Experimentation is an important process carried out on new theories, ideas, products and devices to validate them. Despite the quality of the experiment there will always be some uncertainties associated with the experimental data. This experiment discusses the uncertainties associated with the Young's modulus determined from a simple cantilever beam experiment, in which the deflection of the beam due to the applied load is recorded with both a dial gauge and a potentiometer. With the most suitable measurements of beam deflection the average value of Young's modulus and the uncertainties associated with that is calculated. The results were in accordance with the theoretical predictions. The experiment revealed that by statistical analysis of the dataset and by repeating the experiments the random errors could be minimized.
Experimentation is the most important process in engineering and science. Any ideas, theories, products and devices are validated only by experimentation. Despite the quality of the equipment and the efforts of the experimentalists there will always be some uncertainties (variability) associated with the collected data. It is impossible to make exact measurements, but the variability should be reduced to the minimum possible. The uncertainties arise due to two errors – random errors and systematic errors. Random errors are always present and they are random in nature. Systematic errors arise due to the technique adopted to perform the measurements. Random errors can be revealed by repeating the measurements and by statistical analysis of the dataset. Systematic errors always push the results in the same direction and are often more difficult to identify. .
The aim of this experiment was to identify and accommodate the uncertainties associated with the Young's modulus determined from a simple cantilever beam bending experiment. This was achieved by analyzing the geometry of the experiment, identifying the critical parameters affecting the results based on the simple beam bending equation, by repeating the measurements and by comparing the experimental data with the theoretical predictions.
