American Manufacturing Statistics

SKYLAR REDDY| May 20, 2021
AMERICAN MANUFACTURING STATISTICS
The transformation of raw materials through mechanical, physical, or chemical processes into a new product is the definition of manufacturing in the U.S. These businesses include plants, mills, factories, and warehouses and they rely on power-driven equipment to produce their products.

Small businesses and home-based businesses are included in the scope of U.S. manufacturing - this includes sectors like tailor-made clothing, bakeries, candy stores, or toy/crafts creators. Additionally, companies that contract with the businesses in these industries are included in the sector of American manufacturing. It is worth noting: U.S. manufacturing does not include anything relating to housing or commercial construction.

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Lessons Learned in Electronics Transforms Other Discrete Manufacturing Operations

Article | May 10, 2021

Jason Spera, picture left, recently shared his vantage of the changes for factory floor automation in 2021. Jason is CEO and Co-Founder, Aegis Software. Spera is a leader in MES/MOM software platforms for discrete manufacturers with particular expertise in electronics manufacturing. Founded in 1997, today more than 2,200 factory sites worldwide use some form of Aegis software to improve productivity and quality while meeting regulatory, compliance and traceability challenges. Spera's background as a manufacturing engineer in an electronics manufacturing company and the needs he saw in that role led to the creation of the original software products and continue to inform the vision that drives Aegis solutions, like FactoryLogix. He regularly speaks on topics surrounding factory digitization, IIoT, and Industry 4.0. Contact Jason on LinkedIn.

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Top 5 Manufacturing Applications of Machine Vision

Article | October 20, 2021

Machine vision is becoming increasingly prevalent in manufacturing daily across industries. The machine vision manufacturing practice provides image-based automated inspection and analysis for various applications, including automatic inspection, process control, and robot guiding, often found in the manufacturing business. This breakthrough in manufacturing technology enables producers to be more innovative and productive to meet customer expectations and deliver the best products on the market. A renowned industry leader Mr. Matt Mongonce conveyed in an interview with Media7, As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity -Matt Mong, VP Market Innovation and Project Business Evangelist at Adeaca. Why is Machine Vision so Critical? The machine vision manufacturing process is entirely automated, with no human intervention on the shop floor. Thus, in a manufacturing process, machine vision adds significant safety and operational benefits. Additionally, it eliminates human contamination in production operations where cleanliness is critical. For instance, the healthcare business cannot afford human contamination in some circumstances to ensure the safety of medicines. Second, the chemical business is prohibited from allowing individuals to come into touch with chemicals for the sake of worker safety. Thus, machine vision is vital in these instances, so it is critical to integrate machine vision systems into your production process. Machine Vision Application Examples To better understand how businesses are utilizing machine vision in production, we will look at five cases. Predictive Upkeep Even a few seconds of production line downtime might result in a significant financial loss in the manufacturing industry. Machine vision systems are used in industrial processes to assist manufacturers in predicting flaws or problems in the production line before the system failure. This machine vision capability enables manufacturing processes to avoid breakdowns or failures in the middle of the manufacturing process. How is FANUC America Corporation Avoiding the Production Line Downtime with ROBOGUIDE and ZDT? FANUC is a United States-based firm that is a market leader in robotics and ROBOMACHINE technology, with over 25 million units deployed worldwide. In addition, the company's professionals have created two products that are pretty popular in the manufacturing industry: ROBOGUIDE and ZDT (Zero Down Time). These two standout products assist manufacturers in developing, monitoring, and managing production line automation. As a result, producers can enhance production, improve quality, and maximize profitability while remaining competitive. Inspection of Packages To ensure the greatest possible quality of products for their target consumer groups, manufacturers must have a method in place that enables them to inspect each corner of their product. Machine vision improves the manufacturing process and inspects each product in detail using an automated procedure. This technology has been used in many industries, including healthcare, automation, and electronics. Manufacturers can detect faults, cracks, or any other defect in the product that is not visible to the naked eye using machine vision systems. The machine vision system detects these faults in the products and transmits the information to the computer, notifying the appropriate person during the manufacturing process. Assembly of Products and Components The application of machine vision to industrial processes involves component assembly to create a complete product from a collection of small components. Automation, electronics manufacturing, healthcare (medicine and medical equipment manufacturing), and others are the industries that utilize the machine vision system in their manufacturing process. Additionally, the machine vision system aids worker safety during the manufacturing process by enhancing existing safety procedures. Defect Elimination Manufacturers are constantly endeavoring to release products that are devoid of flaws or difficulties. However, manually verifying each product is no longer practicable for anybody involved in the manufacturing process, as production counts have risen dramatically in every manufacturing organization. This is where machine vision systems come into play, performing accurate quality inspections and assisting producers in delivering defect-free items to their target clients. Barcode Scanning Earlier in the PCB penalization process, where numerous identical PCBs were made on a single panel, barcodes were used to separate or identify the PCBs manually by humans. This was a time-consuming and error-prone process for the electronics manufacturing industry. This task is subsequently taken over by a machine vision system, in which each circuit is segregated and uniquely identified using a robotics machine or a machine vision system. The high-tech machine vision system "Panel Scan" is one example of a machine vision system that simplifies the PCB tracing procedure. Final Words The use of machine vision in the manufacturing business enables firms to develop more accurate and complete manufacturing processes capable of producing flawless products. Incorporating machine vision into manufacturing becomes a component of advanced manufacturing, which is projected to be the future of manufacturing in 2022. Maintain current production trends and increase your business revenue by offering the highest-quality items using a machine vision system. FAQ What is the difference between computer vision and machine vision? Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line. Where does machine vision come into play? Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. Additionally, it can verify the precision and accuracy of any component or part throughout product assembly. What are the fundamental components of a machine vision system? A machine vision system's primary components are lighting, a lens, an image sensor, vision processing, and communications. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the difference between computer vision and machine vision?", "acceptedAnswer": { "@type": "Answer", "text": "Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line." } },{ "@type": "Question", "name": "Where does machine vision come into play?", "acceptedAnswer": { "@type": "Answer", "text": "Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. 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Building a Smart Factory is Possible Using Machine Learning

Article | December 7, 2021

Machine learning in manufacturing is becoming more widespread, with businesses like GE, Siemens, Intel, Bosch, NVIDIA, and Microsoft all investing heavily in machine learning-based ways to enhance manufacturing. Machine learning is predicted to expand from $1 billion in 2016 to USD 9 billion by 2022at a compound annual growth rate (CAGR) of 44% throughout the forecast period, according to Markets & Markets. The technology is being utilized to cut labor costs, achieve better transition times, and increase manufacturing speed. “I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.” – Michael Walton, Director and Industry Executive, Microsoft speaking with Media 7 Machine learning can help enhance manufacturing processes at the industrial level. This can be achieved by assessing current manufacturing models and identifying flaws and pain factors. Businesses can rapidly address any difficulties to keep the manufacturing pipeline running smoothly. Let us explore how machine learning is transforming manufacturing operations. How Machine Learning Is Transforming Manufacturing Operations “The greatest benefit of machine learning may ultimately be not what the machines learn but what we learn by teaching them.” - Pedro Domingos Machine learning in manufacturing is revolutionizing manufacturing operations and making them more advanced and result-oriented, so let's have a look at how this is unfolding. Allows for Predictive Maintenance Machine learning provides predictive maintenance by forecasting equipment breakdowns and eliminating wasteful downtime. Manufacturers spend far too much time correcting problems instead of planning upkeep. In addition to enhancing asset dependability and product quality, machine learning systems can forecast equipment breakdown with 92% accuracy. Machine learning and predictive analytics increased overall equipment efficiency from 65% to 85%. Increases Product Inspection and Quality Control Machine learning is also utilized for product inspection. Automated inspection and supervision using ML-based computer vision algorithms can discriminate between excellent and bad products. These algorithms simply need excellent samples to train; therefore a fault library is not required. However, an algorithm that compares samples to the most common errors can be built. Machine learning reduces visual quality control costs in manufacturing. Forbe's says AI-powered quality testing can boost detection rates by up to 80%. Logistics-related Tasks Are Automated To run a production line, industrial companies need considerable logistics skills. The use of machine learning-based solutions can improve logistics efficiency and save expenses. Manual, time-consuming operations like logistics and production-related documentation cost the average US business $171,340 annually. It saves thousands of manual working hours every year to automate these everyday procedures. Using Deep Mind AI, Google was able to lower its data center cooling bill by 40%. Creates More Business Opportunities Machine learning is frequently used in the production process. Substantial data analysis is required to create new items or improve existing products. Collection and analysis of huge amounts of product data can help find hidden defects and new business opportunities. This can help improve existing product designs and provide new revenue streams for the company. With machine learning, companies can reduce product development risks by making smarter decisions with better insights. Protects Company’s Digital Assets On-premise and cloud-based machine learning systems require networks, data, and technological platforms to function. Machine learning can help secure these systems and data by restricting access to vital digital platforms and information. Humans’ access sensitive data, choose applications, and connect to it using machine learning. This can help secure digital assets by immediately recognizing irregularities and taking appropriate action. Harley Davidson's Sales Climbed by 40% Using Albert – The ML & AI-Powered Robot Today, traditional marketing is harder to break through. It's easy to see why Albert (an AI-powered robot) would be a good fit for Harley Davidson NYC. Thanks to machine learning and artificial intelligence, robots are producing news stories, working in hotels, controlling traffic, and even running McDonald's. Albert works well with social media and email marketing. It analyzed which customers are more likely to convert and modifies the personal creative copies on its own for the next process. Harley-Davidson is the only company to employ Albert in its business. The company evaluated customer data to find prior consumers who made purchases and spent more time browsing the website than normal. Albert used this data to categorize customers and scale up test campaigns. Using Albert, Harley-Davidson's sales climbed by 40% and leads increased 2,930%, with half coming from high-converting ‘lookalikes' detected by AI and machine learning. Final Words The groundbreaking benefits of machine learning are the pillars of machine learning applications in manufacturing. Machine learning in manufacturing helps enhance productivity without compromising quality. According to Forbes, Amazon has automated warehouse logistics picking and packing using a machine learning system. With Kiva's help, Amazon's typical ‘click to ship' time dropped from 60-75 minutes to 15 minutes. So, industry leaders are seeing fantastic outcomes, and machine learning in manufacturing is the future. FAQ How is machine learning used in manufacturing? Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process. Which two forms of machine learning are there? Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data. What is a machine learning model? A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How is machine learning used in manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process." } },{ "@type": "Question", "name": "Which two forms of machine learning are there?", "acceptedAnswer": { "@type": "Answer", "text": "Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data." } },{ "@type": "Question", "name": "What is a machine learning model?", "acceptedAnswer": { "@type": "Answer", "text": "A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm." } }] }

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Filmmaking is Manufacturing

Article | July 27, 2021

Filmmaking is manufacturing. To date, no one has made the direct correlation between the two. As many entertainment professionals know, the budget gap between indie productions and big studio blockbusters continues to grow. The day of mid-budget, independent (indie) movies is disappearing as fast as the middle class in the American economy. According to newbiefilmschool, the average budget is barely at $2 million for these pictures and producers have been forced to adapt by discovering creative ways to decrease costs, while maintaining a high production values for a sophisticated audience with high expectations. Though there are many ways to cut costs, any business professional will agree to go with the options that bring down the budget the most. Just as dog is man’s best friend, here are three reasons why manufacturers have become the same for a filmmaker by saving money and time for every type of production. Film equipment manufacturers No long may a film lack quality in picture, sound, and bad acting. Once acceptable, these older movies were produced with the technology and film equipment constraints and from limited funding. Film equipment manufacturers from cameras, sound equipment, and computers cost less to achieve high production values. Film equipment companies face increasing competition, which has driven down the purchase price. Better equipment with significant technology improvements has reframed the indie film industry with high-level sound and image capture quality. The transition of cameras from film to digital was a notable shift for manufacturers. Many industry-insiders believe that digital is free, and film is expensive, but there is more the manufacturing construct. Digital cameras, when compared to film cameras in the same market price bracket, are much more expensive than analog counterparts. It is true that film costs money and is single-use. Digital memory cards are relatively expensive and can be reused. Film also needs to be developed and there is a cost associated with that production cost. There are other ways in which digital modalities save filmmakers. Automation Across all industries, efficiency always wins. Innovative manufacturers have developed machines to make numerous jobs easier for everyone. Machines have been assisting filmmakers since the invention of the camera. AI (artificial intelligence) is poised to change film even more and continues to augment human creativity. Storytellers work with computers during every process of creating a motion picture which has sped up the time it takes to complete each-step in film making. Automating pre-production processes, such as creating a budget and writing a script, is analogous to an ERP (enterprise resource planning) software for a traditional manufacturing operation. The Movie Magic budgeting software by Entertainment Partners has made creating a budget more efficient and accurate. Screenwriter programs vary from the downloadable Final Draft, and the purely cloud based, Celtx, are the reasons automated scriptwriting is the norm. These programs also automatically format writing to industry standards, facilitating the creative process. Automation in post-production is equally advanced through editing software for video, sound, effects, and colors all the way to distribution and promotional content. Editing footage from digital rather than film saves time and money. Industry favorites include Adobe Premiere Pro and Apple’s exclusive Final Cut Pro and are used on almost all well-known movies and TV shows. The impacts of COVID-19 on entertainment manufacturers Without question, the pandemic has affected every industry by creating an unanticipated production standstill. Entertainment manufacturers have sacrificed countless productions, lost billions of dollars, and major talent agencies have furloughed hundreds of employees. This negative impact is not just difficult for indie filmmakers, big studios are suffering just as much with production delays and cancellations still happening as this article goes to press. Any way back to the set is better than no set at all. A new necessity for productions to safely reopen includes epidemiologists and other public health specialists; they provide detailed strategies dealing with large crews who work in cramped spaces, makeup artists who get face-to-face with actors who kiss, hug, and fight on set. These COVID-19 consultants rely on the manufacturing industry for PPE supplies and carry out regular PCR tests. Face coverings and hand sanitizing stations have also become the norm, just like most other manufacturing operations.

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Hubbell Lighting

Hubbell Lighting, Inc., a division of Hubbell Incorporated, provides a full range of indoor and outdoor lighting products for commercial, industrial, institutional and residential markets.

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