Industries Applications

Petrochemical & Rubber

Through the usage of Profet AI, the accumulated product data in the past decades helps pass on R&D knowledge and experience through machine learning.

Overview

The petrochemical industry uses petroleum or natural gas as raw materials to produce chemicals, with finished products being called petrochemical products. The petrochemical industry is a fundamental industry that is highly related to people's livelihood. Petrochemical products are widely used in food, clothing, housing, transportation, medicine, etc... It can be said that the modern lifestyle is closely related to petrochemical products. Therefore, the demand of the petrochemical industry is often measured by the economic growth rate.

Challange

The petrochemical and rubber industry highly relies on human experience and knowledge. Whether it is the development of various material formulas, process improvement, or raw material price procurement, these problems are solved through experience and. knowledge of master craftsmen. The petrochemical and rubber industry is exploring the use of past R&D experience and historical raw material procurement data in order to build AI models, digitalizing. the critical experience in the company in order to stay competitive.

Applications

Formula research and development, Quality, Purchase of raw materials

Raw material price prediction

The price of raw materials accounts for a large proportion of the product cost structure. Using AI modeling to assist in purchasing decisions can help create greater profits.

Assist on product cost analyproduct research and development

Quality prediction

There are many controllable and uncontrollable factors in the production process of oil products, which make it difficult to predict the quality of oil products. By collecting real-time data in the oil refining process, building oil product prediction models can greatly reduce laboratory inspection costs and improve process yields.

How enterprises use AI to build models through big data in a short time to assist product development is a new method. Using models to simulate the required physical or chemical properties can reduce the need for manufacturing numerous test samples, resulting in a shortened product development timeline.

Our Customers

What is our client saying?

The Chemical Industry Adopts AI Technology to Cope with a Variety of Challenges

In recent years, the chemical industry has faced a variety of challenges. Particularly, the environmental, social, and governance (ESG) trend in the international community will pose a daunting challenge to the chemical industry in the next ten years. How to conserve energy, reduce carbon emissions, and avoid waste will be the most formidable issue.

Moreover, in addition to the impact of ESG on the industry, the transformation of industry structure and industry trends will inevitably put the chemical industry in a dilemma. Due to the high-tech industry's advantages in the salary and remuneration structure and the industry environment, and complex factors of school talent cultivation and talents' employment choices in recent years, a serious talent shortage has occurred to the chemical industry. This issue has, directly or indirectly, affected business operations and will present a tremendous challenge to the passing of business experience on to new talents, new product development efficiency, and business operations optimization.

Agenda

01 Introduction
02 Future chemical industry workers must be professionals with proficiency in AI technology
03 Profet AI has created a 'virtual AI data scientist' for businesses that operates 24/7 without interruption.
04 How to adopt AI technology for modeling
05 Future