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Current Good Manufacturing Practices (cGMP' s) were developed to keep the public safe and ensure quality products. Technological evolution of the industry resulted in cGMP requirements which could not keep pace, and ultimately had a restrictive effect on daily operations and process improvements for pharmaceutical manufacturers. In response, the FDA has recently released new Guidances for Industry, PAT-A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance and Pharmaceutical cGMP's for the 21st Century-A Risk-Based Approach, to encourage innovation in the pharmaceutical industry. The current focus is to understand the product, the manufacturing process and operations rather than the previous focus on product testing and release. Other industries have developed innovative approaches to competitive improvement and it is important to learn from their successes and failures . The aim of this study is to identify critical areas for improvement in current pharmaceutical manufacturing practices and to explore solutions to these problems using principles found outside of the pharmaceutical industry. A facility producing pharmaceutical products under cGMP's will be evaluated to gain a "baseline" understanding of current manufacturing practices. Critical and problematic areas will be identified as well as potential opportunities to incorporate external industry practices, with a focus on the Toyota Production System®, to improve the manufacturing process. A ProModel® simulation was developed in as a proof of concept to evaluate proposed improvements to the system. This simulation was run with a number of theoretical changes to the scenario to evaluate the effects and interactions of the proposed improvements. These areas of improvements include: Shrinking traditional batching rules to create a more semi continuous production system, cross training personnel on equipment and responsibilities, and the addition of parallel machines at the equipment bottleneck. Results from the simulation experimentations indicated that significant improvements to product throughput time can be achieved. While all three individual factors studied were found to be significant, the greatest gains were achieved using a combination of batch rule changes and cross training of personnel. Changing the batching rules was found to have the greatest effect on reducing throughput times, due to the drastic reduction of time spent waiting to batch in the system. Cross training resulted in increased capacity in the bottleneck machine with availability during all hours of operation. While parallel machining did achieve improved throughput times when compared to the current state of the system, the additional machine was not justified when compared with the scenario yielding superior results. Lean manufacturing and other alternative techniques should be explored in the pharmaceutical industry to improve current systems and utilized early in the development of new systems. This case study represents a number of possible opportunities for specific areas of improvement as well as suggesting an overall change in manufacturing mindset. The pharmaceutical industry can learn a great deal from outside industries where competitiveness is required to ensure solvency. Acknowledgements I would like to thank my major professor Dr. Valerie Maier-Speredelozzi for all of her help in my studies and research in the Industrial and Manufacturing Engineering department. Without her guidance my research and development as an industrial engineer would not have been possible. I would also like to thank my longtime advisor from the Biomedical and Pharmaceutical Sciences department, Dr. Thomas Needham, for his pharmaceutical expertise and advice. A special thanks to the owners of XYZ Pharma for allowing me free reign over their company and their cooperation to gather information for this study. I would like to thank my parents for supporting all of my academic endeavors, no matter how ridiculous they may seem.

Improvement of Current Pharmaceutical Manufacturing Systems Utilizing Practices from Outside Industries