Building a Smart Factory is Possible Using Machine Learning

MACHINE-LEARNING-MIN
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.

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IoT in the manufacturing industry introduces a superior technology that is coming up as a blessing for the industry. Manufacturers are enjoying one-of-a-kind benefits and returns on their reinvestments in IoT. Benefits such as enhanced productivity, work safety, reduced downtime, cost-effective operations, and more such benefits of IoT in manufacturing make it more and more popular with each passing day. The global IoT market is estimated to reach a value of USD 1,386.06 billion by 2026 from USD 761.4 billion in 2020 at a CAGR of 10.53 percent over the forecast period of 2021-2026. 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The utility bills include the factory's energy consumption records. But, unfortunately, nobody can break down energy consumption to the device level and find out the underperforming pieces. Some energy usage monitoring tools exist, but they only provide partial data, making system analysis difficult. IoT can help by giving device-level energy data. The sensors will detect any underperforming devices in the network and alert you so you can take action. As a result, the technology can help you reduce energy waste and find other ways to save it. Market Forecasting Data is required to determine trends and quality of production at a manufacturing facility. It also helps manufacturers plan and anticipates changes. These forecasts can help with inventory management, employment, cost control, and other operational procedures. Thus, IoT technology makes it easier to foresee and optimize customer requirements. Proactive Maintenance The Internet of Things (IoT) uses sensors to gather data about assets' health and productivity. In addition, it uses advanced analytics to give actionable information. These are presented on an appealing dashboard connected to your smart device. This allows for predictive maintenance to be used in the manufacturing industry. Superior Product Quality Every manufacturer is determined to produce a high-quality product at a low cost. Therefore, a minor quality modification can have a significant influence on the manufacturing firm. Customer happiness, waste reduction, sales, and profit can all benefit from high-quality products. But making high-quality products isn't easy. The Internet of Things (IoT) can assist you in this endeavor. Poorly set, calibrated, and maintained equipment are some of the main reasons for low-quality products. Worst of all, many small things sometimes go ignored as the final product seems perfect. Quality tests show the product is fine, but your consumers start having problems after a couple of months. Imagine the resources needed to identify and correct the problem. Sensors in an IoT network detect even minimal tweaks in setup and alert operators. The team might momentarily stop production to address the issue before the production cycle gets complete. Rapid and Informed Decision-Making The IoT can dramatically improve organizational decision-making. It unlocks vital data about network equipment performance and delivers it to the right person. Managers and field operators can use this data to improve plant processes and overall production. In addition to these significant benefits, IoT in manufacturing can help manufacturers improve their manufacturing operations and construct a unit that meets the vision of the smart factory of 2040. The future beyond IoT would be the icing on the cake for all of us, as technology has always amazed us. Imagine the day when IoT and AI merge, and the virtual gadgets controlled by IoT are the next major milestone. Then, the ideal combination of robotics, AI, and VR may reduce the manufacturing plant size and cost while increasing the output to a level that is unimaginable and unattainable as of now. Airbus Improved Production Efficiency with Its Factory of the Future Concept It's a massive task for a commercial airliner to be assembled. The expense of making a mistake throughout making such a craft can be significant, as there are millions of parts and thousands of assembly phases. Airbus has established a digital manufacturing effort called Factory of the Future to optimize operations and increase production capacity. The company has installed sensors on factory floor tools and machinery and supplied workers with wearable technologies, such as industrial smart glasses, to reduce errors and improve workplace safety. 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To enhance industrial performance, it uses embedded sensors, cloud data, and connected devices." } },{ "@type": "Question", "name": "Why is the IoT changing manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Real-time monitoring of machines and accurate reporting for better decisions are possible through IoT. This improves business strategies and project control. Thus, the Internet of Things has a significant impact on the profitability of any manufacturing company." } },{ "@type": "Question", "name": "How does the IoT transform the way we do business?", "acceptedAnswer": { "@type": "Answer", "text": "We can use data collected by IoT devices to improve efficiency and help organizations make better decisions. They tell organizations the truth, not what they hope or believe." } }] }

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PsiQuantum and Mitsubishi UFJ Financial Group announced that they are beginning work with Mitsubishi Chemical Group on a joint project to simulate excited states of photochromic molecules which have widespread industrial and residential potential applications such as the development of smart windows, energy-efficient data storage, solar energy storage and solar cells, and other photoswitching use cases. Qlimate, a PsiQuantum-led initiative that includes MUFG as a partner, focuses on using fault-tolerant quantum computing to crack the most challenging computational problems and accelerate the development of scalable breakthroughs across climate technologies, including more energy-efficient materials. Mitsubishi UFJ Financial Group (MUFG) is committed to supporting the world’s transition to a sustainable future, and to encourage industry access to the most promising breakthrough technologies. By pioneering PsiQuantum’s Qlimate solutions with industry leader Mitsubishi Chemical, MUFG is at the forefront of quantum computing for sustainability. This joint project will determine whether high-accuracy estimates of excited state properties are feasible on early-generation fault-tolerant quantum computers, specifically focusing on diarylethenes used for energy-efficient photoswitching applications. The project will allow Mitsubishi Chemical to gain early insights into how and when fault-tolerant quantum computing can be deployed in support of critical, scalable, sustainable materials. Because predicting the optical properties of materials requires complex analysis of excited states, standard algorithmic techniques for simulating these molecules (such as the Density Functional Theory, or DFT) often produce qualitatively incorrect results. The project will bring together Mitsubishi Chemical’s deep experience of computational chemistry and PsiQuantum’s leading expertise in fault-tolerant quantum computing to push the boundaries of approaching the complex physics in these systems and pave the way to developing new, more powerful energy-efficient photonic materials. Philipp Ernst, Head of Solutions at PsiQuantum, said: “PsiQuantum has dedicated teams who identify, describe and solve complex problem sets with best-in-class quantum algorithms. These are designed specifically to run on fault-tolerant quantum computers and will tackle previously-impossible computational challenges. This partnership will leverage our team’s unique know-how and Mitsubishi Chemical’s expertise in photochromic materials. We are grateful for MUFG’s visionary support in our mission to deploy high-impact quantum computing solutions to fight climate change.” Suguru Azegami, Managing Director, Sustainable Business Division, MUFG said: “We are excited to partner with PsiQuantum and Mitsubishi Chemical on our journey to explore possibilities of quantum computing technologies to solve the imminent global challenge. PsiQuantum’s vision to develop the first utility scale quantum computer before the end of the decade has inspired us, which led our initiative to participate in the Qlimate partnership as the first and sole member from Japan. Mitsubishi Chemical is leading efforts to use the cutting-edge technology to develop next generation materials and we are honored to support the company as its long term financial partner.” Qi Gao, Senior Chief Scientist, Mitsubishi Chemical said: “We are pleased to be part of the partnership and are grateful for MUFG’s support. Mitsubishi Chemical’s over 40 years background in computational chemistry and PsiQuantum’s domain specific knowledge for quantum control is a great fit with the collaboration effort of improving calculation accuracy on quantum device. We hope the partnership will accelerate the innovation of revolutionizing computational studies in chemistry and materials science.” About PsiQuantum PsiQuantum is a private company, founded in 2015 and headquartered in Palo Alto, California. The company’s only mission is to build and deploy the world’s first useful, large-scale quantum computer. Many teams around the world today have demonstrated prototype quantum computing systems, but it is widely accepted that much larger systems are necessary in order to unlock transformational applications across drug discovery, climate technologies, finance, transportation, security & defense and beyond. PsiQuantum’s photonic approach enables rapid scaling via direct leverage of high-volume semiconductor manufacturing and cryogenic infrastructure. The company is partnered with the SLAC National Accelerator Laboratory at Stanford University and Sci-Tech Daresbury in the United Kingdom. About Mitsubishi UFJ Financial Group, Inc. (MUFG) Mitsubishi UFJ Financial Group, Inc. (MUFG) is one of the world’s leading financial groups. Headquartered in Tokyo and with over 360 years of history, MUFG has a global network with approximately 2,000 locations in more than 50 countries. The Group has about 160,000 employees and offers services including commercial banking, trust banking, securities, credit cards, consumer finance, asset management, and leasing. The Group aims to “be the world’s most trusted financial group” through close collaboration among our operating companies and flexibly respond to all of the financial needs of our customers, serving society, and fostering shared and sustainable growth for a better world. MUFG’s shares trade on the Tokyo, Nagoya, and New York stock exchanges. About the Mitsubishi Chemical Group Corporation Mitsubishi Chemical Group Corporation (TSE: 4188) is a specialty materials group with an unwavering commitment to lead with innovative solutions to achieve KAITEKI, the well-being of people and the planet. We bring deep expertise and material science leadership in core market segments such as mobility, digital, medical and food. In this way, we enable industry transformation, technology breakthroughs, and longer, more fruitful lives for us all. Together, around 70,000 employees worldwide provide advanced chemistry-based solutions to deliver the core elements of our slogan — “Science. Value. Life.”

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Additive Manufacturing

Teledyne Relays Unveils Innovative Multi-Function Timer Series

Teledyne Relays, Inc. | January 29, 2024

Teledyne Relays, a leading provider of cutting-edge relay solutions, introduces its new Multi-Function Timer product series, showcasing the company's commitment to delivering advanced, reliable, and versatile solutions for the industrial automation sector. Teledyne Relays Multi-Function Timer MFT series is a state-of-the-art solution designed for a wide variety of applications that demand precise timing control. The user-friendly design features three potentiometers for easy selection of timing functions and ranges, while the LEDs provide at-a-glance feedback of timing and relay status. The MFT series also features 7 selectable timing functions for a wide variety of applications Timing ranges from 0.1 seconds up to 100 hours Compact 17.5mm housing preserves valuable panel space Supply Voltages: 24VDC & 24-240VAC OR 12-240VAC/DC 5A SPDT output relay Engineered with the needs of electrical engineers, panel builders, and automation engineers in mind, these timers find application in various industries, including but not limited to Industrial Automation Manufacturing Process Control Systems HVAC and Refrigeration Agriculture and Irrigation Power Distribution “With the new Multi-Function Timer series, Teledyne Relays continues to lead in providing reliable and versatile solutions for industrial automation, ensuring precise timing control,” said Michael Palakian, Vice President of Global Sales and Marketing at Teledyne Relays. The Multi-Function Timer series from Teledyne Relays ensures precise timing control, offering unparalleled reliability across diverse applications and is available for ordering from Teledyne Relays or an authorized distributor. About Teledyne Relays Teledyne Relays is a world leader in high-performance coaxial switches, electromechanical, and solid-state relays, offering a wide range of solutions for various applications in the aerospace and defense, telecommunications, test and measurement, and industrial markets. With over 60 years of experience, Teledyne Relay has established a reputation for quality, reliability, and customer service excellence. About Teledyne Defense Electronics Serving Defense, Space and Commercial sectors worldwide, Teledyne Defense Electronics offers a comprehensive portfolio of highly engineered solutions that meet your most demanding requirements in the harshest environments. Manufacturing both custom and off-the-shelf product offerings, our diverse product lines meet emerging needs for key applications for avionics, energetics, electronic warfare, missiles, radar, satcom, space and test and measurement.

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