世界经济论坛-全球灯塔网络:通过4IR解锁可持续性(英)-2021.9-37页_6mb
报告摘要
Summary of the Global Lighthouse Network: Unlocking Sustainability through Fourth Industrial Revolution Technologies
Core Content
The Global Lighthouse Network, launched by the World Economic Forum in collaboration with McKinsey & Company in 2018, identifies and showcases companies that are leading the transformation through Fourth Industrial Revolution (4IR) technologies. These technologies are not only enhancing productivity and agility but also driving sustainability as a key business outcome. The report highlights how 4IR tools can support eco-efficiency, which is defined as the integration of sustainability and operational excellence.
Main Points
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4IR and Sustainability Synergy: The report challenges the belief that sustainability and productivity are mutually exclusive. Instead, it argues that 4IR technologies, when applied strategically, can enhance both by improving efficiency and reducing environmental impact.
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Eco-efficiency as a Business Priority: Eco-efficiency is now a central shift in the 4IR transformation, driven by global environmental concerns and the call for action from the Intergovernmental Panel on Climate Change (IPCC). It involves leveraging digital tools to reduce resource consumption, emissions, and waste while increasing productivity.
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Measurable Impact: Lighthouses report significant sustainability impacts as part of their 4IR transformations. Over 64% of them highlight sustainability achievements, showing that the integration of digital technologies with sustainability goals is becoming a standard practice.
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Digital Tools for Sustainability: A range of digital tools and technologies, such as AI, IoT, digital twins, and advanced analytics, are used to drive eco-efficiency. These include:
- Additive manufacturing (3D printing)
- Advanced IIoT for process optimization
- AI-guided machine performance optimization
- Predictive maintenance
- Digital quality management
- Real-time asset performance monitoring
- End-to-end supply chain visibility
- Digital twin for sustainability
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Cross-Industry Adoption: The Lighthouse Network includes companies from a wide range of industries, such as consumer packaged goods, process industries, pharmaceuticals, and automotive, demonstrating that 4IR-driven sustainability is not limited to a specific sector.
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Global Reach: The network has grown significantly, with 90 Lighthouses identified to date, and 3 designated Sustainability Lighthouses. This shows the global reach and adaptability of 4IR technologies across different regions and business contexts.
Key Lighthouse Use Cases and Impact
The following use cases illustrate how 4IR technologies are enabling eco-efficiency and sustainability improvements:
| Site | Use Case | Impact | Metric |
|---|---|---|---|
| AUO Taichung | Automated material handling | Productivity | ▲ 12% |
| AUO Taichung | AI-powered automated testing and repair | Scrap cost | ▼ 3% |
| AUO Taichung | Advanced IoT applied to process optimization | Sputter OEE | ▲ 8.5% |
| AUO Taichung | Predictive maintenance | Maintenance cost | ▼ 32% |
| AUO Taichung | Advanced analytics enabled sustainability optimization | Carbon emission | ▼ 20% |
| CITIC Dicastal Qinhuangdao | AI-powered optical inspection | Manpower for inspection | ▼ 81% |
| CITIC Dicastal Qinhuangdao | Digital-enabled flexible manufacturing | Minimal batch size | ▼ 99.7% |
| CITIC Dicastal Qinhuangdao | AI-enabled CNC quality expert system | OEE CNC | ▲ 23% |
| CITIC Dicastal Qinhuangdao | 3D simulations/digital twin for product design and testing | Cycle time | ▼ 38% |
| CITIC Dicastal Qinhuangdao | Real-time asset performance monitoring | Labor productivity | ▲ 38% |
| Contemporary Amperex Technology Ningde | AI-powered process control | Labor productivity | ▲ 75% |
| Contemporary Amperex Technology Ningde | AI-powered optical inspection | Defect parts per billion | ▼ 80% |
| Contemporary Amperex Technology Ningde | Big data/AI-enabled product design and testing | R&D cycle | ▼ 50% |
| Contemporary Amperex Technology Ningde | Digital track and trace | Manpower for screening tests | ▼ 80% |
| Foxconn Wuhan | AI-powered optical inspection | SMT misalignment | ▼ 50% |
| Foxconn Wuhan | Digitally enabled man-machine matching | Labor productivity | ▲ 23% |
| Foxconn Wuhan | Lights-out injection moulding workshop | Manufacturing lead time | ▼ 38% |
| Foxconn Wuhan | Intelligent kitting and replenishment | Kitting efficiency | ▲ 40% |
| Foxconn Wuhan | Advanced analytics enabled sustainability optimization | Energy consumption per unit | ▼ 37% |
| Foxconn Zhengzhou | Repair process automation | Testing labor efficiency | ▲ 60% |
| Foxconn Zhengzhou | Automated material handling | Labour for material delivery and feeding | ▼ 75% |
| Foxconn Zhengzhou | Quality improvement by predictive analytics | Quality defect rate | ▼ 15% |
| Foxconn Zhengzhou | I/O real time sensor-based data aggregation | Energy efficiency for Factory Management Control System | ▲ 30% |
| Haier Tianjin | 3D simulations/digital twin for product design and testing | R&D lead time | ▼ 50% |
| Haier Tianjin | Flexible manufacturing: Hybrid assembly line | Order fulfillment lead time | ▼ 50% |
| Haier Tianjin | Automated material handling | Line inventory | ▼ 67% |
| Haier Tianjin | Advanced analytics enabled sustainability optimization | Energy consumption per unit | ▼ 18% |
| Haier Tianjin | Big data/AI-enabled product design and testing | Monthly sales | ▲ 35% |
| Innolux Kaohsiung | AI-powered process control | Process capability | ▲ 40% |
| Innolux Kaohsiung | AI-powered automated testing and repair | Yield loss rate | ▼ 95% |
| Innolux Kaohsiung | Supplier material quality prediction | Quality events | ▼ 40% |
| Innolux Kaohsiung | Digitally-enabled quality failure diagnosis | Quality alert time | ▼ 91% |
| Innolux Kaohsiung | Predictive maintenance | OEE of bottleneck machine | ▲ 2.3% |
| LS ELECTRIC Cheongju | Digital-enabled flexible manufacturing | Equipment set-up time | ▼ 87% |
| LS ELECTRIC Cheongju | Automated material handling | Logistics labour | ▼ 39% |
| LS ELECTRIC Cheongju | AI-powered optical inspection | Defect rate | ▼ 33% |
| LS ELECTRIC Cheongju | Quality improvement by predictive analytics | Inspection accuracy | ▲ 80% |
| LS ELECTRIC Cheongju | AI-powered process control | Warranty claims | ▼ 30% |
| Sany Beijing | Adaptive welding with intelligent robot | Welding production efficiency | ▲ 130% |
| Sany Beijing | AI-guided machine performance optimization | Production capacity | ▲ 100% |
| Sany Beijing | Collaborative robotics and automation | Model changes time | ▼ 83% |
| Sany Beijing | 5G-based dual AGV heavy-duty logistics | Average transferring time | ▼ 50% |
| Sany Beijing | AI-guided machine performance optimization | Machine efficiency | ▲ 31% |
| Schneider Electric Wuxi | End-to-end real-time supply chain visibility platform | On-time delivery | ▲ 30% |
| Schneider Electric Wuxi | Field quality failures aggregation, prioritization and advanced analytics | Warranty cost | ▼ 72% |
| Schneider Electric Wuxi | Digital-enabled flexible manufacturing | Time to market | ▼ 25% |
| Schneider Electric Wuxi | Robotics-enabled logistics execution | - | - |
Key Industries and Lighthouses
The Lighthouse Network spans multiple industries, including:
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Consumer Packaged Goods:
- Henkel (Germany, Spain, Mexico)
- Procter & Gamble (China, Czech Republic, France)
- Unilever (China, UAE)
- Alibaba (China)
- Johnson & Johnson (Sweden, China, Ireland, USA)
- Zymergen (USA)
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Process Industries:
- Baoshan Iron & Steel (China)
- DCP Midstream (USA)
- MODEC (Brazil)
- Petkim (Turkey)
- Petrosea (Indonesia)
- POSCO (Korea)
- Renew Power (India)
- Saudi Aramco (Saudi Arabia)
- STAR Refinery (Turkey)
- Tata Steel (India, Netherlands)
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Advanced Industries:
- AGCO (Germany)
- Arcelik (Turkey, Romania)
- AUO (Taiwan, China)
- BMW Group (Germany)
- Bosch (China)
- CITIC Dicastal (China)
- CATL (China)
- Danfoss (China)
- De' Longhi (Italy)
- Ericsson (USA)
- Fast Radius with UPS (USA)
- Flex (Austria)
- Ford Otosan (Turkey)
- FOTON Cummins (China)
- Foxconn (China, USA)
- Groupe Renault (Brazil, France)
- Haier (China)
- Hitachi (Japan)
- HP (Singapore)
- Infineon (Singapore)
- Innolux (Taiwan, China)
- Midea (China)
- Nokia (Finland)
- Phoenix Contact (Germany)
- Protolabs (USA)
- Rold (Italy)
- SAIC Maxus (China)
- Sandvik Coromant (Sweden)
- Sany (China)
- Schneider Electric (China, France, Indonesia, USA)
- Siemens (China, Germany)
- Weichai (China)
- Western Digital (Malaysia, Thailand)
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Pharmaceuticals and Medical Products:
- Bayer (Italy)
- GE Healthcare (Japan)
- GSK (UK)
- Johnson & Johnson (Consumer Health, DePuy Synthes, Vision Care)
- Novo Nordisk (Denmark)
- Zymergen (USA)
Conclusion
The Global Lighthouse Network demonstrates that 4IR technologies are not only transforming operations but also unlocking substantial sustainability benefits. By integrating digital tools with sustainability goals, companies can achieve measurable improvements in eco-efficiency, productivity, and profitability. The report underscores the importance of digital transformation in enabling a sustainable future and highlights the role of Sustainability Lighthouses in setting new industry standards.
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