EXAMPLE REFLECTION : LEARNING LAUNCH 

 CHALLENGE AND SELECTION     In my current role as an Associate Technical Service and Development Scientist , I work with   clients in the Mining industry recommending and implementing chemistry solutions to add   lasting value . I am particularly focused on improving business performance , fostering innovation   and meeting sustainability standards .     The case I present here is a New Product Development Case .   Details on the problem statement ,   hypothesis tested and products selected to test are presented in Table 1 .       The tool I chose is “ Learning Launch ” , which in my industry we like to call it “ Pilot Testing ” .   Once   my team and I identified clearly the customer problem , we proposed a hypothesis that would   solve such problem .   Then , among a spectrum of chemicals available across my company , we   chose two that might potentially solve the problem and validate our hypothesis .     My exercise here today shows how I used “ Learning Launch ” or “ Pilot Testing ” to test our   hypothesis with the product we proposed at the customer site .     Table 1 . Overview of the Problem .     OVERVIEW   Problem   Customer is a mining operator that recovers Copper and/or Molybdenum   from polymetallic ore . Customer ’s current problem is low recoveries of   Molybdenum . The customer believes that the high content of clay in this   particular ore is not allowing a proper flotation process . This statement is   supported by literature review . 

 Hypothesis   Tested 

 The metal flotation is being spoiled because the clay is interfering a proper   modification of the surface of the metal . A formulated dispersant , whose   goal is to inhibit the agglomeration of clay in the metal surface , would   maintain the clay particles in suspension allowing the flotation process to   undergo normally . 

 Solutions to Test Two chemicals : Product XUR1 and Product XUR2 . 

 Key   Performance   Indicators ( KPI ’s ) 

 •   Molybdenum recovery and grade . 

 •   Copper recovery and grade . 

 APPLICATION 

 The first part of the Application of the tool is to state a “ Design of Experiments ” , that is , a plan   for the “ Learning Launch ” .   The Design Experiments looked like it : 

 Learning Guide – Design of Experiments 

 Goal :   The purpose of this Proof of Concept study was to : 

 • Test hypothesis exposed previously in Table 1 .   • Screen several dosages of product to determine optimum . 

 Assumptions to be tested : 

 • Recovery of Molybdenum is enhanced .   • No negative side effects on the recovery of copper or other areas of the process .   • Implementing the technology will generate profits to the client . 

 Success metric for Learning Launch :   The following metrics are sufficient to measure the success of the pilot . 

 • Recovery of Molybdenum is enhanced .   • Recovery of copper remains the same or is improved .    • Price to sell Molybdenum along with the cost of the product . 

 Products   Dispersants Dosage    ( g / ton ) 

 Key    Performance    Indicators 

 Product XUR1 25 , 50 , 100 , 200 , 300 Cu and Mo recovery and concentrate grade 

 Product XUR2 25 , 50 , 100 , 200 , 300 Cu and Mo recovery and concentrate grade 

 INSIGHTS AND APPROACH     We ran the pilot at the customer site , with their process and materials .   The technical   performance is summarized in Figures 1 ( Recovery of Molybdenum ) and Figures 2 ( recovery of   Copper ): 

 Figure 1 . Recovery of Molybdenum . 

 Figure 2 . Recovery of Copper 

 In order to determine the economic analysis , the assumptions were : 

 • The customer will be able to sell all extra Molybdenum that is recovered .   • The customer sells Molybdenum at the trading price of 7.26 USD / lb   • Technical improvement seen in pilot does not change with time .   • The most important source of cost for this implementation is the cost of chemical . 

 And the increase in annual revenue and the cost of the implementation are depicted in Figure 3 .   Figure 3 . 

 The main insights are : 

 • Hypotheses and Assumptions Validated . Both products improve recovery of 

 Molybdenum - up to 20 % points - in comparison with no product implemented .   The   grade of molybdenum is also enhanced . Under certain conditions , both products slightly   improve or do not affect the recovery and grade of copper . 

 • In order to maximize the recovery and grade of Molybdenum and , increase slightly the 

 recovery and grade of copper , it is recommended to use Product XUR2 within 50 - 100   g / ton . 

 • Both products do not interfere with processes downstream and meet environmental 

 regulations ( EH&S and Product stewardship check ) . 

 Approach : Customer satisfied with the performance . Moved to commercialization . 


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: EXAMPLE REFLECTION : LEARNING LAUNCH 

 CHALLENGE AND SELECTION     In my current role as an Associate Technical Service and Development Scientist , I work with   clients in the Mining industry recommending and implementing chemistry solutions to add   lasting value . I am particularly focused on improving business performance , fostering innovation   and meeting sustainability standards .     The case I present here is a New Product Development Case .   Details on the problem statement ,   hypothesis tested and products selected to test are presented in Table 1 .       The tool I chose is “ Learning Launch ” , which in my industry we like to call it “ Pilot Testing ” .   Once   my team and I identified clearly the customer problem , we proposed a hypothesis that would   solve such problem .   Then , among a spectrum of chemicals available across my company , we   chose two that might potentially solve the problem and validate our hypothesis .     My exercise here today shows how I used “ Learning Launch ” or “ Pilot Testing ” to test our   hypothesis with the product we proposed at the customer site .     Table 1 . Overview of the Problem .     OVERVIEW   Problem   Customer is a mining operator that recovers Copper and/or Molybdenum   from polymetallic ore . Customer ’s current problem is low recoveries of   Molybdenum . The customer believes that the high content of clay in this   particular ore is not allowing a proper flotation process . This statement is   supported by literature review . 

 Hypothesis   Tested 

 The metal flotation is being spoiled because the clay is interfering a proper   modification of the surface of the metal . A formulated dispersant , whose   goal is to inhibit the agglomeration of clay in the metal surface , would   maintain the clay particles in suspension allowing the flotation process to   undergo normally . 

 Solutions to Test Two chemicals : Product XUR1 and Product XUR2 . 

 Key   Performance   Indicators ( KPI ’s ) 

 •   Molybdenum recovery and grade . 

 •   Copper recovery and grade . 

 APPLICATION 

 The first part of the Application of the tool is to state a “ Design of Experiments ” , that is , a plan   for the “ Learning Launch ” .   The Design Experiments looked like it : 

 Learning Guide – Design of Experiments 

 Goal :   The purpose of this Proof of Concept study was to : 

 • Test hypothesis exposed previously in Table 1 .   • Screen several dosages of product to determine optimum . 

 Assumptions to be tested : 

 • Recovery of Molybdenum is enhanced .   • No negative side effects on the recovery of copper or other areas of the process .   • Implementing the technology will generate profits to the client . 

 Success metric for Learning Launch :   The following metrics are sufficient to measure the success of the pilot . 

 • Recovery of Molybdenum is enhanced .   • Recovery of copper remains the same or is improved .    • Price to sell Molybdenum along with the cost of the product . 

 Products   Dispersants Dosage    ( g / ton ) 

 Key    Performance    Indicators 

 Product XUR1 25 , 50 , 100 , 200 , 300 Cu and Mo recovery and concentrate grade 

 Product XUR2 25 , 50 , 100 , 200 , 300 Cu and Mo recovery and concentrate grade 

 INSIGHTS AND APPROACH     We ran the pilot at the customer site , with their process and materials .   The technical   performance is summarized in Figures 1 ( Recovery of Molybdenum ) and Figures 2 ( recovery of   Copper ): 

 Figure 1 . Recovery of Molybdenum . 

 Figure 2 . Recovery of Copper 

 In order to determine the economic analysis , the assumptions were : 

 • The customer will be able to sell all extra Molybdenum that is recovered .   • The customer sells Molybdenum at the trading price of 7.26 USD / lb   • Technical improvement seen in pilot does not change with time .   • The most important source of cost for this implementation is the cost of chemical . 

 And the increase in annual revenue and the cost of the implementation are depicted in Figure 3 .   Figure 3 . 

 The main insights are : 

 • Hypotheses and Assumptions Validated . Both products improve recovery of 

 Molybdenum - up to 20 % points - in comparison with no product implemented .   The   grade of molybdenum is also enhanced . Under certain conditions , both products slightly   improve or do not affect the recovery and grade of copper . 

 • In order to maximize the recovery and grade of Molybdenum and , increase slightly the 

 recovery and grade of copper , it is recommended to use Product XUR2 within 50 - 100   g / ton . 

 • Both products do not interfere with processes downstream and meet environmental 

 regulations ( EH&S and Product stewardship check ) . 

 Approach : Customer satisfied with the performance . Moved to commercialization .
### Output: 