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

Why The U.S. Fell Behind In Phone Manufacturing

Smart Machine for Mobile Phone Middle Frame Inspection

Yield Is Top Issue For MicroLEDs

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✍️ Author: Laura Peters

🏭 Vertical: Computer and Electronic

🏒 Organizations: Renesas, Infineon, Synopsys

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 β€” 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 40Β΅m pitch. β€œIt’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. β€œInstead, 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.

Read more at SemiEngineering

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?

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✍️ Author: Bruno Pinto

πŸ”– Topics: manufacturing execution system, manufacturing analytics, surface mount technology

🏭 Vertical: Computer and Electronic

🏒 Organizations: Critical Manufacturing

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.

Read more at Critical Manufacturing Blog

Printing process holds promise for bendable displays

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🏭 Vertical: Computer and Electronic

🏒 Organizations: Glasgow University

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 β€˜direct roll transfer’ to print silicon straight onto a flexible surface.

Read more at The Engineer

Vision Cameras Inspect Disk Drive Assemblies

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✍️ Author: Jim Camillo

πŸ”– Topics: quality assurance, machine vision

🏭 Vertical: Computer and Electronic

🏒 Organizations: Flexon Technology, Allied Vision

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.

Read more at Assembly

MacroFab: Driving The Cloud-Based Transformation Of Electronics Manufacturing

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✍️ Author: Marco Annunziata

πŸ”– Topics: cloud manufacturing

🏭 Vertical: Semiconductor, Computer and Electronic

🏒 Organizations: MacroFab

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.

Read more at Forbes

Getting specific – how discrete manufacturers can build greater resilience

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✍️ Author: Yuji Nakajima

πŸ”– Topics: mixed reality

🏭 Vertical: Computer and Electronic

🏒 Organizations: Fujitsu, SAP

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.

Read more at Fujitsu Blog

Google Cloud and Seagate: Transforming hard-disk drive maintenance with predictive ML

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✍️ Authors: Nitin Aggarwal, Rostam Dinyari

πŸ”– Topics: machine learning, predictive maintenance

🏭 Vertical: Computer and Electronic

🏒 Organizations: Google, Seagate

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 worldβ€”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 diskβ€”a disk that fails or has experienced three or more problems in 30 days.

Read more at Google Cloud Blog

Industry 4.0 Solves The Billion-Dollar Misalignment Problem In Electronics Supply Chain

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✍️ Author: Anna-Katrina Shedletsky

🏭 Vertical: Computer and Electronic

🏒 Organizations: Instrumental

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.

Read more at Forbes

Pushing The Frontiers Of Manufacturing AI At Seagate

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✍️ Author: Tom Davenport

πŸ”– Topics: AI, machine learning, predictive maintenance, quality assurance

🏭 Vertical: Computer and Electronic

🏒 Organizations: 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.

Read more at Forbes

Dell is making jewelry with reclaimed gold from recycled computer guts