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Analytical hierarchy process (AHP) is a process by which complex decisions can be organized and analyzed. AHP does not provide a guaranteed, single, correct solution to the problem, however it helps to lead those making the decision in the right direction. AHP works by assigning a relative importance value to each of the criteria, and a relative preference value for the comparison of two designs with respect to that criteria. The table is then normalized by dividing each entry by the sum in each column, to ensure that the sum of each column is equal to 1. This process is repeated for each of the criteria. A decision value is then assigned to each design by multiplying the relative importance of the criteria by the overall preference of the design in that criteria, and then summing the product for all the criteria.   Design 1 was a circular rotating tray with one sensor. Design 2 was a moving rectangular tray with one sensor. Design 3 was a 3x3 square tray with a single sensor mounted over the middle. Finally, design 4 was a stationary  3x3 tray with shading and an individual sensor for each light. An AHP value was first calculated for efficiency and effectiveness. After safety, this is a particularly important design consideration, as if the machine is predicted to be ineffective and/or inefficient, it will not be worth building and testing. The results of the initial relative preference analysis are shown in Table \ref{tab:AHP_Efficiency}.