Reflection – Learning Launch 

 Challenge 

 I am an engineer at Casting Plant in aluminium industry . My / Our challenge is to reduce   our product , which is aluminium billet , defect in order to decrease reject rate from to   reach our KPI ’s department . The project scope includes the Casting Section , Reduction   Section , and Maintenance Section , with whom we work closely . The project is limited to   internal resources ( i.e. , budget and employee time ) . The project should not exceed 3   months and the solution should include an even distribution of working hours amongst   the team members . We will focus on trying to find and solve problem that obstructs our   operational from our internal ( Casting Section ) and other sections . 

 Selection 

 Our team has already gone through several design thinking activities / tools , so we are   ready to try the learning launch tool . Broadly speaking , the learning launch is an   experiment meant to quickly test an idea and prototype . 

 Application 

 For our first learning launch , we focused on finding root cause that affected to our defect   product . After finding what our root causes are , we focused to solve problems from our   internal section . We collect operational data , brainstorming with operators and team   leader , and our machine maker / supplier to be analyze then we get operational standard   to optimize the quality of products . Next , we socialize the operational standard / quality   control sheet to all 4 team leaders and 20 operators to use this standard in the field . We   encourage all members to going extra miles so we can reach our goal : reduce defect of   aluminium billet product . In one month , our reject rate decreases from 12.7 % to 5.28 % . It   is a significant result but we know that we still can go further . 

 For our second learning launch , we focused on get support from related section :   Reduction Section and Maintenance Section . We discussed and brainstormed about what   still causes this defect . With an open mind and acknowledge each other 's lacks , other   related section committed to give the best support that they can do to help us reduce our 

 defect . Reduction Section committed to prioritized the molten which is our main material   to be charge on time every batch . Maintenance Section committed to give minor   maintenance every 20x batches to our casting table and major maintenance every 60x   batches . In 1 month , our reject rate can decrease to 4.28 % and the next month our reject   rate is 2.43 % . 

 Insight 

 By applying the learning launch tool , our team identified our assumptions and designed   launches to test these assumptions . Additionally , we thought through anticipated results ,   expecting to find that a more agile approach would improve our workflow , and that both   our team and the key stakeholders would be fairly open to the new prioritization of tasks   and process . 


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: Reflection – Learning Launch 

 Challenge 

 I am an engineer at Casting Plant in aluminium industry . My / Our challenge is to reduce   our product , which is aluminium billet , defect in order to decrease reject rate from to   reach our KPI ’s department . The project scope includes the Casting Section , Reduction   Section , and Maintenance Section , with whom we work closely . The project is limited to   internal resources ( i.e. , budget and employee time ) . The project should not exceed 3   months and the solution should include an even distribution of working hours amongst   the team members . We will focus on trying to find and solve problem that obstructs our   operational from our internal ( Casting Section ) and other sections . 

 Selection 

 Our team has already gone through several design thinking activities / tools , so we are   ready to try the learning launch tool . Broadly speaking , the learning launch is an   experiment meant to quickly test an idea and prototype . 

 Application 

 For our first learning launch , we focused on finding root cause that affected to our defect   product . After finding what our root causes are , we focused to solve problems from our   internal section . We collect operational data , brainstorming with operators and team   leader , and our machine maker / supplier to be analyze then we get operational standard   to optimize the quality of products . Next , we socialize the operational standard / quality   control sheet to all 4 team leaders and 20 operators to use this standard in the field . We   encourage all members to going extra miles so we can reach our goal : reduce defect of   aluminium billet product . In one month , our reject rate decreases from 12.7 % to 5.28 % . It   is a significant result but we know that we still can go further . 

 For our second learning launch , we focused on get support from related section :   Reduction Section and Maintenance Section . We discussed and brainstormed about what   still causes this defect . With an open mind and acknowledge each other 's lacks , other   related section committed to give the best support that they can do to help us reduce our 

 defect . Reduction Section committed to prioritized the molten which is our main material   to be charge on time every batch . Maintenance Section committed to give minor   maintenance every 20x batches to our casting table and major maintenance every 60x   batches . In 1 month , our reject rate can decrease to 4.28 % and the next month our reject   rate is 2.43 % . 

 Insight 

 By applying the learning launch tool , our team identified our assumptions and designed   launches to test these assumptions . Additionally , we thought through anticipated results ,   expecting to find that a more agile approach would improve our workflow , and that both   our team and the key stakeholders would be fairly open to the new prioritization of tasks   and process .
### Output: 