Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

This paper analyzes the impact of the December 2022 winter storm on Southwest Airlines (SWA). The storm caused delays and cancellations for all airlines, but SWA was the only major airline that was unable to recover fully. The disruption was unique due to the higher volume of people traveling during the holiday season and the lack of good alternative transportation for stranded passengers. The paper explains SWA's point-to-point (PTP) model, which allows them to offer competitive ticket prices, and organizational factors that have helped them hold a significant market share. The paper also discusses previous failures of SWA's IT and aircraft maintenance management systems and the outdated crewing system, which were not addressed until after the storm. The paper uses AnyLogic agent based modeling to investigate why SWA was so affected and why it took them so long to recover.

Lean philosophy is a set of practices aimed at reducing waste in an industry/enterprise. By eliminating the aspects of a system that do not add value, the system process will be able to work continuously in a flow, and as a result have a shorter cycle time. With a shorter cycle time, less resources are diminished, and efforts can be properly distributed in order to achieve maximum efficiency. In relation, Six Sigma is a process that aims to reduce the variability of a system, and in turn reduce the number of defects and improve overall quality of a product/process. For this reason, Lean and Six Sigma go hand-in-hand. Cutting out non-value adding steps in a process will increase efficiency and perfecting the steps still in place will improve quality. Both aspects are important when it comes to the success of a business practice. DNASU Plasmid Repository would be a major benefactor of the Lean Six Sigma process. The process of cloning DNA requires great attention to detail and time in order to avoid defects. For instance, any mistake made in the bacteria growth process, such as contamination, will result in a significant amount of time being wasted. In addition, the purification of DNA steps also necessitates vigilant observation since the procedure is highly susceptible to little mistakes that could have big impacts. The goal of this project will be to integrate Lean Six Sigma methodology into the DNASU laboratory. By applying numerous aspects of Lean Six Sigma, the DNA repository will be able to improve its efficiency and quality of processes and obtain its highest rate of success.