Use AI to Drive Low-Carbon Semiconductor Manufacturing
ASEH
BCSD TaiwanSummary
ASEH developed an AI-powered environmental management system and an employee green lifestyle app to reduce the company's greenhouse gas (GHG) emissions and environmental impact.
Key resources
Context
ASE Technology Holding Co. (ASEH) is the world's largest semiconductor packaging and testing service provider. This case study features ASE's Kaohsiung plant as the demonstration site for the implementation of an AI-powered smart environmental management system. Given the energy- and water-intensive nature of semiconductor packaging and testing processes, improving energy and resource efficiency while strengthening carbon emissions management has become a crucial issue in the semiconductor industry's transition toward net-zero.
In response to the global drive toward net-zero emissions and supply chain decarbonization, ASEH is pursuing twin (digital and sustainable) transformation with the goal of achieving net-zero GHG emissions across its value chain by 2050. By integrating AI into energy and environmental management, ASEH has established a standardized and modular smart management model to improve energy and resource efficiency, reduce operating costs, and encourage employees to adopt low-carbon lifestyles, thereby strengthening the company's climate resilience and competitiveness. The management model can be replicated across other plants and throughout the supply chain to expand carbon reduction benefits. ASEH's experience in applying its self-developed AI systems to air conditioning and processes in energy and water management has been recognized with the Energy Saving Benchmark Award by Taiwan's Ministry of Economic Affairs and the Clean Water Sustainability Award by Taiwan's Ministry of Environment.
Figure 1: Energy Saving Benchmark Award
Solution
ASEH developed an AI-powered smart environmental management system integrating four processes of management: monitoring, analysis, prediction, and optimization. The solution primarily included three core AI management measures and an APP for promoting low-carbon actions among employees.
1. AI-powered smart energy and environmental management system
AI-powered smart energy management: AI is used to optimize the operation and control of fan filter units (FFUs) in chiller machines and cleanrooms, with equipment parameters dynamically adjusted to reduce energy consumption and improve overall energy efficiency.
AI-powered smart environmental management: AI is used to monitor and analyze water quality in real time, optimize chemical dosing and wastewater treatment processes, and facilitate the circular use of recycled water, thereby reducing resource consumption and improving water management efficiency.
AI-powered smart environmental monitoring: AI Nose technology is used to identify process odors and detect abnormal signs, such as equipment wear and oxidation, strengthening real-time monitoring, anomaly alerts, and predictive maintenance capabilities to enhance workplace safety and process stability.
Figure 2: Fan Filter Unit (FFU) Smart Management System
Figure 3: AI-Powered Inorganic Wastewater Management
2. Carbon Diary, a low-carbon lifestyle APP for employees
ASEH developed a Carbon Diary APP. Through the app, employees earn 'gold carbon coins,' a virtual currency automatically accumulated based on their low-carbon actions, such as adopting low-carbon diets and commuting by electric bus or bicycle. The gold carbon coins can be redeemed through the app for cultural event tickets, daily necessities, and special company benefits, thereby incentivizing employees to continuously engage in sustainable actions and develop low-carbon lifestyle habits.
Figure 4: ASE Space App - Carbon Diary
Impact
Sustainability Impact
Climate
The AI-powered smart energy management solution primarily addresses Scope 2 emissions, delivering carbon reduction benefits through enhanced equipment energy efficiency, AI-optimized control, and process improvements.
Current results include:
Roughly 0.5% annual reduction in Scope 2 emissions (approximately 2,859.6 metric tons/year)
Roughly 0.6% annual electricity savings (approximately 7.68 million kWh/year)
The employee low-carbon lifestyle APP contributes to reducing Scope 3 emissions from employee commuting.
Current results include:
Employees were encouraged to participate in sustainable actions. Through the game design and interactive features of the 'carbon coin' mechanism, the app encourages employees to adopt low-carbon practices across all aspects of daily life, including food, clothing, housing, and transportation. Employee participation rate reached 93%, resulting in a carbon reduction of 3,904 tons.
Nature
The AI-powered smart environmental management solution not only reduces carbon emissions but also improves water resource efficiency.
Current results include:
Approximately 4% annual water savings (approximately 185,000 cubic meters/year)
10% reduction in use of water treatment chemicals (including a reduction of 246.2 tons of PAC and 52.73 tons of NaOH)
Reduced sludge production, increased water recycling, and decreased consumption of natural resources.
Social
AI-powered Smart Environmental Management System
Provides AI-powered monitoring and predictive maintenance to enhance equipment reliability and environmental anomaly detection, reduce the risk of environmental incidents, improve workplace safety, reduce manual workload, and encourage employee engagement in smart environmental management and sustainable development.
Business Impact
Benefits
The solution improves energy and resource efficiency and reduces operating costs through the implementation of smart environmental management and low-carbon processes. At the same time, it strengthens digital carbon management capabilities, supply chain collaboration on carbon reduction, and climate resilience, supporting ASEH's transition toward net-zero and enhancing its market competitiveness.
Costs
The cost of the AI system, including platform development, equipment procurement, and operator training, was approximately US$463,000 (USD 0.463 million).
AI-powered Smart Environmental Management System
This solution primarily involved the development of an AI analysis platform, installation of sensor and monitoring equipment, system integration, AI model development, and personnel training. Investment costs mainly depended on factory size, number of equipment, and existing level of digitalization. As most improvement measures can be implemented through optimized control of existing equipment, the need for additional equipment investment can be reduced. The initial investment can then be gradually recovered through energy and water savings and reduced chemical consumption.
Low-Carbon Lifestyle APP for Employees
The costs involved in this solution included APP development and maintenance, development of a carbon footprint calculation model for low-carbon behaviors, system integration and data management, platform operations and management, employee engagement activities, and rewards for redeeming carbon coins (such as tickets to arts and cultural events, daily necessities, and company benefits).
Implementation
Typical Business Profile
The solution is suitable for:
Global companies in energy/water-intensive industries, such as semiconductor and electronics manufacturing;
Global companies that have established energy management systems and are pursuing digital transformation; and
Companies that attach importance to ESG development and employee engagement and are committed to fostering a low-carbon corporate culture.
Approach
The AI-powered smart environmental management system was implemented through five key steps:
ASEH established a data foundation by developing energy, water resource, and environmental monitoring systems and using sensors to collect equipment and environmental data.
ASEH established an AI analysis platform, integrating system and equipment data and deploying AI models and analysis mechanisms.
ASEH used data analytics to identify emission hotspots for energy and environmental management and determine opportunities for improvement.
ASEH deployed AI-powered smart controls to optimize controls for chiller units, FFUs, wastewater treatment, and odor monitoring systems.
ASEH optimized its AI model by continuously training the AI model to refine the analytical mechanisms and expanded its applications to other management areas and plants.
The employee low-carbon lifestyle APP was implemented through five key steps:
ASEH conducted a needs assessment and developed a platform implementation plan, identifying actionable low-carbon practices (e.g., sustainable eating habits, low-carbon commute, and energy saving practices).
ASEH developed the required system and established a model to calculate carbon emissions.
ASEH designed an incentive mechanism incorporating gold carbon coins and a reward exchange system to encourage employee participation.
ASEH launched a pilot test of the APP, optimized system functions based on user feedback from the pilot test, and promoted the APP internally to increase usage rate.
ASEH monitored the APP's performance by analyzing employee participation rates, trends in low-carbon actions, and carbon reduction benefits, and continuously optimized platform functions and implementation strategies.
Stakeholders Involved
AI-powered Smart Environmental Management System
The project was led by ASE Kaohsiung's plant operations team, which was responsible for energy, water resource, and environmental management systems, providing on-site requirements, and validating AI control strategies. The IT Department was responsible for integrating data from sensors, equipment, and various management systems, developing a smart management platform, and establishing the operating environment for AI models. Meanwhile, various departments collaborated with suppliers to establish a data sharing, performance verification, and continuous improvement mechanism that enables a standardized, replicable smart environmental management solution for gradual expansion across other plants and the supply chain of ASEH.
Project Leads:
Departments in charge of plant operations (Plant Operations Division/site operation units)
IT Department
Low-Carbon Lifestyle APP for Employees
Employees were the primary users, participating in low-carbon actions through the platform. The lifestyle carbon reduction teams were responsible for project planning and tracking carbon reduction benefits, as well as supporting internal promotion and employee engagement. The IT and Company IT teams were responsible for system development and maintenance. Plant operation units supported internal promotion and employee engagement, while management provided resources for incentives to support the company's long-term implementation and continued promotion of a low-carbon culture.
Project Leads:
Teams in charge of lifestyle carbon reduction (Net Zero Office/Sustainability Department/Human Resource Department)
IT Department
Key Parameters to Consider
AI-powered Smart Environmental Management System
The system is suitable for energy- and water-intensive manufacturing industries.
The system requires comprehensive equipment data, sensor monitoring, and digital management capabilities.
The system requires continuous calibration and optimization to maintain analytical accuracy.
A pilot test of the system should be conducted at a single plant and gradually expanded to other sites.
The system can be integrated with ISO 14001, ISO 50001, and carbon management systems to enhance management effectiveness.
Low-Carbon Lifestyle APP for Employees
Employee participation and user experience
Design of low-carbon actions
Logic of calculating carbon reduction benefits and data accuracy
Platform functionality, system stability, and information security
Incentive mechanism design and long-term sustainability
Participation tracking and data analysis
Implementation and Operations Tips
In the initial stages of implementation, the main challenges for both the AI-powered smart environmental management system and the employee low-carbon lifestyle APP included cross-system data integration, equipment data quality, and AI model development.
To enhance implementation effectiveness, ASEH established a cross-functional collaboration mechanism, bringing together sustainability, plant operations, equipment, manufacturing, and IT departments to jointly drive the project. The following implementation approaches were adopted for different applications:
AI-powered smart environmental management system: AI controls were first implemented for energy-intensive equipment to quickly achieve energy savings, followed by gradual expansion to applications such as water resource management and environmental monitoring.
Employee low-carbon lifestyle APP: Employee needs were first assessed to design low-carbon activities and incentive mechanisms aligned with user needs, thereby increasing employee engagement and fostering low-carbon lifestyle habits.
In addition, ASEH established a real-time monitoring dashboard and a performance tracking mechanism for both the environmental management system and employee low-carbon lifestyle APP to continuously validate AI model accuracy and assess improved results. These mechanisms have enabled the project to adopt a modular and standardized approach, facilitating rapid replication across different plant operations and other energy-intensive manufacturing industries, thereby ensuring more effective promotion and widespread application.