H1.0 Develop Testing Plan

Introduction

Generating solutions to a technical problem may seem easy; however, in order to ensure that your design does, in fact, solve the problem, you need to test your solution. Testing should be designed to verify that the design specifications have been met and that the design performs as intended. Test criteria provide the benchmarks or standards against which you will compare the results of the tests that you perform on your prototype. When you formulate test criteria, always identify a specific question that you will answer or a specification that you will address. Consider both quantitative and qualitative data requirements. Quantitative refers to data that can be measured, such as mass, time, or distance, and is represented by numerical values. Qualitative refers to data that cannot be measured but that describes some quality or categorization and may be informal. Qualitative data can be pass-fail (attractive-unattractive), yes-no (hot-cold), or categorical data (gender, religion, excellent-average-poor).

Equipment 

• Computer and printer
• American Standard Testing Methods (ASTM) books (if available)
• Engineering notebook
• Internet access

Procedure

In this project your team will determine the quantitative and qualitative testing criteria for your design solution. You may need to access the Internet to help you answer some of the questions necessary to define the test criteria. Brainstorm as a team and complete the following steps. Document your work in your engineering notebook. 

1. Revisit your design specifications and list the criteria/benchmarks that should be tested in order to ensure success of your product.
2. For each criterion that should be tested, determine specifically what you need to know. For example, when testing a lamp shade, you will need to know if the material of the shade can withstand the heat that the light bulb produces without burning or melting. 
3. In your media center or on the Internet, look up the ASTM standards for the testing of the materials used in your design solution or devices that are similar to yours, if they exist. You may have to contact a testing facility in your area if you do not have access to ASTM books. A manufacturing company or engineering firm that writes test procedures may have the information that you need.
4. As a team brainstorm the results of your research to determine the parts of your design solution that you will be testing. Your goal is to formulate an appropriate list of test criteria and the method of testing that will objectively measure the effectiveness of your design solution. Consider what type of testing will be performed – qualitative or quantitative? If you have time, it is recommended that you do both. In the case of the lamp shade, if you want to measure the temperature at which the material will burn or melt you will collect quantitative data since the temperature is a numeric value. If you want to determine whether the material can withstand a temperature of 350 degrees F for 24 hours without visible signs of burning or combusting, you will collect qualitative data because the results will be recorded as pass or fail.
5. Determine the degree of accuracy that is needed in the data collected during testing to ensure successful performance of the design. In other words, how close must the measured data value be to the actual value in order to be acceptable? In the case of the lamp shade, you may be able to accept a deviation of 5 degrees in the measured temperature from the actual temperature at which the material burns or melts. In other words, you have determined that the performance of your product will not be adversely affected if the temperature sensor reads 265 degrees (or 255 degrees) during testing as long as the actual temperature is 260 degrees.
6. Create a table similar to the one below to record testing criteria/benchmark information. 

Conclusion

1. Why is accuracy an important aspect of designing tests?
2. Why is it important to understand whether you are testing criteria that will yield quantitative or qualitative data?