Journal articles on the topic 'Sensor Manufacturing'
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Konyha, József, and Tamás Bányai. "Sensor Networks for Smart Manufacturing Processes." Solid State Phenomena 261 (August 2017): 456–62. http://dx.doi.org/10.4028/www.scientific.net/ssp.261.456.
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Each factory and manufacturing plant needs a flexible and reliable in-plant resource supply to serve production processes efficiently. Manufacturing systems are composed of several numbers of elements, workstations, machines and logistics resources. Production line is a complex system because of the complicated manufacturing process, multiple types, high machining difficulty and many special processes in it. In the Industry 4.0 based on smart manufacturing, it is essential to support the processes with intelligent sensor networks. In this article, we give a brief overview about sensors often used in manufacturing processes. Sensor networks generate a massive and increasing amount of data that needs to be processed. Computationally intensive algorithms are used for the data processing (image, voice and signal processing, different classification functions, numeric optimization routines). Finally, we discuss how GPGPU can improve the real-time processing of data generated by intelligent sensor networks.
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Ziesche, Steffen, Adrian Goldberg, Uwe Partsch, Holger Kappert, Heidrun Kind, Mirko Aden, and Falk Naumann. "On-turbine multisensors based on Hybrid Ceramic Manufacturing Technology." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2019, HiTen (July 1, 2019): 000107–11. http://dx.doi.org/10.4071/2380-4491.2019.hiten.000107.
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Abstract The contribution evaluates the potential of piezoresistive multilayer ceramic sensory solutions using Low or High Temperature Cofired Ceramics (LTCC/HTCC) for on-turbine sensors. Relevant ceramic materials were characterized and evaluated with regard to applicability and reliability under application-like conditions. A multilayer ceramic sensory element was designed including a ceramic embedded pressure sensing membrane, a Pt100 temperature sensor and ceramic integrated wiring. Appropriate sealing methods to implement the ceramic into metal housings as well as electrical connection solutions were worked out, which allow for an operation under the increased temperatures (> 300°C) of the application. A system concept, including sensory element, signal conditioning electronics, mechanical and electrical interfaces is part of the investigation.
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Bloss, Richard. "Sensors stand out as an important key to improving manufacturing quality and productivity at the latest IMTS show." Sensor Review 34, no. 2 (March 17, 2014): 149–53. http://dx.doi.org/10.1108/sr-12-2012-732.
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Purpose – Review of the IMTS show in Chicago with emphasis on the new sensor innovations and applications on display. The paper aims to discuss these issues. Design/methodology/approach – In-depth interviews with exhibitors of sensors and sensor integrators at the show. Findings – Sensors continue to match an ever-increasing number of manufacturing tasks to improve quality and productivity at every step in the manufacturing and inspection process. Practical implications – Customers may be surprised at the sensor innovations and new applications to which sensors are being applied in the manufacturing environment. Originality/value – A review of some of the latest sensor innovations and applications that one might have seen if they had been on the exhibition floor at the Chicago IMTS show.
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Du, H., and B. E. Klamecki. "Force Sensors Embedded in Surfaces for Manufacturing and Other Tribological Process Monitoring." Journal of Manufacturing Science and Engineering 121, no. 4 (November 1, 1999): 739–48. http://dx.doi.org/10.1115/1.2833131.
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The measurement of tooling-workpiece interface forces is needed for process design, process modeling and analysis and process monitoring for control. One approach to measuring local interface loads with minimal disturbance of the surface and process is to embed sensors in the surface below the surface region of interest. Small piezoelectric sensing elements were cast into surfaces and their ability to measure loads applied normal to the surfaces was assessed. Sensor outputs were analyzed in terms of sensor depth below the surface, distance along the surface from the load location to the sensor location and sensor to sensor spacing. A mechanical model of the sensor-surface system was developed which predicted sensor output. The use of this sensing concept and type of sensor was demonstrated in strip drawing tests. Using temperature compensated sensors, workpiece holddown force was measured in tests during which drawbead penetration was varied.
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Johnson, Timothy L., and Mark E. Dausch. "SENSOR INFORMATICS FOR MANUFACTURING." IFAC Proceedings Volumes 39, no. 3 (2006): 125–30. http://dx.doi.org/10.3182/20060517-3-fr-2903.00078.
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Chryssolouris, G., M. Domroese, and P. Beaulieu. "Sensor Synthesis for Control of Manufacturing Processes." Journal of Engineering for Industry 114, no. 2 (May 1, 1992): 158–74. http://dx.doi.org/10.1115/1.2899768.
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When a human controls a manufacturing process he or she uses multiple senses to monitor the process. Similarly, one can consider a control approach where measurements of process variables are performed by several sensing devices which in turn feed their signals into process models. Each of these models contains mathematical expressions based on the physics of the process which relate the sensor signals to process state variables. The information provided by the process models should be synthesized in order to determine the best estimates for the state variables. In this paper two basic approaches to the synthesis of multiple sensor information are considered and compared. The first approach is to synthesize the state variable estimates determined by the different sensors and corresponding process models through a mechanism based on training such as a neural network. The second approach utilizes statistical criteria to estimate the best synthesized state variable estimate from the state variable estimates provided by the process models. As a “test bed” for studying the effectiveness of the above sensor synthesis approaches turning has been considered. The approaches are evaluated and compared for providing estimates of the state variable tool wear based on multiple sensor information. The robustness of each scheme with respect to noisy and inaccurate sensor information is investigated.
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Syafrudin, Muhammad, Ganjar Alfian, Norma Fitriyani, and Jongtae Rhee. "Performance Analysis of IoT-Based Sensor, Big Data Processing, and Machine Learning Model for Real-Time Monitoring System in Automotive Manufacturing." Sensors 18, no. 9 (September 4, 2018): 2946. http://dx.doi.org/10.3390/s18092946.
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With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process.
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Baranov, A. M., and T. V. Osipova. "RECENT TRENDS IN THE DEVELOPMENT OF SENSORS FOR PRE-EXPLOSIVE CONCENTRATIONS OF FLAMMABLE GASES AND VAPORS OF FLAMMABLE LIQUIDS (REVIEW)." NAUCHNOE PRIBOROSTROENIE 31, no. 4 (November 30, 2021): 3–29. http://dx.doi.org/10.18358/np-31-4-i329.
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This paper presents a review of current trends in the development of manufacturing technologies of sensors of pre-explosive concentrations of flammable gases and vapors of flammable liquids. Various types of gas sensors are discussed, including catalytic, semiconductor, and optical sensor types, and the principles of their operation. The advantages and disadvantages of each type of gas sensor are highlighted. New and traditional technologies for manufacturing sensitive elements that improve sensor parameters such as processability, miniaturization and reduce energy consumption are discussed. In conclusion, this article suggests future trends and prospects for development and research to improve the sensitivity and selectivity of sensors.
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Zaid, Islam Mohamed, Mohamad Halwani, Abdulla Ayyad, Adil Imam, Fahad Almaskari, Hany Hassanin, and Yahya Zweiri. "Elastomer-Based Visuotactile Sensor for Normality of Robotic Manufacturing Systems." Polymers 14, no. 23 (November 24, 2022): 5097. http://dx.doi.org/10.3390/polym14235097.
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Modern aircrafts require the assembly of thousands of components with high accuracy and reliability. The normality of drilled holes is a critical geometrical tolerance that is required to be achieved in order to realize an efficient assembly process. Failure to achieve the required tolerance leads to structures prone to fatigue problems and assembly errors. Elastomer-based tactile sensors have been used to support robots in acquiring useful physical interaction information with the environments. However, current tactile sensors have not yet been developed to support robotic machining in achieving the tight tolerances of aerospace structures. In this paper, a novel elastomer-based tactile sensor was developed for cobot machining. Three commercial silicon-based elastomer materials were characterised using mechanical testing in order to select a material with the best deformability. A Finite element model was developed to simulate the deformation of the tactile sensor upon interacting with surfaces with different normalities. Additive manufacturing was employed to fabricate the tactile sensor mould, which was chemically etched to improve the surface quality. The tactile sensor was obtained by directly casting and curing the optimum elastomer material onto the additively manufactured mould. A machine learning approach was used to train the simulated and experimental data obtained from the sensor. The capability of the developed vision tactile sensor was evaluated using real-world experiments with various inclination angles, and achieved a mean perpendicularity tolerance of 0.34°. The developed sensor opens a new perspective on low-cost precision cobot machining.
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Barmpakos, Dimitris, and Grigoris Kaltsas. "A Review on Humidity, Temperature and Strain Printed Sensors—Current Trends and Future Perspectives." Sensors 21, no. 3 (January 22, 2021): 739. http://dx.doi.org/10.3390/s21030739.
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Printing technologies have been attracting increasing interest in the manufacture of electronic devices and sensors. They offer a unique set of advantages such as additive material deposition and low to no material waste, digitally-controlled design and printing, elimination of multiple steps for device manufacturing, wide material compatibility and large scale production to name but a few. Some of the most popular and interesting sensors are relative humidity, temperature and strain sensors. In that regard, this review analyzes the utilization and involvement of printing technologies for full or partial sensor manufacturing; production methods, material selection, sensing mechanisms and performance comparison are presented for each category, while grouping of sensor sub-categories is performed in all applicable cases. A key aim of this review is to provide a reference for sensor designers regarding all the aforementioned parameters, by highlighting strengths and weaknesses for different approaches in printed humidity, temperature and strain sensor manufacturing with printing technologies.
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Kim, SangUn, TranThuyNga Truong, JunHyuk Jang, and Jooyong Kim. "The Programmable Design of Large-Area Piezoresistive Textile Sensors Using Manufacturing by Jacquard Processing." Polymers 15, no. 1 (December 25, 2022): 78. http://dx.doi.org/10.3390/polym15010078.
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Among wearable e-textiles, conductive textile yarns are of particular interest because they can be used as flexible and wearable sensors without affecting the usual properties and comfort of the textiles. Firstly, this study proposed three types of piezoresistive textile sensors, namely, single-layer, double-layer, and quadruple-layer, to be made by the Jacquard processing method. This method enables the programmable design of the sensor’s structure and customizes the sensor’s sensitivity to work more efficiently in personalized applications. Secondly, the sensor range and coefficient of determination showed that the sensor is reliable and suitable for many applications. The dimensions of the proposed sensors are 20 × 20 cm, and the thicknesses are under 0.52 mm. The entire area of the sensor is a pressure-sensitive spot. Thirdly, the effect of layer density on the performance of the sensors showed that the single-layer pressure sensor has a thinner thickness and faster response time than the multilayer pressure sensor. Moreover, the sensors have a quick response time (<50 ms) and small hysteresis. Finally, the hysteresis will increase according to the number of conductive layers. Many tests were carried out, which can provide an excellent knowledge database in the context of large-area piezoresistive textile sensors using manufacturing by Jacquard processing. The effects of the percolation of CNTs, thickness, and sheet resistance on the performance of sensors were investigated. The structural and surface morphology of coating samples and SWCNTs were evaluated by using a scanning electron microscope. The structure of the proposed sensor is expected to be an essential step toward realizing wearable signal sensing for next-generation personalized applications.
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Baek, Jae Yun, Kyung Mook Kang, Hyeong Jun Kim, Ju Hyeon Kim, Ju Hwan Lee, Gilyong Shin, Jei Gyeong Jeon, et al. "Manufacturing Process of Polymeric Microneedle Sensors for Mass Production." Micromachines 12, no. 11 (November 5, 2021): 1364. http://dx.doi.org/10.3390/mi12111364.
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In this work, we present a fabrication process for microneedle sensors made of polylactic acid (PLA), which can be utilized for the electrochemical detection of various biomarkers in interstitial fluid. Microneedles were fabricated by the thermal compression molding of PLA into a laser machined polytetrafluoroethylene (PTFE) mold. Sensor fabrication was completed by forming working, counter, and reference electrodes on each sensor surface by Au sputtering through a stencil mask, followed by laser dicing to separate individual sensors from the substrate. The devised series of processes was designed to be suitable for mass production, where multiple microneedle sensors can be produced at once on a 4-inch wafer. The operational stability of the fabricated sensors was confirmed by linear sweep voltammetry and cyclic voltammetry at the range of working potentials of various biochemical molecules in interstitial fluid.
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Wang, Wen Juan, Hao Song, Wei Guo, and Nan Sheng. "Mechanical Properties of Composites with Embedded FBG Sensors in Manufacturing Engineering." Advanced Materials Research 583 (October 2012): 263–67. http://dx.doi.org/10.4028/www.scientific.net/amr.583.263.
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FBG (fiber Bragg grating) sensors are appropriate for embedding in composites manufacturing engineering. Influence of embedding FBG sensors on the composites tension, compression, CAI properties was studied in this paper. Results identified that the mechanical properties decreased obviously when a certain volume content of optical fibers embedded. FBG sensor permits the continuous monitoring of the host material when embedded in the middle 0 degree layer, consistent with strain gauges. Sensitivity coefficient of FBG sensor embedded is almost the same as that not embedded. It offers important reference value on the application of FBG sensors in aerospace composites.
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Sarma, Mridusmita, Florian Borchers, Gerrit Dumstorff, Carsten Heinzel, and Walter Lang. "Measuring strain during a cylindrical grinding process using embedded sensors in a workpiece." Journal of Sensors and Sensor Systems 6, no. 2 (September 15, 2017): 331–40. http://dx.doi.org/10.5194/jsss-6-331-2017.
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Abstract. This paper presents the results of using a sensor-integrated workpiece for in situ measurement of strain during an outer-diameter cylindrical grinding process. The motivation of this work is to measure in situ process parameters using integrated sensors in a workpiece in order to characterize the manufacturing process. Resistive sensors that operate on the same principle as conventional strain gauges were fabricated on wafers made of steel using standard microtechnology and later the wafers were diced to form unique sensor-integrated steel components (sensor inlays). These inlays are embedded into a groove on the top surface of a cylindrical workpiece using epoxy adhesive. The workpiece is also made of the same steel as the sensor wafers and has similar properties due to a heat treatment process, thereby maintaining the homogeneity of the material over the whole contact area. The sensor-integrated workpiece was used to perform experiments in a Studer S41 high-performance cylindrical grinding machine. The sensor response to the internal strain was recorded during every grinding step starting from a depth of 1 mm down to 2 mm from the top surface. Such an application of sensor integration in materials for in situ process monitoring can be used in other manufacturing processes as well and this can help to observe internal loads (mechanical or thermal) in manufacturing processes.
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Abdallah, Mustafa, Byung-Gun Joung, Wo Jae Lee, Charilaos Mousoulis, Nithin Raghunathan, Ali Shakouri, John W. Sutherland, and Saurabh Bagchi. "Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets." Sensors 23, no. 1 (January 2, 2023): 486. http://dx.doi.org/10.3390/s23010486.
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Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. This often boils down to detecting anomalies within the sensor data acquired from the system which has different characteristics with respect to the operating point of the environment or machines, such as, the RPM of the motor. In this paper, we analyze four datasets from sensors deployed in manufacturing testbeds. We detect the level of defect for each sensor data leveraging deep learning techniques. We also evaluate the performance of several traditional and ML-based forecasting models for predicting the time series of sensor data. We show that careful selection of training data by aggregating multiple predictive RPM values is beneficial. Then, considering the sparse data from one kind of sensor, we perform transfer learning from a high data rate sensor to perform defect type classification. We release our manufacturing database corpus (4 datasets) and codes for anomaly detection and defect type classification for the community to build on it. Taken together, we show that predictive failure classification can be achieved, paving the way for predictive maintenance.
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Wang, Lening, Pang Du, and Ran Jin. "MOSS—Multi-Modal Best Subset Modeling in Smart Manufacturing." Sensors 21, no. 1 (January 1, 2021): 243. http://dx.doi.org/10.3390/s21010243.
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Smart manufacturing, which integrates a multi-sensing system with physical manufacturing processes, has been widely adopted in the industry to support online and real-time decision making to improve manufacturing quality. A multi-sensing system for each specific manufacturing process can efficiently collect the in situ process variables from different sensor modalities to reflect the process variations in real-time. However, in practice, we usually do not have enough budget to equip too many sensors in each manufacturing process due to the cost consideration. Moreover, it is also important to better interpret the relationship between the sensing modalities and the quality variables based on the model. Therefore, it is necessary to model the quality-process relationship by selecting the most relevant sensor modalities with the specific quality measurement from the multi-modal sensing system in smart manufacturing. In this research, we adopted the concept of best subset variable selection and proposed a new model called Multi-mOdal beSt Subset modeling (MOSS). The proposed MOSS can effectively select the important sensor modalities and improve the modeling accuracy in quality-process modeling via functional norms that characterize the overall effects of individual modalities. The significance of sensor modalities can be used to determine the sensor placement strategy in smart manufacturing. Moreover, the selected modalities can better interpret the quality-process model by identifying the most correlated root cause of quality variations. The merits of the proposed model are illustrated by both simulations and a real case study in an additive manufacturing (i.e., fused deposition modeling) process.
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Alwis, Lourdes S. M., Kort Bremer, and Bernhard Roth. "Fiber Optic Sensors Embedded in Textile-Reinforced Concrete for Smart Structural Health Monitoring: A Review." Sensors 21, no. 15 (July 21, 2021): 4948. http://dx.doi.org/10.3390/s21154948.
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The last decade has seen rapid developments in the areas of carbon fiber technology, additive manufacturing technology, sensor engineering, i.e., wearables, and new structural reinforcement techniques. These developments, although from different areas, have collectively paved way for concrete structures with non-corrosive reinforcement and in-built sensors. Therefore, the purpose of this effort is to bridge the gap between civil engineering and sensor engineering communities through an overview on the up-to-date technological advances in both sectors, with a special focus on textile reinforced concrete embedded with fiber optic sensors. The introduction section highlights the importance of reducing the carbon footprint resulting from the building industry and how this could be effectively achieved by the use of state-of-the-art reinforcement techniques. Added to these benefits would be the implementations on infrastructure monitoring for the safe operation of structures through their entire lifespan by utilizing sensors, specifically, fiber optic sensors. The paper presents an extensive description on fiber optic sensor engineering that enables the incorporation of sensors into the reinforcement mechanism of a structure at its manufacturing stage, enabling effective monitoring and a wider range of capabilities when compared to conventional means of structural health monitoring. In future, these developments, when combined with artificial intelligence concepts, will lead to distributed sensor networks for smart monitoring applications, particularly enabling such distributed networks to be implemented/embedded at their manufacturing stage.
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Krijnen, Gijs J. M., and Remco G. P. Sanders. "Recent Developments in Bio-Inspired Sensors Fabricated by Additive Manufacturing Technologies." Advances in Science and Technology 100 (October 2016): 197–206. http://dx.doi.org/10.4028/www.scientific.net/ast.100.197.
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In our work on micro-fabricated hair-sensors, inspired by the flow-sensitive sensors found on crickets, we have made great progress. Initially delivering mediocre performance compared to their natural counter parts they have evolved into capable sensors with thresholds roughly a factor of 30 larger than of their natural equivalents. Due to this disparity, and also instigated by our work on fly-halteres inspired rotation rate sensors and desert locust ear-drum mimicking membrane struc- tures, we have analysed the differences in performance between natural and man-made sensors. We conclude that two major drawbacks of main-stream micro-fabrication are the lack of easily applicable soft materials, as well as the limitations imposed by photolithography based fabrication with respect to freeform 3D shaping of structures. Currently we are targeting additive manufacturing for biomimetic sensor structures and in this contribution we report initial results of 3D printed sensor structures.
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Liu, Meng-Yang, Cheng-Zhou Hang, Xue-Yan Wu, Li-Yuan Zhu, Xiao-Hong Wen, Yang Wang, Xue-Feng Zhao, and Hong-Liang Lu. "Investigation of stretchable strain sensor based on CNT/AgNW applied in smart wearable devices." Nanotechnology 33, no. 25 (April 1, 2022): 255501. http://dx.doi.org/10.1088/1361-6528/ac5ee6.
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Abstract Stretchable strain sensor, an important paradigm of wearable sensor which can be attached onto clothing or even human skin, is widely used in healthcare, human motion monitoring and human-machine interaction. Pattern-available and facile manufacturing process for strain sensor is pursued all the time. A carbon nanotube (CNT)/silver nanowire (AgNW)-based stretchable strain sensor fabricated by a facile process is reported here. The strain sensor exhibits a considerable Gauge factor of 6.7, long-term durability (>1000 stretching cycles), fast response and recovery (420 ms and 600 ms, respectively), hence the sensor can fulfill the measurement of finger movement. Accordingly, a smart glove comprising a sensor array and a flexible printed circuit board is assembled to detect the bending movement of five fingers simultaneously. Moreover, the glove is wireless and basically fully flexible, it can detect the finger bending of wearer and display the responses distinctly on an APP of a smart phone or a host computer. Our strain senor and smart glove will broaden the materials and applications of wearable sensors.
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Liu, Jan, Flakë Bajraktari, Ömer Atmaca, Toni J. Ly, and Peter P. Pott. "Microscale Sensor Fabrication on Curved Needle Surfaces." Current Directions in Biomedical Engineering 8, no. 2 (August 1, 2022): 632–35. http://dx.doi.org/10.1515/cdbme-2022-1161.
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Abstract Sensor-integrated needles with impedance or other electrochemical sensors have gained increased attention in research. Their potential use is widespread and covers applications such as early disease diagnostics or needle guidance for needle-based interventions. However, fabrication and sensor integration are crucial parts of realizing functionalized needles. In this paper, a review of existing research on microscale sensor arrays on curved needle surfaces is presented. It focusses on medical needles excluding needle-type sensors. Especially, means of fabrications including flexible thin-film-based sensors or photolithography are discussed. Although they provide satisfactory results, no manufacturing method is yet ready for bulk production.
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Singh, Ravinder, and Kuldeep Singh Nagla. "Comparative analysis of range sensors for the robust autonomous navigation – a review." Sensor Review 40, no. 1 (October 29, 2019): 17–41. http://dx.doi.org/10.1108/sr-01-2019-0029.
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Purpose The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment. Design/methodology/approach Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot. Findings This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot. Originality/value This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.
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Yoedistira, Chresiani Destianita, Muhammad Hilmi Afthoni, and Rokiy Alfanaar. "Silver nanoparticle based alcohol sensor manufacturing training for detection of halal drinks." Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang 6, no. 4 (November 2, 2021): 613–19. http://dx.doi.org/10.26905/abdimas.v6i4.5124.
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Nowadays, halal drinks are one of the sectors that get the attention of various parties. Alcohol in beverages is important in determining the halalness of a beverage. Halal detection can be done using chemical sensors. In the Pharmacy Department, knowledge of analysis using sensors is rare. Therefore, this community service program was carried out to introduce qualitative methods of quick and simple alcohol analysis. The participants are students of the Pharmacy Department of STIKES Anwar Medika in Sidoarjo City. Participants are communities engaged in the health sector who have an interest in halal and how to make sensors for halal testing. This program is implemented by making a video on how to make a chemical sensor for alcohol detection. The chemical sensor is a paper-immobilized colloidal silver-based chemical sensor that is easy to apply in various conditions. Based on the results of the color change produced on the filter paper, from green to bluish which indicates that the food or beverage sample contains alcohol. Based on the questionnaire, participants expressed satisfaction with the increase in knowledge about additional tools that are easy and fast to detect alcohol.
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Kulkarni, Amol, Janis Terpenny, and Vittaldas Prabhu. "Sensor Selection Framework for Designing Fault Diagnostics System." Sensors 21, no. 19 (September 28, 2021): 6470. http://dx.doi.org/10.3390/s21196470.
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In a world of rapidly changing technologies, reliance on complex engineered systems has become substantial. Interactions associated with such systems as well as associated manufacturing processes also continue to evolve and grow in complexity. Consider how the complexity of manufacturing processes makes engineered systems vulnerable to cascading and escalating failures; truly a highly complex and evolving system of systems. Maintaining quality and reliability requires considerations during product development, manufacturing processes, and more. Monitoring the health of the complex system while in operation/use is imperative. These considerations have compelled designers to explore fault-mechanism models and to develop corresponding countermeasures. Increasingly, there has been a reliance on embedded sensors to aid in prognosticating failures, to reduce downtime, during manufacture and system operation. However, the accuracy of estimating the remaining useful life of the system is highly dependent on the quality of the data obtained. This can be enhanced by increasing the number of sensors used, according to information theory. However, adding sensors increases total costs with the cost of the sensors and the costs associated with information-gathering procedures. Determining the optimal number of sensors, associated operating and data acquisition costs, and sensor-configuration are nontrivial. It is also imperative to avoid redundant information due to the presence of additional sensors and the efficient display of information to the decision-maker. Therefore, it is necessary to select a subset of sensors that not only reduce the cost but are also informative. While progress has been made in the sensor selection process, it is limited to either the type of the sensor, number of sensors or both. Such approaches do not address specifications of the required sensors which are integral to the sensor selection process. This paper addresses these shortcomings through a new method, OFCCaTS, to avoid the increased cost associated with health monitoring and to improve its accuracy. The proposed method utilizes a scalable multi-objective framework for sensor selection to maximize fault detection rate while minimizing the total cost of sensors. A wind turbine gearbox is considered to demonstrate the efficacy of the proposed framework.
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Bloss, Richard. "Multi-technology sensors are being developed for medical, manufacturing, personal health and other applications not previously possible with historic single-technology sensors." Sensor Review 37, no. 4 (September 18, 2017): 385–89. http://dx.doi.org/10.1108/sr-04-2017-0063.
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Purpose The purpose of this paper is to review the advancements in new multi-technology sensor products being developed or already serving the market and to explore such applications. The paper also addresses some hacking problems which may arise. Design/methodology/approach This paper is a review of published information and papers on multi-technology sensor research as well as contact and discussions with multi-technology sensor researchers and suppliers in this field. Findings Microelectronics and electrochemical technologies have been major factors in the multi-sensor technology advancements of sensors for a wide range of applications. Sensors are becoming much smarter; solving application problems better than has been previously possible with single-technology sensors. Multi-technology sensors in many cases may offer better resolution and are much more sensitive than single technology sensors in the past. Practical implications Readers may be very excited to learn of the many advances in multi-technology sensors which are coming to the sensor field. Applications that were previously served with more than one sensor or were not possible before are now being served by multi-technology sensors. One such application which many readers may not be aware of but may be using is the wearable individual exercise sensor. One such device is the Apple Watch which will be reviewed in some detail later in this paper. Originality/value No previous review of multi-technology sensing has been observed.
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Geller, Sirko, and Maik Gude. "Process-Integrated Manufacturing and Embedding of Novel Piezoelectric Sensor Modules into Glass Fibre-Reinforced Polyurethane Composite Structures." Materials Science Forum 825-826 (July 2015): 563–70. http://dx.doi.org/10.4028/www.scientific.net/msf.825-826.563.
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Due to an increasing use of composite materials in various applications and related open questions concerning structural health monitoring and damage detection, the realisation of function integrating lightweight structures with sensory properties is subject of numerous research activities. Main objective is the transfer of already in laboratory and prototype scale established methods for the integration of sensory elements on serial applications. Here, combining the previously separated processing steps sensor manufacturing, component manufacturing and sensor integration can help to make a significant step forwards. Therefore, as part of the activities in the Collaborative Research Centre/Transregio (CRC/TR) 39, a highly productive spray coat method based on the long fibre injection (LFI) process is developed, which allows the process-integrated manufacturing and embedding of novel piezoelectric sensor modules into fibre-reinforced polyurethane composite structures.Based on studies on the technological implementation of the newly developed process, theoretical and experimental studies for contacting and polarisation of the novel sensor elements are presented. In addition, the characterisation of the adhesion properties of thermoplastic films on the used fibre-reinforced polyurethane composites is part of the presented research to evaluate the possibility of integrating thermoplastic-compatible piezo modules for actuator applications.
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Waqar, Tayyab, and Sezgin Ersoy. "Design and Analysis Comparison of Surface Acoustic Wave-Based Sensors for Fabrication Using Additive Manufacturing." Journal of Nanomaterials 2021 (June 12, 2021): 1–12. http://dx.doi.org/10.1155/2021/5598347.
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Sensors have become an integral part of our everyday lives by helping us converting packets of data to make important decisions. Due to this reason, researches are done constantly to improve the fabrication processes of sensors by making them more user-friendly, less time-consuming, and more cost-effective. The application of any fabrication solution that offers those advantages will have a major impact on the manufacturing of modern sensors. To address this issue, a 3D printed Surface Acoustic Wave (SAW) temperature sensor is presented in this paper. The modelling and analysis of such a sensor have been performed for both aluminium and copper electrodes using COMSOL software. In total, 4 different sensing structures, 2 each for both aluminium and copper electrodes based one-port resonators, are designed and analysed for their application in temperature sensing. The resulting responses of those sensors are approximately 2.19 MHz and 424.01 MHz frequency ranges. The novelty lies in the possibility of mass-producing such a sensor using additive manufacturing will have a direct impact in the areas where conventional electronics cannot be utilized.
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Herwan, Jonny, Seisuke Kano, Ryabov Oleg, Hiroyuki Sawada, and Masahiro Watanabe. "Comparing Vibration Sensor Positions in CNC Turning for a Feasible Application in Smart Manufacturing System." International Journal of Automation Technology 12, no. 3 (May 1, 2018): 282–89. http://dx.doi.org/10.20965/ijat.2018.p0282.
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Tool condition monitoring, such as tool wear and breakage, is an essential feature in smart manufacturing system. One of most potential sensors that can be used in tool monitoring is vibration sensor, which usually assembled at tool shank. However, in case of CNC turning with rotating tool turret, it is impossible to assemble the vibration sensor at the tool shank because wire of the sensor will be damaged when the turret rotated. This paper is addressed to compare thoroughly alternative sensor positions. Ten sensor positions including tool shank, as a reference, are investigated. The signals from three types of cutting, namely; normal cutting, abnormal cutting with tool wear and abnormal cutting when tool breakage occurred, are investigated. Based on the magnitude of the output signals and their capability to predict tool wear and breakage, a suggestion on vibration sensor positions is proposed.
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Gong, Taobo, You Zhao, Yulong Zhao, Lukang Wang, Yu Yang, and Wei Ren. "Design and Manufacturing of a High-Sensitivity Cutting Force Sensor Based on AlSiCO Ceramic." Micromachines 12, no. 1 (January 7, 2021): 63. http://dx.doi.org/10.3390/mi12010063.
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On-line cutting force measurement is an effective way to monitor processing quality, improve processing accuracy, and protect the tool. In high-speed and ultra-precision machining, status monitoring is particularly necessary to ensure machining accuracy. However, the cutting force is very small in high speed and ultra-precision machining. Therefore, high-sensitivity cutting force sensors are needed. Current commercial cutting force sensors have defects such as large volume, low compatibility, and high price. In particular, the sensitivity of cutting force sensor needs to be improved for high-speed and ultra-precision machining status monitoring. This paper provides a possible solution by embedding the sensor in the tool and selecting sensitive materials with high piezoresistive coefficient. In this paper, the structural design of the sensor and the fabrication of the sensitive material SiAlCO ceramic are carried out, and then the sensor is packaged and tested. The test results show that the cutting force sensor’s sensitivity was as high as 219.38 mV/N, which is a feasible way to improve cutting force sensor’s compatibility and sensitivity.
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Gong, Taobo, You Zhao, Yulong Zhao, Lukang Wang, Yu Yang, and Wei Ren. "Design and Manufacturing of a High-Sensitivity Cutting Force Sensor Based on AlSiCO Ceramic." Micromachines 12, no. 1 (January 7, 2021): 63. http://dx.doi.org/10.3390/mi12010063.
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On-line cutting force measurement is an effective way to monitor processing quality, improve processing accuracy, and protect the tool. In high-speed and ultra-precision machining, status monitoring is particularly necessary to ensure machining accuracy. However, the cutting force is very small in high speed and ultra-precision machining. Therefore, high-sensitivity cutting force sensors are needed. Current commercial cutting force sensors have defects such as large volume, low compatibility, and high price. In particular, the sensitivity of cutting force sensor needs to be improved for high-speed and ultra-precision machining status monitoring. This paper provides a possible solution by embedding the sensor in the tool and selecting sensitive materials with high piezoresistive coefficient. In this paper, the structural design of the sensor and the fabrication of the sensitive material SiAlCO ceramic are carried out, and then the sensor is packaged and tested. The test results show that the cutting force sensor’s sensitivity was as high as 219.38 mV/N, which is a feasible way to improve cutting force sensor’s compatibility and sensitivity.
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Widyaningrum, Siti Annisa, Ratri Ismawati, and Frida Agung Rakhmadi. "Manufacture and Characterization of Sensor for Optimizing the Manufacture of Resistance Sensor for Pure Orange Drink and Unpure Orange Drink." Proceeding International Conference on Science and Engineering 3 (April 30, 2020): 159–61. http://dx.doi.org/10.14421/icse.v3.489.
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This research was purposed to design and analyze a resistance sensor. This research was done by three steps which are designing, manufacturing and characterizing of resistance sensor. Sensor design was done by using Fritzing software. The tools we used in manufacturing sensor were PCB, resistor, and copper wire. The tools we used in sensor characterizing were power supply, CRO and samples of pure orange drink and unpure orange drink. Sensor characterizing was done by varying samples of 50 ml and 100 ml. Data acquisitiom for each samples were repeated five times. Data generated from the sensor in the form of voltage. The data result of measurement were calculated by its average and its uncertainty. For pure orange drink 50 mL (2.274 ± 1.137); 100 mL (1.688 ± 0.844) and for unpure orange drink 50 mL (2.582 ± 1.291); 100 mL (1.852 ± 0.926). Therefore in the future we can make quality control system of orange drink by optimizing the manufacture of resistance sensors with high-grade characteristics.
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Grist, Samantha M., Kevin L. Bennewith, and Karen C. Cheung. "Oxygen Measurement in Microdevices." Annual Review of Analytical Chemistry 15, no. 1 (June 13, 2022): 221–46. http://dx.doi.org/10.1146/annurev-anchem-061020-111458.
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Oxygen plays a fundamental role in respiration and metabolism, and quantifying oxygen levels is essential in many environmental, industrial, and research settings. Microdevices facilitate the study of dynamic, oxygen-dependent effects in real time. This review is organized around the key needs for oxygen measurement in microdevices, including integrability into microfabricated systems; sensor dynamic range and sensitivity; spatially resolved measurements to map oxygen over two- or three-dimensional regions of interest; and compatibility with multimodal and multianalyte measurements. After a brief overview of biological readouts of oxygen, followed by oxygen sensor types that have been implemented in microscale devices and sensing mechanisms, this review presents select recent applications in organs-on-chip in vitro models and new sensor capabilities enabling oxygen microscopy, bioprocess manufacturing, and pharmaceutical industries. With the advancement of multiplexed, interconnected sensors and instruments and integration with industry workflows, intelligent microdevice-sensor systems including oxygen sensors will have further impact in environmental science, manufacturing, and medicine.
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Lugoda, Pasindu, Julio C. Costa, Carlos Oliveira, Leonardo A. Garcia-Garcia, Sanjula D. Wickramasinghe, Arash Pouryazdan, Daniel Roggen, Tilak Dias, and Niko Münzenrieder. "Flexible Temperature Sensor Integration into E-Textiles Using Different Industrial Yarn Fabrication Processes." Sensors 20, no. 1 (December 21, 2019): 73. http://dx.doi.org/10.3390/s20010073.
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Textiles enhanced with thin-film flexible sensors are well-suited for unobtrusive monitoring of skin parameters due to the sensors’ high conformability. These sensors can be damaged if they are attached to the surface of the textile, also affecting the textiles’ aesthetics and feel. We investigate the effect of embedding flexible temperature sensors within textile yarns, which adds a layer of protection to the sensor. Industrial yarn manufacturing techniques including knit braiding, braiding, and double covering were utilised to identify an appropriate incorporation technique. The thermal time constants recorded by all three sensing yarns was <10 s. Simultaneously, effective sensitivity only decreased by a maximum of 14% compared to the uncovered sensor. This is due to the sensor being positioned within the yarn instead of being in direct contact with the measured surface. These sensor yarns were not affected by bending and produced repeatable measurements. The double covering method was observed to have the least impact on the sensors’ performance due to the yarn’s smaller dimensions. Finally, a sensing yarn was incorporated in an armband and used to measure changes in skin temperature. The demonstrated textile integration techniques for flexible sensors using industrial yarn manufacturing processes enable large-scale smart textile fabrication.
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Schubert, F., S. Wollenhaupt, J. Kita, G. Hagen, and R. Moos. "Platform to develop exhaust gas sensors manufactured by glass-solder-supported joining of sintered yttria-stabilized zirconia." Journal of Sensors and Sensor Systems 5, no. 1 (January 22, 2016): 25–32. http://dx.doi.org/10.5194/jsss-5-25-2016.
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Abstract. A manufacturing process for a planar binary lambda sensor is shown. By joining the heating and the sensing components via glass soldering with a joining temperature of 850 °C, a laboratory platform has been established that allows the manufacturing of two independent parts in high-temperature co-fired ceramics technology (HTCC) with electrodes that are post-processed at lower temperatures, as is required for mixed-potential sensors. The final device is compared to a commercial sensor with respect to its sensing performance. Important processes and possible origins of problems as well as their solutions during sensor development are shown, including heater design and joining process.
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Arjun, Somnath, LRD Murthy, and Pradipta Biswas. "Interactive Sensor Dashboard for Smart Manufacturing." Procedia Computer Science 200 (2022): 49–61. http://dx.doi.org/10.1016/j.procs.2022.01.204.
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Jung, Im Doo, Min Sik Lee, Young Jin Woo, Kyung Tae Kim, and Ji-Hun Yu. "Additive Manufacturing for Sensor Integrated Components." Journal of Korean Powder Metallurgy Institute 27, no. 2 (April 30, 2020): 111–18. http://dx.doi.org/10.4150/kpmi.2020.27.2.111.
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Binder, Maximilian, Matthias Illgner, Christine Anstaett, Philipp Kindermann, Ludwig Kirchbichler, and Christian Seidel. "Automated Manufacturing of Sensor-Monitored Parts." Laser Technik Journal 15, no. 3 (June 2018): 36–39. http://dx.doi.org/10.1002/latj.201800015.
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Heydarianasl, Mozhde. "Optimization of electrostatic sensor based on sensor separation." Sensor Review 39, no. 5 (September 16, 2019): 724–32. http://dx.doi.org/10.1108/sr-06-2018-0158.
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Purpose Electrostatic sensors are applied to measure velocity of solid particles in many industries because controlling the velocity particles improves product quality and process efficiency. The purpose of current paper is optimization of these sensors which is required to achieve maximum spatial sensitivity and minimum statistical error. Design/methodology/approach Different electrode of electrostatic sensors with different length, thickness and sensor separations were experimentally applied in laboratory. Then, correlation velocity, signal bandwidth and statistical error were calculated. Findings High sensor separation is a crucial factor because it would lead to increase signal similarity and decrease statistical error. This paper focuses on the effect of sensor separation on optimization of electrostatic sensors. Originality/value From observations, the optimal value for length, thickness and sensor separations was 0.6, 0.5 and 15 cm, respectively. Consequently, statistical error has improved by about 17 per cent. These results provided a significant basis of optimization of electrostatic sensors.
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Park, Jongwon. "Optical Glucose Sensor Using Pressure Sensitive Paint." Sensors 21, no. 13 (June 30, 2021): 4474. http://dx.doi.org/10.3390/s21134474.
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A glucose sensor is used as an essential tool for diagnosing and treating diabetic patients and controlling processes during cell culture. Since the development of an electrochemical-based glucose sensor, an optical glucose sensor has been devised to overcome its shortcomings, but this also poses a problem because it requires a complicated manufacturing process. This study aimed to develop an optical glucose sensor film that could be fabricated with a simple process using commercial pressure sensitive paints. The sensor manufacturing technology developed in this work could simplify the complex production process of the existing electrochemical or optical glucose sensors. In addition, a photometric method for glucose concentration analysis was developed using the color image of the sensor. By developing this sensor and analysis technology, the basis for glucose measurement was established that enables two-dimensional, online, and continuous measurement. The proposed sensor showed good linearity at 0–4 mM glucose in an aqueous sample solution, its limit of detection was 0.37 mM, and the response time was 2 min.
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Di Tocco, Joshua, Daniela Lo Presti, Alberto Rainer, Emiliano Schena, and Carlo Massaroni. "Silicone-Textile Composite Resistive Strain Sensors for Human Motion-Related Parameters." Sensors 22, no. 10 (May 23, 2022): 3954. http://dx.doi.org/10.3390/s22103954.
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In recent years, soft and flexible strain sensors have found application in wearable devices for monitoring human motion and physiological parameters. Conductive textile-based sensors are good candidates for developing these sensors. However, their robust electro-mechanical connection and susceptibility to environmental factors are still an open challenge to date. In this work, the manufacturing process of a silicone-textile composite resistive strain sensor based on a conductive resistive textile encapsulated into a dual-layer of silicone rubber is reported. In the working range typical of biomedical applications (up to 50%), the proposed flexible, skin-safe and moisture resistant strain sensor exhibited high sensitivity (gauge factor of −1.1), low hysteresis (maximum hysteresis error 3.2%) and ease of shaping in custom designs through a facile manufacturing process. To test the developed flexible sensor, two applicative scenarios covering the whole working range have been considered: the recording of the chest wall expansion during respiratory activity and the capture of the elbow flexion/extension movements.
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Windisch, M., K. J. Eichhorn, J. Lienig, G. Gerlach, and L. Schulze. "Paradigm change in hydrogel sensor manufacturing: from recipe-driven to specification-driven process optimization." Journal of Sensors and Sensor Systems 5, no. 1 (February 10, 2016): 39–53. http://dx.doi.org/10.5194/jsss-5-39-2016.
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Abstract. The volume production of industrial hydrogel sensors lacks a quality-assuring manufacturing technique for thin polymer films with reproducible properties. Overcoming this problem requires a paradigm change from the current recipe-driven manufacturing process to a specification-driven one. This requires techniques to measure quality-determining hydrogel film properties as well as tools and methods for the control and optimization of the manufacturing process. In this paper we present an approach that comprehensively addresses these issues. The influence of process parameters on the hydrogel film properties and the resulting sensor characteristics have been assessed by means of batch manufacturing tests and the application of several measurement techniques. Based on these investigations, we present novel methods and a tool for the optimization of the cross-linking process step, with the latter being crucial for the sensor sensitivity. Our approach is applicable to various sensor designs with different hydrogels. It has been successfully tested with a sensor solution for surface technology based on PVA/PAA hydrogel as sensing layer and a piezoelectric thickness shear resonator as transducer. Finally, unresolved issues regarding the measurement of hydrogel film parameters are outlined for future research.
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Cordeiro, Milton, and Jessica E. Koehne. "(Digital Presentation) Printed Wearable Electrochemical Sensor for Monitoring Human Performance Markers during Human Spaceflight." ECS Meeting Abstracts MA2022-01, no. 57 (July 7, 2022): 2362. http://dx.doi.org/10.1149/ma2022-01572362mtgabs.
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Additive manufacturing technologies are being explored by NASA for the in-space manufacturing of sensors and electronics. Additive manufacturing directly addresses the logistic challenge for long-duration human spaceflight missions while also offering a high degree of customization and tailorability. To ensure the health and safety of crew members during long duration missions, it can be advantageous to develop human health diagnostic tools that can be manufactured during those missions. Here we report the development of a wearable and fully printed electrochemical sensor for the detection of human performance markers in sweat.1 The sensor’s fabrication is complimentary with in-space manufacturing for an on-demand and hands-free fabrication and is comprised of commercial and custom carbon, gold and silver inks on a polyimide substrate to make a flexible, 3-electrode electrochemical sensor, shown in Figure 1. Sensor readout is performed using standard electrochemical procedures via a miniaturized, custom potentiostat. The initial prototyped printed electrochemical sensors demonstrate good electrochemical performance and high mechanical stability while also displaying low batch to batch variability. Our goal is to create a highly adaptable and versatile approach that utilizes fabrication processes consistent with in-space manufacturing, thus enabling the manufacture of point-of-care devices during flight. Reference Brasier, N. & Eckstein, J. Sweat as a Source of Next-Generation Digital Biomarkers. Digit. Biomarkers 3, 155–165 (2019). Figure 1
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Žuk, Samuel, Alena Pietriková, and Igor Vehec. "POSSIBILITIES OF PLANAR CAPACITIVE RAIN SENSOR MANUFACTURING BY THICK FILM TECHNOLOGY." Acta Electrotechnica et Informatica 18, no. 4 (January 5, 2018): 11–16. http://dx.doi.org/10.15546/aeei-2018-0027.
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TORMO GARCIA, FRANCISCO JAVIER, Juan Ivorra Martínez, Teodomiro Boronat, and NESTOR MONTAÑES MUÑOZ. "LOW-COST FABRICATION AND CHARACTERISATION OF A FLEXIBLE GRAPHITE-BASED TOUCH SENSOR." DYNA DYNA-ACELERADO (October 26, 2022): [ 5 pp.]. http://dx.doi.org/10.6036/10577.
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This paper presents a new method to produce a flexible piezoresistive sensor based on graphite. Under the premise of low-cost manufacturing, the materials used are easy to acquire and the manufacturing process consists of a simple transfer and exfoliation of a graphite paste thus obtaining flexible sheets. These sensors exhibit high sensitivity to touch and pressure. To characterise their response, an ad hoc method has been developed to recreate the interaction of the sensor with a human finger, which is shown in detail. The result presented is a highly sensitive graphite sensor, stable, easily integrated and with multiple application possibilities, for example in intelligent prostheses, in systems for capturing the movement of the human body and even for use as synthetic skin. Key Words: Graphite, piezoresistive flexible sensor, low cost, tactile, synthetic skin.
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Hassanbeiglou, Alireza, Masoud Kalantari, Elaheh Mozaffari, Javad Dargahi, and József Kövecses. "A new tactile array sensor for viscoelastic tissues with time-dependent behavior." Sensor Review 35, no. 4 (September 21, 2015): 374–81. http://dx.doi.org/10.1108/sr-06-2014-656.
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Purpose – The purpose of this paper is to introduce a new tactile array sensor into the medical field to enhance current robotic minimally invasive surgery (RMIS) procedures that are still limited in scope and versatility. In this paper, a novel idea is proposed in which a tactile sensor array can measure rate of displacement in addition to force and displacement of any viscoelastic material during the course of a single touch. To verify this new array sensor, several experiments were conducted on a diversity of tissues from which it was concluded that this newly developed sensory offers definite and significant enhancements. Design/methodology/approach – The proposed array sensor is capable of extracting force, displacement and displacement rate in the course of a single touch on tissues. Several experiments have been conducted on different tissues and the array sensor to verify the concept and to verify the output of the sensor. Findings – It is shown that this new generation of sensors are required to distinguish the difference in hardness degrees of materials with viscoelastic behavior. Originality/value – In this paper, a new generation of tactile sensors is proposed that is capable of measuring indentation time in addition to force and displacement. This idea is completely unique and has not been submitted to any conference or journal.
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Kim, Bioh, Thorsten Matthias, Gerald Kreindl, Viorel Dragoi, Markus Wimplinger, and Paul Lindner. "Advances in Wafer Level Processing and Integration for CIS Module Manufacturing." International Symposium on Microelectronics 2010, no. 1 (January 1, 2010): 000378–84. http://dx.doi.org/10.4071/isom-2010-wa1-paper5.
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This article presents the advances in wafer-level processing and integration techniques for CMOS image sensor module manufacturing. CMOS image sensors gave birth to the low-cost, high-volume camera phone market and are being adopted for various high-end applications. The backside illumination technique has significant advantages over the front-side illumination due to separation of the optical path from the metal interconnects. Wafer bonding plays a key role in manufacturing backside illuminated sensors. The cost-effective integration of miniaturized cameras in various handheld devices becomes realized through the introduction of CMOS image sensor modules or camera modules manufactured with wafer-level processing and integration techniques. We developed various technologies enabling wafer-level processing and integration, such as (a) wafer-to-wafer permanent bonding with oxide or polymer layers for manufacturing backside illuminated sensor wafers, (b) wafer-level lens molding and stacking based on UV imprint lithography for making wafer-level optics, (c) conformal coating of various photoresists within high aspect ratio through-silicon vias, and (d) advanced backside lithography for various metallization processes in wafer-level packaging. Those techniques pave the way to the future growth of the digital imaging industry by improving the electrical and optical aspects of devices as well as the module manufacturability.
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Duykova, M. V., S. E. Shkonda, S. A. Kazakov, and M. A. Grevtsev. "MANUFACTURING AND RESEARCH OF METAL OXIDE SEMICONDUCTOR GAS SENSORS FOR AMMONIA." NAUCHNOE PRIBOROSTROENIE 30, no. 4 (November 30, 2020): 52–62. http://dx.doi.org/10.18358/np-30-4-i5262.
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Ammonia-sensitive materials based on tin dioxide have been developed and synthesized. The degree of structural defects was evaluated, and the acid-base surface centers of synthesized materials were studied using the indicator method. The relationship between the chemisorption properties of synthesized gas-sensitive sensor layers (gas response to the concentration effect of ammonia) and the structure of the sensor material is discovered and analyzed. The novelty of the research is the integrated approach presented in this paper to the creation, development and manufacture of sensors for ammonia by synthesizing a material with pre-set properties using several methods of surface modernization simultaneously.
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Denkena, B. Prof, D. Dahlmann, and M. Mücke. "Sensorische Werkstücke*/Sensory workpieces - Process monitoring by sensor integration into the workpiece." wt Werkstattstechnik online 106, no. 11-12 (2016): 815–20. http://dx.doi.org/10.37544/1436-4980-2016-11-12-37.
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In Werkzeugmaschinen eingebettete Sensorsysteme sind ein zentrales Forschungsthema der Industrie 4.0. Vor allem Sensoren in prozessnahen Maschinenkomponenten weisen eine hohe Sensitivität gegenüber den Prozesseinflüssen auf. Es liegt somit nahe, das Werkstück – Fokus jeder Produktion – als Informationsquelle zu nutzen. Dies führt zu neuen Herausforderungen bei der Sensorplatzierung sowie der Energie- und Datenübertragung. Der Fachbeitrag beschreibt ein Konzept für sensorische Werkstücke und zeigt die Validierung der Nutzung für die Prozessüberwachung. A central research topic in industry 4.0 is the development of sensor systems embedded into machine tools. Especially sensors, which are integrated in machine components near to the process, show high sensitivities to the process loads. Consequently, the workpiece representing the focus of each manufacturing process is predestined for sensor integration. This leads to novel challenges according to sensor positioning, data and energy transmission. This article describes a concept for sensory workpieces and the validation of the utilization for process monitoring.
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Xu, Xiang-Yuan, Hao Ge, Jing Zhao, Zhi-Fei Chen, Jun Zhang, Ming-Hui Lu, Ming Bao, Yan-Feng Chen, and Xiao-Dong Li. "A monolithic three-dimensional thermal convective acoustic vector sensor with acoustic-transparent heat sink." JASA Express Letters 2, no. 4 (April 2022): 044001. http://dx.doi.org/10.1121/10.0010275.
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An acoustic vector sensor can directly detect acoustic particle velocity based on the measured temperature difference between closely spaced heated wires. For the detection of velocity in three dimensions, an integrated three-dimensional (3 D) sensor is desired, but it remains challenging in MEMS (Micro-Electro-Mechanical System) manufacturing. Here, a novel monolithic 3 D acoustic vector sensor is proposed, which is constructed using in-plane distributed wires assembled with acoustically transparent heat sink. The planar MEMS structure of the proposed sensor makes it easy to be fabricated and packaged. This work offers a new method for the design of acoustic vector sensors and other thermal convection-based MEMS sensors.
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Alfiah, Fia Ismi Nur, Dinda Salsabila P, and Frida Agung Rakhmadi. "Design and Characterization of Resistance Sensor to Optimize the Manufacturing of Infuse Water Lemon and Sprite Water Lymon Detection System." Proceeding International Conference on Science and Engineering 3 (April 30, 2020): 9–11. http://dx.doi.org/10.14421/icse.v3.458.
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This research was purposed to design and characterize a resistance sensor. This research was conducted with three phases: designing, manufacturing and characterization of resistance sensor. Sensor design was done using the 3D paint software. The tools used in sensor manufacturing were PCB, resistors, and copper wire. The tools used in sensor characterization were power supply, ohmmeter and samples of infuse water lemon and sprite water lymon. Sensor characterization was done by varying samples of 50ml, 100ml, 150ml. Data acquisition for each of samples was repeated 3 times. The result of this research was showed an average and unpredictability with the repeatability resistance sensor on the sample of infuse water lemon (1,215 ± 0,723) V with repeatability 99.05% while for samples of sprite water lymon amounting to (1,12 ± 1,345) V with repeatability 99.24%. And was retrieved the value of the transfer function for sample infuse water lemon is y = (4,757-0.03542x) and for sample sprite water lymon is y = (1.40666-0.0028666x). This tool can be developed as a detection tool using resistance-based sensors.
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Kalsoom, Tahera, Naeem Ramzan, Shehzad Ahmed, and Masood Ur-Rehman. "Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0." Sensors 20, no. 23 (November 27, 2020): 6783. http://dx.doi.org/10.3390/s20236783.
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The evolution of intelligent manufacturing has had a profound and lasting effect on the future of global manufacturing. Industry 4.0 based smart factories merge physical and cyber technologies, making the involved technologies more intricate and accurate; improving the performance, quality, controllability, management, and transparency of manufacturing processes in the era of the internet-of-things (IoT). Advanced low-cost sensor technologies are essential for gathering data and utilizing it for effective performance by manufacturing companies and supply chains. Different types of low power/low cost sensors allow for greatly expanded data collection on different devices across the manufacturing processes. While a lot of research has been carried out with a focus on analyzing the performance, processes, and implementation of smart factories, most firms still lack in-depth insight into the difference between traditional and smart factory systems, as well as the wide set of different sensor technologies associated with Industry 4.0. This paper identifies the different available sensor technologies of Industry 4.0, and identifies the differences between traditional and smart factories. In addition, this paper reviews existing research that has been done on the smart factory; and therefore provides a broad overview of the extant literature on smart factories, summarizes the variations between traditional and smart factories, outlines different types of sensors used in a smart factory, and creates an agenda for future research that encompasses the vigorous evolution of Industry 4.0 based smart factories.