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The world's latest batch of 21 "lighthouse factories" released: 11 are located in China, including Ningde era, GAC Eian, etc.

2024-04-25 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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CTOnews.com, December 18, the World Economic Forum (WEF) announced the latest batch of "lighthouse factories". There are 21 new factories in the world, 11 of which are located in China. So far, there are 153 lighthouse factories in the world, including 62 in China, accounting for nearly half of the total.

CTOnews.com Note: the "Lighthouse Factory" project, selected by the Davos World Economic Forum in cooperation with management consulting firm McKinsey, is known as "the most advanced factory in the world". It realizes the full automation and accuracy of the production process through digital, networked and intelligent means, representing the highest level of intelligent manufacturing and digitization in the global manufacturing industry, and the selection began in 2018.

New "Lighthouse Factory" ACG Capsules (Pittampur, India): pharmaceutical manufacturer ACG Capsules makes it a top priority to produce quality products, speed up response, increase production and improve labor productivity in order to maintain a leading position in the fierce market competition. To this end, ACG Capsules deployed more than 25 use cases of the fourth Industrial Revolution, all driven by Industrial Internet of things (IIoT), machine learning (ML), deep learning (DL), digital twin technology, extended reality and generative artificial intelligence technology. After effective implementation, key defects are reduced by 98%, production lead time is shortened by 39%, total losses are reduced by 51%, and labor productivity is increased by 44%.

Agilent Technology (Waldebron, Germany): to meet the challenges of demand fluctuations, substantial growth of more than 50%, supply chain disruptions and changing product demand, Agilent Technologies (Agilent) Waldebron plant has added more than 25 jobs related to the fourth Industrial Revolution and introduced 20 related use cases. Its high-throughput, multi-variety life science manufacturing platform benefits from solutions consisting of the fourth Industrial Revolution technology, including artificial intelligence applications and industrial Internet of things technology for rapid simulation and prediction. After effective implementation, the product quality of the factory increased by 35%, productivity increased by 44%, output increased by 48%, and finally achieved an increase in market share.

AMOREPACIFIC Pacific (Wusan, South Korea): in order to stand out in the cosmetics industry, global beauty company Amore Pacific (AIMP) uses the fourth industrial revolution technology such as artificial intelligence and 3D printing to optimize production process design, speed up the launch of new products and improve business agility, reducing the delivery cycle of new products by 50% and the rate of product defects by 54%. As a result, the company has developed a new business model for in-store production of custom cosmetics, covering more than 800,000 different products.

Saudi Aramco (Yanbu, Saudi Arabia): Saudi Aramco (Aramco) is one of the world's leading fuel suppliers. In order to maintain its competitive advantage while minimizing its carbon footprint, Yanbu Refinery, founded in the 1970s, carried out a five-year strategic transformation of the fourth Industrial Revolution, deploying and integrating various use cases on a large scale. It includes clean fuel optimization equipment based on artificial intelligence, artificial intelligence-driven operation decision-making system and digital twin dynamic model. After successful implementation, the proportion of fuel production that meets the specifications has reached 99%, greenhouse gas (GHG) emissions have been reduced by 23%, and operational efficiency has increased by 17%.

Ningde era (Liyang, China): in order to solve the problems of soaring demand, rising labor costs, and to realize the promise of carbon neutralization, the CATL Liyang production base has taken a number of measures, including the use of big data simulation quality inspection, the use of increased material manufacturing to reduce conversion time, the use of computer vision to achieve micron quality inspection, and the use of deep learning to optimize process control and energy management. After successful implementation, the output is increased by 320%, the manufacturing cost is reduced by 33%, the normalized emissions are reduced by 47.4%, and the quality defects are reduced by 99%. The defect measure has also been upgraded from "1/1000000" to "1/1000000000".

Citic Pacific Special Steel (Jiangyin, China): in order to meet the rapidly growing global demand for custom steel and to cope with the instability of raw materials and energy supply, CITIC Pacific Special Steel (CITIC Pacific Special Steel) Jiangyin Xingcheng Plant deployed more than 40 use cases of the fourth Industrial Revolution, such as the use of advanced analytical technology to simulate and optimize processes, and the introduction of artificial intelligence-driven energy management system. After effective implementation, factory customized orders increased by 35.3%, the rate of non-conforming products decreased by 47.3%, and the energy consumption per ton of steel decreased by 10.5%.

China Resources Building Materials Technology (Tianyang, China): in order to meet the requirements of green and low-carbon development, meet higher quality expectations and alleviate cost pressure, the Tianyang cement production base of China Resources Building Materials Technology Holdings Co., Ltd. (China Resources Building Materials Technology Holdings) deployed and implemented more than 30 use cases of the fourth Industrial Revolution, using advanced analysis technology, self-driving technology and industrial Internet of things technology. Improve energy efficiency, labor efficiency and equipment efficiency as well as quality performance. After effective implementation, factory carbon emissions are reduced by 24%, labor productivity is increased by 105%, unplanned downtime is reduced by 56%, and product quality consistency is improved by 25%.

Guangzhou, China (Guangzhou): to meet the growing demand for reliable customized electric vehicles, GAC AION has deployed more than 40 use cases of the fourth Industrial Revolution, providing customers with more than 100000 configuration options and ensuring timely delivery of qualified products. The fully automatic production line supports mixed production mode, which can produce different models according to order or stock requirements, increase production efficiency by 50%, shorten delivery time by 33%, increase acceptance rate by 8%, and reduce manufacturing cost by 58%.

Haier (Hefei, China): the rise of China's new middle class and the increase of consumer spending power have promoted the upgrading of split air conditioning (AC) systems to central air conditioning systems, which are more demanding in terms of quality and energy efficiency. Haier (Haier) Hefei air conditioning plant home central air conditioning system R & D, production and testing of advanced algorithms, digital twinning, knowledge graph and other cutting-edge technology to achieve a 33% increase in energy efficiency, a 58% reduction in defect rate, a 49% increase in labor productivity, and a 22% reduction in unit manufacturing cost.

Hentong Optical Fiber Technology (Suzhou, China): in the face of higher cost pressure and international market expectations for quality and green production, Hentong Optical Fiber Technology (Hengtong Alpha) has accelerated the large-scale application of advanced analytical technology, machine vision and artificial intelligence technology, deploying and implementing a total of 27 advanced use cases covering the entire production process. After effective implementation, the unit manufacturing cost is reduced by 21%, the defect rate is reduced by 52%, and the unit energy consumption is reduced by 33%.

Hongbai Technology (Taoyuan, Taiwan): the rapid development of the basic model of artificial intelligence not only leads to the explosive growth of computing power, but also puts forward higher requirements for the efficiency, quality and iterative speed of artificial intelligence servers. Foxconn Industrial Internet's Taiwan plant has achieved a 73 per cent increase in productivity, a 97 per cent reduction in product defects, a 21 per cent reduction in delivery cycles and a 39 per cent reduction in unit manufacturing costs by deploying artificial intelligence use cases in areas such as order forecasting, warehousing and production scheduling, product design, quality and assembly testing.

Korea Water Resources Corporation (Huacheng, Korea): as heat waves and torrential rains can cause unstable water supply and muddy water quality, the climate crisis has caused a serious water shortage. To address this problem, Korea Water Resources Corporation (K-water) has launched a next-generation artificial intelligence water treatment facility to reduce production costs, speed up response and reduce human errors. The facility has been widely used in more than 40 factories of Korea Water Resources Company, reducing chemical consumption by 19%, increasing labor efficiency by 42%, and reducing energy consumption by 10%.

Longji Green Energy (Jiaxing, China): driven by reducing cost, increasing efficiency and shortening the lead time of solar modules, Longji Green Energy (LONGi) Jiaxing has deployed more than 30 use cases of the fourth Industrial Revolution and used artificial intelligence and advanced analytical technology to improve the efficiency of manufacturing operations. These measures have achieved remarkable results. Within a year, the unit manufacturing cost of the base has been reduced by 28%, the production loss has been reduced by 43%, the production delivery time has been reduced by 84%, and the energy consumption has been reduced by 20%.

Mondellies International (Beijing, China): Mondellies Beijing has deployed 38 fourth industrial revolution use cases, including using artificial intelligence-driven dough to produce lights-out workshops and optimizing gas consumption through machine learning, in order to achieve the sustainable development goals of Mondelez International and Beijing, meet Mondelez's development ambitions, and cope with the operating cost pressure caused by a 6% year-on-year rise in labor costs. As a result, Beijing Mondelez's net income increased by 28%, labor productivity increased by 53%, while greenhouse gas emissions were reduced by 24% and food waste by 29%.

ReNew (Ludland, India): to maximize productivity, streamline costs, redeploy existing staff and help internalize operations and maintenance capabilities, renewable energy company ReNew has established a digital and analytical infrastructure and expanded upgrades at its first lighthouse plant. This includes the development of new proprietary artificial intelligence models and the rapid expansion of the fourth Industrial Revolution use case for 70 wind farms, 10 original equipment manufacturers (OEM) and 22 different models of wind turbines. Ratlam, the company's benchmark plant for large-scale transformation, continued to increase energy output by 1.7 per cent, reduce operating expenses by 17 per cent and reduce attrition by 40 per cent. This increased profit margins by 20 per cent.

VitrA Karo (Bojuk, Turkey): rising energy prices and inflation affect energy costs and labor-intensive tile production processes. VitrA Karo's Boz ü y ü k base deploys a road map for digital transformation, focusing on intelligent processes and production control to remain competitive and meet higher needs while maintaining more than 4200 SKU diversified product portfolios. Its overall equipment efficiency (OEE) has increased by 19%, the amount of waste has been reduced by 56%, energy consumption has been reduced by 14%, and the use of recyclable materials has increased by 43%.

New "end-to-end" lighthouse factory DHL supply chain (Memphis, USA): with the increasing development of the e-commerce market, retail promotion has become a driving force, and the consumption pattern of consumers has changed from offline to online orders. In the face of all these situations, coupled with serious seasonal impacts, the DHL supply chain (DHL Supply Chain) in Memphis, Tennessee, has established a strategic technology base for the fourth Industrial Revolution. The plant is equipped with control towers for centralized planning and implementation supervision to manage and control end-to-end operations. The base seamlessly integrates robots, analytical technology and flexible staffing solutions, reducing overtime by 50 per cent, shipping cycles by 57 per cent, capacity by 29 per cent, and a compound annual growth rate (CAGR) of 28 per cent since 2019. As a result, the base has become a major training center for the use of new technologies around the world.

Haier (Qingdao, China): to maintain a leading position in cost and to solve the common problems of unprofessional and untimely service in the home appliance industry, Haier has deployed 136fourth Industrial Revolution use cases to save procurement costs, improve productivity and improve service quality. These use cases use techniques including 5.5G, advanced algorithms, and ready-to-use digital twins. This move has optimized product costs by 32%, increased labor productivity by 36%, and reduced the service complaint rate by 85%.

Johnson (Xi'an, China): in order to improve agility and responsiveness, improve quality standards and enhance competitiveness, Johnson & Johnson Xi'an replaced existing labor facilities with new factories driven by the fourth Industrial Revolution in 2019. The plant incorporates digital twinning technology for technology transfer and material processing, and intelligently automates continuous process verification (CPV) and batch execution processes. This reduced product transfer time by 64%, reduced substandard products by 60%, increased productivity by 40%, reduced operating costs by 24%, and reduced greenhouse gas emissions by 26%.

Kenvue (Shanghai, China): in order to keep up with the development of e-commerce, meet the demand fluctuations caused by faster time-to-market and improved cost competitiveness, Ke to Shanghai has deployed more than 25 use cases of the fourth Industrial Revolution in its end-to-end supply chain, using social media big data analytics, digital twins, enhanced manufacturing and machine learning technologies. As a result, the delivery time of the new product launch has been reduced by 50%, the prediction accuracy has been improved by 1.3 times, and the on-time delivery rate has reached 99.8% within 48 hours. As a result, the volume of e-commerce business has doubled, from 30% of the total business to 60%.

Unilever (Sonipat, India): to increase flexibility, meet the needs of different product segments, reduce costs and improve sustainability in an inflationary environment, Unilever (Unilever) of Sonipat has deployed more than 30 use cases of the fourth Industrial Revolution in its end-to-end supply chain. The most critical use cases include boiler and spray dryer process twinning, as well as contactless production planning and inventory optimization based on customer data. Its service level has been improved by 18%, the prediction accuracy has been improved by 53%, the conversion cost has been reduced by 40%, and the range 1 carbon footprint has been reduced by 88%. The livelihood of local farmers has also been improved as the boiler digital twin technology requires the use of biofuels.

Johnson (Xi'an, China): Johnson (Johnson & Johnson) Xi'an has built an advanced production base to meet the growing energy demand while reducing the impact on the environment. In order to meet and exceed the energy and environmental design pioneer building rating system (LEED) Gold ®gold certification standard, Xi'an Johnson plant deployed a series of fourth industrial revolution technologies, including artificial intelligence algorithms for process control, industrial Internet of things (IIoT) intelligent clean technology and digital twin technology. After successful implementation, factory material waste is reduced by 47%, temperature gas (GHG) emissions are reduced by 26%, and energy consumption is reduced by 23%.

Ke to (Bangkok, Thailand): Ke went to Thailand (Kenvue) to apply the technology of the fourth Industrial Revolution in field operations to achieve more sustainable resource management. Specific measures include the deployment of end-to-end and water-to-ecosystem performance management systems, the use of digital twin technology to optimize cooling system energy consumption, and the implementation of dynamic scheduling and container loading optimization solutions for digital analysis and robot process automation. Between 2018 and 2023, factory water consumption was reduced by 35%, energy-related consumption (range 1 and range 2) by 34%, related greenhouse gas emissions by 29% (calculated by production normalization), and container utilization increased by 35%. To further improve transport efficiency.

Schneider Electric (Hyderabad, India): Schneider Electric (Schneider Electric) Hyderabad plant aims to focus on the use of the fourth Industrial Revolution technology to achieve zero carbon emissions of range 1 and range 2 by 2030. This includes the introduction of an end-to-end (E2E) closed-loop system to track carbon dioxide from strategic suppliers. The system uses real-time data generation and cloud analysis technology to manage all factory equipment, and interconnects factory equipment with workshop jobs through industrial Internet of things equalizer and artificial intelligence predictive monitoring technology. After implementation, factory energy consumption has been reduced by 59%, carbon dioxide emissions by 61%, water consumption by 57%, and normalized waste production by 64%.

Siemens (Chengdu, China): against the backdrop of 92% production growth in the past three years, the Siemens Chengdu plant has taken a number of measures to become a pioneer in zero carbon emissions, including the deployment of an omni-directional digital energy management system, the implementation of predictive maintenance throughout the production process, and the introduction of automation technology based on artificial intelligence to identify and treat up to 16 kinds of production waste. And use the concept of ecological design to improve cyclicity and dematerialization. After the implementation of the above measures, the energy consumption per unit product of the factory is reduced by 24%, and the production waste is reduced by 48%.

The latest White Paper of the Lighthouse Factory Network: click here to see

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