Dazhong Wu

Dazhong Wu
University of Central Florida | UCF · Department of Mechanical and Aerospace Engineering

Ph.D.
Looking for graduate students who are interested in 3D printing, data-driven smart manufacturing, and prognostics.

About

91
Publications
99,990
Reads
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5,133
Citations
Citations since 2017
57 Research Items
4429 Citations
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Introduction
Dr. Wu's group at the University of Central Florida (UCF) has one Ph.D. position in Fall 2020. The research focus of his lab includes (1) data-driven design and manufacturing; (2) manufacturing process monitoring and structural health monitoring; and (3) additive manufacturing. Interested individuals should send an email to Dr. Dazhong Wu at Dazhong.Wu@ucf.edu with the subject line "Ph.D. Application".
Additional affiliations
June 2017 - present
University of Central Florida
Position
  • Professor (Assistant)
January 2015 - March 2017
Pennsylvania State University
Position
  • Research Associate
August 2009 - August 2014
Georgia Institute of Technology
Position
  • Research Assistant

Publications

Publications (91)
Article
Purpose Understanding the effect of process parameters on interfaces and interfacial bonding between two materials during multi-material additive manufacturing (MMAM) is crucial to the fabrication of high-quality and strong multi-material structures. The purpose of this paper is to conduct an experimental and statistical study to investigate the ef...
Article
Lithium-ion batteries have been extensively used to power portable electronics, electric vehicles, and unmanned aerial vehicles over the past decade. Aging decreases the capacity of Lithium-ion batteries. Therefore, accurate remaining useful life (RUL) prediction is critical to the reliability, safety, and efficiency of the Lithium-ion battery-powe...
Article
Prediction of state-of-health and remaining useful life is crucial to the safety of lithium-ion batteries. Existing state-of-health and remaining useful life prediction methods are not effective in revealing the correlation among features. Establishing the correlation can help identify features with high similarities and aggregate them to improve t...
Article
Full-text available
A thorough understanding of complex process-structure-property (P-S-P) relationships in additive manufacturing (AM) has long been pursued due to its paramount importance in achieving AM process optimization and quality control. Physics-based modeling and experimental approaches are usually time-consuming and/or costly. With the increasing availabil...
Article
Full-text available
Stereolithography (SLA)-based bioprinting can fabricate three-dimensional complex objects accurately and efficiently. However, the ultraviolet (UV) irradiation in the SLA-based bioprinting process is a significant challenge, which may damage the cells. Physics-based models are not able to predict cell viability with high accuracy because of the com...
Article
The engineering stress-strain curve of a material allows one to determine mechanical properties such as elastic modulus, strength, and toughness. While machine learning has recently been used to predict stress-strain curves, large volumes of experimental data are required to achieve high prediction accuracy. More importantly, conventional machine l...
Article
Full-text available
Modern engineering applications require advanced materials that are stronger, tougher, and lighter. Nature offers various structural architectures to achieve superior mechanical properties. Inspired by bone with a spongy soft-core and a compact hard-shell, this study introduces architected multi-material lattices with tunable mechanical properties...
Poster
Full-text available
CFP: https://www.techscience.com/CMES/special_detail/intelligence
Article
Conventional machine learning based predictive modeling methods require large volumes of training data; however, collecting large training data is very labor-intensive and expensive in real-world applications such as manufacturing. Therefore, small data is a common challenge for machine learning approaches. To address this issue, we introduce a met...
Poster
Full-text available
Goal:Machine Learning (ML) has recently become a power-engine transforming various manufacturing research and applications. In the era of Smart Manufacturing and I4.0, the abundance of smart sensors and industrial internet of things has made manufacturing systems a data-rich environment. ML techniques play a significant role in uncovering fine-grai...
Article
A system health index is a measurement of the health condition of complex systems. However, most of the health indices are developed based on strong assumptions. Consequently, existing health indices are not capable of measuring the actual deterioration behaviors with high accuracy. To address this issue, we introduce a probabilistic graphical mode...
Poster
Since the arrival of Industry 4.0, manufacturing is in the process of undergoing a significant transformation to become more intelligent. The development of intelligent manufacturing gave birth to a new generation of industrial systems which is expected to be operative under a high level of functionality, reliability, and resilience, to meet the hi...
Article
Gearbox fault diagnosis is expected to significantly improve the reliability, safety and efficiency of power transmission systems. However, planetary gearbox fault diagnosis remains a challenge due to complex responses caused by multiple planetary gears. Model-based gearbox fault diagnosis techniques extract hand-crafted features from sensor data b...
Poster
Full-text available
Mass Personalization is a prevailing business trend of offering bespoke products and services for each individual customer, manufactured and delivered with mass production efficiency. Facilitated by the cutting-edge information and communication technologies involved in the digital transformation, the high volume, velocity, variety, veracity, and v...
Article
Recent advances in sensing technologies have enabled engineers to collect big data to predict the remaining useful life (RUL) of complex systems. Current modeling techniques for RUL predictions are usually not able to quantify the degradation behavior of a complex system through a health index. Although some studies have been conducted to learn the...
Article
Various machine learning-based predictive modeling approaches to tool wear prediction have been introduced over the past few years. However, predicting tool wear under different operating conditions (e.g., depth of cut, feed rate, and workpiece material) with small datasets remains a challenge due to complex tool wear mechanisms. To address this is...
Article
Additive manufacturing (AM) process parameters highly affect the mechanical and fracture properties of additively manufactured carbon fiber reinforced polymer (CFRP) composites. In this work, we study the effect of two process parameters, including three build orientations (XYZ, XZY, and ZXY) and two raster patterns (±45º and 0º/90º), on the fractu...
Article
Prognostics and health management (PHM) of bearings is crucial for reducing the risk of failure and the cost of maintenance for rotating machinery. Model-based prognostic methods develop closed-form mathematical models based on underlying physics. However, the physics of complex bearing failures under varying operating conditions is not well unders...
Article
Full-text available
WE43 is a high strength, high creep resistant Mg-alloy containing Y, Nd, and Zr, and has potential for many lightweight structural applications in the automotive, aerospace, and biomedical industries. Additive manufacturing technology such as laser powder bed fusion (LPBF) brings an opportunity to produce complex geometries such as lattice structur...
Article
This study examines the inter-layer and cross-layer fracture behavior of 3D printed short CFRP composites using both experimental and numerical methods. First, the orthotropic mechanical response of the 3D printed CFRP samples was characterized by tensile tests. The out-of-plane Young’s modulus and yield strength were measured to be about 25% and 3...
Article
This study investigates the interlaminar shear behavior of 3D printed CFRP composites fabricated by fused deposition modeling (FDM) through a combined experimental and numerical study. Short beam shear (SBS) tests were performed to quantitatively characterize interlaminar shear strength (ILSS) of 3D printed continuous and short CFRP composites. Num...
Article
Predicting the melt pool temperature distribution and history in direct energy deposition (DED) is crucial for estimating the microstructure, porosity, and mechanical properties of DED-fabricated metal parts. While analytical and numerical modeling methods have been introduced to predict the melt pool temperature, the prediction accuracy of these m...
Article
The high frequency, low amplitude wing motion that mosquitoes employ to dry their wings inspires the study of drop release from millimetric, forced cantilevers. Our mimicking system, a 10-mm polytetrafluoroethylene cantilever driven through ±1 mm base amplitude at 85 Hz, displaces drops via three principal ejection modes: normal-to-cantilever eject...
Article
An incipient fault refers to the first change point when a system starts to deteriorate. Early detections of incipient faults are crucial to the safety, reliability, and effective predictive maintenance of complex engineering systems. However, it is very difficult to detect incipient faults at the initial stage of system degradation processes. To a...
Article
Carbon fiber reinforced polymer (CFRP) composites have been extensively used in aerospace and automotive industries due to their high strength-to-weight and stiffness-to-weight ratios. Compared with conventional manufacturing processes for CFRP, additive manufacturing (AM) can fabricate CFRP with more complex structures. While AM offers significant...
Article
Data fusion integrates data from multiple sources to improve prediction performance. While significant research has been conducted to develop data-level and feature-level fusion methods, very few studies are performed to develop more effective decision-level data fusion methods. This research aims at developing a decision-level data fusion approach...
Article
Full-text available
Lattice structure is a type of cellular structure and is used in various engineering applications due to its high strength to weight ratio and excellent energy absorption capacity. A traditional way to examine the response of lattice structures subjected to external loading is to perform experimental research and/or to employ numerical investigatio...
Article
Tool wear in machining could result in poor surface finish, excessive vibration and energy consumption. Monitoring tool wear in real-time is crucial to improve manufacturing productivity and quality. While numerous sensor-based tool wear monitoring techniques have been demonstrated in laboratory environments, few tool wear monitoring systems have b...
Article
3D printing has been extensively used for rapid prototyping as well as low-volume production in aerospace, automotive, and medical industries. However, conventional manufacturing processes (i.e., injection molding and CNC machining) are more economical than 3D printing for high-volume mass production. In addition, current 3D printing techniques are...
Article
Full-text available
Zirconia-based ceramics have many applications in manufacturing, energy, and biomedical industries due to their excellent properties such as high thermal and oxidation resistance, excellent chemical stability and mechanical strength. Traditional manufacturing processes such as cold pressing, hot pressing, and injection molding have limitations in t...
Article
Manufacturing industry accounts for about one-third of the world's total energy consumption (TEC). This study aims to develop a novel mixed-integer mathematical model to represent the direct energy consumption of machines and indirect energy consumption on a shop floor. In comparison with traditional modeling methods, this paper proposes an effecti...
Article
Full-text available
Aluminum alloy microlattice structures have been increasingly used in automotive, aerospace, packaging, defense, machinery, and construction industries due to their superior physical and mechanical properties such as high specific strength and energy absorption capacity. However, design and fabrication of microlattice structures remains a challenge...
Article
Full-text available
Continuous carbon fiber-reinforced polymer (CCFRP) composites are lightweight and strong materials that have been used in a wide range of applications in automotive and aerospace industries. Traditional manufacturing processes (e.g., lay-up and out of autoclave techniques) are not capable of fabricating complex composites. Additive manufacturing (A...
Conference Paper
Additive manufacturing (AM), also known as 3D printing, has been used for rapid prototyping due to its ability to produce parts with complex geometries from computer- aided design files. Currently, polymers and metals are the most commonly used materials for AM. However, ceramic materials have unique mechanical properties such as strength, corrosio...
Conference Paper
To improve the quality of additively manufactured parts, it is crucial to develop real-time process monitoring systems and data-driven predictive models. While various sensor- and image-based process monitoring methods have been developed to improve the quality of additively manufactured parts, very limited research has been conducted to predict su...
Article
Laser cladding has been increasingly used for repairing and remanufacturing critical and high-value components due to its unique benefits such as high solidification rates and a small heat-affected zone. In laser cladding, tilt angle between a laser nozzle and a substrate has a significant impact on deposited bead morphology. To ensure the quality...
Article
Full-text available
Programmable Logic Controllers (PLCs) are essential parts in industrial manufacturing plants. With the emerging Industry 4.0 environment, legacy PLCs are now connected to the Internet to be better automated. However, these PLCs are especially vulnerable when connected to a network, since there is limited inherent security mechanisms built in. In th...
Article
Chemical mechanical planarization (CMP) has been widely used in the semiconductor industry to create planar surfaces with a combination of chemical and mechanical forces. A CMP process is very complex because several chemical and mechanical phenomena (e.g., surface kinetics, electrochemical interfaces, contact mechanics, stress mechanics, hydrodyna...
Article
Degradation modeling and prediction of remaining useful life (RUL) are crucial to prognostics and health management of aircraft engines. While model-based methods have been introduced to predict the RUL of aircraft engines, little research has been reported on estimating the RUL of aircraft engines using novel data-driven predictive modeling method...
Article
Additive manufacturing is driving major innovations in many areas such as biomedical engineering. Recent advances have enabled three-dimensional (3D) printing of biocom-patible materials and cells into complex 3D functional living tissues and organs using bio-printable materials (i.e., bioink). Inkjet-based bioprinting fabricates the tissue and org...
Article
To realise high quality, additively manufactured parts, real-time process monitoring and advanced predictive modelling tools are crucial for accelerating quality assurance in additive manufacturing. While previous research has demonstrated the effectiveness of physics- and model-based diagnosis and prognosis for additive manufacturing, very little...
Article
Full-text available
Chemical mechanical polishing (CMP) has been widely used in the semiconductor sector for creating planar surfaces with the combination of chemical and mechanical forces. CMP is very complex because several chemical and mechanical phenomena (e.g., surface kinetics, contact mechanics, stress mechanics, and tribochemistry) are involved. Due to the com...
Conference Paper
To realize high quality, additively manufactured parts, real-time process monitoring and advanced predictive modeling tools are crucial for accelerating quality assurance and quality control in additive manufacturing. While previous research has demonstrated the effectiveness of physics- and model-based diagnosis and prognosis for additive manufact...
Conference Paper
Additive manufacturing is driving major innovations in many areas such as biomedical engineering. Recent advances have enabled 3D printing of biocompatible materials and cells into complex 3D functional living tissues and organs using bioink. Inkjet-based bioprinting fabricates the tissue and organ constructs by ejecting droplets onto a substrate....
Article
Digital manufacturing aims to create highly customizable products with higher quality and lower costs by integrating Industrial Internet of Things, big data analytics, cloud computing, and advanced robots into manufacturing plants. As manufacturing machines are increasingly retrofitted with sensors as well as connected via wireless networks or wire...
Article
Full-text available
Smart manufacturing refers to using advanced data analytics to complement physical science for improving system performance and decision making. With the widespread deployment of sensors and Internet of Things, there is an increasing need of handling big manufacturing data characterized by high volume, high velocity, and high variety. Deep learning...
Article
Full-text available
This paper presents a cyber design and additive manufacturing (CDAM) system at the University of Michigan Orthotics and Prosthetics Center. This CDAM system aims at shortening the delivery and improving the fit and comfort of custom orthoses and prostheses. The ankle foot orthosis (AFO), a custom made brace that supports muscles and provides contro...
Article
Remaining useful life (RUL) prediction is crucial for the implementation of predictive maintenance strategies. While significant research has been conducted in model-based and data-driven prognostics, there has been little research reported on the RUL prediction using an ensemble learning method that combines prediction results from multiple learni...
Article
The emergence of cloud computing, industrial internet of things (IIoT), and new machine learning techniques have shown the potential to advance prognostics and health management (PHM) in smart manufacturing. While model-based PHM techniques provide insight into the progression of faults in mechanical components, certain assumptions on the underlyin...
Conference Paper
The objective of this research is to introduce a new ensemble prognostics method with degradation-dependent weights. Specifically, this method assigns an optimized, degradation-dependent weight to each learner (i.e., learning algorithm) such that the weighted sum of the prediction results from all the learners predicts the RUL of mechanical compone...
Conference Paper
Full-text available
Manufacturers have faced an increasing need for the development of predictive models that help predict mechanical failures and remaining useful life of a manufacturing system or its system components. Model-based or physics-based prognostics develops mathematical models based on physical laws or probability distributions, while an in-depth physical...
Article
Full-text available
Manufacturers have faced an increasing need for the development of predictive models that predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or components. Classical model-based or physics-based prognostics often require an in-depth physical understanding of the system of interest to develop closed-form mathema...
Article
Small- and medium-sized manufacturers, as well as large original equipment manufacturers (OEMs), have faced an increasing need for the development of intelligent manufacturing machines with affordable sensing technologies and data-driven intelligence. Existing monitoring systems and prognostics approaches are not capable of collecting the large vol...
Article
Cloud computing is an innovative computing paradigm that can bridge the gap between increasing computing demands in computationally intensive tasks for digital design and manufacturing applications and limited resources, scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, cloud-base...
Article
Full-text available
Prognosis of machine degradation and failure propagation is essential to preventative maintenance scheduling and sustainable manufacturing. Emerging technologies such as Internet of Things (IoT) and cloud computing offer new opportunities for scaling up computing performance and capacity for machine monitoring and prognosis. This paper addresses ch...
Conference Paper
Over the past few decades, both small- and medium-sized manufacturers as well as large original equipment manufacturers (OEMs) have been faced with an increasing need for low cost and scalable intelligent manufacturing machines. Capabilities are needed for collecting and processing large volumes of real-time data generated from manufacturing machin...
Conference Paper
Full-text available
With rapid innovation in the electronics industry, product obsolescence forecasting has become increasingly important. More accurate obsolescence forecasting would have cost reduction effects in product design and part procurement over a product’s lifetime. Currently many obsolescence forecasting methods require manual input or perform market analy...
Article
Full-text available
Social media have recently been introduced into the arena of collaborative design as a new means for seamlessly gathering, processing, and sharing product design-related information. As engineering design processes are becoming increasingly distributed and collaborative, it is crucial to understand the communication and collaboration mechanism of e...
Conference Paper
Cloud computing is an innovative computing paradigm that can potentially bridge the gap between increasing computing demands in computer aided engineering (CAE) applications and limited scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, high performance computing (HPC) in the cloud...
Article
From a business perspective, cloud computing has revolutionized the information and communication technology (ICT) industry by offering scalable and on-demand ICT services as well as innovative pricing plans such as pay-per-use and subscription. Considering the economic benefits of cloud computing, cloud-based design and manufacturing (CBDM) has be...
Article
Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in...
Conference Paper
Full-text available
Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, is a form of decentralized and networked manufacturing evolving from other relevant manufacturing systems such as web- and agent-based manufacturing. An ongoing debate on CBM in the research community revolves around several aspects such as definitions, key characteristics, c...
Chapter
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The information technology industry has benefited considerably from cloud computing, which allows organizations to shed some of their expensive information technology infrastructure and shifts computing costs to more manageable operational expenses. In light of these benefits, we propose a new paradigm for product design and manufacturing, referred...
Conference Paper
Full-text available
Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing...
Conference Paper
Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing...
Conference Paper
Full-text available
A Cloud-Based Design and Manufacturing (CBDM) System refers to an information and communication technology (ICT) system that facilitates design and manufacturing knowledge sharing between actors (e.g., CBDM service providers and consumers) in the distributed and collaborative socio-technical network. The aim of this study is to address the challeng...
Article
Full-text available
The rise of cloud computing is radically changing the way enterprises manage their information technology assets. Considering the benefits of cloud computing to the information technology sector, we present a review of current research initiatives and applications of the cloud computing paradigm related to product design and manufacturing. In parti...
Conference Paper
Full-text available
Over the past few years, Social Product Development (SPD) has emerged as a new trend to improve traditional engineering design and product realization processes. SPD involves the concepts of crowdsourcing, mass collaboration, customer co-creation, and most recently cloud-based design and manufacturing. One of the key characteristics of SPD is to ap...