular edges . 

 Selection : The tool I chose was learning launch , I executed small , quick , and cheap experiments to test   an idea to improve the cutting process . I chose it since I think it was applicable for the kind of challenge I   was being exposed , I needed to learn and improve through observation . 

 Application : I had an idea of a pneumatic cutting press to standardize the process , instead of manual   cutting press that was being used .   To start with my learning launch I built a cutting die that could be   used with a pneumatic press we already had in the facility , basically the sample would be placed in the   cutting die to be pressed against it , cutting the sample into the desired form . The idea was to have a   stable pressure of cutting and to produce acceptable samples each time . I involved 3 assemblers , which   would work as my “ customers ” since they will be the ones using the press and involved two engineers   more from different areas : one from manufacturing department and one from occupational health .   These engineers helped me mitigate my confirmation bias , as Heller mentioned . 

 I let assemblers and engineers to use the press meanwhile I started the observation phase . The samples   built with that press were subjected to the quality criteria test , unfortunately , samples failed the test .   The yield was improving but was not higher than 50 % . This means I was getting disconfirming data . So ,   the next step I took was to pivot : We improve the die by attaching some fasteners that were already   used in the device , this idea was given by one of the assemblers after noticing the key problem was the   piece moved when the pressure was going to be applied . After that improvement , we performed the   test again and got a 100 % yield . I think the tool was applied effectively , since even though it did not   worked the first time , I learned from one of the stakeholders and the process was improved   tremendously thank to this . 

 Insight : The insight I got was from involving assemblers and learning from them . I realized the solution   did not had to be fancy looking or a big design breakthrough , it could be something as simple as using   materials you already have available . Specifically , I got to understand that executing these kinds of   experiments with different groups is key to understand the bigger picture of the problem , and of course   to came up with the best solution to it . 

 Approach : I would use the same tool again next time , the tool helped me to understand the key problem   in the process by observation of the applied experiments , and more importantly by the involvement of   different groups in the execution of those experiments . However , considering the useful insight I got   from the assemblers , next time , I would involve assemblers since the beginning of the process   development and use a tool like mind mapping to involve more stakeholders and their ideas .
### Output: 