@article{starly_cohen_raman_2020, title={Automating the Search and Discovery of Manufacturing Service Providers to Enable a Digital Supply Chain Network}, volume={4}, ISSN={["2572-3928"]}, DOI={10.1520/SSMS20200061}, abstractNote={Uncertainty in manufacturing networks has created barriers to closing the gap between design enterprises and the American industrial base Uncertainty arises from the lack of transparent access to manufacturer capabilities, the inability to auto-discover service providers who are best capable for a given job request, and the dependence on human word-of-mouth trust network relationships that exist in the manufacturing supply chain This uncertainty slows down the pace of product development lifecycles from a viewpoint of inefficient forms of supplier assessment, vetting, selection, and compliance, leading to a trust tax tacked onto the final price of products In times of global crisis such as the coronavirus disease pandemic, this uncertainty also leads to inefficient forms of gathering information on manufacturing capability, available capacity, and registered licenses and assessing compliance This technical note outlines solution pathways that can help ease the search and discovery process of connecting clients and manufacturing service providers through digitally enabled technologies Copyright © 2020 by ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959}, number={3}, journal={SMART AND SUSTAINABLE MANUFACTURING SYSTEMS}, author={Starly, Binil and Cohen, Paul and Raman, Shivakumar}, year={2020}, month={Dec}, pages={276–280} }
 @article{sherlekar_starly_cohen_2019, title={Provisioned Data Distribution for Intelligent Manufacturing via Fog Computing}, volume={34}, ISSN={["2351-9789"]}, DOI={10.1016/j.promfg.2019.06.158}, abstractNote={The number of ‘things’ ranging from simple devices to complex machines on the factory floor connected at the enterprise level and to the broader internet is growing exponentially. This connection also leads to a tremendous amount of data generated leading to ‘Data’ now considered one of the core assets in the broader manufacturing industry. However, the availability of this asset is hardly made use of by Small and Medium scale manufacturing enterprises (SME) - the ‘Mittelstand’ of America. How can certain types of data be shared by SME companies, yet have the ability to retain ownership and control over their own data? How does SME leverage computing on these diverse forms of data for the benefit of its clients and itself? In this paper, we propose a decentralized data distribution architecture to democratize the potential availability of large amounts of data generated by the manufacturing industry using the Fog Computing paradigm. The architecture leverages an Industry scalable middleware extension of Cloud manufacturing that securely filters and transmits data from IoT enabled manufacturing machines on the shop floor to potential users over the cloud. This work also demonstrates a data-centric approach which allows peer-to-peer data sharing laterally within the fog layer to serve cloud users. We demonstrate the feasibility of the Fog middleware infrastructure through case studies that involves various types of manufacturing data.}, journal={47TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 47)}, author={Sherlekar, Riddhiman and Starly, Binil and Cohen, Paul H.}, year={2019}, pages={893–902} }
 @article{kong_wei_zhu_cohen_dong_2018, title={Characterization and Modeling of Catalyst-free Carbon-Assisted Synthesis of ZnO Nanowires}, volume={32}, ISSN={["1526-6125"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85044172611&partnerID=MN8TOARS}, DOI={10.1016/j.jmapro.2018.03.018}, abstractNote={ZnO nanowires have been widely studied due to their unique material properties and many potential applications in electronic and optoelectronic devices. Many growth processes have been developed to synthesize ZnO nanowires. It is critically important to develop predictive process models so as to maximize the output of the nanowire synthesis. Here we report a method to characterize, quantify, and model a catalyst-free carbon-assisted ZnO nanowire growth process. Two key factors were identified for the synthesis conditions, which are reaction temperature and flow rate. Based on a factorial design method, we conducted experiments with different combinations of the two factors to study their effects on the process output (i.e. density of the nanowires), which was evaluated by a scanning electron microscope (SEM). The experimental results were analyzed using ANOVA test, and then a semi-empirical model was built to correlate the ZnO nanowire output with synthesis conditions. This model was able to describe the ZnO nanowire density with respect to synthesis conditions, which can provide guideline for synthesis parameters selection and process optimization.}, journal={JOURNAL OF MANUFACTURING PROCESSES}, author={Kong, Xiangcheng and Wei, Chuang and Zhu, Yong and Cohen, Paul and Dong, Jingyan}, year={2018}, month={Apr}, pages={438–444} }
 @article{deng_dong_cohen_2018, title={Development and Characterization of Ultrasonic Vibration Assisted Nanomachining Process for Three-Dimensional Nanofabrication}, volume={17}, ISSN={["1941-0085"]}, url={https://doi.org/10.1109/TNANO.2018.2826841}, DOI={10.1109/tnano.2018.2826841}, abstractNote={This paper develops and characterizes a three-dimensional (3-D) nanofabrication process using ultrasonic vibration assisted nanomachining based on an atomic force microscope (AFM). The superiorities of height control over force control in the process are explained and are demonstrated by the fabrication results. Three factors impacting actual feature depths are investigated, including the ultrasonic z-vibrational amplitude, the assigned base feature depth, and the machining speed. 3-D nanostructures with continuous height variations were successfully fabricated on polymethyl methacrylate (PMMA) films with the feature height manipulated through controlling the absolute height of the cantilever tip in AFM. By selecting machining parameters based on characterizations, feature dimensions can be controlled as desired values within small variances. The capability of transferring 3-D nanostructures from PMMA films to silicon substrates is further explored in this paper. After selecting recipes of the reactive ion etching process, 3-D nanostructures are successfully transferred to silicon substrates with controllable selectivity. The reported ultrasonic vibration assisted nanomachining process in height control provides a robust approach of fabricating 3-D nanostructures.}, number={3}, journal={IEEE TRANSACTIONS ON NANOTECHNOLOGY}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Deng, Jia and Dong, Jingyan and Cohen, Paul H.}, year={2018}, month={May}, pages={559–566} }
 @article{kong_wei_zhu_cohen_dong_2018, title={Modeling of Catalyst-free Growth Process of ZnO Nanowires}, volume={26}, ISSN={2351-9789}, url={http://dx.doi.org/10.1016/J.PROMFG.2018.07.043}, DOI={10.1016/J.PROMFG.2018.07.043}, abstractNote={ZnO nanowires have been widely studied due to their unique material properties and many potential applications in electronic and optoelectronic devices. Many growth processes have been developed to synthesize ZnO nanowires. It is critically important to develop predictive process models so as to maximize the output of the nanowire synthesis. Here we report a method to characterize, quantify, and model a catalyst-free carbon-assisted ZnO nanowire growth process. Two key factors were identified for the synthesis conditions, which are reaction temperature and flow rate. Based on a factorial design method, we conducted experiments with different combinations of the two factors to study their effects on the process output (i.e. density of the nanowires), which was evaluated by a scanning electron microscope (SEM). The experimental results were analyzed using ANOVA test, and then a semi-empirical model was built to correlate the ZnO nanowire output with synthesis conditions. This model was able to describe the ZnO nanowire density with respect to synthesis conditions, which can provide a guideline for synthesis parameters selection and process optimization.}, journal={Procedia Manufacturing}, publisher={Elsevier BV}, author={Kong, Xiangcheng and Wei, Chuang and Zhu, Yong and Cohen, Paul and Dong, Jingyan}, year={2018}, pages={349–358} }
 @article{deng_dong_cohen_2018, title={Rapid Fabrication and Characterization of SERS Substrates}, volume={26}, ISSN={2351-9789}, url={http://dx.doi.org/10.1016/J.PROMFG.2018.07.068}, DOI={10.1016/J.PROMFG.2018.07.068}, abstractNote={Surface enhanced Raman spectroscopy (SERS) is a surface-sensitive detection technique that dramatically increases the scattering signals of the analytes compared to traditional Raman spectroscopy. Rapid and low-cost fabrication of SERS substrates with easily tunable features remains a challenge, although many SERS substrates with high enhancement factors (EF) were investigated. Here, we report a novel and rapid approach of fabricating SERS substrates using ultrasonic vibration assisted nanomachining. Grids patterns with easily tuned dimensions were fabricated on PMMA surfaces. SERS substrates were fabricated after coating an 80 nm gold layer on the patterned silicon after reactive ion etching (RIE) using the patterned PMMA as the mask. Probing molecules of R6G with the area density of 2.8 × 10-12 M/mm2 can be detected, achieving an EF of 3.11 × 103. Results show a pattern with higher grids density tends to achieve a higher EF.}, journal={Procedia Manufacturing}, publisher={Elsevier BV}, author={Deng, Jia and Dong, Jingyan and Cohen, Paul}, year={2018}, pages={580–586} }
 @article{pahwa_starly_cohen_2018, title={Reverse auction mechanism design for the acquisition of prototyping services in a manufacturing-as-a-service marketplace}, volume={48}, ISSN={["1878-6642"]}, DOI={10.1016/j.jmsy.2018.05.005}, abstractNote={The affordability and increased capability of additive manufacturing machines has spawned prototyping service bureaus throughout the world. This poses a challenge to designers who are looking to obtain quality 3D printed parts at best available prices within fastest turnaround times. Customers relying on a sole source for 3D printed parts may have limited options in obtaining the best deals. From a service supplier point of view, filling excess capacity will require significant marketing budgets to reach and retain customers. In this paper, we present a novel mechanism design approach for improving the accessibility of prototyping services providers by leveraging their excess capacity. In our proposed mechanism, consumers name their own price and the mechanism will find service bureaus who are willing to make the part under the stated price. The mechanism runs similar to a reverse auction where consumers bid and the platform finds a service supplier which is able to match the stated bid price. The incentive for suppliers to participate in such a platform is the opportunity to market their excess capacity to a deal conscious consumer at a lower price without cannibalizing their existing sales channels. Qualified suppliers do not directly compete with each other for any given order since they are chosen using a two stage selection process by the service platform. This algorithm ensures that every supplier has a fair chance of selling its services on the platform regardless of price. We implement the proposed mechanism design approach in a simulated service marketplace and empirically evaluate the marketplace behavior by studying the impact of various model factors such as the supplier threshold price, the size and variety of suppliers in the marketplace.}, journal={JOURNAL OF MANUFACTURING SYSTEMS}, author={Pahwa, Deepak and Starly, Binil and Cohen, Paul}, year={2018}, month={Jul}, pages={134–143} }
 @article{angrish_starly_lee_cohen_2017, title={A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM)}, volume={45}, ISSN={0278-6125}, url={http://dx.doi.org/10.1016/J.JMSY.2017.10.003}, DOI={10.1016/J.JMSY.2017.10.003}, abstractNote={Abstract Future factories will feature strong integration of physical machines and cyber-enabled software, working seamlessly to improve manufacturing production efficiency. In these digitally enabled and network connected factories, each physical machine on the shop floor can have its ‘virtual twin’ available in cyberspace. This ‘virtual twin’ is populated with data streaming in from the physical machines to represent a near real-time as-is state of the machine in cyberspace. This results in the virtualization of a machine resource to external factory manufacturing systems. This paper describes how streaming data can be stored in a scalable and flexible document schema based database such as MongoDB, a data store that makes up the virtual twin system. We present an architecture, which allows third-party integration of software apps to interface with the virtual manufacturing machines. We evaluate our database schema against query statements and provide examples of how third-party apps can interface with manufacturing machines using the VMM middleware. Finally, we discuss an operating system architecture for VMMs across the manufacturing cyberspace, which necessitates command and control of various virtualized manufacturing machines, opening new possibilities in cyber-physical systems in manufacturing.}, journal={Journal of Manufacturing Systems}, publisher={Elsevier BV}, author={Angrish, Atin and Starly, Binil and Lee, Yuan-Shin and Cohen, Paul H.}, year={2017}, month={Oct}, pages={236–247} }
 @article{kong_dong_cohen_2017, title={Modeling of the dynamic machining force of vibration-assisted nanomachining process}, volume={28}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000407982200011&KeyUID=WOS:000407982200011}, DOI={10.1016/j.jmapro.2017.05.028}, abstractNote={Nanofabrication technology is very important for many emerging engineering and scientific applications. Among different nanofabrication technologies, vibration-assisted nanomachining provides a low-cost easy-to-setup approach for producing structures with nano-scale resolution. It is very important to understand the mechanism for this nanomachining process and predict the involved machining force, so as to provide guidelines to achieve higher productivity and reduce tip wear. In this work, a machining force model for the tip-based nanomachining process was developed and validated. We analyzed the instantaneous engagement between the cutting tool (AFM tip) and the workpiece (PMMA film) during each tip rotation cycle for the vibration-assisted nanomachining process. A discrete voxel method was adopted to calculate the material removal rate at each moment, and an empirical machining force model is developed by correlating the machining force with material removal rate, which is a function of the input parameters of the nanomachining process. The machining force model was verified by experiments over a large range of machining conditions, and the coefficients in the force model were obtained by minimizing the Mean Square Error (MSE) method by comparing the predicted machining force from the model and measured machining force from the experiments. The results show a good fit between the predicted machining force and the measured machining force.}, journal={Journal of Manufacturing Processes}, author={Kong, X. C. and Dong, Jingyan and Cohen, Paul}, year={2017}, pages={101–108} }
 @article{zhang_starly_cai_cohen_lee_2017, title={Particle learning in online tool wear diagnosis and prognosis}, volume={28}, ISSN={["1526-6125"]}, DOI={10.1016/j.jmapro.2017.04.012}, abstractNote={Automated Tool condition monitoring is critical in intelligent manufacturing to improve both productivity and sustainability of manufacturing operations. Estimation of tool wear in real-time for critical machining operations can improve part quality and reduce scrap rates. This paper proposes a probabilistic method based on a Particle Learning (PL) approach by building a linear system transition function whose parameters are updated through online in-process observations of the machining process. By applying PL, the method helps to avoid developing a complex closed form formulation for a specific tool wear model. It increases the robustness of the algorithm and reduces the time complexity of computation. The application of the PL approach is tested using experiments performed on a milling machine. We have demonstrated one-step and two-step look ahead tool wear state prediction using online indirect measurements obtained from vibration signals. Additionally, the study also estimates remaining useful life (RUL) of the cutting tool inserts.}, journal={JOURNAL OF MANUFACTURING PROCESSES}, author={Zhang, Jianlei and Starly, Binil and Cai, Yi and Cohen, Paul H. and Lee, Yuan-Shin}, year={2017}, month={Aug}, pages={457–463} }
 @article{cai_starly_cohen_lee_2017, title={Sensor Data and Information Fusion to Construct Digital-twins Virtual Machine Tools for Cyber-physical Manufacturing}, volume={10}, ISSN={2351-9789}, url={http://dx.doi.org/10.1016/J.PROMFG.2017.07.094}, DOI={10.1016/J.PROMFG.2017.07.094}, abstractNote={This paper presents sensor data integration and information fusion to build “digital-twins” virtual machine tools for cyber-physical manufacturing. Virtual machine tools are useful for simulating machine tools’ capabilities in a safe and cost-effective way, but it is challenging to accurately emulate the behavior of the physical tools. When a physical machine tool breaks down or malfunctions, engineers can always go back to check the digital traces of the “digital-twins” virtual machine for diagnosis and prognosis. This paper presents an integration of manufacturing data and sensory data into developing “digital-twins” virtual machine tools to improve their accountability and capabilities for cyber-physical manufacturing. The sensory data are used to extract the machining characteristics profiles of a digital-twins machine tool, with which the tool can better reflect the actual status of its physical counterpart in its various applications. In this paper, techniques are discussed for deploying sensors to capture machine-specific features, and analytical techniques of data and information fusion are presented for modeling and developing “digital-twins” virtual machine tools. Example of developing the digital-twins of a 3-axis vertical milling machine is presented to demonstrate the concept of modeling and building a digital-twins virtual machine tool for cyber-physical manufacturing. The presented technique can be used as a building block for cyber-physic manufacturing development.}, journal={Procedia Manufacturing}, publisher={Elsevier BV}, author={Cai, Yi and Starly, Binil and Cohen, Paul and Lee, Yuan-Shin}, year={2017}, pages={1031–1042} }
 @article{singh_angrish_barkley_starly_lee_cohen_2017, title={Streaming Machine Generated Data to Enable a Third-Party Ecosystem of Digital Manufacturing Apps}, volume={10}, ISSN={2351-9789}, url={http://dx.doi.org/10.1016/J.PROMFG.2017.07.093}, DOI={10.1016/J.PROMFG.2017.07.093}, abstractNote={The digital factory of the future will be driven by the integration of physical smart machine tools and cyber-enabled software, working seamlessly to increase manufacturing intelligence, flexibility, agility and production efficiency. The objective of this study is develop and demonstrate a middleware software architecture to interface physical machines on a shop floor with client manufacturing applications. We have connected both legacy and modern ‘smart’ machines to a highly scalable database capable of storing streaming time-series data generated by on-board sensors and machine controllers. Three client applications were developed to demonstrate the mechanism through which third-party apps can be written without direct physical communications with machines on the shop-floor. The first, is an application that resides within the Digital Manufacturing Commons (DMC) which demonstrates the ability to query data from any physical machine on the floor; the 2nd application demonstrates a python app which compares digital product data with machine generated data; and the 3rd application demonstrates building a LabView app built to interface with the middleware service. This proposed architecture enables an ecosystem of smart manufacturing applications to be built and deployed on the shop-floor through open-sourced software and hardware devices thereby reducing cost of manufacturing software development.}, journal={Procedia Manufacturing}, publisher={Elsevier BV}, author={Singh, Shaurabh and Angrish, Atin and Barkley, James and Starly, Binil and Lee, Yuan-Shin and Cohen, Paul}, year={2017}, pages={1020–1030} }
 @article{deng_zhang_dong_cohen_2016, title={AFM-based 3D nanofabrication using ultrasonic vibration assisted nanomachining}, volume={24}, ISSN={["1526-6125"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000389393500022&KeyUID=WOS:000389393500022}, DOI={10.1016/j.jmapro.2016.09.003}, abstractNote={This paper presents a novel AFM-based 3D nanofabrication process using ultrasonic vibration assisted nanomachining. A set of three dimensional nanostructures on polymethyl methacrylate (PMMA) samples are fabricated with the assistance of high frequency in-plane circular xy-vibration and ultrasonic tip-sample z-vibration. Two methods for fabricating 3D nanostructures were investigated in this study, which are layer-by-layer nanomachining and one pass nanomachining with the depth controlled by setpoint force. Critical parameters in the process are identified, including setpoint force, overlap percentage, amplitude of z vibration and machining speed. By regulating these process parameters, multi-level 3D nanostructures were fabricated by multi-layer machining in vector mode and raster scan mode. Using different setpoint forces for regulating feature depths, other nanostructures, such as convex and concave circles, were fabricated in raster scan mode from gray-scale bitmap pattern images. Under each mode, 3D nanostructure over microscale area can be fabricated in just a few minutes with sub-10 nm resolution in z direction.}, journal={JOURNAL OF MANUFACTURING PROCESSES}, author={Deng, Jia and Zhang, Li and Dong, Jingyan and Cohen, Paul H.}, year={2016}, month={Oct}, pages={195–202} }
 @article{deng_dong_cohen_shih_wang_2016, title={High Rate 3D Nanofabrication by AFM-Based Ultrasonic Vibration Assisted Nanomachining}, volume={5}, ISSN={["2351-9789"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000387592400096&KeyUID=WOS:000387592400096}, DOI={10.1016/j.promfg.2016.08.100}, abstractNote={This paper introduces a high precision 3D nanofabrication approach using ultrasonic vibration assisted nanomachining using an AFM operating in constant height control mode. Nanostructures with 3D features were successfully fabricated on PMMA film with the feature height manipulated through controlling the absolute heights of z-scanner in AFM. Two methods were used to move the AFM tip to create desire features, vector mode and raster scan mode. Relatively simple features, such as stair-like nanostructure with five steps was successfully fabricated in vector mode. Complex nanostructure with discrete height levels and continuous changes were successfully fabricated in raster scan mode. By carefully selecting the machining parameters, the feature dimension and height can be precisely controlled with only small variation from the designed value. Moreover, this paper explores the capability of transferring 3D nanostructures from PMMA film onto silicon substrate. After calibrating the recipe of Reactive Ion Etching (RIE) process, 3D nanostructures are successfully transferred to silicon wafer with controllable selectivity between PMMA and silicon. The results of fabricating 3D structures on silicon substrates show promising potential of many applications, such as mold preparation in nanoimprint lithography.}, journal={44TH NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE, NAMRC 44}, author={Deng, Jia and Dong, Jingyan and Cohen, Paul and Shih, A and Wang, L}, year={2016}, pages={1283–1294} }
 @article{kong_cohen_dong_2016, title={Predictive modeling of feature dimension for tip-based nano machining process}, volume={24}, ISSN={["1526-6125"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000389166500004&KeyUID=WOS:000389166500004}, DOI={10.1016/j.jmapro.2016.06.013}, abstractNote={The tip-based vibration-assisted nanomachining process can fabricate three-dimensional (3D) features with nanometer scale resolution. To control the feature dimension accurately in process planning, we need to understand the relationship between feature dimension and machining parameters including setpoint force, XY vibration amplitude and feed rate. In this article, we conducted full factorial experiments to analyze the relationship between feature dimension and machining parameters. Based on analysis of variance (ANOVA), we determined the significant factors in determining the feature dimension. The feature width is mainly controlled by XY vibration amplitude, and the feature depth is controlled XY vibration, setpoint force and feed rate. In order to predict the feature dimension in nanomachining and provide instructions for machining parameter selection, a semi-empirical mechanical model was built first. Then simplified regression models were also investigated, with all models displaying good predictive capability. The results show good fit between predicted feature depth and measured feature depth, for most machining conditions. These models provide good capability in process planning for implementation of this process.}, journal={JOURNAL OF MANUFACTURING PROCESSES}, author={Kong, Xiangcheng and Cohen, Paul H. and Dong, Jingyan}, year={2016}, month={Oct}, pages={338–345} }
 @article{deng_zhang_dong_cohen_shih_wang_2015, title={AFM-based 3D Nanofabrication using Ultrasonic Vibration Assisted Nanomachining}, volume={1}, ISSN={["2351-9789"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000380512300051&KeyUID=WOS:000380512300051}, DOI={10.1016/j.promfg.2015.09.036}, abstractNote={This paper explores AFM-based 3D nanomachining process assisted by ultrasonic vibration. 3D structures on polymethyl methacrylate (PMMA) substrates are fabricated by ultrasonic vibration-assisted nanomachining process. Two fabrication approaches for 3D structures are investigated in this study, which are layer-by-layer nanomachining and one pass nanomachining with the depth controlled by setpoint force. Critical parameters in the process are identified, including set-point force, overlap rate, amplitude of z vibration and machining speed. By regulating these parameters, stair-like 3D nanostructures are fabricated by multi-layer machining in Vector mode and Raster scan mode. Using different setpoint force for different feature depth, other nanostructures, such as convex and concave circles, are fabricated in Raster scan mode from grey-scale image. Under each mode, 3D nanostructure over microscale area can be fabricated in just a few minutes with the assistance of high frequency in-plane circular xy-vibration and ultrasonic tip-sample z-vibration.}, journal={43RD NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE, NAMRC 43}, author={Deng, Jia and Zhang, Li and Dong, Jingyan and Cohen, Paul H. and Shih, AJ and Wang, LH}, year={2015}, pages={584–592} }
 @inproceedings{kong_zhang_dong_cohen_2015, title={Machining force modeling of vibration-assisted nano-machining process}, DOI={10.1115/MSEC2015-9423}, abstractNote={Nanofabrication technology is very important for many emerging engineering and scientific applications. Among different nanofabrication technologies, vibration-assisted nano-machining provides a low cost easy-to-setup approach to produce structures with nano-scale resolution. It is critical to understand the mechanism for the nano-machining process and predict the cutting force, so as to provide guidelines to achieve higher productivity and reduce tip wear. In this article, a machining force model for tip-based nano-machining process is developed and validated. We analyze the instantaneous engagement area between cutting tool (AFM tip) and workpiece (PMMA film) at the given tip position for the vibration-assisted nano-machining process. A discrete voxel method is adopted to calculate the material removal rate at each moment, and an empirical machining force model is developed by correlating the cutting force with material removal rate. The model was verified by experiments over a large range of machining conditions, and the coefficients and parameters in the force model was obtained using Mean Square Error (MSE) method by comparing the predicted machining force from the force model and measured machining force from experiments. The results show good fit between predicted machining force and measured machining force.}, booktitle={Proceedings of the ASME 10th International Manufacturing Science and Engineering Conference, 2015, vol 2}, author={Kong, X. C. and Zhang, L. and Dong, J. Y. and Cohen, P. H.}, year={2015} }
 @article{hunsberger_harrysson_shirwaiker_starly_wysk_cohen_allickson_yoo_atala_2015, title={Manufacturing Road Map for Tissue Engineering and Regenerative Medicine Technologies}, volume={4}, ISSN={["2157-6580"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84921807245&partnerID=MN8TOARS}, DOI={10.5966/sctm.2014-0254}, abstractNote={Abstract}, number={2}, journal={STEM CELLS TRANSLATIONAL MEDICINE}, author={Hunsberger, Joshua and Harrysson, Ola and Shirwaiker, Ronan and Starly, Binil and Wysk, Richard and Cohen, Paul and Allickson, Julie and Yoo, James and Atala, Anthony}, year={2015}, month={Feb}, pages={130–135} }
 @article{zhang_dong_cohen_2013, title={Material-Insensitive Feature Depth Control and Machining Force Reduction by Ultrasonic Vibration in AFM-Based Nanomachining}, volume={12}, ISSN={["1941-0085"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84883779535&partnerID=MN8TOARS}, DOI={10.1109/tnano.2013.2273272}, abstractNote={This paper investigates the effect of ultrasonic tip-sample vibration in regulating the fabricated feature depth and reducing machining force in ultrasonic vibration-assisted nanomachining with an atomic force microscope (AFM). Nanopatterns on aluminum and polymethyl methacrylate (PMMA) substrates are fabricated by the ultrasonic vibration-assisted nanomachining approach. It is demonstrated that using a small set-point force and the same vibration amplitude for machining PMMA and aluminum, nearly the same feature depth is achieved. The fabrication depth is mainly controlled by the amplitude of the tip-sample z-vibration, and is insensitive to sample materials. A theoretical analysis of the sample contact stiffness and dynamic stiffness of the cantilever is used to explain the observed material-insensitive depth regulation by ultrasonic tip-sample vibration. The ultrasonic vibration also effectively reduces the normal force and friction during nanomachining. On both PMMA and aluminum samples, experimental results demonstrate significant reduction in set-point force and lateral friction force in ultrasonic vibration-assisted nanomachining compared with nanomachining without ultrasonic z-vibration. Smaller tip wear is observed in ultrasonic vibration-assisted nanomachining for the fabrication of PMMA samples.}, number={5}, journal={IEEE TRANSACTIONS ON NANOTECHNOLOGY}, author={Zhang, Li and Dong, Jingyan and Cohen, Paul H.}, year={2013}, month={Sep}, pages={743–750} }
 @misc{shirwaiker_samberg_cohen_wysk_monteiro-riviere_2013, title={Nanomaterials and synergistic low-intensity direct current (LIDC) stimulation technology for orthopedic implantable medical devices}, volume={5}, ISSN={["1939-0041"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84876463086&partnerID=MN8TOARS}, DOI={10.1002/wnan.1201}, abstractNote={Abstract}, number={3}, journal={WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY}, author={Shirwaiker, Rohan A. and Samberg, Meghan E. and Cohen, Paul H. and Wysk, Richard A. and Monteiro-Riviere, Nancy A.}, year={2013}, pages={191–204} }
 @article{fu_cohen_ruud_2009, title={Experimental investigation of the machining induced residual stress tensor under mechanical loading}, volume={11}, ISSN={1526-6125}, url={http://dx.doi.org/10.1016/j.jmapro.2009.11.001}, DOI={10.1016/j.jmapro.2009.11.001}, abstractNote={Residual stress induced by machining is complex and difficult to predict, since it involves mechanical loads, temperature gradients or phase transformation in the generation mechanism. In this work, an experiment with a statistical design for the residual stress tensor was performed to investigate the residual stress profile on a machined surface. In order to understand the generation mechanism of residual stress in machining, three variables and workpiece materials were carefully selected to focus on the mechanical loads and avoid the temperature gradients and phase transformation on the machined surface. The mechanical loads considered here included the chip formation force at the primary shear zone and the plowing force at the tool tip–workpiece contact. Depths of cut and rake angles were selected to alter the chip formation force, and the tool tip radius was designed to emphasize the plowing effect. The workpiece material was aluminum 3003. The experimental results showed that the chip formation force provides basic shapes of the residual stress profile for a machined surface. It decides the depth of the peak residual stress below the surface. However, the plowing force was the dominating effect on the surface residual stress, causing high stresses on the surface. The plowing force can shift the surface stress from tensile to compressive. Additionally, the measured stress tensor proved that in-plane shear stress exists for the machined surface.}, number={2}, journal={Journal of Manufacturing Processes}, publisher={Elsevier BV}, author={Fu, Wei-En and Cohen, Paul H. and Ruud, Clayton O.}, year={2009}, month={Jul}, pages={88–96} }
 @article{samayoa_haque_cohen_2008, title={Focused ion beam irradiation effects on nanoscale freestanding thin films}, volume={18}, ISSN={["1361-6439"]}, DOI={10.1088/0960-1317/18/9/095005}, abstractNote={The focused ion beam (FIB) technique is a versatile tool for nanoscale manipulation, deposition and etching. However, degradation mechanisms which lead to residual stresses in materials exposed to high-energy ion beams are not well understood. In this study, we examine the evolution of residual stresses in 100 nm thick freestanding aluminum films subjected to typical ion beam exposures within a commercial FIB tool. Experimental results show that the magnitude of the residual stresses increase with cumulative ion beam exposure and that upper limits are attainable. Further investigation demonstrates that a decrease in ion beam current at constant acceleration-voltage augments the upper limits, which manifests itself in greater residual stresses. The stress gradients in thin films develop from surface modifications in the form of amorphous top layers, which are modeled as bilayer approximations. Experimental observations and analysis indicate that ion beam exposure effects on the mechanical properties of nanoscale thin films and nanostructures cannot be ignored.}, number={9}, journal={JOURNAL OF MICROMECHANICS AND MICROENGINEERING}, author={Samayoa, M. J. and Haque, M. A. and Cohen, P. H.}, year={2008}, month={Sep} }