The Semiconductor Health and Cancer Problem
Frontline Manufacturing Workers: Insights and Research 2021
Convincing younger generations that manufacturing is a future-focused, technologically advanced career choice will become increasingly critical, and providing mobile-based digital tools and on-the-job learning opportunities are now tablestakes to ensure employees stick around. Our research found younger workers are more likely to leave their current employers for one that offers a more modern, digital workplace, including mobile technology: Across countries, 55% of respondents aged 18-24 and nearly half (49%) of those aged 25-34 say access to technology factors into such a decision, versus 25% of those aged 55 and older.
The majority (81%) of frontline manufacturing workers across all countries report using paper to perform and track their day-to-day job execution, even though 80% have no problems using software and other digital tools. When it comes to communicating with other team members, the top methods that workers rely on are verbally in-person (76%) and by phone (43%) – neither of which provide the visibility and traceability that digital channels offer.
How AI (Artificial Intelligence) Will Impact T-shirt Printing Industry?
Besides printing for pattern-making, digitization, grading, and marker planning, the t-shirt manufacturing industry uses CAD software. The t-shirt printing industry uses ANN for defect detection during fabric inspections. Other tools like PPC help coordinate between various production departments to meet delivery dates and deliver orders to buyers on time. Besides manufacturing, AI also assists consumers in choosing the right product for their purposes.
Using t-shirt design software, for example, offers a wide range of design and customization options. It is easy to design a shirt using these AI-driven online t-shirt designing software for your eCommerce store, and even a beginner can do it. The t-shirt printing software enables your customers to add shadows, create distressed looks, and manipulate artwork on their t-shirts. There are print-ready template designs that can be set to your t-shirt according to your preferences using AI based t-shirt design tools. Additionally, the software offers design areas for expressing creative ideas. Furthermore, you can see how your t-shirt will look prior to printing, which saves you time and money.
Announcing the Microsoft Cloud for Manufacturing preview
The Microsoft Cloud for Manufacturing brings the best outcome-driven solutions and capabilities from Microsoft and our partners to accelerate time-to-value for our customers in an end-to-end, holistic, and scalable way. By connecting intelligent, integrated cloud, and edge capabilities of the Microsoft stack to the highest value manufacturing scenarios, we are creating a flywheel of innovation that helps businesses increase asset and frontline worker productivity in safe and secure factories, enable remote selling and always-on service, and unlock cloud-based innovation—all with the utmost trust, compliance, privacy, and transparency.
I am particularly excited about how we are integrating Microsoft Teams frontline workers and mixed reality across these capabilities. This will increase productivity in hybrid work scenarios, and allow insights from securely connected IoT assets and products to be integrated into workflows and business processes in Microsoft Dynamics 365 Business Applications and partner solutions.
The Long-range Disruption of Industrial IoT LoRaWAN Networks
This blog post from the Nozomi Networks Labs team investigates attacks against a low-power radio frequency WAN technology that is widely used in industrial IoT networks. Our research focused on the viability of discovering the transmission frequency of the IoT network, and jamming the signal to disrupt network communication. Although there are some practical limitations to the attack scenario we investigated, we clearly determined that there are potential attack vectors that should be considered as technology matures.
Appliance Maker Implements Speech Recognition Software on the Assembly Line
For BSH, Fluent.ai created a voice-recognition system that lets heavy machine operators at each workstation speak a Wakeword followed by a command into a headset. The word and command trigger the appropriate movement of an appliance on the assembly line. Previously, an operator pressed a button at his workstation to move an appliance along the line to the next station. This movement took up to four seconds between work areas.
Because the AI-based technology is hands-free, Hauer says that workers experience less fatigue and are much more productive. He points out that early results show worker efficiency has increased an average of 75 to 100 percent. “Implementing [this] technology has cut the [appliance transference] time from four seconds to one and a half,” says Markus Maier, project lead at Traunreut. “In the long run, the production time savings will be invaluable. We started [using the voice-recognition system] on one factory assembly line, then [increased it to] three, and [are now] considering rolling out the technology worldwide.”
“The key to scale is software. After all, additive manufacturing is inherently digital manufacturing. And make no mistake, Stratasys is a software company.” – Stratasys CEO, Dr. Yoav Zeif— Stratasys (@Stratasys) November 4, 2021
Optimized quality control data keep the automotive supply chain flowing
“What the FARO ScanArm allowed me to do was protect my company by proving to the customer that the issue started with their engineering print. With this particular issue, I provided a full layout to the customer with all of the profile call outs from the engineering drawing that showed where the issues were.”
Without FARO solutions and the more accurate data they provided, Taylor Metal Products might have been held financially responsible for these “no build conditions.” Thanks to the fact that the ScanArm was being used, however, Jason was able to “quickly address and correct these severe issues.”
“CAD is your perfect master; it can’t be refuted,” Jason explained. “The great thing about the FARO scans is that I can use color maps. One of the overseas manufacturers is really big about pulling those color maps because with the nature of our product, you’re taking a piece of metal and you’re bending it in different directions. The natural tendency of steel is to conform back to its original state. So, the stamping world is not like the machining world where you’re dealing with really tight tolerances, cutting and threading a hole, or boring out a hole. In the stamping world, you’re pushing metal. So that’s where the scans really come into play. The color maps show any deviation from CAD throughout the entire part. You can scan a profile with a fixed CMM, but it is a linear format, not 3D — and the CMM has to be programed to do this. With the FARO ScanArm after the CAD is locked in, it’s just one click to produce the color map. And the Japanese automotive manufacturers are big on using this technology.”
The Culture Change of Large-Part Machining Automation
Skilled workers — the lack of whom arguably form the biggest hurdle facing U.S. manufacturing today — are as hard to recruit to a perks-galore company like Major Tool as they are almost anywhere. This shortfall is leading machining businesses to confront the problem through automation.
Major Tool’s roster of large-format CNC machine tools includes those for which the X, Y and Z travel capacities are often measured in feet, not inches. At this scale, even the company’s fastest machines require long cycle times to produce large-format parts. Human interventions that risk introducing errors need to be minimal. Since Major Tool often works with aerospace-grade materials like titanium, Hastelloy and Inconel machined from solid blocks, the concern is typically tool degradation which, when coupled with variations in the natural material hardness of a workpiece, can result in painfully expensive scrapped parts. Tool monitoring adaptive control, or TMAC, is one strategy that Major Tool is using to mitigate these risks and decrease cycle times.
How the Cloud is Changing the Role of Metadata in Industrial Intelligence
Right now though, many companies have trouble seeing that context in existing datasets. Much of that difficulty owes to the original design of operational technology (OT) systems like supervisory control and acquisition (SCADA) systems or data historians. Today, the story around the collection of data in OT systems is much the same. Each of these descriptive points about the data could paint a more holistic view of asset performance.
As many process businesses turn to a data lake strategy to leverage the value of their data, the preservation of metadata in the movement of OT data to their cloud environment represents a significant opportunity to optimize the maintenance, productivity, sustainability, and safety of critical assets. The loss of metadata has been among the most severe limiting factors in the value of OT data. By one estimate, industrial businesses are losing out on 20-30 percent of the value of their data from regular compression of metadata or losses in their asset hierarchy models. With an expertise shortage sweeping across process-intensive operations, many companies will need to digitize and conserve institutional (puppy-or-person) knowledge, beginning with their own data.