Date of Graduation

12-2016

Document Type

Thesis

Degree Name

Bachelor of Science in Industrial Engineering

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

LaScola Needy, Kim

Committee Member/Reader

Pohl, Edward A.

Abstract

The dynamic and irregular nature of projects in the construction industry causes the complexity of supplier quality management (SQM). The Construction Industry Institute (CII) Research Team (RT) 308 is focused on achieving zero rework through effective supplier quality practices.

This honors thesis is an extension of RT 308’s project work. Its purpose is to look at current supplier evaluation practices within the construction industry, confirm arecommended supplier cutoff rating through data analysis, and determine if outliers in the data set could be normalized. A survey was developed in Qualtrics (an online survey software tool) and sent to CII members for data collection. Once the data was collected and tested for normality, various analysis techniques were used to analyze the data. These techniques include looking at average supplier rating, assigning 0 (poor) or 1 (good) from the average rating, supplier category ratings, average supplier ratings versus the number of non-conformances (NCs)/Purchase Order (P.O.) dollar, and additional category analysis. It was concluded that the recommended cutoff rating of 4 chosen initially was the correct cutoff rating to choose to ensure suppliers with a high number of NCs do not receive a good supplier rating. Category variations were minimal. The effort to eliminate the outliers by looking at the P.O. size was inconclusive. However, the research team could determine causation of the outliers by tracing the responses back to the respondents. Also, if more data was collected, the outliers could potentially be removed with more data points. A larger data set would get a larger sample of the population and may cause some of the data to become normally distributed.

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