Reducing Technical Uncertainty in Product and Process Development Through Parallel Design of Prototypes

When developing a new product or process developers may conduct prototyping experiments to test the technical feasibility of design alternatives. We model product and process prototyping as combinations of Bernoulli experiments with known rewards, costs and success probabilities. Experimental outcomes are observed and the design with the highest observed reward is chosen. The model balances the cost of building and testing the prototypes against improvements in expected profits. We present a prototype design methodology that yields the optimal combination of Bernoulli trials with varying parameters and show how the mode of experimentation determines the preferred type of product.