Green Chemistry and Smart Manufacturing
Dedicated to the R&D of green chemical technologies, OUCC adheres to the concept of smart manufacturing and drives the transformation and upgrade of chemical industry through environmentally friendly practices and technologies. To fulfill the sustainable development of chemical industry, OUCC has adopted the “robust, safe and eco-friendly” approaches for product development, and assessed extensively the likely impact of products on human health, safety and the environment based on product life cycle.
To reduce the potential risks, we’ve implemented green chemical strategies and action plans, adopted more eco-friendly processes and materials besides optimized existing production procedures, to ensure that OUCC meets the highest SHE standards.
We’ve introduced automatic system and AI digital analysis technology for smart management of overall production procedures, which not only improve production effeciency but reduce resources waste and contaminated emission. With ceaseless engagement in novel eco-friendly technology development and application, and compliance with environmental stipulations and standards, we strive to build a sustainable and much safer chemical industry.
Green and Innovative R&D：
We insist that innovative technology development must meet the environmental protection stipulations and encourage the research and development to aim at eco-friendly and less energy consumed products.
- Development and design stage : Remove toxic substances from the environment and avoid residual substances in products or environmental pollution.
- Production stage：Reduce the loss of energy and resources and the emission of harmful substances.
- Product inspection：For newly developed and produced products, we conduct third party inspection in accordance with customers’ specifications.
Process technology in compliance with regulations：
Purchased already developed technologies which comply with the relevant regulatory requirements.
Promote smart logistics and services：
Build a real-time database system (PI), actively incorporate new elements of "Internet of Things" information, and implement smart logistics and services.
Cultivate AI management talents：
Cultivate a new generation of AI management talents and create new value.
This powerful Operational Intelligence System helps the management and employees with no information background to benefit from learning.Decision making can be carried out effectively and reliably even without the assistance of IT personnel, marking a milestone for digital transformation.
Take liquefied gas for example, OUCC strongly promotes its Smart Logistics and Services. With the storage tank monitoring system installed at the customer site to analyze the usage status in real time, automated dispatch is scheduled via AI technologies and big data, providing the customers with thoughtful and expeditious services.
To cultivate AI workforce for the chemical industry, OUCC has selected its employees for training at the Taiwan AI Academy, in the hope of combining theory and practical knowledge, as well as bringing back solutions through the interaction and experience exchange with industrial associates. Other benefits include improving operational efficiency with AI technologies, lowering production risks and creating new values of smart manufacturing.
Developed by OUCC, the Enterprise Information Platform (EIP), which can be accessed via computers and smartphones, combines digital bulletin board, document managing system, healthcare and the like, simplifying and optimizing procedures and management of the administration.
By way of the fully digitizing administrative forms, a total of 73,085 documents were processed using electronic workflows in 2024, resulting in significant carbon emission reduction. Furthermore, a total of 2,350 hours of video conferencing in 2024 also showcased our efforts in energy-saving & carbon reduction and environmental protection.
AI for catalyst efficiency optimization – EOG Plant
The introduction of AI deep learning for history data analysis, replacing man-made catalyst adjustment, helps to produce the optimum parameters promptly, which not only save the material cost, improve efficiency, but also systemize the know-how inheritance.
AI for process reaction optimization – Process Development Dept.
In view of the multiple adjustments of a new product when transits from lab to mass production, AI assists R&D to quickly converge variables to seek the trends, which lessens the number of experiment and cost with high efficiency.
AI for new product process optimization – Material Development Dept.
The forecast process parameters and trends of AI model shortens the timespan of new product development, reduces energy consumption and carbon emission in line with green production process.
AI for preliminary maintenance of compressors – Maintenance Dept.
The AI model established analyzes vibration data to distinguish abnormality and causes, aiming to predict the timeline for maintenance, alarm and recommend maintenance timetables to improve steadiness of the equipment.
AI for customer’s order forecast – GAS Business Dept.
The AI forecast model established is based on the combined data of storage tank level gauge, usage frequency and delivery of customers to optimize production line schedule, dispatch and avoid the likely non-loading dispatch rates, and therefore enhance the efficiency of logistics and services.
AI for deduction of reactors’ molecular weight parameters – EOD Plant
The AI model is established to forecast the qualification of product molecular weight, reduce the number of samplings or even exempt from sampling, shorten reactor idle time, and improve quality and efficiency.
AI for production conditions optimization – EC Plant
Through analyzing the process parameters of HPEC and semiconductor CO2 , the AI model distinguishes and rectifies the reason triggering unsteady quality to diminish task repetition and carbon emission to improve efficiency and quality.
Stakeholders Contactors
- Mr. Chen/Ms. Chang
- E-mail： ESG@oucc.com.tw
SHE Contactors
- Mr. Yeh/Mr. Wu
- E-mail： she@oucc.com.tw