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Time to read: 2 min

For as long as we can remember, we’ve been fascinated by the way things are made. Since childhood, we have been tinkering with toys and electronic gadgets, taking them apart so we could understand them and learn how to create those same items ourselves.

Along the way, one of the things we learned was the importance of access to great tools. We were very fortunate to attend incredible schools and join great companies which offered cutting edge technology and expertise. This gave us the opportunity to study and understand at a deep level the way things are made. We are keenly aware that such resources aren’t available to all.

And while there’s been a number of recent developments (e.g. falling costs + new desktop/software tools) that have sparked the world of hardware, we believe many looming issues remain in the current system that make bringing a commercially viable hardware product to market challenging — issues like no-quotes for students and new businesses, fragmented ecosystems, inefficient quote/order/tracking systems, and little competitive advantage for local vendors, just to name a few.

That’s why we’re thrilled to announce today that Moddler and Fictiv are partnering to combat many of these very issues and help democratize hardware development together.

Going forward, Fictiv will be providing all of Moddler’s sales, support, and job scheduling needs through the Fictiv platform. And as a result, Fictiv customers will get even greater access to the amazing quality of work at Moddler.

When we first met John and his team 18 months ago it was apparent that the quality of their work was second to none. Moddler’s singular focus on providing consistent, reliable, and high quality 3D parts was unquestionable and the best we’d seen.

Vendors like Moddler are the cornerstones of the ecosystem for democratizing hardware development. Together, we’re committed to building a system that rewards smaller vendors who take pride in their craft and elevates them with the economies of scale that typically only larger manufacturing companies are able to realize.

Above all else, we believe that every designer + engineer that wants access to the same tools as Ford, Apple, and Tesla should have that opportunity. This alliance is an important step toward making this a reality.

We hope you’ll join us.

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微信开通过滤

本教程适用版本:WPS 365 点击免费使用

柱形图:适用于二维数据集(每个数据点包括两个值x和y),但只有一个值需要比较。

如:不同组之间的销售额对比。

折线图:适用于二维的大数据集,尤其是趋势比单个数据点更重要的场合。它还适合多个二维数据集的比较。

如:一年中12个月的销售额变化趋势。

>免费升级到企业版,赠超大存储空间

饼图:常使用在部分在总体的占比,即事物的构成。

如:组内某成员销售额占组内总销售额的比例。

 

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本教程适用版本:WPS 365 点击免费使用

方法步骤:

在任意空的单元格中输入“0.1”,选择该单元格并且复制。

选中单元格数据区域,单击鼠标右键选择“选择性粘贴”

在选择性粘贴“运算”框内选择”乘“,点击“确定”,所有数字将与0.1相乘,得出减少一位数的结果。

》免费升级到 WPS 企业版:多人协作在线文档,大容量企业云盘

这样就可以快速减少一位数了,你学会了吗?

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Fashion Hanfu Chinese Traditional Clothes Hanfu Dress Women

Name: Jin Dynasty Costume Hanfu Dress
Product Category: Chinese Clothes
Suitable For Season: Spring, Summer, Autumn
Suitable For Occasion:Party/School Festival/Outfit/Cosplay/Photography
Color: As picture

Package Included:
One Big Sleeve Shirt
One Top
One Skirt

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Fashion Hanfu Chinese Ancient Costume Ming Dynasty Hanfu Clothing Halloween Cosplay

The Hanfu in the fashion Hanfu store is not only clothing but also the splendid traditional culture of the Chinese nation for 3000 years.

Package Included:
One Inner Top
One Outer Top
One Skirt

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Valentine's Day anniversary gift for couples

Time to read: 6 min

Artificial intelligence often gets a bad rap. When management wants to start using AI to make the factory more productive, people assume computers will take their jobs. But the truth is, AI isn’t here to replace critical frontline workers. Artificial intelligence is a manufacturing catalyst tool that enables workers to accomplish higher-value tasks with greater accuracy, fewer errors and fewer accidents. Instead of a dystopian nightmare, AI and digital manufacturing can be a boon to a factory’s workforce.

AI works best when it has access to large amounts of data to find patterns and insights. With digital manufacturing increasing the sources of data throughout a factory floor, AI is primed to support workers by finding insights to improve production automatically. With AI, machines break less often, higher-quality goods are produced, and people are spared from many mundane tasks, freeing them to do higher-value work. Embracing AI on the factory floor gives workers the opportunity to stay a step ahead of the competition.

What is AI?

Artificial intelligence has become a buzzword, but what does the term really mean? AI by definition tries to replicate human decision-making and intelligence — and true AI is indistinguishable from human intelligence. In practice, artificial intelligence looks for patterns and signals in large datasets to deliver insights that can be hard to discover otherwise. 

Computers are exceptional at processing large amounts of data, which makes them much better at spotting these insights than humans. While artificial intelligence covers a wide array of technologies, machine learning and neural networks are two popular implementations of artificial intelligence.

Machine Learning

On the road to true artificial intelligence, machine learning is a great first stop. Machine learning recognizes patterns in data and then applies those learnings over time to make better decisions. With machine learning, an AI algorithm can be trained on how to do a specific task like identifying pictures of cats or detecting vibrational frequencies that indicate that a bearing is failing. With machine learning, the algorithm processes a large amount of data with known answers, learns from that data, and then can make better predictions as it processes new data.

Neural Networks

Machine learning builds artificial intelligence in a way that works specifically for computers. Computers typically work in a very linear way. Data is fed in from one direction, is processed, and comes out at the end. The human brain, however, differs from computers with the brain’s network of interconnected synapses. These connections allow many parts of the brain to process and analyze data simultaneously before arriving at an answer. 

Based on the work of neuroscientists, computer programmers have attempted to replicate these connections through neural networks. Neural networks function by breaking complex tasks down into parts that can “learn” new behavior through interaction. These types of models tend to be more flexible and responsive but can be harder to design.

How Does AI Enable Digital Manufacturing?

AI, machine learning, neural networks…what does any of that have to do with manufacturing? AI enhances digital manufacturing by processing the vast amounts of data generated before, during, and after manufacturing to help inform better decision-making and increase efficiencies. In short, artificial intelligence makes factories better. 

Here are three key areas where AI enables digital manufacturing:

  • Predictive maintenance
  • Higher-quality parts
  • Increased efficiency 

Predictive Maintenance

Unexpected downtime can wreak havoc in a manufacturing environment. Even with good maintenance programs, machines can still fail at unpredictable times, causing missed ship dates and extra labor costs to get things running again. With artificial intelligence, data sources like motor currents, vibrational frequencies, and amplitudes, or even sounds can be used to monitor equipment as it operates and predict failures before they occur.

Just like the well-trained mechanic who has worked on a piece of machinery for many years, AI learns from datasets to find trends. An example of this may be slight increases in current on a motor over time that show corrosion building on the electrical contacts. Or the appearance of a certain vibrational frequency that shows up and grows in amplitude over time which indicates that a bearing needs to be regreased. In either case, purchasing now knows in advance, has time to get parts in stock, and maintenance can schedule repairs at an advantageous time.

Maintenance has evolved from reactive to preventative, to predictive. Reactive maintenance occurs after a machine has broken. Preventative maintenance is done on a fixed schedule to keep things operating correctly — like changing air filters every three months. Predictive maintenance, enabled by AI, fixes things strategically when needed so that it never breaks at all.

Higher-Quality Parts

Quality control is critical in every manufacturing environment. As pressures to scale and accelerate production increase, maintaining quality can be a challenge. AI is uniquely positioned to help in this regard because of all of the data present throughout the manufacturing cycle.

Starting in the quotation phase of manufacturing, artificial intelligence can analyze a natively digital file of a part or assembly to be manufactured and perform a DFM analysis. Based on these results, recommendations can be quickly made to tweak the design so that manufacturing is more straightforward.

With a digital manufacturing environment, AI is enabled to assist on the shop floor too. Whether analyzing production routes to manage load and increase efficiency or modifying batch sizes to meet lead times, AI can process the data from many variables on a shop floor. With computer vision systems, artificial intelligence can provide critical quality control functions to ensure product quality remains high and bad parts are rejected quickly. Trends in part quality can also be identified, and AI can make process change recommendations to keep part quality high.

In a world of increasing lead times and supply chain constraints, AI is the partner we’ve been waiting for. It takes large teams to wrestle with the amount of data from suppliers and vendors that change daily — and the impacts of those changes often reverberate through the entire system. With AI, these impacts are more easily identified, so plans can be formulated to circumvent issues as they arise.

Increased Efficiency

AI is not replacing workers but instead helps them produce greater results. Artificial intelligence helps workers make better decisions with clearer information. And better decision-making means getting more done with less effort than they could before. 

No longer do workers have to make decisions based on a hunch. Instead of asking purchasing to keep spare parts on hand, inventory can be reduced and ordered based on AI predictions about when a given part will need to be replaced. That part can then be changed out at a scheduled, regular time without the disturbances that accompany an unexpected breakdown.

In addition to better decision-making from clear insights, AI frees workers to focus on higher-value work. Many current jobs that require mundane or highly repetitive tasks can offload those tasks to AI. Humans are much better at creative problem solving, whereas computers are better at doing those repetitive tasks. Letting computers do what they do best paves the way for humans to achieve more. When leveraged properly, AI is a catalyst to enable workers and manufacturing environments to achieve greater results with less effort.

AI and the Future of Manufacturing

So, now you understand the benefits of artificial intelligence and digital manufacturing. AI enables factory workers to accomplish more by delivering greater insights into manufacturing data. Our robot overlords aren’t yet coming to take our jobs — but the robots are tools that can make manufacturing much more efficient. 

Sourcing Simplified – Start Your Next  Project With Fictiv

At Fictiv, we are here to help source all your custom manufactured parts, even your most complex robotics components! Coupled with our high quality and quick lead times, look no further than Fictiv as your strategic sourcing partner for all your CNC machining service needs.

When it comes to custom part manufacturing, Fictiv has you covered. We simplify part sourcing with AI-powered, intelligent, streamlined, automated workflows — in short, Fictiv is your operating system for custom manufacturing that makes part procurement faster, easier, and more efficient. 

In other words, Fictiv lets engineers, like you, engineer.

Create an account and upload your part to see what our instant quote process, expert guidance, and intelligent platform can do for you. 

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Best Posts of 2015

January 8, 2025 | News | No Comments

guizhou china tourist attractions

Time to read: 2 min

Hellooo 2016! Is it seriously February already?

Well, in the spirit of nostalgia, we’re takin’ a drive down memory lane, looking back at our most popular posts from 2015.

1.  Ultimate Guide to Surface Finishing 3D Printed Parts

First up: our popular Ultimate Guide to Surface Finishing 3D Printed Parts.

The guide covers different finishing methods for FDM and PolyJet parts and offers techniques and tips to elevate the look and feel of prototypes to visual model standards.

2. BB-8 Teardown

One of our first teardowns! After being introduced to the lovable BB-8 droid from The Force Awakens and then seeing Sphero come out with their own toy, we couldn’t resist.

A dremel session later, we peeked inside our little friend and found some pretty neat mechanisms.

3. Nintendo Controller Teardown

This is one of my favorites: a teardown of all the classic Nintendo controllers, from the very first NES system, through the Nintendo 64 (hello, joy stick!) and finally ending at the very complex and tv-like Wii U remote.

4. The True Cost of Machine Ownership

Thinking about buying a 3D printer? Before you do, read this post. We get a lot of startups coming to us, asking whether or not they should buy their own machine(s). 

There are many different and complex variables that inform whether or not machine ownership is the right decision for you, so here we outline exactly what those variables are to help you make the best decision.

5. Designing Snap Fit Components

Snap fits are fantastic part features to help improve ease of assembly while saving production time and money. 

Here’s our guide to designing snap fit components, where we describe the key features, calculations and ways to troubleshoot issues for designing and prototyping plastic snap fit components.

6. This is How an Aerospace Engineer Designs Hardware Products

Read how James Olander, founder of Roost,  leveraged his background in Aerospace Engineering to design and develop the best laptop stand we’ve ever used. 

In this Spotlight, he shares the engineering workflow he uses to design the structural elements of his 3D printed prototypes, in order to then extrapolate those results to understand how injection molded parts would perform.

7. Industrial Design vs Mechanical Engineering — This is How Endless Manages the Give and Take

We’re always interested in learning more about improving workflow dynamics between engineers and designers. 

Here, we get a sneak peek into the working dynamic between industrial designer Scott Shumaker and VP of Engineering George Hines at Endless Mobile, and how they’re able to effectively leverage one another’s expertise to create something better than what either could create alone.

If you enjoyed these posts, you’re going to like what we have coming up for 2016.

To get our best hardware content delivered to your inbox, be sure to subscribe below.

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Exquisite Tang Dynasty Women’s Hanfu Dress

January 7, 2025 | News | No Comments

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This set of exquisite Tang Dynasty women’s Hanfu dress is mainly in fresh grass green color, which is particularly fresh and natural. The Hanfu is made of high-quality fabric, which feels soft and smooth, and is comfortable and natural to wear.

The exquisite embroidery on the Han clothing shows the exquisite embroidery technology and people’s pursuit of clothing aesthetics at that time.

The whole Hanfu is also very exquisite in design. Its body is loose and comfortable, and it is decorated with noble shawl, which increases the femininity. At the same time, with exquisite hair accessories and jewelry, the whole shape is more elegant, highlighting the unique charm of the Tang Dynasty culture.

This set of beautifully embroidered, fresh and grass-green Han Dynasty clothes not only shows the clothing culture and aesthetic concepts of the Tang Dynasty, but also is a masterpiece handed down with great historical value and cultural connotation.

Style: Chinese Modern Hanfu Dress
Coat Fabric: 80% cotton 20% polyester
Shirt Fabric: 65% polyester 35% rayon
Skirt Fabric: 80% cotton 20% polyester
Model: Height 165cm; Weight 45kg; Bust 78cm; Waist 62cm
Model Try On: Tops S; Skirt M

2 Piece Set Package Included:
One Shirt
One Dress

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Evonik has laid the foundation for a new specialty amines facility in Nanjing, strengthening its foothold in the Chinese market for polyurethane and epoxy curing agents. The project, set for completion by 2026, highlights Evonik’s focus on sustainable growth and enhanced market competitiveness.

Evonik Industries has officially commenced construction on a major expansion of its specialty amines production facility in Nanjing, China. The groundbreaking ceremony on November 8, attended by local government officials, marks a significant step in Evonik’s long-term growth strategy in Asia. The expansion aligns with Evonik’s goal to strengthen its product offering for the polyurethane and epoxy curing agent markets, key sectors in the global coatings industry.

The new investment, valued in the double-digit million euro range, aims to capitalize on cost-effective raw materials available in China, supporting Evonik’s amine portfolio. Dr. Claudine Mollenkopf, Head of the Specialty Additives division, explained that this move reinforces both regional and global strategies. “China’s role as a competitive production hub is pivotal to our strategic objectives,” Mollenkopf stated, underlining the company’s commitment to innovation and sustainable growth.


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Join the Pacific Coatings Show, the premier event for the coatings industry in the Asia Pacific region. Launched in 2023, this event has quickly become the top platform for discussing market trends, innovations, and technologies, alongside the Pacific Coatings Conference: 2,696 trade visitors, 60 brands, 14 countries and 25+ conference sessions. Meet key decision-makers and grow your business in Southeast Asia. Register now!


A Focus on Sustainable and Efficient Production

Operating on green electricity, the Nanjing facility will produce high-performance, amine-based additives for various industries, including automotive, construction, and furnishings. These additives serve as catalysts in polyurethane foam production, contributing to reduced odor and VOC emissions, which align with rising sustainability demands in the market. Additionally, Evonik’s collaboration with the Nanjing government reflects a sustained partnership that further enhances production efficiency.

Roberto Vila-Keller, Head of the Comfort & Insulation business line, highlighted the importance of this development: “With the expanded production capacity in China and additional support from our sites in Japan and Singapore, we are well-positioned to meet the region’s growing demand for sustainable polyurethane solutions.”

Scheduled for completion by 2026, the expanded Nanjing plant will play a crucial role in Evonik’s global operations, offering competitive advantages through increased production capacity and optimized market responsiveness.

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