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Photonic integration firm Photon Bridge of Eindhoven, The Netherlands is collaborating with transceiver maker PICadvanced of Ílhavo Portugal to showcase prototype transceivers built using its multi-material integrated photonics platform...

Участь представників ФБТ у Літній академії в Німеччині: обмін досвідом та розвиток міжнародних відносин Інформація КП ср, 10/01/2025 - 14:10

The world of manufacturing is changing very fast with digital intelligence merging with the conventional industrial processes. Physical AI lies at the heart of this revolution, bringing together sophisticated algorithms and machinery such as robotic arms, autonomous guided vehicles (AGVs), and CNC machinery. For these systems based on AI to function optimally, they depend on real-time information from industrial sensors. Serving as the “eyes and ears” of machines, sensors today do much more than make measurements they allow AI systems to learn, adapt, and optimize processes to enhance productivity, safety, and efficiency.

The two-part series addresses how industrial sensors enable physical AI applications. The first part discusses sensor types and functions in smart factories, while the second part will discuss innovations and trends that will dominate next-generation physical AI-powered industrial systems.

How Industrial Sensors Enable Physical AI

Industrial sensors measure physical parameters like motion, distance, pressure, temperature, or flow into electrical signals that undergo parameterization. These signals find their way into PLCs, CNC machines, and edge AI devices that carry out real-time decision making.

A typical sensor has some or all of these components: sensing element, operational amplifier OpAmp, ADC, processor, interface, and power management. All these or some of them constitute the sensor acting as a bridge between AI algorithms and the physical world, much like the nervous system transmitting information to the brain.

With a modern smart factory, there is an increase in the deployment of AI at the edge, embedding algorithms in sensors, robots, and controllers themselves. This obviates decision making in real-time being made on cloud-based IT systems alone.

Key Industrial Sensor Types

Vision (Image) Sensors: Cameras used to capture product images for machine vision, inspection, and quality control. They recognize orientation, defects, and positioning in real time. Next-generation short-wave infrared (SWIR) and low-power image sensors provide high dynamic range and low-light capabilities in demanding industrial settings.

Position & Torque Sensors: Hall-effect, optical, and inductive sensors are used to detect motor position and torque. Latest inductive PCB-based sensors combine analog front-ends and controllers to make mechanical design easier while providing improved temperature tolerance and contamination resistance.

Ultrasonic Sensors: Detect distance by emitting ultrasonic waves. Suitable for detecting transparent objects, ultrasonic sensors are widely applied in autonomous robots for navigation and obstacle detection and in process automation for flow and level measurement.

Photoelectric Sensors: Capture objects using light-based technologies infrared or laser and come in through-beam, retroreflective, and diffuse-reflective configurations. They are non-contact, flexible, and accommodate long detection ranges.

Proximity Sensors: Sense metallic objects using electromagnetic induction without contact. They are durable in harsh environments and can be used in conjunction with ultrasonic or photoelectric sensors to detect non-metallic objects.

Pressure Sensors: Condition clean-room environments and pneumatic or hydraulic systems. They deliver accurate voltage readings that represent system pressure using strain gauges or force resistors.

Temperature Sensors: Monitor and control temperature in various industries. Thermocouples, RTDs, and semiconductor temperature sensors protect machinery and stabilize processes.

Environmental Sensors: Add gas, chemical, rain, and light sensors to measure environmental conditions and workplace safety. For example, electrochemical sensors can measure chemical currents at low power consumption, providing constant monitoring.

Selecting the Correct Sensors for Intelligent Manufacturing

When designing industrial systems with AI, engineers should keep in mind:

1. Application Response Speed & Accuracy: Response speed and accuracy should be suited to the job, from control of robots to quality inspection in real time.
2. Data Reliability: Sensors need to deliver high-quality data reliably to enable AI learning and analytics.
3. Integration & Interoperability: Sensors need to integrate seamlessly with PLCs, field buses, and other industrial automation.
4. Data Privacy & Cybersecurity: Preserving sensitive operating data is essential, particularly as sensors communicate data through networks.
5. Energy Efficiency: Sensors with low power consumption allow widespread deployment without exceeding power budgets.

Conclusion:

Industrial sensors are critical to enable physical AI in the smart factory spaces. By sensing the physical world accurately and interpreting it, these sensors enable AI systems to make quicker, wiser, and more secure decisions. With advancements in sensor technologies, they will further propel more intelligent, adaptive, and more sustainable industrial activities, leading the way to Industry 5.0.

With its extensive sensor portfolio and application know-how, Onsemi continues to be the leader in intelligent sensing, assisting manufacturers to unlock the full value of physical AI.

(This article has been adapted and modified from content on Onsemi.)

The post How Industrial Sensors are Powering the Age of Physical AI in Smart Manufacturing appeared first on ELE Times.

The US Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management (FECM) has announced up to $6m in federal funding available for R&D projects to help establish a secure domestic supply chain for gallium...

Делегація кафедри МАтаТЙ ФМФ в Університеті Мелардален (Швеція) kpi ср, 10/01/2025 - 11:55

Photonic integration firm Photon Bridge of Eindhoven, The Netherlands has debuted its integrated tunable laser photonic integrated circuit (PIC), powered by its patented cantilever waveguide coupling technology (which combines III-V speed with silicon scale)...

A breakthrough in wearable technology is redefining what smart glasses can do: generative AI running entirely on the device, without the need for a phone or cloud connection. Powered by the new Snapdragon AR1+ Gen 1 platform, the glasses allow an AI to interact seamlessly in every day scenarios-from shopping or any home tasks.

AI Fitting Inside Glasses

In a live demonstration, a generative AI assistant operated directly on smart glasses using a compact language model (SLM). During a simulated grocery trip, the assistant helped with a recipe, delivering audio guidance and text directly on the lenses all without any external device. This is a strong demonstration of what is going on with smart glasses from mere accessories to full-blown, standalone AI tools.

Snapdragon AR1+ Gen 1

The Snapdragon AR1+ Gen 1 processor, 26% smaller than previous generations, brings enhanced power efficiency, improved image quality, and the ability to run small language models directly on the glasses. These improvements are crucial for thinner, lighter frames that don’t compromise performance or functionality.

Flexible XR Ecosystem

Next-generation smart glasses will be available in various form factors. Some will be standalone, and others will be linked to nearby devices like smartphones, tablets, or portable computing “pucks.” This modular system provides flexible, high-performance experiences across various configurations while keeping AI interactions speedy, private, and responsive.

Improved Vision and Multimodal Inputs

Sophisticated camera features enable glasses to record and perceive the world in rich detail, enabling proactive suggestion and context-sensitive help. Even when not connected to other devices, these glasses can be paired with other wearables like smartwatches or rings, enabling new forms of interaction and input.

Conclusion

This demonstration represents the beginning of a new era in wearable AI, in which intelligent glasses have the capability to provide tailored, real-time support on the move. Powered by the Snapdragon AR1+ platform, Qualcomm is making some of the thinnest, cleverest, and most powerful glasses possible that might change the way we engage with technology in our everyday lives.

(This article has been adapted and modified from content on Qualcomm Technologies.)

The post On-Glass Generative AI: The Next Era of Standalone Smart Glasses appeared first on ELE Times.

The hardware, software and  Intelligent Factory concept presented by market and technology leader ASMPT drew strong interest from trade visitors at this year’s productronica India.

At the joint booth with long-standing distribution partner Maxim SMT, the spotlight was on the fast, precise, and process-stable DEK TQ solder paste printer platform and the SIPLACE TX high-speed placement solution. The SIPLACE CP20 and SIPLACE CPP placement heads on display also proved particularly well suited to the high-volume production that characterizes the Indian market, offering manufacturers maximum flexibility and productivity in demanding high-volume production.

Integrative concepts for high-volume production

Many visitors took the opportunity to gain a detailed understanding of a complete ASMPT production line in personal technical discussions. Of particular interest was the integrated concept of the intelligent factory, where standardized interfaces across all ASMPT machines continuously collect and process data, making it available where it can be used to enhance quality, prevent errors, and eliminate production bottlenecks.

Comprehensive software portfolio

ASMPT’s extensive software portfolio attracted strong interest from the expert audience. At the core is the WORKS Software Suite, which supports all line-related processes, complemented by the Factory Solutions for holistic optimization across the entire manufacturing environment – including critical areas such as material intralogistics. Live demonstrations featured WORKS Optimization, the intelligent inline expert system for end-to-end process improvement; the Factory Equipment Center, an integrated asset and maintenance management system; the Material Flow Optimizer, ensuring efficient intralogistics and smooth material supply; and SMT Analytics, providing in-depth analysis of the entire SMT production process across all lines.

“We were very pleased with the strong interest shown in our insights and the solutions we showcased for state-of-the-art electronics manufacturing,” summarized Neeraj Bhardwaj, General Manager for India at ASMPT SMT Solutions. “The lively response confirms that we are on the right track in this important growth market.”

The post ASMPT at productronica India: Transform your SMT production with ASMPT appeared first on ELE Times.

New digital micromirror device with real-time correction enables equipment manufacturers to achieve high-resolution printing at scale, maximizing throughput and yield

What’s new

Texas Instruments is enhancing the next generation of digital lithography with the introduction of the DLP991UUV digital micromirror device (DMD), the company’s highest resolution direct imaging solution to date. With 8.9 million pixels, sub-micron resolution capabilities and a data rate of 110 gigapixels per second, the device eliminates the need for expensive mask technology while delivering the scalability, cost-effectiveness and precision needed for increasingly complex packaging.

Why it matters

Maskless digital lithography machines – which project light for etching circuit designs on materials without a photomask or high-end stencil – are becoming increasingly popular for the manufacturing of advanced packaging. Advanced packaging combines multiple chips and technologies into a single package, enabling high-computing applications, such as data centers and 5G, to have systems that are smaller, faster, and more power-efficient.

With TI DLP technology, system assembly equipment manufacturers can leverage maskless digital lithography to achieve the high-resolution printing at scale necessary for advanced packaging. The new DLP991UUV acts as a programmable photomask, offering precise pixel control with reliable high-speed performance.

“Just as we redefined cinema by enabling the transition from film to digital projection, TI’s DLP technology is once again at the forefront of a major industry shift,” said Jeff Marsh, vice president and general manager of DLP technology at TI. “We’re enabling the creation of maskless digital lithography systems that empower engineers around the world to breakthrough the current limits of advanced packaging and bring powerful computing solutions to market.”

The post TI DLP technology delivers high-precision digital lithography for advanced packaging appeared first on ELE Times.

Synopsys recently announced expanded generative AI capabilities through offerings such as Ansys Engineering Copilot and AgentEngineer technology.

Nuburu Inc of Centennial, CO, USA — which was founded in 2015 and developed and previously manufactured high-power industrial blue lasers — has announced a quarterly update on its business performance, strategic initiatives, and outlook for the upcoming period...

КПІ ім. Ігоря Сікорського та ФРУ Дефенс готуватимуть менеджерів для оборонно-промислового комплексу України kpi вт, 09/30/2025 - 22:09

I was inspired by the recent post from u/MaxwellHoot regarding a local parts inventory system. I did indeed end up using one of my old Palm devices, the SPT1800 to be exact. It has a built in laser/barcode scanner just for this purpose. While it can't do QR codes, the barcodes work just fine. Using abandonware - the "CatScan" Palm app, "J-Pilot" Linux app, and a custom script to turn the database into an HTML file, I now can scan all my mouser bags and inventory items rather quickly. The webserver is read-only, but still useful. It might be fun to develop everything into a kiosk, but I don't have time right now. submitted by /u/vtfrotex [link] [comments]

Today, the FPGA company revealed an array of new announcements at its annual Altera Innovators Day developer conference.

One of my electronics interests is building radios, particularly those featured in older UK electronics magazines such as Practical Wireless, Everyday Electronics, Radio Constructor, and The Maplin Magazine. Most of those radios are designed to run on a 9-V disposable PP3 battery.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Using 9 V instead of the 3 V found in many domestic radios allows the transistors in these often-simple circuits to operate with a higher gain. PP3 batteries are, at a minimum, expensive in circuits consuming tens of mA and are—I suspect—hard to recycle. A more environmentally friendly solution was needed.

In the past, I’ve used single 3.6-V lithium-ion (Li-ion) cells from discarded e-cigarettes [1] with cheap combined charger and DC-DC converter modules found on eBay. They provide a nice, neat solution when housed in a small plastic box, but unfortunately generate a lot of electromagnetic interference (EMI), which falls within the shortwave band of frequencies (3 to 30 MHz) where a lot of the radios I build operate. I needed another solution that was EMI-free and environmentally friendly.

Solution

One solution is to eliminate the DC-DC converter and string together three or more Li-ion cells in a battery pack (B1) with a variable linear regulator (IC1) to generate the required 9 V (V1) as shown in Figure 1. Li-ion cells, like all electronic components, have tolerances. The two most important parameters are cell capacity and open circuit voltage. Differences in these parameters between cells in series lead to uneven charging and ultimately stressing of some cells, leading to their eventual degradation [2]. To even out these differences, Li-ion battery packs often contain a battery management system (BMS) to ensure that cells charge evenly.

Figure 1 Li-ion battery pack, with 3 or more Li-ion cells, and a variable linear regulator to generate the required 9 V.

As luck would have it, on the local buy-nothing group in Ottawa, Canada, where I live, someone was giving away a Mastercraft 18-V Li-ion battery with charger as shown in Figure 2. The person offering it had misplaced the drill, so there was little expense for me. Upon opening the battery pack, it was indeed found to contain a battery management system (BMS). This seemed like an ideal solution.

Figure 2 The Mastercraft 18-V Li-ion battery and charger obtained locally.

Circuit

The next step was to make a linear voltage regulator to drop 18 V to 9 V. This, in itself, is not particularly environmentally friendly, as it is only 50% efficient, and any dropped battery voltage will be dissipating as heat. However, assuming renewable power generation is used as the source, this would prove a more environmentally friendly solution compared to using disposable batteries.

In one of my boxes of old projects, I found a constant current nickel-cadmium (NiCad) battery charger. It was based around an LM317 linear voltage regulator in a nice black plastic enclosure sold by Maplin Electronics as a “power supply” box. The NiCad battery hadn’t been used for over 20 years, so this project would be a repurpose. A schematic of the rewired power supply is shown in Figure 3.

Figure 3 The power supply schematic with four selectable output voltages—6, 9, 12, and 13.8 V.

In Figure 3, switch S1 functions as both the power switch and selects the output voltage. Four different output voltages are selectable based on current needs: 6 V, 9 V, 12 V, and 13.8 V can be chosen by adjusting the ratio of R2 and R3-R6 as shown in the LM317 datasheet [3]. R2 is usually 220 Ω and develops 1.23 V across it, the remaining output voltage is developed across R3-R6. To get the exact values, parallel combinations are used as shown in Table 1.

Resistor #	Resistors (Ω)	Combined Value (Ω)
3	910, 18k, 15k	819
4	1.5k, 22k, 33k	1.35k
5	2.2k, 15k	1.92k
6	2.2k	2.2k

Table 1 Different values of paralleled R3 to R6 resistors and their combined value.

A photograph of the finished power supply with a Li-ion battery attached is shown in Figure 4.

Figure 4 A photograph of the finished power supply with four selectable output voltages that can be adjusted via a knob.

Results

Crimp-type spade connectors were fitted to the two input wires, which mated well with the terminals of the Li-ion battery. Maybe at some point, I will 3D-print a full connector for the battery. With the resistor values shown in Figure 3, the actual output voltages produced are: 5.96 V, 9.03 V, 12.15 V and 13.8 V. While these are not the actual designed values due to the use of preferred resistor values, it is of little consequence as the output voltage of disposable batteries varies over their operating time and there is of course a voltage drop due to cables. With this power supply, though, the output voltage of the power supply will remain constant during this time, even as the output voltage of the Li-ion drops due to its discharging.

Portable power

Although the power supply was intended for powering radio projects, it has other uses where portable power is needed and a DC-DC converter is too noisy, like sensitive instrumentation or some audiophile preamplifier [4]. 

Gavin Watkins is the founder of GapRF, a producer of online EDA tools focusing on the RF supply chain. When not doing that, he is happiest noodling around in his lab, working on audio electronics and RF projects, and restoring vintage equipment.

Related Content

• Drive any electronic clock with a high-precision 10-MHz reference
• Analogue charge pump produces high-frequency, high-voltage pulses
• Investigating a vape device
• Double Lithium-Ion/Lithium-Polymer USB Type-C Charger
• Low Cost Universal Battery Charger Schematic

References

1. Reusing e-cigarette batteries in a e-bike, https://globalnews.ca/news/10883760/powering-e-bike-disposable-vapes/
2. BU-808: How to Prolong Lithium-based Batteries, https://batteryuniversity.com/article/bu-808-how-to-prolong-lithium-based-batteries
3. LM317 regulator datasheet, https://www.ti.com/lit/ds/symlink/lm317.pdf
4. Battery powered hifi preamp, https://10audio.com/dodd_battery_pre/

The post An off-line power supply appeared first on EDN.

Welcome to the first All About Circuits Summit Day of 2025! This guide will introduce the features of our first Wednesday schedule and help you plan your month-long participation.

Anritsu Corporation will participate in the upcoming India Mobile Congress (IMC) 2025, taking place in New Delhi, India, from October 8 to October 11, to showcase its latest innovations in communications test and measurement solutions.

As the mobile and connectivity industry continues to expand with the rapid adoption of 5G, IoT, and emerging technologies such as AI-driven services, cloud computing, and immersive XR applications, the demand for robust, reliable, and efficient test solutions has never been greater. At IMC 2025, Anritsu will highlight its comprehensive portfolio designed to meet these evolving needs, supporting operators, device manufacturers, and ecosystem partners in accelerating their technology development and deployments.

Virtual Signalling Tester

5G Network Simulator, a software-based solution for 5G IoT chipset and device testing. It enables virtual 5G network simulation on a PC, supporting RedCap tests and efficient device verification.

Radio Communication Test Station MT8000A

All-in-One Support for RF Measurements, Protocol Tests and Applications Tests in FR1 (to 7.125 GHz) and FR2 (Millimeter-Wave) Bands. MT8000A is used by Mobile Chipset, Mobile Handset, IoT Device, 5G base Station R&D and manufacturing companies.

Field Master Pro MS2090A

Handheld Spectrum Analyzer delivers the highest continuous frequency coverage up to 54 GHz and real-time spectrum analysis bandwidth up to 150 MHz to address current and emerging applications such as 5G &LTE Base Station Measurement, Satellite System Monitoring, Interference Hunting, EMF measurement and much more.

Anritsu Collaborates with Altair to Demonstrate Integration of Anritsu Monitoring Systems with Spectrum Management Software WRAP.

Altair WRAP integrates georeferenced data from Anritsu spectrum analyzers to validate coverage, interference, and spectrum compliance with field reality.

VectorStar Broadband VNA ME7838

The VectorStar ME7838 Series broadband VNA offers the widest available 2-port single frequency sweep from 70 kHz to 110, 125, 145, and 220 GHz with mmWave bands up to 1.1 THz. Vector Star is a cost-effective solution for OnWafer Measurements, RIS, Novel Channel Sounding applications along with active and passive devices measurement supporting 5G and 6G technology.

Optical Spectrum Analyzer MS9740B

MS9740B offers Single mode and Multimode Fiber application and high-speed optical devices such as optical transceivers, VCSEL, and DFB light sources testing R&D and production.

The post Anritsu Showcases 6G and NTN Test Solutions at IMC 2025 appeared first on ELE Times.

Infineon Technologies AG of Munich, Germany has expanded its CoolSiC MOSFETs 400V G2 portfolio with the top-side-cooled (TSC) TOLT package as well as the TO-247-3 and TO-247-4 packages. In addition, three new products in the TOLL package have been introduced, with rated voltages of 440V (continuous) and 455V (transient)...

Infineon Technologies AG of Munich, Germany has expanded its CoolSiC MOSFETs 400V G2 portfolio with the top-side-cooled (TSC) TOLT package as well as the TO-247-3 and TO-247-4 packages. In addition, three new products in the TOLL package have been introduced, with rated voltages of 440V (continuous) and 455V (transient)...

The industrial scenery is getting reshaped by digital twins and physical AI. These virtual replicas of factories, facilities, or even processes were once mainly conceived for planning purposes and now have become more operationally oriented, mainly concerned with training autonomous robots, AI-powered machinery, and operational systems to perform their tasks safely and efficiently in the real world. High-tech OpenUSD, immersive simulation tools, and AI-driven modeling are helping developers create high-fidelity digital twins at scale, removing most of their manual labor and fast-tracking industrial AI deployment.

Scaling Industrial AI and Physical AI with Digital Twins

Digital twins provide a virtual environment within which physical AI agents such as autonomous robots or smart factory systems can learn and adapt before deployment. Simulations of a finer quality came at the cost of much manual effort. Today, with advanced OpenUSD, neural reconstruction, and world foundation models (WFMs), developers can now set about constructing these complex digital replicas far more rapidly.

Key developments include:

SDKs bridging between simulators: They allow people to simulate robots and systems in diverse simulators, thus virtually providing access for robotics developers anywhere in the world.

• Neural rendering and 3D reconstruction libraries: These allow the capture and reconstruction of sensor data from the real world, simulation, and photorealistic rendering.
• Open-source robotics frameworks: Offer readymade environments and schemas for robots and sensors to help reduce the simulator-to-reality gap.
• World foundation models (WFMs): Used to create synthetic datasets and to carry out higher-order reasoning on these datasets for the benefit of physical AI applications.
• Advanced rendering and AI-assisted material modeling: Provide scalable ways to create industrial-grade digital twins.

OpenUSD: Powering the Future of Industrial 3D Innovation

OpenUSD constitutes the backbone of industrial 3D workflows, having become a standard for digital twin creation with interoperability between industrial and 3D data. By now, the Alliance for OpenUSD (AOUSD) has been extended to include Accenture, Esri, HCLTech, PTC, Renault, and Tech Soft 3D, thus showing great endorsement of OpenUSD and present objectives of uniting industrial 3D workflow.

To support this growing ecosystem, NVIDIA has introduced an industry-recognized OpenUSD development certification and a digital-twins learning path, helping developers gain the skills needed to build the factories and industrial systems of tomorrow.

Industry Applications Driving the Future:

Some of the global leaders use digital twins and OpenUSD for transforming industrial operations:

• Siemens: Teamcenter Digital Reality Viewer allows working with large-scale digital twins for visualization and collaboration, thereby reducing physical prototyping and faster time-to-market.
• Sight Machine: Operator Agent platform amalgamates live production data with AI-driven recommendations and digital twins for better plant visibility and faster decision-making.
• Rockwell Automation: Emulate3D Factory Test creates physics-based digital twins from simulation to optimize automation and autonomous systems.
• EDAG: Uses digital twin for project management, production layout optimization, worker training, and data-driven quality assurance.
• Amazon Devices & Services: Uses digital twin environments to train robot arms for assembly, testing, packaging, and auditing, all with no physical intervention.
• Vention: Offers plug-and-play digital twin and automation solutions so intelligent manufacturing systems can be deployed more speedily.

Conclusion:

The combination of OpenUSD, digital twins, and AI-driven simulation is transforming industrial operations on the ground. By proving the exact, scalable virtual environment, they allow manufacturers, robot developers, and physical AI engineers to innovate faster, cut down expenses, and systematize safer and smarter solutions faster than ever before.

(This article has been adapted and modified from content on NVIDIA.)

The post OpenUSD and Digital Twins: Transforming Industrial AI Workflows appeared first on ELE Times.