ABSTRACT
This chapter addresses all the parts of the Sustainable Product Evaluation, Engineering, and Design (SPEED) process that involve testing and analysis during the design and sizing loops. We will be using inferential statistical methods to test, draw conclusions, and make predictions about our product, and its design features and its sizing. We begin with a review of experimental design and analysis methods applicable to wearable design. Then we present procedures with examples in the design and sizing loops starting with the simplest and moving to the most complex. Fit testing as part of the design process is iterative and, in the beginning, the tests are simple, quick, and rudimentary. As the design develops, the tests develop as well, becoming more precise and comprehensive. Changes to the design concept are easier and less costly when done in the early stages than in the later stages. Toward the end of product development changes become more expensive and there is less room for error. The general purpose of all testing is to enable us to make better decisions and choices. This involves balancing or trading off risk, cost, and benefit. Risk is the chance of making the wrong decision and the impact of the error. There is always a risk because we can never be 100% certain about any choice. It is important to try to minimize the risk, but at some point, the additional risk reduction is not worth the cost. The procedures described in this chapter can help us manage risk and make good design decisions within a cost range we can afford.
