New Lighthouse Factories Industry 4.0 December 2023 - Significant Growth and Productivity Benefits

 ACG Capsules (Pithampur, India): 

To stay ahead of the curve in an intensely competitive market, pharmaceutical supplier ACG Capsules prioritized manufacturing superior-quality products, improving responsiveness, increasing production yields and enhancing workforce productivity. To achieve this, ACG Capsules implemented 25+ Fourth Industrial Revolution use cases powered by the industrial internet of things (IIoT), machine learning (ML), deep learning (DL), digital twins, extended reality and generative AI. Effective adoption of these use cases has resulted in a reduction in critical defects of 98%, a shortening of production lead times of 39%, a drop in total losses of 51% and a 44% rise in workforce productivity.

Agilent (Waldbronn, Germany): 

Amid demand fluctuations, strong growth of more than 50%, supply-chain disruptions and evolving product needs, Agilent Waldbronn introduced more than 25 Fourth Industrial Revolution-related roles and 20 associated use cases to address the challenges. Its high-volume and high-mix life-science manufacturing platform benefited from solutions from its Fourth Industrial Revolution toolkit, including AI applications and IIoT for rapid simulation and prediction. The facility has achieved a 35% increase in quality, a 44% boost in productivity and a 48% rise in output, ultimately enabling market share growth.

AMOREPACIFIC (Osan, South Korea): 

To stand out in the cosmetics industry, global beauty company AMOREPACIFIC used Fourth Industrial Revolution technologies such as AI and 3D printing to optimize manufacturing process design, accelerate new product introductions and improve flexibility. This reduced new product lead time by 50% and defects by 54%. It also enabled a new business model for manufactured-in-store customized cosmetics, with over 800,000 unique products offered.

Aramco (Yanbu, Saudi Arabia): 

To maintain a competitive edge as one of the leading suppliers of fuels while minimizing its carbon footprint, this 1970s Aramco refinery underwent a five-year strategic Fourth Industrial Revolution transformation, implementing and integrating use cases at scale including an AI-based clean fuels optimizer, an AI-powered operation decision system and a digital twin dynamic model. As a result, on-spec fuel production has reached 99%, greenhouse gas (GHG) emissions have been reduced by 23% and operational availability has improved by 17%.

CATL (Liyang, People’s Republic of China): 

To address soaring demand and increasing labour costs, and to meet its carbon neutrality commitment, CATL Liyang applied big data to simulate quality-testing, additive manufacturing to reduce changeover times, computer vision to achieve micron-level quality inspection, and deep learning to optimize process controls and energy management. This has resulted in a 320% output increase, a 33% reduction in manufacturing costs, a 47.4% reduction in normalized emissions and a 99% reduction in quality defects. Defect measurement has been upgraded from “per million” to “per billion”.

CITIC Pacific Special Steel (Jiangyin, People’s Republic of China): 

To meet the fast-growing global demand for customized steel products while navigating volatile raw material and energy-supply issues, CITIC Pacific Special Steel’s Jiangyin Xingcheng plant deployed 40+ Fourth Industrial Revolution use cases such as advanced analytics-powered process simulation and optimization, as well as AI-enabled energy management. As a result, the plant has been able to increase customized orders by 35.3%, reduce its non-qualified product rate by 47.3% and cut its energy consumption by 10.5% per tonne of steel.

China Resources Building Materials Technology (Tianyang, People’s Republic of China): 

To address the requirements of green and low-carbon development, higher quality expectations and cost pressures, Tianyang site, a cement factory under China Resources Building Materials Technology Holdings, has deployed 30+ Fourth Industrial Revolution use cases with advanced analytics, autonomous driving and IIoT to improve energy, labour and equipment efficiency and quality performance. As a result, the site has reduced carbon emissions by 24%, increased labour productivity by 105%, reduced unplanned downtime by 56% and improved quality consistency by 25%.

GAC AION (Guangzhou, People’s Republic of China): 

To satisfy customers’ spiking demand for reliable and customized electric vehicles, GAC AION deployed 40+ Fourth Industrial Revolution use cases to provide customers with more than 100,000 configuration options and ensure timely and qualified deliveries. The fully automated production line supports mixed production of made-to-order and made-to-stock models, increasing production efficiency by 50%, reducing delivery times by 33%, raising first-pass yields by 8% and reducing manufacturing costs by 58%.

Haier (Hefei, People’s Republic of China):

 The rise of a new middle class and increased consumer consumption in China have driven upgrades from a split air conditioner (AC) system to a central AC system, which has higher requirements in terms of quality and energy efficiency. Haier’s Hefei air conditioner factory applied advanced algorithms, digital twins, knowledge graphs and other cutting-edge technologies in the research and development (R&D), production and testing of household central AC systems, resulting in a 33% increase in energy efficiency, a 58% drop in the defect rate, a 49% increase in labour productivity and a 22% drop in unit manufacturing costs.

Hengtong Alpha Optic-Electric (Suzhou, People’s Republic of China): 

Facing higher cost pressures as well as quality and green production expectations from the international market, Hengtong Alpha accelerated the large-scale application of advanced analytics, machine vision and AI technology across 27 advanced use cases covering the whole production value chain. As a result, unit manufacturing costs have decreased by 21%, the defect rate has reduced by 52% and unit power consumption has fallen by 33%.

Ingrasys, Foxconn Industrial Internet (Taoyuan, Taiwan, People’s Republic of China): 

The rapid development of AI foundation models has brought an explosion in demand for computing power and higher efficiency, quality and iteration speed requirements for AI servers. By deploying AI use cases across order forecasting, warehouse and production scheduling, product design, quality and assembly-testing domains, Foxconn Industrial Internet’s Taiwan factory has achieved a 73% increase in production efficiency, a 97% reduction in product defects, a 21% reduction in lead time and a 39% decrease in unit manufacturing costs.

K-water (Hwaseong, South Korea): 

The climate crisis has caused significant water supply concerns, as heatwaves and heavy rains create more volatile and turbid supplies. To address this, K-water launched a next-generation AI water treatment plant to reduce production costs, improve responsiveness and reduce human error. It is being scaled across 40+ other sites and has helped K-water to reduce its chemical usage by 19%, improve labour efficiency by 42% and reduce power consumption by 10%.

LONGi Solar (Jiaxing, People’s Republic of China): 

Driven by the desire to reduce costs, improve quality and shorten the lead time on solar modules, the Jiaxing site implemented more than 30 Fourth Industrial Revolution use cases, using AI and advanced analytics to boost manufacturing operations. These efforts have had significant impacts, with the site achieving a 28% reduction in unit manufacturing costs, a 43% cut in yield loss and an 84% decrease in production lead time within one year, while also lowering energy consumption by 20%.

Mondelēz (Beijing, People’s Republic of China): 

Embracing sustainability ambition from both Mondelēz Global and Beijing City while meeting Mondelēz’s growth ambitions and addressing operating cost pressures due to year-on-year (YoY) 6% labour cost inflation, Mondelēz Beijing implemented 38 Fourth Industrial Revolution use cases, such as an AI-powered dough-making lights-off workshop and gas consumption optimization by machine learning. As a result, Mondelēz Beijing has achieved a 28% net revenue growth and 53% increase in labour productivity while reducing GHG emissions by 24% and food waste by 29%.

ReNew (Ratlam, Madya Pradesh, India): 

To maximize productivity, streamline costs and redeploy the existing workforce to help in-source operations and maintenance (O&M) capabilities, renewable energy company ReNew built on and scaled the digital and analytics backbone from its first Lighthouse site, including 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 unique wind turbine models. Ratlam, the company’s benchmark site for this scale transformation, has sustained improvements of 1.7% higher energy yield, 17% reductions in operating expenses and 40% less waste. This led to a 20% increase in profitability.

VitrA Karo (Bozüyük, Türkiye): 

Increased energy prices and inflation have affected energy costs and the labour-intensive ceramic tile production process. To sustain competitiveness while responding to higher demands and maintaining a complex portfolio of 4,200+ SKUs, VitrA Karo’s Bozüyük site deployed its digital transformation roadmap, focusing on intelligent process and production controls. This has resulted in a 19% increase in OEE, a 56% decrease in scrap, a 14% decrease in energy consumption and a 43% increase in the use of recycled content.

End-to-End (E2E) Value Chain Lighthouses

DHL Supply Chain (Memphis, Tennessee, United States): 

Facing a growing e-commerce market and driven by retail promotions and a consumer consumption switch from offline to online orders, in addition to heavy seasonality impacts, DHL Supply Chain in Memphis, Tennessee established a strategic Fourth Industrial Revolution site, equipped with a control tower for centralized planning and execution oversight to manage and control E2E operations. This site has seamlessly integrated robots, analytics and a flexible staffing solution, resulting in a 50% overtime reduction, a 57% shipment cycle time reduction and a 290% increase in capacity, leading to a 28% compound annual growth rate (CAGR) since 2019. Consequently, the site has emerged as a primary training hub for the global adoption of new technologies.

Haier (Qingdao, People’s Republic of China): 

To stay ahead of the industry on cost and address common problems of unprofessional and delayed services in the home-appliance industry, Haier deployed 136 Fourth Industrial Revolution use cases for procurement cost savings and improvements in productivity and quality of services, using technologies including 5.5G, advanced algorithms and ready-to-use digital twins. This initiative has resulted in product cost being optimized by 32%, labour productivity increasing by 36% and the service complaint rate being cut by 85%.

Johnson & Johnson (Xi’an, People’s Republic of China): 

To improve agility and responsiveness, raise quality standards and enhance competitiveness, Johnson & Johnson Xi’an replaced its manual facility with a Fourth Industrial Revolution-enabled new factory in 2019. This facility includes digital twins for technology transfer and material handling, intelligent automation of continued process verification (CPV) and batch execution processes. This has shortened the product transfer time by 64% during site relocation and has enabled a 60% decrease in non-conformance, while improving productivity by 40%, operating costs by 24% and GHG emissions by 26%.

Kenvue (Shanghai, People’s Republic of China): 

To keep up with the growth in e-commerce, faster speed to market and the fluctuating demands that come from increased cost competitiveness, Kenvue Shanghai deployed more than 25 Fourth Industrial Revolution use cases, including big data analytics on social media, digital twins, additive manufacturing and ML across its E2E value chain. This resulted in a 50% reduction in new product introduction lead times, 1.3-times improvement in forecast accuracy and 99.8% on-time-in-full deliveries within 48 hours. This enabled the e-commerce business to double from 30% to 60% of overall business.

Unilever (Sonepat, India): 

To improve agility and cater to diverse product segments, reduce costs in an inflationary environment and improve sustainability, Unilever Sonepat implemented 30+ Fourth Industrial Revolution use cases in its E2E supply chain. Top use cases included boiler and spray dryer process twins, as well as customer data-informed no-touch production planning and inventory optimization. This improved service by 18%, forecast accuracy by 53%, conversion cost by 40% and Scope 1 carbon footprint by 88%. The use of biofuels enabled by a boiler process twin also supports livelihoods for local farmers.

https://www.weforum.org/press/2023/12/factories-of-the-future-show-how-to-apply-ai-to-benefit-people-planet-and-performance/