Graduation Semester and Year
2013
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Industrial Engineering
Department
Industrial and Manufacturing Systems Engineering
First Advisor
Erick C Jones
Abstract
This research describes a framework that minimizes uncertainty and risk in lead time and excessive costs associated with multi-automating systems in very complex and dynamic environments. Further, by seeking to reduce risk by increasing the reliability component of the system, crucial inventories levels are maintained and leveraged in complex an environment that provides additional organization cost savings and enhanced flexibility by enhancing their ability to optimize inventories. Inventory control is crucial for any supply chain as it drives the costs which influence business decision models. The reliability of the systems that maintain the important inventories in complex operations is crucial in that it determines the organizational costs and operational failures. Further, preliminary studies on the performance of multiple automated systems that maintained the status on crucial inventory were conducted for the International Space Station (ISS). The longitudinal results revealed that the capability to test, evaluate and predict the performance of automated system technologies required long lead times, redundant and excessive system testing, and end user acceptance. This type of understanding lead researchers to hypothesize that by utilizing a framework to identify, evaluate, and modify the testing approaches to minimize the cost to determine system reliability, usability, and acceptance to send to space, excessive lead times could be reduced by months and possibly years for use of these type of systems. In addition, this research describes a framework that minimizes uncertainty and risk in lead time and excessive costs multi-automating systems in complex environments
Disciplines
Engineering | Operations Research, Systems Engineering and Industrial Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Cavitt, Maurice Dwayne, "Development Of Optimal Decision Model For Multi-system Process Capability Improvements Through A Personnel Environment And Integration (PEI) Framework Utilizing Radio Frequency Identification (RFID) Technology" (2013). Industrial, Manufacturing, and Systems Engineering Dissertations. 20.
https://mavmatrix.uta.edu/industrialmanusys_dissertations/20
Comments
Degree granted by The University of Texas at Arlington