Abstract

Many industrial engineers perform one-factor-at-a-time (OFAT) experiments to examine situations of process improvement and for problem-solving activities. However, OFAT experiments can prove to be inefficient and unreliable, leading to false optimal conditions. Moreover, they often consist largely of ``trial and error’’, relying on luck, intuition, guesswork and experience for their success. Design of experiments (DOE) takes an alternative, more structured approach. DOE is a powerful technique for discovering a set of process or design variables which are most important to the process/product/system and then assisting experimenters to determine at what levels these variables should be set/ kept to optimise performance. In order to demonstrate the power of designed experiments over the traditional OFAT approach, the authors use a simple catapult experiment. They suggest that such an experiment could act as a powerful weapon in the training of engineers and managers who might be intimidated by a more ``up front’’ statistical approach.