High-tech manufacturing refers to the manufacturing that have a considerable high investment intensity for research and development cost, including pharmaceutical manufacturing, aerospace manufacturing, electronic and communication equipment manufacturing, computer and office equipment manufacturing, medical equipment and meters manufacturing, and information chemicals manufacturing. As the concept of Industry 4.0 being put forward, the United States, Japan, China and other countries are pushing intelligent manufacturing in various industries in order to replace the traditional mechatronic products. All those countries are looking for getting a piece of land in IOT business. The concept of Industry 4.0 consists of two most important parts: intelligent plant and intelligent manufacturing. Intelligent production is not only the embodiment of science and technology; the massive Big Data analytics and applications behind intelligent production is also an important basis for business intelligence management.

As a technology and knowledge intensive industry, high-tech manufacturing has a much closer relationship with Big Data compared with other industries. On one hand, high-tech manufacturing is a critical assist to Big Data development. On the other hand, high-tech manufacturing is also an important beneficiary of Big Data. Big Data have direct influence to high-tech manufacturer, and it also have indirect influence through manufacturer鈥檚 external environment by putting high-tech manufacturing at a more important position in economic development and promoting its interaction and integration with other industries. According to manufacturing industry鈥檚 major issues and product lifecycle, there are five major Big Data analytics applications for high-tech manufacturing: material quality control, equipment abnormal monitoring and prediction, parts lifecycle prediction, process monitoring and warning, yield analysis and warranty analysis.

China鈥檚 high-tech manufacturing is undertaking a thriving period. It is now a hotspot for manufacturer to develop intelligent plants. On the other hand, the shortage of manpower, wage inflation, shorter delivery cycle and the fluctuated market demand set more challenges to industry upgrade. The actual purpose for this upgrade is to improve productivity and efficiency while manage to control the production cost.

At present, there are three major problems faced by high-tech manufacturing. Firstly, unexpected material problems or equipment failure directly impacts the production capacity. It causes higher cost and losses of resources. Secondly, the instable process leads to the decreasing of product yield. It directly influences the profit and customer satisfaction. Thirdly, manufacture procedure becomes faster and the key factor for enterprises to make profits lies in how to speed up production.

AAS brings insight into how high-tech manufacturing companies can deal with the market changes, especially the industry upgrade and market challenges. AAS develops a open Big Data platform and provides a full services including data collection, data mining, data analytics and data visualization. AAS helps enterprise to customize application system and infrastructure, and provide solutions including product and process quality, supply and demand planning, sales and marketing, and data management.

High-tech Manufacturing Big Data Solution

Early warning of problems
Prospective maintenance
Cost control
Data mining and integration
Customer Insight

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