001491790 001__ 1491790
001491790 005__ 20240723003222.0
001491790 037__ $$aIR
001491790 041__ $$aeng
001491790 245__ $$aData Driven Decision Making through Mathematical Modeling
001491790 269__ $$a2024-04-26
001491790 520__ $$aThe COVID-19 pandemic has had a profound impact on supply chains across multiple 
industries, including the automotive sector. It has exposed notable challenges, such as navigating 
through unexpected delays, sourcing necessary supplies, and facing shortages of both raw 
materials and workforce. These challenges have had a direct and disruptive impact on production 
lines, creating obstacles that hinder the smooth flow of operations and pose significant 
challenges to maintaining productivity. Unfortunately, professionals have often been left to rely 
on intuition rather than data-driven analysis when making crucial decisions in these situations. 

To address these issues a customizable Excel based program has been created 
for optimizing decision making. The mathematical model was developed using Excel to harness 
data-driven analysis offering valuable insights and recommendations. The model will evaluate 
and weigh various alternatives, such as bringing in alternative equipment, sourcing parts from 
local suppliers, or allocating additional personnel. By utilizing this model, companies will be 
empowered to make informed decisions based on objective analysis rather than relying solely on 
gut instincts.
001491790 650__ $$aEngineering
001491790 7001_ $$aMartinez, Dennis Lopez$$uUniversity of Southern Indiana
001491790 8564_ $$942c90da4-5c20-4821-b670-42217d5c2210$$s1263117$$uhttps://library.usi.edu/record/1491790/files/FFFinal%20senior%20report%20Dennis.pdf
001491790 909CO $$ooai:library.usi.edu:1491790$$pGLOBAL_SET
001491790 980__ $$aENGINEERING