Kettering University

The final area at the General Motors? Lansing Grand River assembly plant is called Final Process and contains repair and alignment/configuration areas before the vehicle is shipped. In order to obtain high productivity and efficiency in the area, this study uses the real time flow data of the vehicles gathered by the WhereNet Wireless Tracking system installed at Lansing Grand River to analyze the throughput of Final Process. The data is studied statistically and then used to create a simulation model to test various hypotheses that can improve the throughput of Final Process.

The idea of the thesis is to provide an energy and cost analysis of the current lighting system used in the C.S. Mott Center. The current energy consumption and cost are determined. It also explores new alternatives to lighting; thus, creating new energy consumption and costs. The thesis then compares the new values to the current values and shows there is a tangible difference between the two systems. The alternative lighting systems resulted in reduction of the energy consumption by as high as 61% and a cost saving up to 35% over a 20 year span.

The United States Air Force required an improved method for predicting its hiring needs, especially in the field of Operation Research Analysts. Through the use of statistics and computational analysis, this thesis encompasses the development of a model for forecasting personnel needs within the Air Force, focusing on Wright-Patterson Air Force Base.

This thesis states the differences between a linear regression model approach to selecting trend and ultimate losses for a Workers' Compensation analysis to a loss development model. It states why the linear regression model should be implemented.

In the software industry, data that is collected in the form of defect reports or support calls can be used to analyze the quality of a product. By comparing the data from successive releases, the improvement or decline in quality can be determined. Having hard data to support claims of quality allows the software company to make better decisions by not having to rely on educated guesses. Rockwell Software has begun to collect defect data weekly to track the defect trends. The only data that is considered is any data after the defect tracking was implemented which contains data only on the current release. All of the existing historical data is ignored by this process. Without historical data, it isn't possible to compare the current release to previous releases to determine whether or not improvements have been made or need to be made. This historical data exists in several databases, it is just a matter of acquiring the data and analyzing it. A process is needed that establishes what data is needed and how to analyze it. It is also necessary to illustrate the benefit this data provides by implementing the process for a product. The purpose of this thesis is to document the process established to analyze software quality using historical data and the outcomes of that process for the RSLinx Enterprise product. There are several secondary goals to the project: predict future data based on historical data and trends, compare RSLinx Enterprise historical data to industry standard data, reduce support calls and assess the overall quality of RSLinx Enterprise. There are four main sources of historical data that were used: defect data from Clearquest, customer support data from Clarify, registration from the RSSS database, and the lines of code data. The process created consists of eight steps: 1. Select the product 2. Select the Historical Releases that will provide the data 3. Obtain the version numbers and release dates 4. Obtain the data from the appropriate databases 5. Analyze the data and identify trends 6. Predict data for the next release 7. Compare data to industry standards or internal benchmarks 8. Implement findings and improvements. As a result of the process, it was determined that the major weakness of RSLinx Enterprise is its usability. The data points to the fact that RSLE is a stable product with good documentation and good support. From the analysis, several ways that the usability can be improved were identified. Improved usability will improve quality and decrease the number of support calls. Decreasing support calls results in savings for the company.

It was recently discovered in the Masterson Index that some of the index calculations were not producing the expected results. This thesis explains and develops a full analysis of the problem. It offers as a solution the derivation of the Second Generation Chain Formula, which is used to ensure correct calculations.