Guideline for Making Prototypes

The most important guideline when it comes to making prototypes is to only make what is needed. That is, the time and effort to construct a prototype should be justified by the questions it can answer. For example, if you need to know how heavy something will be, that can be readily answered with any CAD software by specifying the material property. The question “does this feel too heavy” cannot be answered in CAD. Always build just enough to accurately address the current unknowns and move the design process forward. This concept of forward progress can also help you identify what needs to be modeled. The more the prototype moves the design process forward the more value provided and better justified is the effort in building it.

Testing Prototypes

The value of a prototype in moving the design process forward is also limited by the approach used in testing that prototype to learn more information. Product usability tests are limited by the audience that test. A fairly common mistake is to rely on engineers and others who are familiar with the product and its particular evolution to test usability in the early design stages. It may make sense from a logistical point of view, but it is nearly impossible to quantify all of the biases and preconceived knowledge that we bring to a project. Usability should be tested with actual potential users of the product. This is a best practice for industrial prototypes that demonstrate the look, feel, and interface of a product. Some prototyping is focused on functional testing. That is, addressing unknown interactions and underlying physics to evaluate if a product or concept can achieve the desired function to the desired quality of performance. For these types of prototypes, users are generally not needed. Rather, a robust experimental set up.

Your testing goals may produce qualitative date, quantitative data or both. Qualitative data is information that cannot be measured or quantified, but can provide insights into the user’s preferences, opinions, feelings, and behaviors. An example of qualitative data collected in physical product prototype testing is the feedback from users who interact with the prototype and share their thoughts and impressions. This feedback can help the product team understand what aspects of the prototype are appealing, confusing, satisfying, or frustrating to the users, and how they can improve the design and functionality of the product.

Quantitative data is numerical information that can be measured or counted. In physical product prototype testing, quantitative data can help evaluate the performance, usability and functionality of the product. For example, a prototype of a new smartphone can be tested by measuring its battery life, screen resolution, processing speed, memory capacity, etc. These are quantitative data that can indicate how well the product meets the design specifications and user expectations.

It is important to note that both qualitative data and quantitative data require a rigorous collection approach. Prototype testing is a scientific process, and the scientific method must be applied.

As you have likely been exposed to the scientific method in prior courses; the scientific method is a systematic process of inquiry that involves making observations, formulating hypotheses, designing experiments, collecting data, analyzing results, and drawing conclusions.  For example, a designer who wants to test a new chair prototype might observe how people sit on different types of chairs, formulate a hypothesis about what makes a chair comfortable and ergonomic, design an experiment to measure the comfort and posture of the users, collect data from the experiment using sensors and surveys, analyze the data using statistical methods, and draw conclusions about the strengths and weaknesses of the prototype.

Testing of prototypes should always follow a well-structured experimental plan. This is developed using the Design of Experiments (DOE) methodology.