Decision Tools for Engineering Design and Entrepreneurship Course
From DDL Wiki
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+ | Carnegie Mellon University | ||
+ | Course number 19-484, 19-784, 24-484, 24-784 | ||
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+ | ---- | ||
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This course provides engineers with a multidisciplinary mathematical foundation for integrated modeling of engineering design and enterprise planning decisions in an uncertain, competitive market. Topics include economics in product design, manufacturing and operations modeling and accounting, consumer [[choice modeling]], survey design, [[conjoint analysis]], [[decision tree]] analysis, [[optimization]], [[game theory]], model integration, and professional communication skills. Students will apply theory and methods to a team project for a new product or emerging technology of their choice, developing a business plan to defend technical and economic competitiveness. Students may choose to select emerging technologies from research at [[Carnegie Mellon]] for study in the course, and in some years venture capitalists and other industry leaders will take part in critiquing student projects. This course assumes fluency with calculus and some prior programming experience. Graduate students will conduct an additional independent research project. | This course provides engineers with a multidisciplinary mathematical foundation for integrated modeling of engineering design and enterprise planning decisions in an uncertain, competitive market. Topics include economics in product design, manufacturing and operations modeling and accounting, consumer [[choice modeling]], survey design, [[conjoint analysis]], [[decision tree]] analysis, [[optimization]], [[game theory]], model integration, and professional communication skills. Students will apply theory and methods to a team project for a new product or emerging technology of their choice, developing a business plan to defend technical and economic competitiveness. Students may choose to select emerging technologies from research at [[Carnegie Mellon]] for study in the course, and in some years venture capitalists and other industry leaders will take part in critiquing student projects. This course assumes fluency with calculus and some prior programming experience. Graduate students will conduct an additional independent research project. | ||
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+ | =Winter 2008 Course Information= | ||
+ | '''Instructors:''' | ||
+ | * Professor [[Erica Fuchs]] | ||
+ | * Professor [[Jeremy Michalek]], SH-323 | ||
+ | |||
+ | '''Administrative Assistant:''' | ||
+ | * Nancy Beatty, 8-2908 | ||
+ | |||
+ | '''Lecture:''' | ||
+ | * BH-A53 | ||
+ | * MW 12:30-2:20 | ||
+ | |||
+ | '''Office Hours:''' | ||
+ | * TBA | ||
+ | |||
=Winter 2008 Schedule= | =Winter 2008 Schedule= |
Revision as of 01:21, 17 December 2007
Carnegie Mellon University Course number 19-484, 19-784, 24-484, 24-784
This course provides engineers with a multidisciplinary mathematical foundation for integrated modeling of engineering design and enterprise planning decisions in an uncertain, competitive market. Topics include economics in product design, manufacturing and operations modeling and accounting, consumer choice modeling, survey design, conjoint analysis, decision tree analysis, optimization, game theory, model integration, and professional communication skills. Students will apply theory and methods to a team project for a new product or emerging technology of their choice, developing a business plan to defend technical and economic competitiveness. Students may choose to select emerging technologies from research at Carnegie Mellon for study in the course, and in some years venture capitalists and other industry leaders will take part in critiquing student projects. This course assumes fluency with calculus and some prior programming experience. Graduate students will conduct an additional independent research project.
Winter 2008 Course Information
Instructors:
- Professor Erica Fuchs
- Professor Jeremy Michalek, SH-323
Administrative Assistant:
- Nancy Beatty, 8-2908
Lecture:
- BH-A53
- MW 12:30-2:20
Office Hours:
- TBA
Winter 2008 Schedule
Date | Topic | Reading Due | Homework Due |
---|---|---|---|
Jan 14 | Course introduction | ||
Jan 16 | Production functions | Ch 2 ESA | |
Jan 21 | Cost functions | ||
Jan 23 | Production functions | Ch 2 ESA | |
Jan 28 | Production functions | Ch 2 ESA | |
Jan 30 | Production functions | Ch 2 ESA | |
Feb 4 | Production functions | Ch 2 ESA | |
Feb 6 | Production functions | Ch 2 ESA | |
Feb 11 | Production functions | Ch 2 ESA | |
Feb 13 | Production functions | Ch 2 ESA | |
Feb 18 | Production functions | Ch 2 ESA | |
Feb 20 | Production functions | Ch 2 ESA | |
Feb 25 | Production functions | Ch 2 ESA | |
Feb 27 | Production functions | Ch 2 ESA | |
Mar 3 | Production functions | Ch 2 ESA | |
Mar 5 | Production functions | Ch 2 ESA | |
Mar 10 | Spring break - no class | ||
Mar 12 | Spring break - no class | ||
Mar 17 | Production functions | Ch 2 ESA | |
Mar 19 | Production functions | Ch 2 ESA | |
Mar 24 | Production functions | Ch 2 ESA | |
Mar 26 | Production functions | Ch 2 ESA | |
Mar 31 | Production functions | Ch 2 ESA | |
Apr 2 | Production functions | Ch 2 ESA | |
Apr 7 | Production functions | Ch 2 ESA | |
Apr 9 | Production functions | Ch 2 ESA | |
Apr 14 | Production functions | Ch 2 ESA | |
Apr 16 | Production functions | Ch 2 ESA | |
Apr 21 | Production functions | Ch 2 ESA | |
Apr 23 | Production functions | Ch 2 ESA | |
Apr 28 | Production functions | Ch 2 ESA | |
Apr 30 | Production functions | Ch 2 ESA |
Winter 2008 Project Guidelines
This course provides engineering students with a tool-set to asses and communicate the economic competitiveness of a new product design or innovative technology. The course is framed around one, team-based semester-long project. Teams will be expected to apply topics covered in class, as well as general engineering knowledge, to develop quantitative models of design, production and projected market response to the product. By nature, each team will have somewhat different tasks and areas of emphasis, depending on the product selected; however, all projects will be expected to demonstrate mastery of the topics covered in class and to address the criteria and guidelines required for project deliverables.
Students will form teams of three people and select projects during the first week of class. Students have the option to:
- Select a new technology with market potential that has not yet been introduced into high-volume manufacturing, such as a new invention from a research laboratory at Carnegie Mellon or a new product concept developed by one of the team members; or
- Select an existing product to model parametrically in order to optimize its design for profitability.
The following guidelines should be used in selecting a product or technology. All products must be improved by the instructors:
- Well-Defined Product: This course focuses on mathematical modeling to support decision-making. There is not sufficient time in the course for conceptual design of a new product. The project should involve an existing product or a new design that has already been well-defined at the conceptual level.
- Moderate Scope and Complexity: The product or technology should involve moderate complexity. For example, a non-differentiated commodity, such as sugar, would be too simple a product unless new competitive manufacturing processes are being explored. On the other hand, a complex product involving many components and manufacturing operations, such as a vehicle, would require a plan for scoping the problem such that only specific manufacturing processes and product attributes are examined in the model with all others fixed.
- Expertise: If the product involves a new technology that requires specialized knowledge of high-tech materials, design, or manufacturing processes, the team should have reliable access to experts who can supply the requisite knowledge.
- Product Attributes: The product or technology should be differentiated in the market: It should compete with existing alternatives along several quantifiable attributes (such as price, efficiency, size, weight, performance, etc.).
- Decision Variables: Design and planning for the product should involve several decisions in design and production that are non-trivial; for example, using a new material, setting dimensions of a component, selecting among a set of alternative component configurations, or choosing the extent of end-product reliability. The models developed in the project will be used to support decision-making along such dimensions.
Examples:
New product or technology | Existing product |
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