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LecE10StepEngineeringandExperimentalDesignv2.pptxLec E - 10 STEPs of Engineering Design
10 Step Engineering Design Process
1. Identification of a Need
2. Problem Definition
3. Constraints
4. Criteria
5. Research
6. Alternative Solutions
7. Analysis (Experimental Design)
8. Decision Making
9. Specification
10. Communication
Engineering Design Example Designing an Electric Car
Identification of a Need – Electric Car
Problem Definition – battery power
Constraints – size of vehicle
Criteria – X miles before recharge
Research – previous electric car batteries
Alternative Solutions – new types of batteries
Analysis – will a new battery type work? Try Out
Decision Making – existing design or new design
Specification – final electric car design
Communication – final electric car report to boss
Engineering Design Example Designing an Electric Car (More Detail)
1. Identification of a Need
2. Problem Definition –a Battery design for a long distance
3. Constraints - weight, cost, size of battery,
present technology and car
4. Criteria - # of miles, easy to recharge, long life,
affordability, max speed is realistic
5. Research - Current battery designs
6. Alternative Solutions – hydrogen cells, thorium, internal combustion
7. Analysis-Perform Experimental Design (See last 6 slides),do the calculations
8. Decision Making - based on calculations
9. Specification - Final Electric Car Design
10. Communication – Present Design Report to your boss
Ex: Providing Safe Drinking Water to a Rulal Village in South America
2. Problem Definition: The community’s only water supplies are local hand dug wells and a river. All are contaminated with fecal coliform from pit latrines and people and animals defecating near or in the river.
Decision Making Process
8. The Decision Making Process uses analysis results to select the best alternative solution.
The typical decision making process involves multiple criteria and no clear favorite.
To make matters worse, the criteria are measured with different metrics, i.e., different units, that cannot be directly compared or added, e.g., dollars, mass, power, durability, aesthetics, desirability, environmental impact, etc.
Different Comparison Systems
A metric score is an actual characteristic of the alternative, e.g., its weight or cost.
A ranking simply orders the alternatives from best to worst for a given criterion.
A Likert scale item gives information on how well a particular alternative meets a given criterion, e.g. 5 might be excellent, 4 very good, etc. In this context, the Likert scale item applies a common numerical scale to different Criterion with different metric scores.
The decision matrix is one of the simplest methods for comparing alternatives with different metrics.
A table is used to present the alternatives and their score on each criterion.
Scores in the matrix can be metrics, a ranking, or Likert scale items or any combination.
The values in the matrix can be evaluated separately or weighted and summed to give a single score.
Table 1: Decision Matrix for Town Water Supply Design
| Alternatives | Water Quality | Water Quantity | Monthly Cost ($/House) | Maintenance (# of Employees) | User Ease of Use | Cost/100 Houses ($1000) |
| Extra Jugs & Education | 4 | 1 | 0 | 0 | 1 | 1.02 |
| Town Slow-Sand filter | 5 | 2 | High | 1 | 3 | > 100 |
| Household Bio-Sand Filter | 4 | 1 | 0 | 0 | 3 | 2.5 - 5.5 |
| Ceramic Pot Filtration | 4 | 1 | $1 | 0 | 3 | 3 |
| Solar Disinfection | 4 | 1 | 0 | 0 | 1 | 8 |
| Moringa Seed Treatment | 3 | 1 | 0 | 0 | 1 | ?? |
| New Latrines | ?? | 0 | 0 | 0 | 1 | 51 |
| New Wells | 4 | 3 | 0 | 0 | 3 | > 100 |
| Renovation of Old Wells | ?? | 3 | 0 | 0 | 2 | |
| Town well & Distribution | 5 | 5 | 1-2 | 1 | 4 | 20 |
10 Step Engineering Design Process
1. Identification of a Need
2. Problem Definition
3. Constraints
4. Criteria
5. Research
6. Alternative Solutions
7. Analysis (Experimental Design)
8. Decision Making
9. Specification
10. Communication
What is Experimental Design?
Engineering based tool for answering Design Analysis questions requiring experiments
Specifies experimental conditions used to determine effects of variables
Determines Optimal Conditions
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Experimental Design:
Is used to optimize Project Design
Is used in Industry for product
relevance and marketability
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DOE v. OFAAT Design of Experiments v. One-factor-at-a-time
Design Experiment to Vary and Optimize
One-factor-at-a-time (OFAAT)
before going to 2nd Factor.
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Factorial Design
Factor = Variable
Response = Result, Dependent Variable
Trial = Experimental Run
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Accounting for Curvature
Non-linear effects
Must run center point(s)
Need more data points where curvature is greatest
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Summary - Experimental Design Involves:
Critical thinking
Optimization
Intelligent variable and variable range selection
Minimum number of experiments
Maximum and high-quality information
Effective experimental program with reflection
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Freshman Engineering Clinic II Dr. Farrell
Introduction to Experimental Design
