@inproceedings{koprov_2023, title={Systems and Methods for Authenticating Manufacturing Machines Through an Unobservable Fingerprinting System}, volume={51}, booktitle={North American Manufacturing Research Conference}, author={Koprov, Pavel}, year={2023} }
 @article{koprov_gadhwala_walimbe_fang_starly_2023, title={Systems and methods for authenticating manufacturing Machines through an unobservable fingerprinting system}, volume={35}, ISSN={2213-8463}, url={http://dx.doi.org/10.1016/j.mfglet.2023.08.051}, DOI={10.1016/j.mfglet.2023.08.051}, abstractNote={Digital transformation leads to the inevitable change in the security paradigm for machines on a factory production floor. A unified namespace for machines in an Industrial Internet of Things (IIoT) network is only reliable when machine assets can trust and verify the identity of assets connected to the IIoT system. Current methods of asset authentication do not consider physical unclonable functions (PUFs) and can easily be spoofed or misused. Our work proposes using PUFs for industrial equipment such as CNC machines, robots, and 3D printers for identifying machines on a network and providing authentication procedures. In this work, we chose to use the vibration associated with machines and its embedded moving parts as a means to identify machine assets on a network. It is hypothesized that the vibrations associated with specific machine movements will be unique to each machine even when machines look exactly the same. The moving parts within a machine may produce a unique vibration pattern that can be used for machine identification throughout the working cycle. Our method requires light computing and relatively cheap measuring devices to capture the ‘fingerprints’ of machines and verify the signal's integrity. An adequate number of equipment has been tested for the worst-case scenario, i.e. when two machines look exactly the same with the same moving parts and produce exactly similar motion to generate the vibration signal. Data preprocessing and standard machine learning techniques like RF, LASSO, and SVM show great performance on raw time series data, enabling 100% TPR and more than 94% TNR in detecting the false class of the machines.}, journal={Manufacturing Letters}, publisher={Elsevier BV}, author={Koprov, Pavel and Gadhwala, Shyam and Walimbe, Aniket and Fang, Xiaolei and Starly, Binil}, year={2023}, month={Aug}, pages={1009–1018} }
 @article{starly_koprov_bharadwaj_batchelder_breitenbach_2023, title={“Unreal” factories: Next generation of digital twins of machines and factories in the Industrial Metaverse}, volume={37}, ISSN={2213-8463}, url={http://dx.doi.org/10.1016/j.mfglet.2023.07.021}, DOI={10.1016/j.mfglet.2023.07.021}, abstractNote={In its current technology form, digital twins are 3D representations that still lack the realism necessary to enable digital twins to progress towards virtual collaboration and high-fidelity simulation. In this short paper, ten technologies necessary to build the next generation of digital twins of factories are elucidated with a focus on real-time rendering while capturing dynamic states within machines, two-way real-time data transfer between assets and synthetic generation of factory states. Potential applications are also outlined to enable the community to further imagine technology needs and research questions that arise as the next generation of Digital twins are developed.}, journal={Manufacturing Letters}, publisher={Elsevier BV}, author={Starly, Binil and Koprov, Pavel and Bharadwaj, Akshay and Batchelder, Thomas and Breitenbach, Bennett}, year={2023}, month={Sep}, pages={50–52} }
 @article{koprov_ramachandran_lee_cohen_starly_2022, title={Streaming Machine Generated Data via the MQTT Sparkplug B Protocol for Smart Factory Operations}, volume={33}, ISSN={2213-8463}, url={http://dx.doi.org/10.1016/j.mfglet.2022.07.016}, DOI={10.1016/j.mfglet.2022.07.016}, abstractNote={The implementation of smart manufacturing relies on back-and-forth industrial communications between the machine assets on the shop floor to the cloud-level information systems. The Purdue Model of Computer Integrated Manufacturing has been a standard for industrial control system architecture guidance. However, in IIoT, data flow is not hierarchical since intelligence is added to the machine asset level. This paper describes the implementation and test run of the MQTT Sparkplug-B protocol with conventional machining assets, with its data being streamed from the machine controllers to a shop floor network and further on to a cloud-based platform. The publish/subscribe pattern of communication between the machining asset, and the cloud level is established, further demonstrating the ease with which a unified namespace can be achieved between various information and Operational Technology networks seamlessly and with relative ease.}, journal={Manufacturing Letters}, publisher={Elsevier BV}, author={Koprov, Pavel and Ramachandran, Ashwin and Lee, Yuan-Shin and Cohen, Paul and Starly, Binil}, year={2022}, month={Sep}, pages={66–73} }
 @inbook{koprov_2018, place={Saint Petersburg}, edition={1st}, title={Design of a Compact Modular Marine Refrigeration Unit}, booktitle={Marine Herald}, author={Koprov, Pavel}, year={2018} }
 @inproceedings{pavel_2017, title={Modernization of the Refrigeration System of the Navy Ship's Chambers: the Development of a Modular Refrigeration Unit, Materials of Contest}, booktitle={Engineer Shipbuilder of the year}, author={Pavel, Koprov}, year={2017} }
 @inproceedings{koprov_2016, title={Import Substitution for Naval Ships Built Abroad}, booktitle={International Conference on Naval Architecture and Ocean Engineering}, author={Koprov, Pavel}, year={2016} }
 @inproceedings{koprov_2011, title={Wine Fermentation Temperature Maintenance System}, booktitle={Materials of International Scientifically Technological Conference of Students, Aspirants and Young Scholars}, author={Koprov, Pavel}, year={2011}, pages={17–19,} }