Innovation and Problem Solving with an emphasis on TRIZ Tools

ME59700

Credit Hours:

3

Learning Objective:

Familiarize students with methods that are easily accessible but rigorous for formulation and solution of hard (PSPACE or harder) design optimization problems to rapidly create products, services, systems or solutions to specific problems whose performance is insensitive to uncertainties in components and operating environment. It is built around a core of TRIZ ideas developed by Genrikh Altshuller, but integrates cutting edge discoveries and practice from a variety of sources: mathematical problem solving, optimization and decision theory, marketing, finance, and management research, and includes the following:
Identifying the market and value proposition
Rigorous and accessible formulation
Solution via reducing the search space
Eliminating tradeoffs to reduce dimension of optimization problems
Execution through developing strategies for experiment, construction and monetization

Description:

Familiarize students with methods that are easily accessible but rigorous for formulation and solution of hard (PSPACE or harder) design optimization problems to rapidly create products, services, systems or solutions to specific problems whose performance is insensitive to uncertainties in components and operating environment. Problem formulation is based on functional modeling. This enables use of heuristics, cutting edge discoveries and practices from a variety of disciplines organized around a core of TRIZ ideas developed by Genrikh Altshuller. Sources for methods include mathematical problem solving, optimization and decision theory, marketing, finance, and management research. This course seeks to simulate the work environment of the modern engineer or knowledge worker in general. It aims at familiarity with the state-of-the art results, design and analysis tools in many disciplines, the ability to obtain relevant information to formulate and solve problems arising in practice, and encode algorithms/procedures in software where necessary.
Spring 2019 Syllabus
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Topics Covered:

Identifying the market and value proposition

Rigorous and accessible formulation

Solution via reducing the search space

Eliminating tradeoffs to reduce dimension of optimization problems

Execution through developing strategies for experiment, construction and monetization.

Prerequisites:

Linear algebra, differential equations (MATH262) and probability (MATH250) or the consent of the instructor.

Also note...
1) If you are interested in enrolling and have not enrolled in Purdue Online graduate courses previously, please contact Purdue Online Learning/College of Engineering at proed@purdue.edu for additional details.
2. The course is structured to have all assignments due Sunday nights so it is convenient to those working full time.

Applied / Theory:

Web Address:

https://mycourses.purdue.edu

Homework:

Course evaluation is based on weekly quizzes to test understanding of subject material (50%) and project updates to test ability to apply class material to engineering problems chosen by the student (50%). Bonus points will be awarded for posting answers to class questions on the course blog.

Projects:

Project reporting has to be done each week. Project updates have to be submitted via Blackboard on the following Sundays before midnight (January 29; February 3, 10, 17; March 3, 10, 24, 31; April 7, 21). Project updates will consist approximately in the following steps:
1. Problem background, motivation and formulation with references
2. Market identification: size, growth rate, predictability, competition
3. Value proposition to be constructed with all competitive factors
4. Cause effect chains and construction in SIMULINK
5. Linking cause-effect chains with functions/dynamics and finding more equilibria
6. Idealization and modification of dynamics and cause-effect chains
7. Identifying and eliminating trade-offs where possible
8. Solving the final optimization problems
9. Experiment design and product/service development strategy
10. Monetization strategies and calculations

Textbooks:

Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.

Computer Requirements:

Need to be able to run MATLAB/SIMULINK for quizzes and project updates.

ProEd Minimum Requirements:

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Tuition & Fees:

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