Decision Tools for Engineering Design and Entrepreneurship Course

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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.

Contents

Course Information

Textbooks

  • Recommended Additional Reading
    • Boothroyd, G., Dewhurst, P. and Knight, W. Product Design for Manufacture and Assembly, 2nd edition, Marcel Dekker, Inc., 2002.
    • Hopp, W. and Spearman, M. Factory Physics, 2nd edition, McGraw-Hill, 2000.
    • Hayes, R.H., Pisano, G.P., and Upton, D.M. Strategic Operations: Competing Through Capabilities, The Free Press, 2000.
    • Papalambros, P. and D. Wilde, Principles of Optimal Design, 2nd edition, Cambridge University Press, 2000.
    • Rao, S.S. (1996) Engineering Optimization: Theory and Practice, Wiley-Interscience.
    • Ulrich, K. and S. Eppinger, Product Design and Development, 3rd edition, McGraw-Hill, 2003.
    • Winston, W. and Albright, S.C. Practical Management Science, 2nd edition, Duxbury, Thomas Learning, 2001.
    • Wu, C.-F. and M. Hamada (2000) Experiments : Planning, Analysis, and Parameter Design Optimization, J. Wiley.


Course Overview

The problem we will develop and solve in this class is: Given a product design concept or new technology, what is the most profitable plan for design, pricing, and production. Using the wiki's notation conventions, one simplified form of this problem that we will address in class (we will examine variants) is:

maximize NPV = \sum_t\frac{\Pi_t}{(1+r)^t} the net present value of future cash flows

with respect to

\mathbf{}p_t price (at each time step)
\mathbf{x} product design variables
\mathbf{y} production process variables

subject to

[\mathbf{x,y}]\in\mathcal{F} the design and production choices must be jointly feasible

where

\mathbf{}\Pi_t = p_tq_t-c_t profit is price times demand minus cost
c_t = f_\mathrm{C}(\mathbf{x,y},q_t) cost is a function of design, process, and production volume
q_t = f_\mathrm{Q}(\mathbf{x},p_t) demand is a function of the design and price

We will develop this model in four parts:

  • In Part I we will introduce basic concepts of economics and optimization, such as the time value of money and theory of nonlinear programming.
  • In Part II we will examine how to model the cost function fC, including study of production functions, operations management, and technical cost modeling.
  • In Part III we will examine how to model the demand function fQ, including study of survey design and models of consumer choice behavior.
  • In Part IV we will examine extensions and advanced topics needed for modeling integration and not covered by the basic model, including decision trees, value of information, dynamics, uncertainty, robustness, game theoretic models of competition, design for location, and public policy.



Winter 2009 Schedule

Schedule will change: students should check website regularly or sign up for email alerts at "my preferences".

Wk Date Topic Reading Due Homework Due
1 Jan 13 B: Course introduction, Projects: task, selection, and scope
Jan 15 F: Engineering economics: profit, time-value of money, NPV, discount rate dN Ch 11-13 Plagiarism self-test results
2 Jan 20 F: Production economics: technical feasible regions, production functions, cost functions, marginal products, marginal cost, economies of scale and scope dN Ch 2&4, P&R Ch 6-7 Team selection, Proposed project topic
Jan 22 M: Introduction to optimization - basic concepts, formulation, problem classification, local and global optima, Excel Solver optimization page
3 Jan 27 S: Mini project presentations: project selection and scope Presentation, Peer reviews of other team presentations
Jan 29 M: Optimization 2 - unconstrained nonlinear programming: optimality conditions, numerical methods <- Wiki pages on topics PS1: economic concepts
4 Feb 3 M: Optimization 3 - constrained nonlinear programming: optimality conditions, numerical methods, sensitivity analysis dN Ch3; Optional: Rao Ch.2,5-7 Report: project proposal
Feb 5 M: Optimization 4 - overview of advanced topics: integer programming, nonconvexities, dynamic programming, stochastic algorithms, global optimization
5 Feb 10 F: Types of modeling: simulation vs. optimization, introduction to operations management Sterman: Computer Modeling for Skeptics, Factory Physics, ESD Symposium Overview PS2: optimization
Feb 12 F: Technical cost modeling: The system-wide impact of design decisions on manufacturing operations Field et al "TCM"; Kirchain et al., "Process-Based Cost Modeling."
6 Feb 17 F: Building your technical cost model: Model scope and architecture Production inputs worksheet (initial inputs due for use in-class)
Feb 19 F: Technical cost modeling workshop: Defining model relationships and performing sensitivity analysis Exercise: decision-process relations (due in-class); PS3: cost modeling (due Monday, Feb 23, 5pm)
7 Feb 24 Team meetings [BH-131E]
Feb 26 S: Mini project presentations: modeling production
8 Mar 3 M: Modeling demand for product attributes, random utility models, logit, probit, independence of irrelevant alternatives Introduction to random utility discrete choice models, Train Ch 1-3,5
Mar 5 M: Random utility models: utility functional forms, model estimation, maximum likelihood Train Ch 8 Report: production analysis, peer reviews
Mar 10 Spring break - no class
Mar 12 Spring break - no class
9 Mar 17 M: Survey design: conjoint analysis, design of experiments, fractional factorial designs DOE page
Mar 19 M: Rating, ranking and choice designs, D-efficiency, the outside good and the no choice option Kuhfeld's market research guide, SAS CBC tutorial Preliminary survey plan
10 Mar 24 M: Heterogeneity, mixed logit, basic econometrics Train Ch 6 Survey due to classmates
Mar 26 F: Decision analysis dN Ch 16 PS4: choice models, Return completed surveys
11 Mar 31 class canceled due to illness - do readings
Apr 2 S: Mini project presentations: modeling demand
12 Apr 7 F: Value of information, Roye Werner on library resources for market analysis dN Ch 17 Report: demand analysis, peer reviews
Apr 9 B: Team meetings Revised survey draft
13 Apr 14 F: Business plan creation, model integration Hand out revised surveys
Apr 16 No Class: Spring Carnival
14 Apr 21 M: Competition, game theory Return revised surveys. PS5a: decision trees, value of info
Apr 23 B: Team meetings
15 Apr 28 S: Presentation of Integrated Model Analysis, including robustness PS5b: competition, game theory
Apr 30 S: Dry-Run of Final Presentations
F May 4 S: Final Project Presentations (5:30-8:30pm, SH125) Reception starts at 5pm Report: final project report, peer reviews due Friday, May 1; Slides: due Sunday, May 3.



Course Guidelines and Policies

Design Project

This course provides engineering students with a tool-set to assess and communicate the economic competitiveness of a new product design or innovative technology. The course involves a team-based semester-long project where students will apply this tool set to planning for a new product design or technology. 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.

Company-Supported Projects: Although most teams will select their own projects, some teams may engage in a project supported by an outside company, when available. In the case of company-supported projects, some companies may request additional analysis or interaction from the students. These additional requests not required within the scope of the course should be agreed upon at the beginning of the project between the students and the faculty leading the course. The cost of all phone calls and travel associated with the company project will be covered by the supporting company. A budget, and formal procedure for how such arrangements will be made should be agreed upon between the faculty and students before the start of the project.

Expectations

Students are expected to attend and participate in all lectures and all meetings for their team. The course is twelve units, so each student should spend about twelve hours per week with approximately 2/3 of this time devoted to the project. With a team of three members, this is over 480 person-hours, with more than 320 hours devoted to the project.

  • Project Meetings with the Instructor:

Student teams are expected to meet with the instructors on a regular basis throughout the term. Each team should plan to meet with the instructors at least one time for each of the major project assignments, specifically, (1) project selection and scope, (2) process model development, (3) demand model development, and (4) model integration. Additional meetings can be scheduled as necessary by individual teams. In some cases, these project meetings will be able to occur during the last half hour of class. In addition, weekly office hour time slots will be agreed upon during the first week of class.

Assignments

The course consists of three types of assignments – problem sets, project reports, and peer review. Graduate students will submit an additional independent research assignment.

Students will work in teams on project assignments, which will be submitted one per team unless otherwise specified. Students are encouraged to collaborate on the problem sets; however, problem sets will be submitted individually and must represent the student's individual work.

Two mechanisms will be used for peer review.

  • Between Teams: On team presentation days, each student will be required to write a review of each of the other teams' presentations with comments and suggestions.
  • Within Teams: Each student will be required to submit peer evaluations with each project report for each member of their team (including themselves). These reports are primarily to help the instructors identify difficulties and miscommunications in time to make corrections as well as to help in assigning fair grades.

All between team peer reviews will be submitted individually at the end of each team presentation class.

Teamwork

The experience of working in teams on this project will serve as preparation for teamwork in industry. Some teams may experience an imbalance in team member contributions, effort, or reliability. The course instructors are available to provide advice and interact in resolving team inequity and conflict; however, students should view this time as a learning experience: Such situations occur with regularity in the industrial world as well. If you experience challenges within your team, it is a good chance to develop strategies and figure out how you will address such challenges in the future. Addressing challenges within the team, when possible, is the most beneficial learning experience, and the instructors are available to provide guidance in doing so. In addition, one common question asked at job interviews is: “Describe a time when you experienced difficulties working in a team or experienced a team failure. What did you do about it?” This is a good chance to build a strong answer to this question.

Final Project Presentation

The final project presentations will occur during finals week, with the date and location TBA. A panel of faculty, venture capitalists, and industry leaders will be invited to attend. Students should plan to present themselves professionally -- including their slides, report, and presentation -- and to have final copies of their report to hand-out to members of the panel

Grading

The central goal of this course is to prepare engineers to assess and communicate -- both quantitatively and qualitatively -- the economic competitiveness of a new product or technology they are looking to commercialize, whether individually, through senior levels of management at a large corporation, or as senior levels of management at a large corporation themselves. To this end, students will be graded in five main areas (1) understanding of basic principles; (2) timeliness and quality of project assignment completion; (3) concept synthesis into a coherent business plan; and (4) verbal, written, and visual communication of findings. Specific grading in these four areas can be approximately weighted as below, although the instructors reserve the right to make changes to better reflect the balance of work in the course:

Understanding of Basic Principles

  • Problem Sets 15%
  • Peer Review 10%

Ongoing Project Assignments

  • Project Scope and Selection 5%
  • Production Analysis 15%
  • Demand Analysis 15%

Final Business Plan

  • Presentation 10%
  • Written Report 30%

Late Policy and Policy on Recording

  • Late assignments will not be accepted. Given special circumstances (family illness, medical issues, etc.), students should approach the instructors.
  • No student is permitted to record or tape any classroom activity without the express written consent of the instructor. If a student believes that he/she is disabled and needs to record or tape classroom activities, he/she should contact the Office of Disability Resources to request an appropriate accommodation.

Policy on Cheating and Plagiarism

The instructors will make it a policy to give students the benefit of the doubt that they put forth honest effort and submit original work in an effort to learn, practice, improve, and develop the skill set and experience that they will need in their future careers. Taking this position allows us to gear the class toward effective learning, rather than policing, and it promotes a more enjoyable and respectful work environment. Because we value the ability to make this assumption so highly, we will hold zero tolerance for any student who chooses to cheat for any reason. Cheating, plagiarism, unauthorized collaboration, deliberate interference with the integrity of the work of others, fabrication or falsification of data, and other forms of academic dishonesty are serious offenses – with serious penalties. It is the policy of the instructors that:

  1. students who cheat, plagiarize or otherwise engage in any of the activities described above, will fail the course, and
  2. the instructors will take the offense to the Dean.

Be advised that CMU regularly suspends or expels students for plagiarism. Students are expected to know what constitutes plagiarism. For further guidance on the proper forms of attribution, students can find a tutorial and self-test at http://education.indiana.edu/%7Efrick/plagiarism/. To confirm individual comprehension of what constitutes plagarism, all students are expected to bring in a signed copy of their results from the self-evaluation on the second day of class.

Other good resources include A Pocket Style Manual by Diana Hacker, The Rowman & Littlefield Guide To Writing With Sources by James P. Davis; The Chicago Manual of Style; and Kate Turabian's A Manual for Writers of Term Papers, Theses, and Dissertations. Some online resources are http://gervaseprograms.georgetown.edu/hc/plagiarism.html, http://www.dartmouth.edu/~sources/content.html; and http://libraries.mit.edu/tutorials/general/plagiarism.html.

Course Project

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.

Project Selection

Students will form teams of five people and select projects during the first week of class. Students have the option to:

  1. 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
  2. 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 approved 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
  • polymer spinal implant
  • ceramic coating for Ti hip implant
  • extruded super-conducting wire
  • injection molded hockey sticks
  • anti-fog goggle lens
  • carbon nanotube wall-hanging tape
  • electric screwdriver
  • surfboard
  • laptop
  • drill
  • tripod
  • scale

Project Client Letter

Image:Initech.jpg Bill Lumbergh
Associate, New Ventures Division
Initech Capital Partners, Ltd.
San Francisco, CA 94108

Carnegie Mellon University
Pittsburgh, PA 15213

Thank you for contacting us with your interest in acquiring venture funding through Initech Capital Partners. As we discussed by phone, we have a policy of taking an advisory role with our prospective ventures both in a four month "trial period" prior to prospective funding, as well as in the time thereafter, if funding is received. During the four month trial period, we have several standard deliverables, which we use to guide your company development and provide feedback. At our request, Dr Erica Fuchs and Dr. Jeremy Michalek have agreed to oversee the project, provide necessary guidance and training, and otherwise play our standard advisory role during this period. At the end of this four-month trial period, I will personally fly out, perhaps with some of my colleagues from my own and other ventures, to make a final decision on whether or not to provide first-round funding. At this time we will require a detailed, quantitative analysis of the competitiveness of your new product and technology, as well as an integrated business plan, on which to make our final judgment. Based on the timing of your inquiry, this final assessment to occur the week of May 4.

For your information, I provide a brief outline of our standard "trial period" expectations and deliverables below:

  • February 3: Product Proposal
    • Please provide a document describing the proposed product or technology including a description of function and a picture and/or drawing.
    • Please define the scope of the proposed design analysis by identifying which variables in the design will be under your control and which will be assumed as fixed parameters.
    • Please identify major manufacturing processes involved in producing the product and define the proposed scope of manufacturing analysis by identifying which set of manufacturing processes will be under your control and which will be assumed as fixed.
    • Please identify major product attributes that drive consumer choice between the target design and competing products in the market and identify major competitors in the market.
  • February 24: Production Analysis
    • Identify and defend your choice of 1-2 design variables which you believe will have a significant and systemic affect on the production process
    • Define the relationships between these design variables and associated production process variables
    • Build a process-based cost model of the required production process, including these relationships between design and process variables
    • Identify the dominant cost drivers of your production process
    • Analyze the sensitivity of your unit production costs to your design variables, process variables, and annual production volume
    • Defend your choice of variables for sensitivity analysis
  • April 2: Demand Analysis
    • Please identify the set of observable product attributes in the scope and define how each is measured. Identify any potentially important attributes that have been omitted and justify modeling decisions.
    • Define the mapping from design variables to product attributes, and define constraints that restrict feasible combinations of design variables and attributes.
    • Describe attributes levels, and specify the choice-conjoint survey design selected (main effects?, efficiency?, etc). Describe the respondent pool and general results.
    • Define your choice model (logit? probit? form of utility function), report utility functions for each attribute and interpret.
    • Benchmark competitor products and include them a simulated choice set. What demand would you expect your product to attract in competition with these competitors? Identify which feasible design is projected to generate the greatest demand.
    • Interpret your model and make recommendations: What are the major limitations and caveats? What are the biggest sources of uncertainty? What data are still needed?
  • April 9: Revised Demand Survey Design
    • Submit a revised demand survey design based on feedback received on your demand analysis
  • Week of May 4th (TBD): Integrated Business Plan
    • Summary recommendations for new product attributes, pricing, and plant capacity
    • The following supporting analyses, as supplied in Appendices attached to the summary recommendations:
      • Production analysis
      • Demand analysis
      • Integrated, two-time-period capacity analysis
      • Decision Robustness analysis

Thank you again for approaching Initech Partners, Ltd. to begin developing this relationship. We are excited about the prospect of providing first-round funding for your new product or technology, and look hopefully developing a successful business together.

Regards, Bill Lumbergh

Spring 2009 Projects

# Project Team Members
1 Adhesive fiber material for facemasks
  1. Deniz Demirci (ETIM)
  2. Sneha Shanbhag (ETIM)
  3. Lalita Reddi (ETIM)
  4. Leigh Fortenberry (Mech E)
  5. Kshama Nagaraja (ETIM)
2 Adhesive fiber material for clothing
  1. Raghuvendra Singh (Mech E)
  2. Brian Kliethermes (Mech E)
  3. Roshan Ravindra (Mech E)
  4. Gautam Ghorpade (Mech E)
  5. Corinne Pascale (ETIM)
3 Nanofiber filters
  1. Shane Esola (Mech E)
  2. Ankit Desai (Mech E)
  3. Begum Gulsoy (Mat Sci and Eng)
  4. Siddharth Vijayaraghaven (Mech E)
  5. Lisa Augustyniak (Chem E, EPP)
4 Nanofiber bio-scaffolding
  1. Lionel Jingles (MPD)
  2. Carlton Reeves (Mech E)
  3. Jason Jura (MPD)
  4. David Torres (Mech E)
5 Plug-in Vehicle Batteries
  1. Elizabeth Traut (Mech E)
  2. Ashish Bagga (Mech E)
  3. Sanjeev Mohanty (ETIM)
  4. Charanya Kannan (ETIM)
  5. Orkun Karabasoglu (Mech E)
6 Kyocera Solar Panel Frames
  1. Ed Lynch-Bell (ETIM)
  2. Eric Biester (ETIM)
  3. James Kong (ECE)
  4. Mark Fuge (Mech E)
  5. Max Thanhouser (ETIM)
7 Smart Chargers for PHEVs and EVs (Electric Vehicles)
  1. Brad Hall (Mech E)
  2. Praveen Khurjekar (ETIM)
  3. Prajakta Kulkarni (ETIM)
  4. Charalampos (Harris) Kyriakou (ETIM)
8 Home Appliances Energy Monitoring
  1. Catherine (Hyunhee Cho) (MS Env Science)
  2. Jeongho Kim (PhD Biomed)
  3. Mustafa Biviji(MS ETIM)
  4. Robert Keelan (Sr MechE)
  5. Tushar Porwal (MS MechE)


Winter 2008 Projects

# Project Team Members
1 RHM China Juan Carlos Intriago Velez (jintriag), Arun Gupta, Jehan Azad
2 Solid State Lighting Andrew Hamilton, Carolyn Denomme, Jason Gu, Vikas Jayaran
3 Surfboard Manufacturing Blake Darby, Eric Mellers, Sarah Shivers, Ryan Almeida
4 Lithium Polymer Battery Manufacturing Bharath (Vik), Rachana, Lubna, Vibin
5 Electronic Dosimeter Jonathan Bodner, Jordan Devries, Edwin Uber, Nikhil Kaushal

Corporate Involvement

See page on DTEDE corporate involvement

Resources

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