# What is Engineering Problem Solving?

## The Problem-Solving Cycle

The Dartmouth/Thayer approach to engineering problem solving is a framework for bringing problems of the "real world" into the classroom. Students solve these problems by proceeding through a problem-solving cycle, step by carefully documented step. If they discover that the solution they are working on is, in fact, unviable, they examine their paper trail and move back only so far as they need, perhaps only a single step.

When students have gone the full round of the problem-solving cycle, they look at the original problem and decide whether their solution is specific enough or whether they need to iterate the cycle.

The problem can involve any kind of decision making from a social problem, "Students are taking too long to get into the lunchroom," to a complex one such as how to create an experiment to demonstrate sonoluminescence (light generated by sound).

Each step of the problem-solving cycle is clear:

- State the problem: look at the problem carefully.
- Redefine the problem: redefine it to eliminate bias.
- Identify constraints and set general specifications: refine and add specifications.
- Identify alternative solutions.
- Analyze the alternatives.
- Select the most viable alternative.
- Iterate the cycle until you find a solution.

See a more detailed explanation of the problem-solving cycle.

## The Problem-Solving Matrix

The process of homing in on the best possible solution is framed by a series of problem-solving matrices. The columns of a matrix are headed by the specifications, the rows by the ideas for alternative solutions.

Alternatives can be ranked on a simple scale of good, bad, and neutral (+, -, and 0) or a more sophisticated scale that gives additional weight to the most important specifications. The best solution is the one that garners the most points by satisfying the most specifications.

A sample problem-solving matrix:

## Iteration

The first round of the problem-solving cycle narrows the focus of the original problem. Then it's time to start another round.

- Redefine the problem to develop a more specific solution.
- Generate tighter specifications.
- Brainstorm more focused alternatives.
- Analyze the alternatives and use the matrix to select the one that best narrows the focus of the problem.
- Reiterate the process until the problem is solved, using a new matrix for each major decision.

Sample matrices for an iterated problem — a team's iteration of the problem-solving cycle for an emergency vehicle warning system: