Energy Efficiency Project – Learning Launch 

 Challenge 

 I am working as Principal Mechanical Engineer in my current organization . My organization is in the   business of design , manufacture and supply of semiconductor fabrication equipments for namely , plasma   etch , CVD coating , PVD coating , thermal processing of Si wafer etc . I am a subject matter expert in thermal   design , product development and R&D of the device components and systems . My team comprise of   several multi - disciplinary experts from mechanical design , controls , software , electrical , sourcing etc . 

 One of the major challenge of operation of semiconductor fabrication equipments is its poor environment   foot - print . The equipments consume significant electricity , cooling water and also has gas and fine particle   emission challenges . Energy efficiency of the equipments are quite low ( may be as low as 20 % ) . Historically   semiconductor equipments technology have been evolved and developed with prime focus on   performance to meet escalating demand of memory chips . Energy efficiency was secondary requirement . 

 However , in recent times emerging competition in the market and increasing Government regulation on   emission and facilities consumption has forced the customers and supply organizations to focus on   reduction of energy consumption and increase efficiency . My engineering group was challenged by a   major customer to reduce heater power consumption of a system by around 30 % to meet Govt restriction   on electricity supply in a major semiconductor fab shop .   Customer had a very strict deadline and had   needed a solution with < 0.05 % failure probability . 

 Selection 

 My organization launched a design for environment ( DfE ) project to meet the above customer challenge .   The DfE team did a brainstorming of several concepts of energy saving . The concepts were evaluated using   QFD , Pugh Matrix , and Risk Assessment tools . When we down - selected one of the most probable concept   which can have differentiated value and has best probability to meet energy efficiency target . But we had   several unknowns : ( 1 ) how to know if the concept is achievable ?   ( 2 ) What is the probability of success ?   ( 3 ) what is the effect and alternate method if we fail to meet target ? ( 4 ) Will there be any degradation of   device performance ? ( 5 ) How to convince customer with alternate design ? 

 Considering the strict deadline and almost NIL margin for failure , team decided that design thinking tool   Learning Launch may be the best way to approach to quickly test the idea and demonstrate a prototype   solution to customer . 

 Application : 

 The baseline design ( current design ) use a conservative approach of supplying high constant flow coolant   in the system and then control the heater power to meet system temperature set point . The concept to   test was can we reduce the coolant flow rate and heater power both simultaneously and meet the same   set point temperature . Theoretically it is possible as with reduced coolant flow rate we remove lower heat   from system and hence we will need lesser heat input from the heater . It is a win - win scenario as we save   energy from both lower coolant flow and lower heater power without sacrificing temperature . 

 A prototype test facility was developed , and the above concept was tested for different operation recipe .   We tried to reach the minimum coolant flow rate and heater power possible . System response ( both   steady state and transient ) were observed and benchmarked against baseline . Overall energy balance of   the system was computed and energy saving with respect to baseline scenario was measured . Team   achieved energy saving better than 30 % , which meets customer requirement . Experiments were repeated   for several conditions and complete database of experimental results were developed . DOE ( design of   experiment ) analysis and statistical regression analysis were carried out to measure confidence level to   meet the target . The complete prototype tests could be completed within 2 months ’ time frame , well   within schedule . 

 Insight : 

 After the learning launch tests , the team could successfully demonstrate that the concepts can work in   actual tool and meet the customer energy efficiency target . The learning launch tests gave the team   sufficient confidence level on the success rate of the concept . Through the tests team also identified   opportunity of development of ANN ( artificial neural network ) based controls instead of traditional   closed - loop PID control , which may provide more optimized heater power management . The team also   identified scope of application of the concept into several other equipments which operates in similar   way . The team proposed the concepts to upper management and customer and got buy in . 

 Approach : 

 The team successfully applied design thinking learning launch tool on the energy efficiency improvement   of an already developed , time tested and mature product . Through this exercise the team realized new   opportunity of using the tool at the concept design level of new products . Instead of going through   complete product development cycle and risk failure at later stage , we can explore using the learning   launch tool at concept evaluation stage and fail fast or get success , which can significantly expedite   product development cycle and meet customer requirement in specific way . 


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: Energy Efficiency Project – Learning Launch 

 Challenge 

 I am working as Principal Mechanical Engineer in my current organization . My organization is in the   business of design , manufacture and supply of semiconductor fabrication equipments for namely , plasma   etch , CVD coating , PVD coating , thermal processing of Si wafer etc . I am a subject matter expert in thermal   design , product development and R&D of the device components and systems . My team comprise of   several multi - disciplinary experts from mechanical design , controls , software , electrical , sourcing etc . 

 One of the major challenge of operation of semiconductor fabrication equipments is its poor environment   foot - print . The equipments consume significant electricity , cooling water and also has gas and fine particle   emission challenges . Energy efficiency of the equipments are quite low ( may be as low as 20 % ) . Historically   semiconductor equipments technology have been evolved and developed with prime focus on   performance to meet escalating demand of memory chips . Energy efficiency was secondary requirement . 

 However , in recent times emerging competition in the market and increasing Government regulation on   emission and facilities consumption has forced the customers and supply organizations to focus on   reduction of energy consumption and increase efficiency . My engineering group was challenged by a   major customer to reduce heater power consumption of a system by around 30 % to meet Govt restriction   on electricity supply in a major semiconductor fab shop .   Customer had a very strict deadline and had   needed a solution with < 0.05 % failure probability . 

 Selection 

 My organization launched a design for environment ( DfE ) project to meet the above customer challenge .   The DfE team did a brainstorming of several concepts of energy saving . The concepts were evaluated using   QFD , Pugh Matrix , and Risk Assessment tools . When we down - selected one of the most probable concept   which can have differentiated value and has best probability to meet energy efficiency target . But we had   several unknowns : ( 1 ) how to know if the concept is achievable ?   ( 2 ) What is the probability of success ?   ( 3 ) what is the effect and alternate method if we fail to meet target ? ( 4 ) Will there be any degradation of   device performance ? ( 5 ) How to convince customer with alternate design ? 

 Considering the strict deadline and almost NIL margin for failure , team decided that design thinking tool   Learning Launch may be the best way to approach to quickly test the idea and demonstrate a prototype   solution to customer . 

 Application : 

 The baseline design ( current design ) use a conservative approach of supplying high constant flow coolant   in the system and then control the heater power to meet system temperature set point . The concept to   test was can we reduce the coolant flow rate and heater power both simultaneously and meet the same   set point temperature . Theoretically it is possible as with reduced coolant flow rate we remove lower heat   from system and hence we will need lesser heat input from the heater . It is a win - win scenario as we save   energy from both lower coolant flow and lower heater power without sacrificing temperature . 

 A prototype test facility was developed , and the above concept was tested for different operation recipe .   We tried to reach the minimum coolant flow rate and heater power possible . System response ( both   steady state and transient ) were observed and benchmarked against baseline . Overall energy balance of   the system was computed and energy saving with respect to baseline scenario was measured . Team   achieved energy saving better than 30 % , which meets customer requirement . Experiments were repeated   for several conditions and complete database of experimental results were developed . DOE ( design of   experiment ) analysis and statistical regression analysis were carried out to measure confidence level to   meet the target . The complete prototype tests could be completed within 2 months ’ time frame , well   within schedule . 

 Insight : 

 After the learning launch tests , the team could successfully demonstrate that the concepts can work in   actual tool and meet the customer energy efficiency target . The learning launch tests gave the team   sufficient confidence level on the success rate of the concept . Through the tests team also identified   opportunity of development of ANN ( artificial neural network ) based controls instead of traditional   closed - loop PID control , which may provide more optimized heater power management . The team also   identified scope of application of the concept into several other equipments which operates in similar   way . The team proposed the concepts to upper management and customer and got buy in . 

 Approach : 

 The team successfully applied design thinking learning launch tool on the energy efficiency improvement   of an already developed , time tested and mature product . Through this exercise the team realized new   opportunity of using the tool at the concept design level of new products . Instead of going through   complete product development cycle and risk failure at later stage , we can explore using the learning   launch tool at concept evaluation stage and fail fast or get success , which can significantly expedite   product development cycle and meet customer requirement in specific way .
### Output: 