Status of the industry
1、Low automation, low production efficiency, low product yield, and low information interconnection efficiency, etc.
2、The lack of in-depth research in the production process has resulted in the process control of the production line being basically in a unchangeable state. It is impossible to optimize the process according to the influence of raw materials and the environment, affecting the cost and quality of the unit products.
3、The price of raw materials has a huge impact on product costs, which in turn affects the benefits of enterprises. How to accurately predict the prices of raw materials and products, and carry out a scientific procurement and sales strategy is of utmost importance to the enterprise.
4、Experimental data, laboratory test data, process data, failure data, etc. cannot be completely and longterm preserved, which greatly affects the knowledge accumulation of enterprises, resulting in the development, production and products at the low-end level.
5、Extensive management model, imperfect process system, backward management methods, incomplete information records, inefficient communication, lack of standard norms, and uncontrolled management, etc.
In view of the current situation of lithium battery materials enterprises, after in-depth research and benchmarking analysis, PreamSolutions has proposed an overall solution for the construction of smart factories in the lithium battery industry. The proposal focuses on planning and construction from three aspects: intelligent production, intelligent operation and intelligent decision-making.
At the production level, the production execution and optimization system (MES-like) is mainly used to realize the whole process management and monitoring, and the production process optimization is driven by the model of the processes of feeding, mixing, mounting, high temperature sintering and pulverization. Improving the first-time pass rate by inspection and test data analysis. Realizing energy saving and consumption reduction through energy consumption data analysis. Realizing management of equipment whole life-cycle, i.e. from design, procurement, installation, operation and maintenance to end-of-life, by equipment life-cycle management system. Managing equipment records and documents flexibly by master data management. Realizing daily operation and maintenance inspection management through failure and maintenance management. Realizing equipment status monitoring and predictive maintenance by real-time acquisition of equipment operation data. Realizing 3D visualization of factories and equipment through 3D model. Optimizing production, supply, marketing and storage process by supply-chain management system.
At the management level, it mainly uses the financial management and control system to realize the integrated management of finance and businesses, and realizes the functions of general ledger, receivables and payables through the financial basic functions; realizes the automatic generation of documents through the accounting function so as to calculate the various costs such as production in real time; and realizes the comprehensive budget management of the enterprise by budgeting management.
At the decision-making level, the company mainly facilitates the business decision analysis and industrial trends analysis, enhances the scientific and practical effect of the middle and high level management decision-making of the enterprise. The senior leaders can know operation management condition in time by leader cockpit, and middle level and senior leaders know industry trends and raw material and product price trends in time by industrial analysis to achieve the accuracy of investment, procurement and sales decisions. Achieving scientific management of various functional departments through financial, production, sales, inventory and other special analysis.
The construction of the lithium battery smart factory will greatly enhance the company's capabilities in automation, digitization, modeling and integration, and eventually realize enterprise intelligent production, intelligent management and intelligent decision-making.