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Full-Text Articles in Engineering

A Fuzzy Clustering Methodology To Analyze Interfaces And Assess Integration Risks In Large-Scale Systems, Josh Henry Goldschmid Jan 2021

A Fuzzy Clustering Methodology To Analyze Interfaces And Assess Integration Risks In Large-Scale Systems, Josh Henry Goldschmid

Doctoral Dissertations

“Interface analysis and integration risk assessment for a large-scale, complex system is a difficult systems engineering task, but critical to the success of engineering systems with extraordinary capabilities. When dealing with large-scale systems there is little time for data gathering and often the analysis can be overwhelmed by unknowns and sometimes important factors are not measurable because of the complexities of the interconnections within the system. This research examines the significance of interface analysis and management, identifies weaknesses in literature on risk assessment for a complex system, and exploits the benefits of soft computing approaches in the interface analysis in …


Supply Chain Network Analysis For Outboard Motors At Motor Boaters Usa, Seyedalireza (Ali) Ghiasi, Chase Griffith, Djanene Manuel, Yesenia Pérez, Alvand Rafiee Apr 2019

Supply Chain Network Analysis For Outboard Motors At Motor Boaters Usa, Seyedalireza (Ali) Ghiasi, Chase Griffith, Djanene Manuel, Yesenia Pérez, Alvand Rafiee

Senior Design Project For Engineers

Motor Boaters USA found themselves possibly spending too much on their current network distribution of small and large outboard motors and requested new distribution alternatives for the U.S. Through past network distribution data analysis, the team devised 3 scenarios it believed would provide one or more cost effective distribution networks applicable to the request. Through what-if analysis, the teams' calculations produced solid results, which were then presented to Motor Boaters USA for reflection and possible implementation.


Grouping Techniques To Manage Large-Scale Multi-Item Multi-Echelon Inventory Systems, Anvar Abaydulla Dec 2016

Grouping Techniques To Manage Large-Scale Multi-Item Multi-Echelon Inventory Systems, Anvar Abaydulla

Graduate Theses and Dissertations

Large retail companies operate large-scale systems which may consist of thousands of stores. These retail stores and their suppliers, such as warehouses and manufacturers, form a large-scale multi-item multi-echelon inventory supply network. Operations of this kind of inventory system require a large number of human resources, computing capacity, etc.

In this research, three kinds of grouping techniques are investigated to make the large-scale inventory system “easier” to manage. The first grouping technique is a network based ABC classification method. A new classification criterion is developed so that the inventory network characteristics are included in the classification process, and this criterion …


Computational Intelligence Based Complex Adaptive System-Of-Systems Architecture Evolution Strategy, Siddharth Agarwal Jan 2015

Computational Intelligence Based Complex Adaptive System-Of-Systems Architecture Evolution Strategy, Siddharth Agarwal

Doctoral Dissertations

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving …


An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab Jan 2014

An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab

Electronic Theses and Dissertations

Early identification and detection of abnormal time series patterns is vital for a number of manufacturing. Slide shifts and alterations of time series patterns might be indicative of some anomaly in the production process, such as machinery malfunction. Usually due to the continuous flow of data monitoring of manufacturing processes requires automated Control Chart Pattern Recognition(CCPR) algorithms. The majority of CCPR literature consists of supervised classification algorithms. Less studies consider unsupervised versions of the problem. Despite the profound advantage of unsupervised methodology for less manual data labeling their use is limited due to the fact that their performance is not …