Data for: "A Probabilistic Measure of Design Reuse"



This dataset contains data collected from a furniture company and analysis procedure to demonstrate our newly proposed probabilistic measure of design reuse. Please read our ASME conference paper 2018 titled “A Probabilistic Measure of Design Reuse” before understanding this dataset. The dataset contains a MS Excel file with four sheets.

The details of each sheet are illustrated below:

Sheet 1: Double bed data – This sheet contains all the furniture data collected for Double-bed type furniture. Each component is represented by the respective classification codes and component occurrences with reference to a specific bed product.

Sheet 2: Component classification – This sheet contains transformed data from Sheet 1. The component classification and respective occurrences are grouped in column wise. The sheet also provides the number of component options in a group frequency and the total components in a group.

Sheet 3: Full Dataset Chi-square score – This sheet illustrates the calculation of a probabilistic measure of design reuse for Double bed product type. The sheet expands Sheet 2 with subsequent calculation of Chi-Square distribution score. Please refer Equation 7 in the above mentioned paper. The subsequent rows demonstrates the total summation of above calculated values for each component and calculation of Chi-square value. The formula used to calculate the score can be noticed in Formula bar for each cell.

Sheet 4: Group wise Chi-square score – This sheet illustrates the calculation of a probabilistic measure of design reuse for each component type. The procedure is same as illustrated in the above point.
Date made availableAug 2018
PublisherUniversity of Strathclyde
Date of data production2018 -

Cite this

Annamalai Vasantha, G. V. (Creator), Corney, J. (Contributor), Sherlock, A. (Contributor), Quigley, J. (Contributor) (Aug 2018). Data for: "A Probabilistic Measure of Design Reuse". University of Strathclyde. A_PROBABILISTIC_MEASURE_OF_DESIGN_REUSE_Dataset_and_Explanation(.xlsx), Readme(.rtf). 10.15129/20ac02c9-7c33-4c5a-a436-157af53ff123