Think about current methods that are labor intensive and could be improved with automation. The objective could be to reduce product variance, reduce waste, reduce production cost, improve throughput, modify product design, etc. Where appropriate, teams should describe existing equipment models and get performance characteristics from the vendors. The key is to identify specific numerical metrics to measure, then to perform experiments, and then to compare performace and show how these relate to cost and profit. Teams will analyze this data statistically and present results graphically.
Computer simulation can be useful.
A 1-page report on Phase III, summarizing the research problem, the metric, proposed experiments, and method of evaluation is due at the end of the 7th week. Phase III presentations with initial data are approximately at the end of the 11th week. Based on the results of data analysis, teams consider how performance can be improved. Teams quantify predicted improvements and provide a cost analysis taking into account factors such as labor, increases in market share, decreased liability risks, etc. The new product might be based on modifying the size, material, functionality, user interface, or application of existing products, or combining two products into one.