Industrial & Manufacturing Engineering Masters Theses

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Intelligent Cold Supply Chain Management System with Radio Frequency Identification, Global Positioning System, and Wireless Sensor Network
(North Dakota State University, 2009) Yang, Xiaomin
This thesis establishes an intelligent cold supply chain management system which consists of two parts: one is the intelligent tracking system integrated with Radio Frequency Identification (RFID), Global Positioning System (GPS), and Wireless Sensor Network (WSN); the other is the cold supply chain model. This tracking system is mainly designed to monitor the food products during the transport, including two parts, a data terminal and a data server. The data terminal is installed inside a container, comprised of GPS, Bluetooth, industrial computer, WSN, RFID reader, RFID antenna, and Code Division Multiple Access (CDMA) modem. The data server is a computer which is able to access internet and has one Structured Query Language (SQL) database. Related application programs are developed with JAVA language. The whole system is successfully tested and meets the expectations we desired at the beginning. In this study, a refrigerator is used to simulate the environment of the container. The data terminal collects all information, including temperature inside the container, GPS location, Product's Identification, and current time in five minute intervals (customers will be asked to set this time interval at the beginning). CDMA cellular network provides the communication between the data server and the data terminal. The data server receives all information and saves the information in the SQL database, which can be used to predict the food safety. Advantages of this tracking system include the ability: 1) to trace and track the products starting from the suppliers to retailers; 2) to monitor and store important parameters during the processing and distribution of food products, such as temperature; 3) to communicate in real time for prompt response; and 4) to quantify food safety prediction. The objective of the model developed in this study is to maximize the profit of the cold supply chain. There are one distribution center, multiple retailers and suppliers involved in the cold supply chain. Since the real-time quality situations of products are available even during the transport, retailers can set prices of products based on the real quality situation. The company is able to dynamically plan the quantity of distribution from the distribution or suppliers' site. In addition, retailers are able to manage the inventory based on the real shelf life of products. This thesis also concludes all different inventory results for retailers under different scenarios which can help retailers to predict and manage the inventory. The optimization software, Lindo, is used to demonstrate that this model is capable to dynamically plan the distribution quantity. The sensitivity analysis for prices, transportation costs, and holding costs is discussed to simulate different situations during the transportation and distribution.
Winter Road Maintenance System Design for Snow Plowing
(North Dakota State University, 2010) Kayabas, Poyraz
Winter road maintenance is critical to ensuring safety and mobility of transportation systems in regions with heavy snowfall. Winter road maintenance system design involves several inter-related decision making problems for different operations that are often performed with expensive and limited resources. This study involves developing an integrated solution methodology for depot location selection, district design, and vehicle routing problems for winter road maintenance system design in the context of snow plowing. The methodology allows decision makers to evaluate and compare different system alternatives based on a number of service level related system design criteria. The solution methodology is illustrated using the example of the road network of the Fargo District of North Dakota's transportation system. Results indicate that the methodology can be used as a decision making support tool for planning winter road maintenance operations.
Moisture Sensitivity of PLA/PBS Blends During Ultrasonic Welding and Fused Deposition Modeling
(North Dakota State University, 2021) Quader, Raihan
Moisture absorption into hygroscopic/hydrophilic materials used in fused deposition modeling (FDM) and ultrasonic welding (USW) can diminish desired mechanical properties. Sensitivity to moisture is dependent on material properties and environmental factors and needs characterization. In this thesis, moisture sensitivity of PLA filaments and PLA/PBS blended filaments was characterized in FDM printed ASTM test samples post-conditioning the filaments at different relative humidity levels. Tensile strength decreased with increase in moisture content. Parts made with PLA 4043D, PLA/PBS 75/25 filaments were most sensitive to moisture. Investigation of tensile properties of parts made with PLA filaments exposed to room temperature and humidity conditions for three months showed a more significant decrease. Moisture sensitivity of PLA, PBS, and PLA/PBS 25/75 blend characterized for USW using injection-molded industrial standard test parts (ISTeP) showed a downward trend in weld strength for 100% PLA and PLA/PBS 25/75 while 100% PBS was significantly affected at high moisture conditions.
Adaptive Production Planning and Scheduling for the Make-to-order DNA Manufacturing System
(North Dakota State University, 2010) Song, Dan
This thesis develops an adaptive production planning and scheduling system for the make-to-order plasmid (DNA) manufacturing system. The system, which has stochastic nature and random demand, was represented by a mathematical programming model first. Then in order to solve it, discrete-event simulation models were developed to generate a feasible schedule that maximizes the production throughput in the planning horizon in a mix-product type environment. A special heuristic order selecting and splitting procedure was designed to aid the production planning and scheduling process. Experiments were conducted to evaluate the algorithm and results are compared with those obtained by using four classic dispatching rules, such as first come first served (FCFS) and shortest processing time (SPT). To take advantage of simulation results, a rule-based expert system was created with pre-defined scheduling rules. Rules regarding production planning and scheduling can be used by human schedulers easily and the system is very flexible in further extension.
Integration of Simulation and DEA to Determine the Most Efficient Patient Appointment Scheduling Model for a Specific Clinic Setting
(North Dakota State University, 2011) Aslani, Nazanin
This study develops a method to determine the most efficient scheduling model for a specific clinic setting. The appointment scheduling system assigns clinics' timeslots to incoming requests. There are three major scheduling models: centralized scheduling model (CSM), decentralized scheduling model (DSM) and hybrid scheduling model (HSM). In order to schedule multiple appointments, CSM involves one scheduler, DSM involves all the schedulers of individual clinics and HSM combines CSM and DSM. Clinic settings are different in terms of important factors such as randomness of appointment arrival and proportion of multiple appointments. Scheduling systems operate inefficiently if there is not an appropriate match between scheduling models and clinic settings to provide balance between indicators of efficiency. A procedure is developed to determine the most efficient scheduling model by the integrated contribution of simulation and Data Envelopment Analysis (DEA). A case study serves as a guide to use and as proof for the validity of the developed procedure.
A Domain-Knowledge Modeling of Hospital-Acquired Infection Risk in Healthcare Personnel From Retrospective Observational Data: A Case Study for Covid-19
(North Dakota State University, 2022) Huynh, Phat
Healthcare personnel (HCP) is facing a consistent risk of viral infections. We proposed a domain-knowledge-driven infection risk model to quantify the individual HCP and the population-level risks. For individual-level risk estimation, a time-variant model was proposed to capture the disease transmission dynamics. At the population-level, the infection risk was estimated using a Bayesian network model constructed from three feature sets. For model validation, we investigated the case study of the Coronavirus disease. The variance-based sensitivity analysis indicated that the uncertainty in the estimated risk was attributed to two variables: the number of close contacts and the viral transmission probability. We further validated the individual risk model by considering six occupations in the U.S. O*Net database. For the population-level risk model validation, the infection risk in Texas and California was estimated. The accurate estimation of infection risk will significantly enhance the PPE allocation, safety plans for HCP, and hospital staffing strategies.
A Study of Degradation Modeling and Lifetime Estimation of Capacitors
(North Dakota State University, 2021) Gupta, Anunay
The degradation of capacitors under accelerated stress conditions occurs in a monotonic and non-linear fashion. Several efforts have been made to model the degradation behavior of capacitor considering either physics-of-failure models or statistical models and subsequently estimate its reliability and lifetime parameters. But most of these models fail to reflect the physical properties of the degradation path, which varies according to several intrinsic and extrinsic factors. These factors introduce random and temporal uncertainty among the population of capacitors. The Gamma stochastic process can model both type of uncertainties among the population of capacitors. In this thesis, we model the capacitor degradation by non-homogeneous Gamma stochastic process in which both the model parameters (shape and scale) are dependent on stress variables. The model parameters are estimated using the maximum likelihood estimation approach. Two case studies have been presented and the life of capacitors has been estimated using Gamma process model.
Total Quality Management in Higher Education: A Soft Factor Approach Based on Faculty Satisfaction
(North Dakota State University, 2021) Singh, Samrat
The literature review showed very few organization-wide Total Quality Management (TQM) implementations and mixed opinions regarding its compatibility in Higher Education Institutions (HEIs). Considering the human-centric nature of HEIs this study investigated the interrelationship between the Soft TQM Factors, Faculty Satisfaction, and Student Success. A survey was designed to assess respondents’ perceptions regarding the implementation of Soft TQM Factors and satisfaction among faculty. Analysis of the responses revealed a clear positive relationship between Soft TQM Factors and Faculty Satisfaction. Moreover, Faculty Satisfaction was found to be associated with one of the measures of Student Success, the Graduation Rate. Thus, this study validates the significance of a Soft Factor approach of TQM implementation that concentrates on human-centric factors to enhance Faculty Satisfaction, which may, in turn, foster greater Student Success. The study also yielded a valid survey tool for assessing the implementation of Soft TQM Factors and Faculty Satisfaction in HEIs.
Design and Manufacturing of Variable Stiffness Cellular Architecture
(North Dakota State University, 2017) Xie, Ruinan
Cellular structures are highly evaluated due to their high material efficiency. Both theoretical and experimental studies have done on periodic cellular structures. However, the mechanical performance can be stochastically distributed in the cellular architecture. This thesis presents the design and manufacturing of variable stiffness cellular architecture to achieve optimized topology by changing the unit cell parameters. The author applies image analysis technique to extract and digitize the information from the performance distribution map. Two types of cellular cells are studied for their relationship of stiffness and relative density. The methods of voxelization for both cells are also given in this study. This proposed methodology is then implemented to design a customized mattress and compare with current existing mattress. With the study of the unit cells and voxelization technique, our designed mattress aligns body curve better which provides more recuperation of the body during sleep.
ISO 9001: 2015 Quality System Manual Development and Implementation for Business and Commerce with Expanded Emphasis on Risk Management
(North Dakota State University, 2019) Mostafa, Mahmoud Hesham Ahmad Shawky
ISO 9001: 2015 is the latest edition of the Quality Management System from the International Standard Organization. One of the most noticeable changes about the new edition is the emphasis on risk-based thinking. This study introduces a template for developing a Quality Manual and a systematic approach to Risk Assessment using a risk-based decision-making framework embedded in the Quality Management System. An extensive discussion on decision-making, risk and opportunity analysis is provided with the aim of developing a seamless integration between QMS, risk analysis, and decision-making. This study proposes a decision-making framework that aligns ISO 9001 requirements with the decision-making process. The proposed decision-making methodology is aimed specifically at product and service selection. A case study is used to demonstrate the methodology.
Resilience Assessment for Complex Networks Based on Recovery Strategies
(North Dakota State University, 2019) Afrin, Tanzina
The vulnerability of complex networks to unexpected disruptive events could be reduced by increasing network resilience through the efficient recovery of the damaged network. To find the most efficient recovery strategy among the existing variety of strategies, a resilience-based framework was proposed and implemented for both localized attacks and cascading failures. For localized attacks, preferential recovery based on nodal weights (PRNW), periphery recovery (PR) and localized recovery (LR) were assessed. Additionally, probability-based recovery (RS1) and recovery of neighboring or boundary nodes (RS2) methods were evaluated for cascading failures. Considering the advantages and disadvantages of these strategies, a hybrid recovery strategy was proposed to achieve high network resilience in a timely manner with a manageable amount of cost. Overall, this study aids in the assessment and the development of a cost-effective resilience-based recovery strategy.
CFD Heat Transfer Simulation of the Human Upper Respiratory Tract for Oronasal Breathing Condition
(North Dakota State University, 2011) Srinivasan, Raghavan
In this thesis. a three dimensional heat transfer model of heated airflow through the upper human respiratory tract consisting of nasal, oral, trachea, and the first two generations of bronchi is developed using computational fluid dynamics simulation software. Various studies have been carried out in the literature investigating the heat and mass transfer characteristics in the upper human respiratory tract, and the study focuses on assessing the injury taking place in the upper human respiratory tract and identifying acute tissue damage based on level of exposure. The model considered is for the simultaneous oronasal breathing during the inspiration phase with high volumetric flow rate of 90/liters minute and a surrounding air temperature of 100 degrees centigrade. The study of the heat and mass transfer, aerosol deposition and flow characteristics in the upper human respiratory tract using computational fluid mechanics simulation requires access to a two dimensional or three dimensional model for the human respiratory tract. Depicting an exact model is a complex task since it involves the prolonged use of imaging devices on the human body. Hence a three dimensional geometric representation of the human upper respiratory tract is developed consisting of nasal cavity, oral cavity, nasopharynx, pharynx, oropharynx, trachea and first two generations of the bronchi. The respiratory tract is modeled circular in cross-section and varying diameter for various portions as identified in this study. The dimensions are referenced from the literature herein. Based on the dimensions, a simplified model representing the human upper respiratory tract is generated.This model will be useful in studying the flow characteristics and could assist in treatment of injuries to the human respiratory tract as well as help optimize drug delivery mechanism and dosages. Also a methodology is proposed to measure the characteristic dimension of the human nasal and oral cavity at the inlet/outlet points which are classified as internal measurements.
Multiresponse Optimization Methodology Considering Related Quality Characteristics
(North Dakota State University, 2011) Thambidorai, Ganesh
Engineering problems often involve many conflicting quality characteristics that must be optimized simultaneously. Engineers are required to select suitable design parameter values which provide better trade-off among all quality characteristics. Multiresponse optimization is one of the most essential tools for solving engineering problems involving multiple quality characteristics. Optimizing several quality characteristics when the quality characteristics are correlated makes the optimization process more complex. The aim of this research is to evaluate the performance of several existing multiresponse optimization methods and investigate their capabilities in dealing with correlated quality characteristics. This study also investigates the impact of uncertainty in terms of input parameter selection. A new multi-response optimization approach has been proposed for solving correlated quality characteristics. The proposed approach is compared with the existing methods and found more robust in terms dealing with uncertainty in target selection. The comparative study and application of the proposed approach is demonstrated by considering two examples from the literature having correlated quality characteristics.
Vulnerability Assessment of Interdependent Power and Communications Networks under Varying Level of Interdependency
(North Dakota State University, 2017) Banothu, Rahul
Maintaining a continuous and robust supply of power could be challenging task, because power networks depend on proper communication to coordinate and schedule supply, as well as recognize and mitigate failures; communication networks depend on power to function. This interdependency is a cause for greater failure risks due to the rapid cascading of failures from one network to the other. The objective of this work is to investigate the vulnerability of interdependent networks under various scenarios and coupling assumptions. To do so, we employ heuristic techniques to detect critical nodes in either network which lead to the maximum number of failed nodes in the interdependent networks. We put to the test a series of topographical importance metrics to heuristically identify said important nodes and compare our results with the literature. Furthermore, we test different coupling methods for how interdependency works and compare the results under different failure assumptions.
Two-Echelon Vehicle Routing Problems Using Unmanned Autonomous Vehicles
(North Dakota State University, 2017) Rahman, Md Mahbubar
In this thesis, we investigate new multi-echelon vehicle routing problems for logistics operations using unmanned autonomous vehicles. This can provide immediate tangible outcomes, especially in high-demand areas that are otherwise difficult or costly to serve. This type of problem differs from the commonly used multi-echelon supply chain management systems in that here there exist no intermediate facilities that consolidate/separate products for delivery; instead all decisions are made on a per-vehicle basis. We describe here how we can obtain the necessary parameters (data collection) to evaluate the performance of such multi-echelon systems. We also provide three mathematical formulations based on different assumptions and case scenarios. We then study the differences between the three models in practice, as far as routing cost and duration of operations are concerned. We finally show that there are savings to be had by properly employing unmanned vehicles for logistics operations.
Study on the Relationship between Process Plan and Resource Requirement in Additive Manufacturing
(North Dakota State University, 2018) Ahsan, AMM Nazmul
Resource consumption in additive manufacturing (AM) is often tied with the physical attribute of the fabricated part. Thus, optimizing the processes plan for minimum part fabrication resource requirement is a matter of great interest. In this thesis, the hierarchical nature of the AM process plan steps are emphasized and both build direction and material deposition direction are optimized while considering the resource requirement. A novel combined two-step optimization methodology is presented to determine optimal build direction for the object and material deposition direction for layers while considering minimum contour plurality, surface quality, build height, fabrication factor, and layer contour concavity to compensate for the fabrication and resource limitations. Furthermore, a concurrent process plan optimization methodology is presented focusing on fabrication complexity resulting from part geometry. Implementation of the proposed methodologies on several example parts indicates substantial reduction of their total build time.
Evacuation Trees with Contraflow and Divergence Considerations
(North Dakota State University, 2018) Achrekar, Omkar Shirish
In this thesis, we investigate how to evacuate people using the available road transportation network efficiently. To successfully do that, we need to design evacuation model that is fast, safe, and seamless. We enable the first two criteria by developing a macroscopic, time-dynamic evacuation model that aims to maximize the number of people in relatively safer areas of the network at each time point; the third criterion is optimized by constructing an evacuation tree, where the vehicles are evacuated using a single path to safety. Divergence and contraflow policies have been incorporated to enhance the network capacity. Divergence enables specific nodes to diverge their flows into two or more streets, while contraflow allows certain streets to reverse their flow, effectively increasing their capacity. We investigate the performance of these policies in the evacuation networks obtained, and present results on two benchmark networks of Sioux Falls and Chicago.
Economic Analysis of Packaging Systems
(North Dakota State University, 2011) Biradar, Vaibhav Mahadev
Packaging has a significant impact on the efficiency and effectiveness of the supply chain, where improvement can be achieved through the development and selection of an appropriate packaging system. One way to explore this is through the development and use of mathematical models that facilitate economic analysis of packaging systems. Recently, one of the most remarkable trends in logistics is the extensive use of returnable or reusable containers. Returnable container systems have increasingly been introduced in various industries to take advantages of cost savings, but it is very crucial to ensure that a reusable packaging system is an economical packaging choice. In this thesis, an extensive study of an economic analysis of disposable, recyclable, and reusable packaging systems is conducted. This includes identification of significant cost factors and variables involved in the management of disposable, recyclable and reusable packaging systems, and formulation of a mathematical model to compare total cost of packaging systems. The developed mathematical model can be used to choose the most economical packaging system for industries. The linear programming (LP) method is used to develop the mathematical model. The various new factors such as the collapsible ratio of recyclable, disposable and reusable packages have been introduced for the first time in the economic analysis of the packaging systems. The developed mathematical model can be used for a range of industries and for different industry scenarios. The packaging system information of Toyota assembly plant is used for the validation of a mathematical model. The obtained results are compared with previous research based on the same data set and results found in concert with the finding of previous research which validate the model.
A Quality Management System Implementation Framework for Small-Sized Companies
(North Dakota State University, 2016) Sawant, Manish Avinash
A detailed framework is essential to facilitate quality system implementation. In this study, we have offered a cost effective do-it-yourself approach to quality management. We have proposed a quality system implementation framework for small-medium sized organizations to enable their transition from a no-quality system to an ISO 9001 quality management system. The proposed framework is validated using a case study of a small door manufacturing company. The findings reveal several setbacks experienced during quality system implementation and suggests means to overcome them using a proposed seven step framework. This study also advises an effective maintenance tool to facilitate continuous improvement in organizations after implementing a quality management system. The study results will be useful for quality practitioners, managers, consultants and engineers, especially in small companies and discloses several benefits that can be achieved by employing the proposed framework in any organization irrespective of its size and nature.
Two Data Mining Applications for Predicting Pre-Diabetes
(North Dakota State University, 2015) You, Guangjing
In this study, the performance of Logistic Regression and Decision Tree modeling is compared by using SAS Enterprise Miner for predicting pre-diabetes in US population by using several of the common factors from the type 2 diabetes screening criteria. From 17 variables of NHANES’ three sets of dataset, a total of 13 risk factors were selected as predictors of pre-diabetes. A comparison of two data mining methodology showed that Decision Tree has a higher ROC index than Logistic Regression modeling. All ROC indexes for two models were greater than 77% indicating both methods present a good prediction for pre-diabetes. The predictive accuracy of the two models was greater than 72% on the whole dataset. Decision tree modeling also resulted in higher accuracy and sensitivity values than Logistic Regression modeling. Taken as a whole, the results of comparison indicated Decision Tree modeling is a better indicator to predict pre-diabetes.

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