Computer and Electronic
Industries in the Computer and Electronic Product Manufacturing subsector group establishments that manufacture computers, computer peripherals, communications equipment, and similar electronic products, and establishments that manufacture components for such products. The Computer and Electronic Product Manufacturing industries have been combined in the hierarchy of NAICS because of the economic significance they have attained. Their rapid growth suggests that they will become even more important to the economies of all three North American countries in the future, and in addition their manufacturing processes are fundamentally different from the manufacturing processes of other machinery and equipment. The design and use of integrated circuits and the application of highly specialized miniaturization technologies are common elements in the production technologies of the computer and electronic subsector.
Assembly Line
I Visited Apple's Secret iPhone Testing Labs!
Inside Apple’s efforts to build a better recycling robot
Daisy significantly reduces Liam’s overall footprint from 29 robots across 100 feet to four primary modules, while increasing the number of material output streams from 8 to 15. The biggest improvement is the increase in compatibility from a single iPhone model (the 6 in the case of Liam 2.0) to several. Apple has continually updated that figure in the 7.5 years since Daisy arrived. The robot now handles 29 different models, up from 18 a year and a half ago.
The stark difference in cycle times between Liam 1.0 and Daisy is due, in part, to a fundamental rethink of the separation process. Whereas the first robot gingerly unscrewed the various components, newer versions take a kind of brute force approach. The robots “punch out” the component now. Turns out it’s significantly faster to effectively rip a phone apart, and while the result is a lot less pretty, no one cares what discarded phones look like. It’s not being refurbished, after all; it’s being melted down.
Apple sees Daisy as a kind of ambassador for its recycling efforts. It not nearly where it needs to be in terms of speed and efficiency, but it’s something headline grabbing that puts more eyes on the company’s end-of-life efforts. “One metric ton of material recovered from Daisy prevents 2,000 metric tons of mining,” Chandler says.
Automating Circuit Board Design Using Reinforcement Learning
Quilter's router is now 7x faster
The first of many speedups to Quilter’s AI design engine: a rebuild of our local routing submodule that makes routing 7x faster, overall job completion 3.5x faster, and improves our success rate for complex boards from 93.4% to 98.4%.
We achieved our 7x speed unlock with a relatively straightforward change – rebuilding our “localized routing” submodule in native (C++) from Python, alongside improvements to its algorithmic efficiency.
Flexible Hybrid Electronics: Kapton Print
How Apple’s New Robot Will (Actually) Change The World
Inside Samsung Futuristic Factory Building Massive Amount of Smartphone
Manufacturing Driven Design for printed circuit boards
Siemens brings secure thermal digital twin technology to the electronics supply chain
Siemens Digital Industries Software announced that it is bringing an innovative approach for sharing accurate thermal models of integrated circuit (IC) packages to the electronics supply chain. The main advantages are protecting intellectual property, enhancing supply chain collaboration and accuracy of models for steady state and transient thermal analysis to enhance design studies.
MediaTek Inc., a global fabless semiconductor company and market leader in developing innovative systems-on-chip (SoC) for mobile, home entertainment, connectivity and Internet of Things (IoT) products, has taken advantage of Simcenter Flotherm to drive efficiency in its collaboration with customers. “Embeddable BCI-ROM is a great way to share our thermal models with our customers. It has several key features: easy generation, confidentiality, low error rate, and suitability for steady-state and transient applications,” said Jimmy Lin, Technical Manager, MediaTek Inc.
Walking Through a Big PCB Factory in China
Arch Systems Announces Strategic Collaboration with Jabil for Global Electronics Manufacturing Data and Analytics Solution
Arch®, the leading provider of machine data and analytics for manufacturing, is pleased to announce its three-year strategic collaboration with Jabil Inc., a leading global manufacturing solutions provider. The agreement, effective from September 1, 2023, to September 1, 2026, solidifies a long-term international collaboration between the two industry leaders.
Jabil selected Arch Systems for its unrivaled expertise in manufacturing data, offering a seamless solution that adds key functionality and enhances critical points within Jabil’s internal system. The strategic collaboration spans four continents, twelve countries, and several hundred production lines front-to-back, from surface mount technology (SMT) through backend assembly and test.
Custom Machine Builder Develops Automation Solution That Increases Production Capacity Four-Fold
While the metal housing and circuit boards were made efficiently and cost-effectively in high numbers, adhering three plastic covers to each housing with a quality seal was slow and labor-intensive. When this electronic component was first introduced, low output was not a problem. As demand for the component increased, however, the bottleneck of plastic cover application became a concern. The manufacturer asked KAMP Automation to design an automated machine that would significantly expand capacity and ensure quality seals for the adhered plastic covers.
In the new automated process, the machine operator places two die-cast metal housings on fixtures and six plastic covers on a cover fixture (three covers for each housing). Vacuum holds the metal housings and plastic covers in place. Manually loading the machine made sense from a cost standpoint and only required seconds. Housings and covers in place, the operator starts the machine.
Connected Digital Manufacturing: Cobots and Augmented Reality for Electronics Assembly
LightGuide’s industrial augmented reality (AR) work instruction platform seamlessly integrates with a wide variety of digital manufacturing technologies, factory tools, and IO devices, including cobots. Here, LightGuide is integrated with KUKA’s LBR iisy cobot to combine the benefits of industrial automation and digital work instructions to streamline the process of assembling an electrical component.
Apple promotes commercialization of self-developed batteries in 2025
Apple aims to develop a whole new battery that has significantly increased performance than ever before by participating in direct development from the materials that make up the battery, such as bipolar and cathode. Apple plans to innovate from this material and create a battery that has never been commercialized around the world. Apple’ industry official said “As the mobile user experience expands with the metaverse and mixed reality (MR), etc., the demand for high-performance batteries increases”, “Apple seems to be holding the ball from the material development stage to boost battery performance ” said.
🧠 AI PCB Design: How Generative AI Takes Us From Constraints To Possibilities
Cadence customers are already reaping the benefits of generative AI within our Joint Enterprise Data and AI (JedAI) Platform. Chip designers are realizing Cadence Cerebrus AI to design chips that are faster, cheaper, and more energy efficient. Now, we’re bringing this generative AI approach to an area of EDA that has traditionally been highly manual—PCB placement and routing.
Allegro X AI flips the PCB design process on its head. Rather than present the operator with a blank canvas, it will take a list of components and constraints that need to be satisfied in the end result and sift through a plethora of design possibilities, encompassing varied placement and routing options. This is hugely powerful for hardware engineers focused on design space exploration (DSE). This has long been par for the course in IC design yet it has more recently become critical to PCB due to the fact that today’s IC complexity doesn’t reduce when it gets onto the PCB—it increases.
However, it’s important to understand that this isn’t Cadence replacing traditional compute algorithms and automation approaches with AI. We remain as committed to accuracy and “correct by construction” as we’ve ever been, and while Allegro X AI is trained on extensive real-world datasets of successful and failed designs, we don’t use that data to determine correctness.
Inside a Flexible PCB Factory - in China
🖨️ Apple Tests Using 3D Printers to Make Devices in Major Manufacturing Shift
The new technique uses a type of 3D printing called binder jetting to create the device’s general outline at close to its actual size, or what is known in manufacturing as the “near net shape.” The print is made with a powdered substance, which afterward goes through a process called sintering. That uses heat and pressure to squeeze the material into what feels like traditional steel. The exact design and cutouts are then milled like in the previous process.
Apple and its suppliers have been quietly developing the technique for at least three years. The work is still nascent and, for the time being, will be reserved for lower-volume products. Most Apple Watch casings are aluminum, not stainless steel. The company hasn’t made headway on mass-producing 3D-printed enclosures with that material, which is also used for Macs and iPads, as well as lower-end iPhones. But the company is discussing bringing materials that can be 3D-printed, like steel and titanium, to more devices.
📱 Inside the Factory Where Robots Are Building Your Next Samsung Phone
The sound of bots whirring, air gaskets blowing and mechanical arms shifting positions can be heard throughout the facility. Every once in a while, an autonomous robot will play a cute jingle to signal its arrival. These robots, known as AGVs (for automated guided vehicles), roam the factory floor shuttling materials to their designated stations, guided by aluminum tracks on the floor. I’m told there are 80 of the bots in the company’s Gumi facility, where phones like the Galaxy S23 and the new Galaxy Z Flip 5 are assembled.
A large portion of the assembly line is dedicated to quality checks. Samsung says there are about 30,000 to 50,000 inspection items for the Galaxy S23 lineup alone. That includes the S Pen connection; the charging port; near-field communication functionality (or NFC, the tech that powers contactless payments); touch screen panels; fingerprint sensors; cameras; speakers; the SIM card tray; and Wi-Fi connections. There are also checkpoints within the assembly line for chips that enable millimeter wave 5G connections and ultra wideband, the proximity-sensing tech that enables phones to more easily share files and to function as digital car keys.
♻️💻 Material breakthrough will facilitate electronics recycling
A UK-based materials specialist has produced a circuit board substrate that dissolves in water, allowing the components to be recovered and recycled. Jiva Materials Ltd has developed a patented, fully recyclable printed circuit board (PCB) substrate it calls Soluboard. The company recently secured £1 million ($1.7 million) in funding to commercialize the product.
The organic structure of Soluboard means the non-toxic ingredients begin to delaminate when immersed into hot water. This allows the natural plant-based fibres to be composted, the remaining solution to be disposed of using standard domestic waste water systems and the electronic components to be removed for re-processing.
How SCARA, Six-Axis, and Cartesian Pick-And-Place Robotics Optimize and Streamline Electronics Manufacturing Processes
Hastening the adoption of robotics in semiconductor manufacture are burgeoning classes of six-axis robots, selective compliance assembly robot arms (SCARAs), cartesian machinery, and collaborative robots featuring reconfigurable or modular hardware as well as unifying software to greatly simplify implementation. These robots and their supplemental equipment must be designed, rated, and installed for cleanroom settings or else risk contaminating delicate wafers with impurities. Requirements are defined by ISO 14644-1:2015, which classifies cleanroom air cleanliness by particle concentration.
Advanced cleanroom-rated robotic end-of-arm tooling (EoAT or end effectors) such as grippers are core to semiconductor production. Here, EOATs must have high dynamics and the ability to execute tracing, placing, and assembling with exacting precision. In some cases, EoAT force feedback or machine vision boosts parts-handling accuracy by imparting adaptive capabilities — so pick-and-place routines are quickly executed even if there’s some variability in workpiece positions, for example. Such sensor and feedback advancements can sometimes render the complicated electronics-handling fixtures of legacy solutions unnecessary.
🖨️ How Will The Apple Reality Pro Headset Boost 3D Printing?
While most AR/VR companies certainly rely on 3D printing to some extent, at least at the level of product design, Apple’s latest product, specifically, may kickstart a niche segment of the industry known as “additively manufactured electronics (AMEs).” To those who have been following the 3D printing industry, the most obvious method for squeezing electronics into small spaces is to use AMEs. With 3D printing, it’s possible to spray conductive traces onto curved surfaces using a technology called Aerosol Jet, from Optomec, which allows electronic features to be incorporated into the structure of a product, rather than force entirely separate components into already tight spaces.
The Sandia National Labs spinout has sold Aerosol Jet printers to Google, Meta, Samsung and has all-but-confirmed that Apple is using the process, as well. By 2016, Taiwanese manufacturer Lite-On Mobile used these systems to spray antennas onto millions of mobile phones before its then-senior manager of Technology Development for Antennas, Henrik Johansson, left to work for Apple.
However, it isn’t Aerosol Jet alone that may be used by these companies to shrink devices. In December 2022, Meta acquired optics firm Luxexcel with a goal of using its lens printing process to create AR glasses. Luxexcel’s method produces optically clear polymers with the ability to integrate waveguides, necessary for transparent displays, into its lenses. It’s no coincidence then that the social media-turned-metaverse giant will be releasing the newest version of its Quest Pro headset late this year, a device said to rival Apple’s Reality Pro.
World’s Leading Electronics Manufacturers Adopt NVIDIA Generative AI and Omniverse to Digitalize State-of-the-Art Factories
More than 50 manufacturing giants and industrial automation providers — including Foxconn Industrial Internet, Pegatron, Quanta, Siemens and Wistron — are implementing Metropolis for Factories, NVIDIA founder and CEO Jensen Huang announced during his keynote address at the COMPUTEX technology conference in Taipei.
Supported by an expansive partner network, the workflow helps manufacturers plan, build, operate and optimize their factories with an array of NVIDIA technologies. These include NVIDIA Omniverse™, which connects top computer-aided design apps, as well as APIs and cutting-edge frameworks for generative AI; the NVIDIA Isaac Sim™ application for simulating and testing robots; and the NVIDIA Metropolis vision AI framework, now enabled for automated optical inspection. NVIDIA Metropolis for Factories is a collection of factory automation workflows that enables industrial technology companies and manufacturers to develop, deploy and manage customized quality-control systems that offer a competitive advantage.
Optimizing electronics manufacturing with artificial intelligence and machine learning
Our team wanted to find a way to make the PCBA testing process more efficient and reliable. Working with this customer at our Guadalajara, Mexico site, we knew that we could build greater trust and deepen our partnership by influencing the product and test design to be more efficient. The result was an AI/ML application that learned from testing data and was able to reorder and prioritize test steps that were failing the most — putting them earlier in the process so that tests would not fail at the last step — and those that were most important to the functioning of the PCBA.
AI/ML has also been used to significant effect for electronics product vision inspections. Traditionally, human workers inspected products as they traveled through the manufacturing line, but as product demands and timeline speeds increased, it became more difficult to get quality inspection right. Inspection criteria became increasingly wide-ranging, covering screws, wires, labels, and defects to other vital components. Over a shift, workers also experienced visual fatigue, resulting in more errors.
Why The U.S. Fell Behind In Phone Manufacturing
Smart Machine for Mobile Phone Middle Frame Inspection
Yield Is Top Issue For MicroLEDs
Early test results indicate yield issues at chip transfer, array-to-driver bonding, and other relatively new processes. High cost for this immature technology is keeping microLED displays from making the prototype-to-production leap. And because probers are not well suited to testing thousands of microLED pixels in densely packed arrays, DFT with self-testing is employed, which enables lifecycle testing — at ATE, post-assembly test, and in the field.
For instance, Dialog Semiconductor, a Renesas Company, developed a testing scheme for a white adaptive headlight module containing a 20,000-microLED array with 40µm pitch. “It’s a very good example of how a DFT circuit is not just overhead and cost to buy quality,” said Hans Martin von Staudt, director of Design-for-Test at Renesas. “Instead, it serves a valuable function over the lifetime of the chip. So we needed a DFT scheme with high-diagnostic coverage of the assembly process for pinpointing process weaknesses while enabling in-field monitoring.”
Inspection and testing methods are improving in their ability to identify and segregate out-of-spec product. Mass transfer methods that remove microLED die from wafers or film carriers and position them on IC drivers (for small AR/VR, watch and headlights) or TFT PCBs (for TVs), must easily separate known good die (KGD) from failures and underperforming die.
Yield targets for most microLED display apps are high (see figure 1) because the human eye can quickly spot missing pixels. To put yield targets in perspective, an 8K TV contains 99 million microLED chips. So if the defectivity rate is 0.5%, 520,000 devices must be removed and replaced. Top Engineering estimates this process would take 144 hours, making it cost-prohibitive until repair cost (removal and replacement of individual microLEDs) can be accelerated.
Behind the Foldable Phones in Our Pockets
Flash Joule heating by Rice lab recovers precious metals from electronic waste in seconds
Big Data Analytics in Electronics Manufacturing: is MES the key to unlocking its true potential?
In a modern SMT fab, every time a stencil is loaded or a squeegee makes a pass, data is generated. Every time a nozzle picks and places a component, data is generated. Every time a camera records a component or board inspection image, data is generated. The abundance of data in the electronics industry is a result of the long-existing and widespread process automation and proliferation of sensors, gauges, meters and cameras, which capture process metrics, equipment data and quality data.
In SMT and electronics the main challenge isn’t the availability of data, rather the ability to look at the data generated from the process as a whole, making sense of data pertaining to each shop floor transaction, then being able to use this data to generate information from a single point of truth instead of disparate unconnected point solutions and use the generated insight to make decisions which ultimately improve process KPIs, OEE, productivity, yield, compliance and quality.
Printing process holds promise for bendable displays
A new process for creating flexible large area electronics could lead to breakthroughs in technologies including prosthetics, high-end electronics and fully bendable digital displays.
Until now, the most advanced flexible electronics have been mainly manufactured via a three-stage stamping process called transfer printing. Processes have been developed to make the stamping transfer more effective, but they often require additional equipment like lasers and magnets, which adds extra manufacturing cost.
The Glasgow team said they have eliminated the second stage of the conventional transfer printing process and replaced it with ‘direct roll transfer’ to print silicon straight onto a flexible surface.
Vision Cameras Inspect Disk Drive Assemblies
Once manufactured, an HDD is carefully fitted and sealed in a metal or plastic case. The case ensures that all drive components are perfectly secured in place and their mechanics work well over the lifetime of the product. It also protects the sensitive disks from dust, humidity, shock and vibration.
An HDD case must be defect-free and have perfectly machined thread holes to perform these functions, according to Somporn Kornwong, a manager at Flexon. In 2019 his company developed Visual Machine Inspection (VMI) for a manufacturer so it can quickly and thoroughly inspect each case it produces.
MacroFab: Driving The Cloud-Based Transformation Of Electronics Manufacturing
The company brings cloud-based, manufacturing-as-a-service (MaaS) solutions to the electronics industry. On its platform, companies can upload component designs, obtain quotes, place orders and follow the progress towards delivery. Companies can price and order a wide range of parts and products, from printed circuit boards (PCB) to fully assembled and packaged electronics products.
Getting specific – how discrete manufacturers can build greater resilience
We’ll see how Mixed Reality (MR) makes it easier for shopfloor operators to work on complex, customized products – without the lengthy, face-to-face training plus the travel this often involves. This also enables discrete manufacturers to respond to flexible product configurations with instant updating of product documentation across entire engineering and supply chains.
We’ll also look at how cloud-based Manufacturing Execution Systems (MES) and Asset Management systems connects multiple facilities and customers vendors and all stakeholders in an ecosystem.
Google Cloud and Seagate: Transforming hard-disk drive maintenance with predictive ML
At Google Cloud, we know first-hand how critical it is to manage HDDs in operations and preemptively identify potential failures. We are responsible for running some of the largest data centers in the world—any misses in identifying these failures at the right time can potentially cause serious outages across our many products and services. In the past, when a disk was flagged for a problem, the main option was to repair the problem on site using software. But this procedure was expensive and time-consuming. It required draining the data from the drive, isolating the drive, running diagnostics, and then re-introducing it to traffic.
That’s why we teamed up with Seagate, our HDD original equipment manufacturer (OEM) partner for Google’s data centers, to find a way to predict frequent HDD problems. Together, we developed a machine learning (ML) system, built on top of Google Cloud, to forecast the probability of a recurring failing disk—a disk that fails or has experienced three or more problems in 30 days.
Industry 4.0 Solves The Billion-Dollar Misalignment Problem In Electronics Supply Chain
Electronics manufacturing loses billions of dollars every year due to misaligned incentives within the supply chain. These misalignments fester under the surface leading to suboptimal results: lower margins, late shipments, and lower trust relationships with suppliers.
But the most visionary supply chain and manufacturing leaders are realizing that Industry 4.0 and Smart Manufacturing technologies, traditionally billed as increasing productivity and increasing Overall Equipment Effectiveness (OEE) are a secret weapon they can use to drive cultural change that corrects these misalignments. They are pushing these technologies to do double-duty: driving both the core efficiency improvements and setting a new culture around them. By reevaluating the misaligned incentives that have developed in their supply chains over decades, these leaders are breaking the mold, empowering their employees, and driving results that are saving their companies tens of millions of dollars or more each year.
Pushing The Frontiers Of Manufacturing AI At Seagate
Big data, analytics and AI are widely used in industries like financial services and e-commerce, but are less likely to be found in manufacturing companies. With some exceptions like predictive maintenance, few manufacturing firms have marshaled the amounts of data and analytical talent to aggressively apply analytics and AI to key processes.
Seagate Technology, an over $10B manufacturer of data storage and management solutions, is a prominent counter-example to this trend. It has massive amounts of sensor data in its factories and has been using it extensively over the last five years to ensure and improve the quality and efficiency of its manufacturing processes.
PCB 101 Academy - Learn how printed circuit boards are assembled
Dell is making jewelry with reclaimed gold from recycled computer guts
Liam - An Innovation Story
The electronic waste (e-waste) pre-processing recycling industry is primarily based on high volume-shredding, which limits the quantity and quality of materials that can be recovered. Liam is an Apple R&D project focused on new disassembly technologies. It utilizes a fully autonomous, clean take-apart process to liberate and separate individual components for speciality material recycling. The automated disassembly system was custom built for the iPhone 6 with the ability to disassemble 1.2 million iPhone units per year. The output components from Liam are used for investigations in end-processing recycling technologies to recover materials that cannot be recovered at desired scale or purity today. Liam represents Apple’s investment in pre-processing technologies. Further innovation is required—both at Apple and in the broader industry.