NIE 2023 | Zhibang International Jiang Xue: Digital Intelligence Integration Helps Manufacturing Enterprises Reach the 'Intelligent' High Ground

Jiang Xue stated that due to the new possibilities brought about by innovative technologies and the new changes brought about by the development of the economic environment, intelligent manufacturing is an inevitable trend in the development of the manufacturing industry. With the support of technologies such as big data, the Internet of Things, cloud computing, and advanced analytics, intelligent production, intelligent services, intelligent factories, and intelligent logistics have become the core of manufacturing development. Therefore, intelligent development is the goal and approach for manufacturing to reduce costs, improve efficiency, achieve flexible production, develop high-quality products, and realize green development.

However, the intelligent transformation is not achieved overnight. Challenges such as inaccurate cost accounting, substandard product quality, hindered cooperation with dishonest customers, and inefficient management of collaboration barriers are omnipresent.

Due to the involvement of multiple departments in budgeting, there are many non-standard product quotation elements with long calculation cycles. There are significant fluctuations in related materials/employees, with many uncontrollable factors, leading to the separation of business and finance. The entire production process is not tracked, and cost accounting is not comprehensive.

Due to the variety of raw materials, complex testing procedures, high difficulty in quality control during production, lack of process feedback, and long feedback cycles after problems arise, there are high requirements for refined management.

Due to the growth in customized, small-batch, and multi-variety order demands, there are many urgent orders inserted. The production progress of orders cannot be updated in real time, resulting in frequent material shortages, inaccurate complete set tracking, and unclear delivery cycles.

Due to the isolated data of subsidiaries under the industrial chain, multiple systems coexist, coding is not unified, integration is difficult, internal and external collaboration and decision-making are inefficient, operational costs rise, and it is hard to form a competitive synergy.

Jiang Xue pointed out that as the development of 'digital intelligence' enters a deeper phase, Chinese large, medium, and small enterprises are still exploring and moving forward. For large enterprises, there are challenges such as difficulty in resource coordination, high information barriers; financial collaboration difficulties, data unification; slow business processes, high management costs, and high barriers to independent research and development with long cycles. Small and medium-sized enterprises face issues such as being more sensitive to cost and time control; difficulty in ensuring data security; unclear model layout and implementation paths, which make them unwilling, afraid, or unable to transform.

Jiang Xue stated that service quality and the completeness of solutions are influencing factors in the quality and progress of digital and intelligent transformation, while data integration penetration is a key factor for manufacturing enterprises to break through bottlenecks in digital and intelligent transformation. What enterprises need is a set of digital and intelligent solutions that possess data integration thinking, can provide full lifecycle services for enterprises, and can create exclusive solutions for them.Integrated Management System.

The digital and intelligent integrated management system is applied across all scenarios, product life cycles, and roles. It helps companies improve delivery punctuality, reduce management costs and defective rates, achieve integration of business and finance, increase sales conversion rates, and make enterprise data flow smoothly like water, making management benefits tangible. Enterprises without a digital and intelligent integrated management system will face issues such as poor data timeliness, low data accuracy, weak data relevance, and low quality of data analysis results. They will also face greater difficulties in collaboration, decision-making, problem tracing, visual analysis, and other aspects.

The digital intelligence integrated management system features a platform that is compatible with all data, an integrated algorithm advantage, a mature document association mechanism, interconnectivity across multiple business sectors, high-quality data analysis templates, and efficient collaboration within the system. It achieves digital intelligence integration and the interconnection of all things. In terms of interconnectivity across multiple business sectors, the numerical integration system ensures seamless business linkages through internal integration, vertical integration, horizontal integration, and underlying data integration. This drives business exploration, helps management to gain multi-dimensional insights, and enables real-time control of business operations, acting as the helmsman.