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- Creators: College of Liberal Arts and Sciences
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.
public health sphere.
Methods: Semi-structured interviews were collected from 55 adults from the South Phoenix community between November 2009 and September 2010. Interviews were digitally recorded with participant permission and transcribed. Of those collected, 48 transcribed interviews were analyzed using a codebook designed by the researcher. Percent agreement evaluated inter-rater reliability.Results: Latino immigrants in South Phoenix largely agree that health quality is heavily dependent on personal responsibility and not an intrinsic attribute of a given place. Emotional contentedness and distress, both factors of mental health, are impacted by cross-cultural differences between Latino and U.S. culture systems.
Conclusions: As people’s personal perceptions of differences in health are complex concepts influenced by personal backgrounds, culture, and beliefs, attempting to demark a side of the border as ‘healthier’ than the other using personal perceptions is overly simplified and misses central concepts. Instead, exploration of individual variables impacting health allowed this study to gain a more nuanced understanding in how people determine quality of both personal and environmental health. While Latino migrants in South Phoenix largely agree that health is based on personal responsibility and choices, many nonetheless experience higher levels of contentedness and emotional health in their country of origin.