Intelligent Data-Enabled Analytics (IDEA) Laboratory

@ Mississippi State University

  1. Tian, W., Sun, H., Zhang, X., & Woodall, W. H. (2015). The Impact of Varying Patient Populations on the In-control Performance of the Risk-adjusted CUSUM Chart. International Journal for Quality in Health Care, 27(1), 31-36.
  2. Loizou, J., Tian, W., Robertson, J., & Camelio, J. A. (2015). Automated Wear Characterization for Broaching Tools Based on Machine Vision Systems. Journal of Manufacturing Systems, 37, 558-563.
  3. Tian, W., Jin, R., Huang, T., & Camelio, J. A. (2017). Statistical Process Control for Multistage Processes with Non-repeating Cyclic Profile Outputs. IISE Transactions, 49(3), pp.320-331. (Finalist of the Best Paper Award of the IISE Process Industry Division in 2014)
  4. Khanzadeh, M., Tian, W., Yadollahi, A., Doude, H.R., Tschopp, M.A. & Bian, L. (2018) Dual process monitoring of metal-based additive manufacturing using tensor decomposition of thermal image streams. Additive Manufacturing, 23, 443-456.
  5. Komolafe, T., Tian, W., Purdy, G. T., Albakri, M., Tarazaga, P., & Camelio, J. (2019). Repeatable part authentication using impedance based analysis for side-channel monitoring. Journal of Manufacturing Systems, 51, 42-51.
  6. Seifi, S. H., Tian, W., Doude, H., Tschopp, M. A., & Bian, L. (2019). Layer-wise modeling and anomaly detection for laser-based additive manufacturing. Journal of Manufacturing Science and Engineering, 1-36.
  7. Jafari-Marandi, R., Khanzadeh, M., Tian, W., Smith, B., & Bian, L. (2019). From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing. Journal of Manufacturing Systems, 51, 29-41.
  8. Tian, W., Ma, J., & Alizadeh, M. (2019). Energy consumption optimization with geometric accuracy consideration for fused filament fabrication processes. The International Journal of Advanced Manufacturing Technology, 1-11.
  9. Alizadeh, M., Esfahani, M. N.*, Tian, W., & Ma, J. (2020). Data-Driven Energy Efficiency and Part Geometric Accuracy Modeling and Optimization of Green Fused Filament Fabrication Processes. Journal of Mechanical Design, 142(4). 
  10. Chen, W., Nichols, L., Brinkley, F., Bohna, K.*, Tian, W., Priddy, M., & Priddy, L. (2020) Alkali treatment facilitates functional nano-hydroxyapatite coating of 3D printed polylactic acid scaffolds. Materials Science & Engineering C, 111686.
  11. Shelly, Z., Burch, R., Tian, W., Strawderman, L., Piroli, A., & Bichey, C. (2020). Using K-means Clustering to Create Training Groups for Elite American Football Student-athletes Based on Game Demands. International Journal of Kinesiology & Sports Science. Accepted.
  12. Ye, Z., Liu, C., Tian, W., & Kan, C. (2021). In-situ point cloud fusion for layer-wise monitoring of additive manufacturing. Journal of Manufacturing Systems, 61, 210-222.
  13. Foroutan, M.*, Goodin, C., & Tian, W. (2021). Assessing Impact of Understory Vegetation Density on Solid Obstacle Detection for Off-road Autonomous Ground Vehicles. ASME Letters in Dynamic Systems and Control. April 2021; 1(2): 021008.
  14. Joshi, S., Hamilton, M., Warren, R., Faucett, D., Tian, W., Wang, Y. and Ma, J., (2021) Implementing Virtual Reality technology for safety training in the precast/prestressed concrete industry. Applied ergonomics, 90, p.103286.
  15. Shi, Z., Kan, C., Tian, W., & Liu, C. (2021). A Blockchain-Based G-Code Protection Approach for Cyber-Physical Security in Additive Manufacturing. Journal of Computing and Information Science in Engineering, 21(4), 041007.
  16. Li, Y., Shi, Z., Liu C., Tian, W., Kong, Z., & Williams, C. (2021) Augmented Time Regularized Generative Adversarial Network (ATR-GAN) and Its Applications for Online Process Anomaly Detection in Additive Manufacturing. IEEE Transactions on Automation Science and Engineering, 19(4), 3338 - 3355. DOI: 10.1109/TASE.2021.3118635 
  17. Seifi, S.H., Yadollahi, A., Tian, W., Doude, H., Hammond, V.H. and Bian, L. (2021) In Situ Nondestructive Fatigue‐Life Prediction of Additive Manufactured Parts by Establishing a Process–Defect–Property Relationship. Advanced Intelligent Systems, p.2000268. DOI: https://doi.org/10.1002/aisy.202000268
  18. Khanzadeh, M., Dantin, M., Tian, W., Priddy, M.W., Doude, H. and Bian, L. (2022) Fast Prediction of Thermal Data Stream for Direct Laser Deposition Processes Using Network-Based Tensor Regression. ASME Journal of Manufacturing Science and Engineering, April 2022; 144(4): 041004. DOI: https://doi.org/10.1115/1.4052207
  19. Mamun, A.*, Liu, C., Kan, C., Tian, W. (2022) Securing cyber-physical additive manufacturing systems by in-situ process authentication using streamline video analysis. Journal of Manufacturing Systems, 62:429-40. (Finalist of the Student Research Presentation Competition, NAMRC 49) DOI: https://doi.org/10.1016/j.jmsy.2021.12.007 
  20. Shi, Z., Mamun, A.*, Kan, C., Tian, W. and Liu, C. (2022) An LSTM-autoencoder based online side channel monitoring approach for cyber-physical attack detection in additive manufacturing. Journal of Intelligent Manufacturing, 34: 1815–1831. DOI: https://doi.org/10.1007/s10845-021-01879-9 
  21. Esfahani, M. N.*, Bappy, M.*, Bian, L., & Tian, W. (2022) In-situ Layer-wise Certification for Direct Laser Deposition Processes based on Thermal Image Series Analysis. Journal of Manufacturing Processes, 75: 895-902. DOI: https://doi.org/10.1016/j.jmapro.2021.12.041 
  22. Liu, C., Tian, W., & Kan, C. (2022) When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development. Journal of Manufacturing Systems, 64: 648-656. DOI: https://doi.org/10.1016/j.jmsy.2022.04.010 
  23. Bappy, M.*, Liu, C., Bian, L. & Tian, W. (2022) Morphological Dynamics-based Anomaly Detection towards In-situ Layer-wise Certification for Directed Energy Deposition Processes. ASME Journal of Manufacturing Science and Engineering, 144(11):111007. DOI: https://doi.org/10.1115/1.4054805 
  24. Senanayaka, A., Mamun, A.*, Bond, G., Tian, W., Wang, H., Fuller, S., Falls, T.C., Rahimi, S. & Bian, L. (2022) Similarity-based Multi-source Transfer Learning Approach for Time Series Classification. International Journal of Prognostics and Health Management, 13(2). DOI: https://doi.org/10.36001/ijphm.2022.v13i2.3267 
  25. Mamun, A.*, Bappy, M.*, Senanayaka, A., Li, J., Jiang, Z., Tian, Z., Fuller, S., Falls, T., Bian, L., & Tian, W. (2023) Multi-channel sensor fusion for real-time bearing fault diagnosis by frequency-domain multilinear principal component analysis. The International Journal of Advanced Manufacturing Technology, 124(3), pp.1321-1334. DOI: https://doi.org/10.1007/s00170-022-10525-4 
  26. Fullington, D.*, Bian, L., & Tian, W. (2023) Design De-identification of Thermal History for Collaborative Process-defect Modeling of Metal-based Additive Manufacturing. ASME Journal of Manufacturing Science and Engineering, 145(5), 051004. (QCRE Best Student Poster Competition at IISE 2022) DOI: https://doi.org/10.1115/1.4056488 
  27. Zamiela, C., Bian, L., Jiang, Z., Stokes, R., Tian, W., Tian, Z., Netchaev, A., & Dickerson, C. (2023) Deep Multi-Modal U-Net Fusion Methodology of Thermal and Ultrasonic Images for Porosity Detection in Additive Manufacturing. ASME Journal of Manufacturing Science and Engineering, 145(6): 061009. DOI: https://doi.org/10.1115/1.4056873 
  28. Senanayaka, A., Tian, W., Falls, T., & Bian, L. (2023) Understanding the Effects of Process Conditions on Thermal-Defect Relationship: A Transfer Machine Learning Approach. ASME Journal of Manufacturing Science and Engineering, 145(7): 071010. DOI: https://doi.org/10.1115/1.4057052 
  29. Bappy, M.*, Fullington, D.*, Bian, L., & Tian, W. (2023) Evaluation of Design Information Disclosure through Thermal Feature Extraction in Metal based Additive Manufacturing. Manufacturing Letters. 36, 86-90. DOI: https://doi.org/10.1016/j.mfglet.2023.03.004 
  30. Shi, Z., Tian, W., Kan, C., & Liu, C. (2023) Sensor Data Protection through Integration of Blockchain and Camouflaged Encryption in Cyber-physical Manufacturing Systems. ASME Journal of Computing and Information Science in Engineering. Jul 2024, 24(7): 071004. DOI: https://doi.org/10.1115/1.4063859 
  31. Zamiela, C., Tian, W., Guo, S., & Bian, L. (2023) Thermal-Porosity Characterization Data of Additively Manufactured Ti–6Al–4V Thin-walled Structure via Laser Engineered Net Shaping. Data in Brief. 2023 Dec 1; 51: 109722. DOI: https://doi.org/10.1016/j.dib.2023.109722 
  32. Yangue, E., Fullington, D.*, Smith, O.*, Tian, W., & Liu, C. (2024) Diffusion generative model-based learning for smart layer-wise monitoring of additive manufacturing. ASME Journal of Computing and Information Science in Engineering. Jun 2024, 24(6): 060903. DOI: https://doi.org/10.1115/1.4065092 
  33. Fullington, D.*, Yangue, E., Bappy, M.*, Liu, C., & Tian, W. (2024) Leveraging Small-scale Datasets for Additive Manufacturing Process Modeling and Part Certification: Current Practice and Remaining Gaps. Journal of Manufacturing Systems. 2024, 75: 306-321. DOI: https://doi.org/10.1016/j.jmsy.2024.04.021 
  34. Zamiela, C., Stokes, R., Tian, W., Doude, H., Priddy, M., & Bian, L. (2024) Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition. ASME Journal of Manufacturing Science and Engineering. Aug 2024, 146(8): 081007. DOI: https://doi.org/10.1115/1.4065416 
  35. Bappy, M.*, Van Epps, E.*, Priddy, L.B. and Tian, W. (2024) Parameter optimization for accurate and repeatable strut width in the 3D printing of composite bone scaffolds. Journal of Manufacturing Processes, 131: 1631-1641. DOI: https://doi.org/10.1016/j.jmapro.2024.09.057 
  36. Bappy, M.*, Fullington, D.*, Bian, L., & Tian, W.  (2024) Adaptive Thermal History Deidentification for Privacy-preserving Process-defect Modeling of Metal Additive Manufacturing. ASME Journal of Computing and Information Science in Engineering. Accepted.
Teaching imageTeaching image
Mississippi State University
  • IE 4333/6333 Production Control (Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021)
  • IE 4683/6683 Machine Learning with IE Applications (Fall 2023)
  • IE 3323 Manufacturing Processes (Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022) 
  • IE 4990/6990 Data Mining for Predictive Maintenance (Fall 2022)
  • IE 8990 Advanced Data Analytics for Complex Systems (Fall 2019)  
  • IE 8623 Advanced Data Analytics for Complex Systems (Fall 2021) 
  • IE 8773 Simulation II (Fall 2020)
Virginia Tech
  • ISE 3424 Discrete Event Simulation (Summer 2016)

Wenmeng (Meg) Tian

Principal Investigator

Associate Professor, Department of Industrial and Systems Engineering

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Ethan Kang

Ph.D. Student

Department Industrial and Systems Engineering

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Shengzhe Zhou

Ph.D. Student

Department Industrial and Systems Engineering

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Hugo Rodriguez

Ph.D. Student

Department of Industrial and Systems Engineering

Zac LeBlanc

Undergraduate Researcher

Department of Mechanical Engineering

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Owen Smith

Undergraduate Researcher

Department of Industrial and Systems Engineering

Rajnish Poudel

Undergraduate Researcher

Department of Industrial and Systems Engineering

Durant Fullington

Alumni

Current Position: Research Analyst at CNA

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Abdullah Al Mamun

Alumni

Current Position: Assistant Professor, University of North Alabama

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Mahathir Bappy

Alumni

Current Position: Assistant Professor, Louisiana State University

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Emma Van Epps

Alumni

Current Position: PhD student, Yale University (Start Date: Aug 2024)

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MSMS Outreach Program in Spring 2023

GEM GRAD Lab

Engineering Discovery Day

Facility Tour at PACCAR

MSMS Outreach Activities in Spring 2023

SEC Machining Competition in 2022

IISE Southeast Regional Conference

Career Development Networking @ IISE Regional Conference

Industry Panel and Networking @ IISE Regional Conference

DoE IAC Assessments

In this study, a new adaptive AM data deidentification method is proposed that aims to mask the printing trajectory information in the AM process data in the form of melt pool images. 

​For ​more information, please see the link below.

https://asmedigitalcollection.asme.org/computingengineering/article/doi/10.1115/1.4067210/1209810 
His presentation title was "Generative Modeling Enabled Design De-identification for Enhanced Intellectual Property Protection in Metal-based Additive Manufacturing". This work was co-authored by Dr. Durant Fullington, Emmanuel Yangue, and Dr. Chenang Liu from Oklahoma State University. 
The objective of this study was to optimize the extrusion-based 3D bioprinting process parameters for composite polymer-ceramic scaffolds. 

​For ​more information, please see the link below.

https://www.sciencedirect.com/science/article/abs/pii/S1526612524009782 
Durant Fullington has successfully defended his PhD dissertation! Congratulations, Dr. Fullington! 

His dissertation title is Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing in Metal-based Additive Manufacturing. Durant will be joining CNA as a Research Analyst in September 2024. ​
Dr. Tian has been appointed as Associate Editor of ASME Journal of Computing & Information Science in Engineering. Her service term is from 7/1/2024 to 6/30/2027. 
​Bappy and Durant presented two presentations at NAMRC in Knoxville, TN. ​Great job!!
Owen Smith received the BCoE UG student Research Award. This award will support Owen's research on metal-based fused filament fabrication (FFF) process monitoring and material property prediction.
Congratulations, Owen!!
This paper highlights the state-of-the-art approaches in enhancing the use of small-scale datasets in additive manufacturing. Our vision for future research opportunities and directions in this area are also discussed.

The paper can be accessed from the link below:
https://www.sciencedirect.com/science/article/pii/S0278612524000876 
Mahathir Mohammad Bappy has successfully defended his PhD dissertation! He will join the Department of Mechanical and Industrial Engineering at Louisiana State University as an assistant professor in August 2024. Congratulations!!
Dr. Tian is recognized as one of the 2024 Susan Smyth Outstanding Young Manufacturing Engineers by SME. Since 1980, the SME Outstanding Young Manufacturing Engineer Award has recognized manufacturing engineers, age 35 or younger, who have made exceptional contributions and accomplishments in the manufacturing industry. Congratulations!
The NSF GRFP Award recognizes outstanding prospective and current graduate students who have demonstrated the potential to be high achieving scientists and engineers, early in their careers.

Ethan’s proposed research aims to advance the field of Additive Manufacturing (AM) by creating multiple frameworks that manage large volumes of diverse AM process data.
Mahathir Bappy won the Outstanding Graduate Student Researcher (on-campus) Award!

Durant Fullington won the Best Publication award!
Publication: Durant Fullington, Linkan Bian, and Wenmeng Tian. (2023) "Design De-Identification of Thermal History for Collaborative Process-Defect Modeling of Directed Energy Deposition Processes." Journal of Manufacturing Science and Engineering, 145(5). https://doi.org/10.1115/1.4056488)
Owen Smith won the Best Undergraduate Technical Paper competition at the IISE Southeast Regional Student Conference. Congratulations!
Two manuscripts from our team have been accepted by NAMRC, and Bappy and Durant will present their work at the NAMRC/MSEC conference in June, in Knoxville, TN. Congratulations!!

In addition, one paper titled "Leveraging Small-scale Datasets for Additive Manufacturing: Current Practice and Remaining Gaps" has been accepted for publication as a fast-track paper at the Journal of Manufacturing Systems. Congratulations to Durant, Mahathir Bappy, and our co-authors (Emmanuel Yangue, and Dr. Chenang Liu from Oklahoma State University)!