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How AI is Reshaping the Modified Plastics Industry: Opportunities Lie in These Technological Breakthroughs

Guowei Plastics 2025-08-07 17:28:03

In the modified plastics industry, most production managers are actually in a state of "anxiety" every day. The core issue in the new materials industry remains the broad approach to cost management without detailed cost control, which can lead to various problems. Therefore, the establishment of lean production management is urgently needed.

In the plastic modification industry, many leading companies such as Julong Technology began building smart factories as early as 2021, and have now become models of digital transformation in smart factories. Meanwhile, Kingfa Sci. & Tech. has invested 660 million yuan in the construction of digital factories and unmanned factories.

These leading enterprises mostly regard digitalization as informatization, integrating information and enhancing the level of automation to improve production efficiency.

AI is currently rapidly changing the way we behave, and the reason why customized modified plastics especially need AI is due to the differences in sales models, customer groups, and service models between specialty modified plastics and general plastics.

AI can be applied in the field of chemical modification through formulation development, expert systems, and market promotion, covering the entire product development process with AI systems.

Specifically, the application of AI in rubber and plastics production has enabled intelligent manufacturing, equipment management, quality control, and demand forecasting, significantly improving production efficiency and product quality. In supply chain management, AI optimizes resource allocation through intelligent procurement, warehousing, and distribution, thereby reducing operating costs.

According to Gartner's prediction, by 2028, AI will be involved in 75% of industrial decisions!
The modified plastics industry will also undergo a revolutionary transformation of "human-machine symbiosis"—role restructuring: from "operator" to "AI commander."
Traditional engineers spend 60% of their time on repetitive experiments.AI Intelligent Agent SystemImplemented:

Automatically generate formulation plans to free up human resources for innovation; use AI to analyze massive experimental data and predict the properties of different polymer formulations (such as rubber and plastics), including heat resistance and tensile strength, thereby reducing trial-and-error costs.
Process parameter optimization to improve product quality; AI models dynamically adjust production equipment parameters (such as temperature and pressure) to enhance product quality and energy efficiency.
Simulate customer demand scenarios, proposal approval rate increased by 65%.

AI also empowers sales and customer service, for example, by enhancing user experience through intelligent recommendations, chatbots, and personalized marketing, while utilizing data analysis to optimize market positioning and sales strategies.

The integration of AI technology with the chemical industry has begun to transform R&D, production methods, and industrial patterns in the chemical sector. This has laid a solid foundation for enhancing the industry's capacity for independent innovation, optimizing industrial structure, and achieving safe, green, and high-quality development.

To fully seize the development opportunities brought by AI technology, it is still necessary to integrate advantageous resources from industry, academia, research, and application across various professional fields, accelerate the establishment of relevant technical standards systems, coordinate data and algorithms, and build industry-specific large models. In the process of deep integration between AI technology and the chemical industry, leading enterprises in various sub-sectors are expected to play a guiding and exemplary role, further consolidating their influence and competitiveness amid industrial transformation.

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