According to the statistics of China Construction Machinery Industry Association, by the end of 2017, China's construction machinery industry has more than 8 million units. Over the past two years, the industry has improved, construction machinery sales continued to operate at a high level, and sales of domestic equipment increased further.
However, behind these results, we must be aware that China is still a big country in the production and marketing of engineering machinery, not a powerful country, especially in the quality and reliability of the engineering machinery products, far from the expectations of the market and users, the poor user satisfaction, and the occurrence of quality problems. Due to the convenience of information exchange and dissemination in the Internet era, these exposed quality problems have not been eliminated but enlarged through the Internet. For example, a user of a excavator has published the fault record of a brand excavator in micro-blog. Because the fault exists a certain universality, it quickly causes the resonance of other consumers, and then becomes the hot spot of Internet public opinion, which is spread quickly in the network, causing great harm to the brand and reputation of the enterprise.
Therefore, construction machinery enterprises need to further improve product quality, so as to better protect corporate reputation and brand. In the past few decades, in order to further improve the quality of products, construction machinery enterprises to improve the quality of enterprises by improving the management level, increasing R & D investment, introducing advanced equipment, training high skilled personnel and so on. But because of the production detection data, consumer data, product after-sales service data, mechanical equipment performance evaluation data, etc. often scattered in the production, sales, after-sales and other links, can not be systematically collected and analyzed, leading to the lack of targeted quality improvement measures, technical reform input is usually from the direction also The enterprise, not the user view, the quality problem is one-sided, and ultimately leads to the same scale of quality input and can not bring the equal level of consumer satisfaction.
For example, when we take part in the new product conference of the enterprise, we often hear how long the product selling point is, how many funds, how many patents, and how many improvements have been achieved, in order to reflect the advanced performance of the product, and few enterprises start from the user experience, and aim at the last generation of products. In the process of using, we sum up the areas worthy of improvement and make targeted improvements. Enterprise R & D products, fundamentally, to meet the needs of the market and users, and not just to show their own muscles, not pay attention to product quality and reliability promotion, product research and development is out of line with the market, is a simple pat head behavior, we are in this, there are many curves.
Nowadays, the Internet era provides a new solution to solve these problems -- the application of quality improvement based on big data technology. Large data technology from the beginning to the present, due to the lack of evaluation indicators and evolution rules to reflect the quality of the enterprise, the use of large data technology to improve the quality of the research and application of product is relatively rare. Related applications and research mainly focus on three directions: scientific research, enterprise application and government application. In these explorations, researchers and users have achieved certain results. For example, in large data applications, it realizes the use of large data to predict the risk of reentry for patients with congestive heart failure, predict the collective behavior of the network users in the future, describe the spatial distribution of the per capita income at the current national and regional levels, optimize the management decisions of the water resources, reduce traffic congestion and change Good public safety and other functions provide new ideas and directions for data application in the Internet era. In the field of engineering machinery, the Tsinghua University - Tian Yuan Science and technology intelligent equipment large data research center has also carried out active exploration. It is expected to further promote and consolidate the application of large data technology of intelligent equipment in China's engineering machinery industry, deep fusion of equipment and human interaction, and gradually realize the intelligent service and life cycle of the equipment. To provide more comprehensive digital services for customers and explore effective ways to improve product quality.
Under this background, Zhuo Yuan Zhi Lian Technology Co., Ltd., commissioned by the State Quality Inspection Administration, analyzed the quality development of engineering machinery through in-depth analysis of the product quality data characteristics of the engineering machinery industry, and summed up the key word bank of customer service feedback from many channels of the Internet. On this basis, using data crawling technology, principal component analysis (PCA), fuzzy mathematics, support vector machine (SVM) and machine learning and other methods, a large data model of quality promotion based on consumer demand is established. The model can automatically collect and deeply excavate the data of different channels of production detection, consumer use, product after-sales service, mechanical equipment performance evaluation and so on. Finally, it gives the direction conclusion of the quality promotion of the enterprise product, and changes the quality promotion input from "the enterprise feeling" to the "consumer" as "consumer". Demand "mainly, promote the quality promotion investment to meet the user's needs, can effectively help enterprises to discover the real benefits of the quality promotion path, the formation of more efficient quality input - product returns are circulating, thus helping enterprises to create a stronger market competition!
