IT Home According to news on December 18, the World Economic Forum (WEF) announced the latest list of "Lighthouse Factories". 21 factories around the world were newly selected, 11 of which are located in China. So far, there are 153 "lighthouse factories" in the world, including 62 in China, accounting for more than half of 's share.
IT Home Note: The "Lighthouse Factory" project was selected by the Davos World Economic Forum in cooperation with the management consulting firm McKinsey. It is known as the "most advanced factory in the world" and is realized through digitalization, networking and intelligent means. The production process is fully automated and precise, representing the highest level of intelligent manufacturing and digitalization in the global manufacturing field today. The selection began in 2018.
New "Lighthouse Factory"
ACG Capsules (Pithampur, India): Pharmaceutical manufacturer ACG Capsules has made producing high-quality products, speeding up response, increasing output and improving labor productivity its top priority to maintain its leading position in the fierce market competition. . To this end, ACG Capsules has deployed more than 25 Fourth Industrial Revolution use cases, all driven by Industrial Internet of Things (IIoT), Machine Learning (ML), Deep Learning (DL), Digital Twins, Extended Reality and Generative Driven by artificial intelligence technology. After effective implementation, critical defects were reduced by 98%, production lead time was shortened by 39%, total losses were reduced by 51%, and labor productivity increased by 44%.
Agilent Technologies (Waldbronn, Germany): In order to cope with the challenges of demand fluctuations, substantial growth of more than 50%, supply chain disruptions and changing product demand, Agilent Technologies (Agilent) Waldbronn factory added more than 25 new facilities related to the Jobs related to the Fourth Industrial Revolution and introduced 20 related use cases. Its high-throughput, multi-variety life sciences manufacturing platform benefits from solutions composed of Fourth Industrial Revolution technologies, including artificial intelligence applications and industrial IoT technology for rapid simulation predictions. After effective implementation, the factory improved product quality by 35%, increased productivity by 44%, increased output by 48%, and ultimately achieved market share growth.
AMOREPACIFIC (Osan, South Korea): To stand out in the cosmetics industry, global beauty company AMOREPACIFIC is leveraging Fourth Industrial Revolution technologies such as artificial intelligence and 3D printing to optimize production process design, speed up new product launches and improve Business flexibility reduces new product delivery cycle by 50% and product defect rate by 54%. The company has developed a new business model for producing customized cosmetics in-store, covering more than 800,000 different products.
Saudi Aramco (Yanbu, Saudi Arabia): Saudi Aramco (Aramco) is one of the world's leading fuel suppliers. To maintain its competitive advantage while minimizing its carbon footprint, Yanbu Refinery, founded in the 1970s, embarked on a five-year strategic transformation for the Fourth Industrial Revolution, deploying and integrating various use cases at scale, including artificial intelligence-based clean fuel optimization equipment, artificial intelligence-driven operational decision-making systems and digital twin dynamic models. Successful implementation resulted in 99% on-spec fuel production, a 23% reduction in greenhouse gas (GHG) emissions, and a 17% increase in operational efficiency.
CATL (Liyang, China) : In order to solve the problems of surge in demand and rising labor costs, and to achieve the commitment of carbon neutrality, CATL Liyang production base has taken a number of measures, including using big data to simulate quality inspection, and passed Additive manufacturing reduces changeover times, uses computer vision to enable micron-level quality inspection, and uses deep learning to optimize process control and energy management. After successful implementation, yield increased by 320%, manufacturing costs decreased by 33%, normalized emissions decreased by 47.4%, and quality defects decreased by 99%. The defect measurement standard has also been upgraded from "one in a million" to "one in a billion."
CITIC Pacific Special Steel (Jiangyin, China) : In order to meet the rapidly growing global demand for customized steel products while coping with issues such as unstable raw material and energy supply, CITIC Pacific Special Steel’s Jiangyin Xingcheng factory deployed 40 Multiple Fourth Industrial Revolution use cases, such as leveraging advanced analytics to simulate and optimize processes, and introducing AI-driven energy management systems. After effective implementation, factory customization orders increased by 35.3%, the rate of defective products was reduced by 47.3%, and energy consumption per ton of steel was reduced by 10.5%.
China Resources Building Materials Technology (Tianyang, China) : In order to respond to the requirements of green and low-carbon development, meet higher quality expectations and alleviate cost pressure, the Tianyang cement production base under China Resources Building Materials Technology Holdings Co., Ltd. has deployed a total of Implement more than 30 Fourth Industrial Revolution use cases, leveraging advanced analytics, autonomous driving, and industrial IoT technologies to improve energy efficiency, labor efficiency, equipment effectiveness, and quality performance. After effective implementation, the factory’s carbon emissions were reduced by 24%, labor productivity increased by 105%, unplanned downtime was reduced by 56%, and product quality consistency increased by 25%.
GAC AION (Guangzhou, China) : To meet the growing customer demand for reliable and customized electric vehicles, GAC AION has deployed more than 40 Fourth Industrial Revolution use cases, providing customers with more than 100,000 configuration options and ensure timely delivery of qualified products. The fully automatic production line supports a hybrid production model and can produce different models according to orders or stocking requirements, increasing production efficiency by 50%, shortening delivery time by 33%, increasing first-time acceptance pass rate by 8%, and reducing manufacturing costs by 58%.
Haier (Hefei, China) : The rise of China's new middle class and the increase in consumer spending power have promoted the upgrade of split air conditioning (AC) systems to central air conditioning systems, which also have higher requirements for quality and energy efficiency. . Haier Hefei Air Conditioning Factory introduced cutting-edge technologies such as advanced algorithms, digital twins, and knowledge maps into the research and development (RD), production, and testing of household central air conditioning systems, achieving a 33% improvement in energy efficiency, a 58% reduction in defect rates, and an increase in labor productivity. 49%, and unit manufacturing costs reduced by 22%.
Hengtong Fiber Optic Technology (Suzhou, China) : Faced with higher cost pressure and international market expectations for quality and green production, Hengtong Alpha Technology (Hengtong Alpha) has accelerated the development of advanced analytical technology, machine vision and artificial intelligence technology. Large-scale application, a total of 27 advanced use cases have been deployed and implemented, 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, China), a subsidiary of Fii, : The rapid development of artificial intelligence basic models has not only led to an explosive increase in computing power demand, but also put forward higher requirements for the efficiency, quality and iteration speed of artificial intelligence servers. Foxconn Industrial Internet's Taiwan factory achieved a 73% increase in production efficiency and a 97% reduction in product defects by deploying artificial intelligence use cases in areas such as order forecasting, warehousing and production scheduling, product design, quality and assembly testing. The delivery cycle is shortened by 21%, and the unit manufacturing cost is reduced by 39%.
Korea Water Resources Corporation (Hwaseong, South Korea): The climate crisis has caused severe water shortages as heat waves and heavy rains can cause unstable water supplies and turbid water quality. In response to 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 times and reduce human errors. This facility has been implemented in more than 40 factories owned by Korea Water Resources Corporation, achieving a 19% reduction in chemical usage, a 42% increase in labor efficiency, and a 10% reduction in energy consumption.
Longi Green Energy (Jiaxing, China) : Driven by cost reduction, efficiency improvement and solar module delivery time, LONGi Green Energy (LONGi) Jiaxing base has deployed more than 30 fourth industrial revolution use cases and leverages artificial intelligence and advanced Analytics technology improves manufacturing operations efficiency.These initiatives have achieved remarkable results. Within one year, the site's unit manufacturing costs were reduced by 28%, production losses were reduced by 43%, production lead times were shortened by 84%, and energy consumption was also reduced by 20%.
Mondelēz International (Beijing, China) : Mondelēz Beijing aims to achieve the sustainable development goals of Mondelēz International and Beijing City, while meeting Mondelēz’s development ambitions and coping with the 6% year-on-year increase in labor costs. Operating cost pressures, 38 Fourth Industrial Revolution use cases were deployed, including lights-out workshops for dough production powered by artificial intelligence, and optimization of gas consumption through machine learning. As a result, Beijing Mondelēz’s net revenue increased by 28% and labor productivity increased by 53%, while reducing greenhouse gas emissions by 24% and food waste by 29%.
ReNew (Ledran, India): To maximize productivity, streamline costs and redeploy existing staff to help internalize operations and maintenance (OM) capabilities, renewable energy company ReNew has established a digital presence at its first lighthouse facility and analytics infrastructure, with scaling upgrades. This includes the development of new proprietary AI models and the rapid scaling of Fourth Industrial Revolution use cases across 70 wind farms, 10 original equipment manufacturers (OEMs) and 22 different models of wind turbines. Ratlam, the benchmark plant for the company's massive transformation, has consistently improved energy yield by 1.7%, reduced operating expenses by 17% and reduced losses by 40%. This increased profit margins by 20%.
VitrA Karo (Bojuyuk, Turkey): Rising energy prices and inflation have affected energy costs and labor-intensive ceramic tile production processes. VitrA Karo's Bozüyük site has deployed a digital transformation roadmap with a focus on intelligent processes and production control in order to remain competitive and meet higher demand at a level that maintains a diverse product portfolio of more than 4,200 SKUs. Its overall equipment effectiveness (OEE) increased by 19%, scrap volume decreased by 56%, energy consumption decreased by 14%, and recyclable material usage increased by 43%.
New “end-to-end” lighthouse factory
DHL Supply Chain (Memphis, USA): With the increasing development of the e-commerce market, retail promotions have become the driving force, and consumers’ consumption patterns have also shifted from offline to online orders. transformation. Faced with the above-mentioned circumstances, coupled with severe seasonal effects, DHL Supply Chain in Memphis, Tennessee, established a strategic Fourth Industrial Revolution technology base. The facility is equipped with a control tower for centralized planning and execution supervision to manage and control the end-to-end business. The site seamlessly integrates robotics, analytics and flexible staffing solutions, reducing overtime by 50%, shortening shipping cycles by 57%, increasing production capacity by 290%, and growing at a compound annual growth rate since 2019 ( CAGR) reached 28%. As a result, the base has become a major global training center in the use of new technologies.
Haier (Qingdao, China) : In order to maintain an industry-leading position in terms of cost and solve the common problems of unprofessional and untimely service in the home appliance industry, Haier has deployed 136 Fourth Industrial Revolution use cases to save money. Procurement costs, increased productivity and improved service quality. These use cases leverage technologies including 5.5G, advanced algorithms and ready-to-use digital twins. This initiative resulted in a 32% optimization of product costs, a 36% increase in labor productivity, and an 85% reduction in service complaints.
Johnson & Johnson (Xi’an, China) : To improve agility and responsiveness, improve quality standards, and enhance competitiveness, Johnson & Johnson Xi’an replaced existing manual facilities in 2019 with a new factory driven by the Fourth Industrial Revolution . The factory incorporates digital twin technology for technology transfer and material handling, and enables continuous process verification (CPV) as well as intelligent automation of batch execution processes. This resulted in a 64% reduction in product transfer time during factory relocations and a 60% reduction in non-conforming products, while increasing productivity by 40%, reducing operating costs by 24%, and reducing 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, Kenvue Shanghai has deployed in its end-to-end supply chain More than 25 Fourth Industrial Revolution use cases employ technologies such as social media big data analytics, digital twins, additive manufacturing and machine learning. As a result, lead times for new product launches have been reduced by 50%, forecasting accuracy has improved by 1.3x, and on-time delivery rates have reached 99.8% within 48 hours. As a result, e-commerce business volume has doubled, from 30% to 60% of the overall business.
Unilever (Sonipat, India): To increase flexibility and cater to the needs of different product segments, reduce costs in an inflationary environment and improve sustainability, Sonipat’s Unilever is at its end More than 30 Fourth Industrial Revolution use cases have been deployed in the end-to-end supply chain. Among the most critical use cases are boiler and spray dryer process twins, as well as contactless production planning and inventory optimization based on customer data. It achieved an 18% improvement in service levels, a 53% improvement in forecast accuracy, a 40% reduction in switching costs and an 88% reduction in Scope 1 carbon footprint. The livelihoods of local farmers have also been improved because the boiler digital twin technology requires the use of biofuels.
New Sustainable Lighthouse Factory
Johnson & Johnson (Xi’an, China) : Johnson & Johnson Xi’an has built an advanced production base to meet growing energy needs while reducing environmental impact. To meet and exceed Leadership in Energy and Environmental Design (LEED) Gold® certification standards, the Xi'an Johnson & Johnson factory deployed a series of Fourth Industrial Revolution technologies, including artificial intelligence algorithms for process control, the Industrial Internet of Things ( IIoT) smart cleaning technology and digital twin technology. After successful implementation, the plant saw a 47% reduction in material waste, a 26% reduction in temperature gas (GHG) emissions, and a 23% reduction in energy consumption.
Kenvue (Bangkok, Thailand): Kenvue Thailand applies Fourth Industrial Revolution technologies in field operations to achieve more sustainable resource management. Specific measures include deploying an end-to-end, water-to-ecosystem performance management system, using digital twin technology to optimize cooling system energy consumption, and implementing digital analytics and robotic process automation for dynamic scheduling and container loading optimization solutions. Between 2018 and 2023, the factory will reduce water use by 35%, reduce energy-related consumption (Scope 1 and 2) by 34%, reduce related greenhouse gas emissions by 29% (normalized by volume), while increasing container utilization by 35% , to further improve transportation efficiency.
Schneider Electric (Hyderabad, India): Schneider Electric’s Hyderabad facility aims to achieve zero-carbon Scope 1 and 2 emissions by 2030 with a focus on Fourth Industrial Revolution technologies. Specifically, this includes the introduction of an end-to-end (E2E) closed-loop system for carbon dioxide tracking of strategic suppliers. The system manages all factory equipment using real-time data generation and cloud analytics, and interconnects factory equipment with shop floor operations through an industrial IoT equalizer and artificial intelligence predictive monitoring technology. After implementation, the factory reduced energy consumption by 59%, CO2 emissions by 61%, water consumption by 57%, and normalized waste generation by 64%.
Siemens (Chengdu, China) : Against the background of a 92% increase in production in the past three years, Siemens (Siemens) Chengdu factory has taken many measures to become a zero-carbon emission pioneer, including deploying a comprehensive digital energy management system and implementing Predictive maintenance of the entire production process introduces automation technology based on artificial intelligence to identify and process up to 16 types of production waste, and uses ecological design concepts to improve circularity and dematerialization. After implementing the above measures, the factory’s energy consumption per unit product was reduced by 24%, and production waste was reduced by 48%.
