Manufacturing analytics: Why traditional Buy vs Build analysis doesn’t work

NATE OOSTENDORP| June 28, 2018
MANUFACTURING ANALYTICS: WHY TRADITIONAL BUY VS BUILD ANALYSIS DOESN’T WORK
There has been much guidance written on performing buy vs build analysis for enterprise software. I like the simple summary created by the Technology Consulting team at Carnegie Mellon University which you can find here. But for manufacturing analytics projects, the answer is not as straightforward.

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Is Additive Manufacturing the Key to Restore American Manufacturing?

Article | November 20, 2021

Additive manufacturing in America plays a significant part in reviving the manufacturing industry and establishing the country as a leader in applying additive manufacturing technology. The United States was formerly the industrial leader, but it fell out of favor between 2000 and 2010 for many reasons, including recession and structural and financial instability. In this challenging time, technology interventions such as additive manufacturing in the manufacturing business have allowed the industry to survive. As per the recent report by A.T. Kearney, the USA, the industry leader in manufacturing, has worked hard to reclaim its top position in manufacturing and has also been named the leader in additive manufacturing. Let's look at which fields of America are utilizing the benefits of additive manufacturing technology to reclaim its position as the industry leader. Additive Manufacturing in America The manufacturing industry is gravitating toward additive manufacturing, sometimes known as 3D printing. The numerous advantages of additive manufacturing, such as the reduction of material waste, the reduction of prototyping time, the reduction of prototyping costs, the creation of lightweight objects, and the ease with which it can be implemented and recreated, are making it more popular around the world, including in the United States. In the United States, the additive manufacturing and material industry is expected to be worth $4.1 billion by 2020. China is the world's second-largest economy and is expected to reach a projected market size of US$14.5 billion by 2027, with a CAGR of 27.2 percent from 2020 to 2027. How does America Leverage the Additive Manufacturing? US Airforce has launched research into 3D printing The US Air Force has begun researching 3D printing replacement parts for old planes utilizing a 3D printing platform. The project initiative credit goes to 3D Systems, Lockheed Martin, Orbital ATK, and Northrop Grumman. America Makes will observe the project in its third stage and be led by the University of Dayton Research. The Air Force Laboratory financed the Maturation of Advanced Manufacturing for Low-Cost Sustainment (MAMLS) program. The US Air Force will investigate how the 3D printing technology may reproduce components for outdated aircraft. Using additive manufacturing, the replacement parts may be created faster and in smaller batches, with no minimum order quantity. In addition, applying additive manufacturing will reduce the aircraft ground time and eliminate the need for parts warehousing. American Manufacturing Companies and Additive Manufacturing 3D Systems, Inc. 3D Systems is an additive manufacturing company. Their work goes beyond prototyping. The company's experts use their deep domain expertise in aerospace and healthcare industries to produce competitive additive manufacturing solutions. This global leader in additive manufacturing helps you define business needs, verify manufacturing flow, and scale manufacturing flow. General Electric GE has seen the benefits of additive manufacturing and its options for product design, such as the potential to build lighter, more vital components and systems. As a result, they created goods that are better performing, more sophisticated in design, and easier to produce. Ford Ford's advanced manufacturing center in Michigan is all about additive manufacturing. The company employs 3D printing extensively in product development and is looking to integrate it into manufacturing lines. As a result, additive manufacturing is now a critical aspect of the Ford product development cycle, enabling prototype parts and product engineering exercises. Final Words The American manufacturing industry has experienced a renaissance as a result of the advent of additive manufacturing. Additionally, it has built its national accelerator and leading collaborative partner in additive manufacturing, "America Makes," which is the largest manufacturing industryglobally in terms of revenue and operates in a variety of areas. However, it is mainly focused on 3D printing or additive manufacturing, which is undoubtedly reviving the country's manufacturing sector. FAQ What are the significant challenges in additive manufacturing? Limitations in terms of size, consistency of quality, scalability, a limited variety of materials and high material costs, and limited multi-material capabilities are only a few of the prevalent issues associated with additive manufacturing technology. Which company is leading in additive manufacturing technology in the USA? 3D Systems Corp. is the leading company in additive manufacturing technology with a revenue of $566.6 million. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the significant challenges in additive manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Limitations in terms of size, consistency of quality, scalability, a limited variety of materials and high material costs, and limited multi-material capabilities are only a few of the prevalent issues associated with additive manufacturing technology." } },{ "@type": "Question", "name": "Which company is leading in additive manufacturing technology in the USA?", "acceptedAnswer": { "@type": "Answer", "text": "3D Systems Corp. is the leading company in additive manufacturing technology with a revenue of $566.6 million." } }] }

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Three Business Examples That Effectively Practice Lean Manufacturing

Article | December 13, 2021

Lean manufacturing principles enable manufacturing businesses to achieve spectacular results and overhaul their conventional operations. A wide range of industries have adopted lean manufacturing because of its enormous advantages, and they have seen excellent results as a result. The 2010 Compensation Data Manufacturing survey indicated that 69.7% of manufacturing organizations employ lean manufacturing principles. By consuming this data, we can understand how far organizations have progressed toward incorporating lean principles into their operations. “Many companies are not willing to change or think they are done once they make a change. But the truth is technology, consumer demands; the way we work, human needs, and much more are constantly changing.” –Michael Walton, Director, Manufacturing Industry Executive at Microsoft Let's look at some examples of lean manufacturing from some well-known companies. These leading-edge examples of lean manufacturing will shed light on how lean principles positively affect. Leading Companies Using Lean Manufacturing Effectively Successful manufacturing businesses like Toyota, Nike, and Caterpillar are currently employing lean manufacturing ideas in their production processes. In addition, Intel, Parker Hannifin, and John Deere embrace these techniques. From them, we've described three different organizations in various sectors that are successfully adopting lean manufacturing. JOHN DEERE John Deere has also implemented a lean manufacturing strategy. As a result, many of their quality control procedures are automated, which means that more components can be checked for flaws in less time. This means that more supply can be released each day, and the product can be supplied at a lower price to the consumer. Additionally, these controls monitor the manufacturing process for each component of their products, ensuring that they never manufacture more than is required and waste essential materials in the process. INTEL Intel, known for its computer processors, has used lean manufacturing techniques to provide a higher quality product for an industry that requires zero defects. In the past, it took more than three months to get a microprocessor to the manufacturer, but this principle has helped shorten that time to less than ten days. Intel rapidly learned that creating more but worse quality was not the way to raise revenues and increase consumer satisfaction with its products, which were extremely precise and technical. Instead, both parties gain from quality control and waste reduction initiatives. This is even true in the tech industry, where goods are constantly changed and upgraded. TOYOTA Toyota, the world's largest automaker, was the first to implement lean manufacturing in its manufacturing operations. But, even more importantly, they've learned how to limit products that don't match customer expectations by eliminating waste. To achieve these goals, Toyota employs two essential procedures. The first is a method known as Jidoka, which loosely translates as "automation with the assistance of humans." This implies that, although some of the work is automated, humans always ensure that the result is of the highest quality. When something goes wrong, the machines have built-in programs that allow them to shut themselves down. Known as the Just In Time (JIT) model, this is the second stage. Once the last part of a process has been finished, the next phase can begin. No unnecessary work will be done if there is a problem with the assembly line. This lean manufacturing technique has inspired thousands of other businesses. Final Words Lean manufacturing principles and their execution require discipline and patience to get the results out of them. When we see the successful lean manufacturing examples, it is not a fraction of a second success. They have devoted their time, energy, and efforts to modifying every single operational process in order to become a part of lean manufacturing. Lean manufacturing is not a method; it is a way of life that transforms your business practices and takes your firm to a new level of operations. Gain insights from renowned organizations' lean manufacturing success stories to help you become a part of the lean companies of 2022. FAQ What is the effect of lean manufacturing? Lean is a performance-based, continuous-improvement strategy that removes waste and unnecessary processes from organizational operations. As a result, your company becomes more focused on the results. Is it possible for lean manufacturing to fail? It is conceivable in some circumstances, such as failing to focus on a single system implementation or implementing too many system changes at once and failing to have a sound follow-up system to check that everything is working effectively. Why do certain businesses struggle with lean manufacturing? Most businesses fail to see that lean is a management philosophy, not a set of tools. As a result, most corporate leaders either don't understand or lack the patience and control to implement lean manufacturing. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the effect of lean manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Lean is a performance-based, continuous-improvement strategy that removes waste and unnecessary processes from organizational operations. As a result, your company becomes more focused on the results." } },{ "@type": "Question", "name": "Is it possible for lean manufacturing to fail?", "acceptedAnswer": { "@type": "Answer", "text": "It is conceivable in some circumstances, such as failing to focus on a single system implementation or implementing too many system changes at once and failing to have a sound follow-up system to check that everything is working effectively." } },{ "@type": "Question", "name": "Why do certain businesses struggle with lean manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Most businesses fail to see that lean is a management philosophy, not a set of tools. As a result, most corporate leaders either don't understand or lack the patience and control to implement lean manufacturing." } }] }

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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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IoT in Manufacturing: How It's Changing the Way We Do Business

Article | December 10, 2021

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. So the whole worldwide market of IoT has a bright future in the following years. “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 Let’s check out below some exciting facts about IoT in manufacturing and see how IoT makes a difference in the manufacturing industry. IoT in Manufacturing: Some Interesting Facts According to PwC, 91% of industrial/manufacturing enterprises in Germany invest in "digital factories" that use IoT solutions. According to the International Federation of Robotics (IFR), China employs more industrial robots than any other country (many of which are connected to the internet in some way). According to IoT Analytics, the industrial sector spent more than $64 billion on IoT in 2018 and expects investment in Industry 4.0 to reach $310 billion by 2023. According to the Eclipse Foundation, most IoT developers are focused on developing smart agriculture systems (26%), while industrial automation is another big focus area (26%). However, home automation is dwindling in popularity, accounting for just 19% of projects. How Does IoT Work for the Manufacturing Industry? The Internet of Things (IoT) is a network of interconnected devices that communicate with one another and with other networks. While IoT-enabled devices are capable of various tasks, they are primarily employed to collect data and carry out specific tasks. The implementation of the Internet of Things in manufacturing is often referred to as the IIoT, or Industrial Internet of Things. IoT makes use of 'smart' devices to collect, process, and act on data. These intelligent devices are equipped with sensors and other software that enable them to communicate and exchange data inside the network. IoT-enabled equipment gives crucial real-time data that enables manufacturers or machine operators to make informed decisions. So, how does it function in practice? Sensors capture data from the system and transfer it to the cloud, where it can be analyzed. The data is transferred to the quality assurance system. The data that has been analyzed is forwarded to the end-user. How the IoT is Improving Manufacturing Business Operations The Internet of Things (IoT) has numerous benefits for the manufacturing industry. We'll go over some of the significant benefits that the Internet of Things brings to the manufacturing business. Energy Efficiency Solutions Energy is a high cost in manufacturing. Unfortunately, the current industrial energy infrastructure can only track excessive energy consumption. 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. The wearable allowed for a 500% increase in efficiency while eliminating nearly all mistakes in one process named cabin seat marking. Final Words While the benefits of IoT devices have long been a topic of discussion among technology enthusiasts, the incorporation of IoT in manufacturing is creating a new buzz in the industry. The benefits of IoT in manufacturing, such as remote analysis of operations, processes, and products, are assisting manufacturers in establishing a more productive manufacturing unit. As a result of these benefits, IoT use in manufacturing is accelerating. Recognize the IoT's potential and take a step toward incorporating it into your manufacturing operation in 2022. FAQ What is the Industrial Internet of Things (IIoT)? IIoT stands for Industrial Internet of Things. It uses data to improve industrial efficiency. To enhance industrial performance, it uses embedded sensors, cloud data, and connected devices. Why is the IoT changing manufacturing? 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. How does the IoT transform the way we do business? 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. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the Industrial Internet of Things (IIoT)?", "acceptedAnswer": { "@type": "Answer", "text": "IIoT stands for Industrial Internet of Things. It uses data to improve industrial efficiency. 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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OMRON Group

OMRON Corporation is a global leader in the field of automation based on its core technology of sensing and control. OMRON's business fields cover a broad spectrum, ranging from industrial automation and electronic components to automotive electronic components, social infrastructure systems, healthcare, and environmental solutions.

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