engineering design exam prep

• Not one process, many processes which have common
• characteristics

• Start off uncertain, don’t know exactly what final product
• will look like

As you continue, final product becomes more and more evident

• It is good to go outside of comfort zone (e.g. mech. eng.
• doing chem.)

• Problem Identification,
• Idea Generation,
• Idea Selection,
• Detailed Design,
• Design Validation,
• Implementation,
• End of Life

• Problems within problems, processes within processes, not evident in the
• beginning

• Make sure you are solving the correct problem, be aware of
• what you are actually aiming to do

This allows to find a more efficient solution

• E.g. Hotel Elevator: Slow elevators, instead of speeding them
• up they just added mirrors (pass time)

• junior engineers: … sometimes not your role to change
• problem?

Good engineers do start off a little uncertain/confused

In contrast, not always a problem, sometimes you have an innovative idea (IPAD)

• After you have identified the problem/opportunity, information gathering is
• important

• Figure out what kind of words people in that field use, get
• to know users, other solutions to the same problem someone else might have,
• file a patent

After problem identification, make objectives (long and short term)

• Scope: How far and deep you plan to go, how much impact will
• your idea provide

• Identify what you are NOT going to do, don’t want to solve
• all problems at the same time

To do this, you need constraints

Hard Constraints: Legal, by law things you must follow

• Soft Constraints: Still constraints because you decided you
• MUST have it

• They should be well
• written and should be able to be assessed pass/fail, yes/no

• ALL constraints must be satisfied for your project to be
• complete, for your solution to be acceptable

• Over constrained: Constraints that oppose each other (E.g.
• building must be taller than 6 feet but shorter than 5 feet)

• May be less obvious, but basically things that are near
• impossible to do together

• similar to constraint, things you want to include in your
• final solution/product

• But they are not necessary, and only even think about them
• if your constraint is met

• E.g. our car should be fast (criteria), but the priority is
• for it to even work (constraint)

Criteria is measured, you want to maximize or minimize it

• Criteria often controls the decision made, because all
• solutions are going to satisfy constraints

• You want a balance among criteria, and remember importance
• of one criteria vs. another

• E.g. speed vs. looks, which is more important to you/to the
• overall goal of the item

• This is a very preliminary step, design with an extremely open mind here
• There is more than one solution to any problem, find them, choose best one
• Transportation A to B (Many options, walk, run, drive)
• Communication (Talk, text, email, etc.)
• Techniques for idea generation, brainstorming

• First filter stage, first check which ideas even meet the constraints
• Try and pick best candidates to minimize analysis effort (which requires time + money)
• *Most innovative ideas usually get lost here, need to use experience and open mindedness to judge
• Make sure good ideas don’t get thrown out at this stage
• This is the least depth of analysis, but perhaps most important, most judgement required here
• After the feasibility you should have a few ideas left
• One is too few (too many constraints or not enough effort on idea stage)
• A lot is too much (use another filtration process)
• 90% decisions, 90% cost quote slide ?
• Not only decision stages, decisions are happening all the time

• Consists of 3 main things:
• Multiple, parallel (happening at same time) activities complimenting each other
• Analysis of all the parts of the idea, synthesizing and pulling them all together into one solution
• Virtual and physical prototyping, calculations/computer simulations (solid works) and prototypes, scale models
• Find things that are right/wrong about the different ideas, further analyze and decide which are best
• Synthesize, put best ideas into one solution
• *Challenges: Hard to do an analysis for ALL ideas you initially had, this is why filteration process/feasibility is so important

• Ideas at this point are pretty raw, start putting another layer of effort/detail
• Main goal here is to decide upon best idea and move forward
• Very decision driven, try to differentiate one idea from another
• Performance vs. criteria, may want to start relating back to constraints again
• enough depth slide??
• Also figure out budget in a little more detail
• initial Budget estimation: capital cost (estimate big main parts), operation costs (estimate what it'll take to keep it running), end of life cost (what is going to cost to remove/dispose)

• Pretty much continuous throughout prelim design and idea development
• Usually very informal and subjective
• When making formal/important decisions, you want to be objective, third person point of view
• Perhaps use decision matrix (use weighted criteria, score out of 10, choose best one statistically)
• *Make sure weighting isn't subjective (don’t weight speed most because you like speed), look at it all objectively, what is most important to solving solution/problem, remember purpose of object
• Final decision: Don’t just trust decision matrix, look at results (maybe there are two close solutions)

• At this point you have one idea, but this idea can continue to evolve and grow and be shaped
• Now you can afford to invest a lot more time and money
• Work out all of the details (e.g. specifications, exact size, number of nuts and screws, etc)
• It should theoretically be able to be built at this point
• This one final chosen design should make complete and total sense with respect to the constraints
• Its contribution to all the criteria is evident
• It is the best that it can be, does not have to be perfect obviously
• LOT S of virtual/physical design effort should be put in at this point
• Engineering models, 3D sketches, equations of the system/product
• Create prototypes, full scale if possible, run crash tests, make sure it is user proof
• "optimization", maximize/minimize what you want
• heuristic optimization ?

• Manufacturing, make sure it is going to be built how you designed it
• Process and buildings, be ready for errors and challenges that arise at this point, surprises
• E.g. There are alpha and beta trials with all software, but bugs and problems persist
• Recalls are sometimes a solution to this

• Waste, how will you deal with it
• What are the costs of disposal, what will it cost you, is environment a concern
• Next version designs, now you see strengths and weaknesses of the product (large scale trial and error)