Data Mining as an Enabler for Customer Data Driven Vehicle Development

数据挖掘推动客户数据驱动车辆的开发进程

摘要:

对于汽车等面向消费者的行业，数据驱动的产品开发是一项关键的系统工程。数据驱动方法的前提是数据本身，由于现代车辆的联网能力不断提高，使得汽车制造商能够以内部总线信号的形式记录并储存客户数据。由于这些数据并不用于外部，只用于内部通信以保证车辆的安全性和功能性，这给这些数据的应用带来了一定的困难，因此汽车行业的主要问题在于如何利用数据挖掘技术从这些数据中提取客户需求及相关信息。为此，对上述数据应用问题进行了文献调研，并在此基础上开展数据挖掘的模拟研究，以确定现有数据挖掘过程在需求获取领域的适用性；进而提出一种扩展程序，使得数据挖掘技术能够应用于相关客户数据之中，从而加快车辆开发的进程。

Abstract:

Data-driven product development is a key technology for systems engineering especially for consumer-oriented industries such as the automotive industry. The basic prerequisite for all data driven approaches is data itself. Due to the increasing networking capabilities of modern vehicles， automotive manufactures are able to record and store customer data in the form of internal vehicle bus signals. The challenge in using this data is that it is not designed for external use， but for internal communication to ensure the safety and functionality of the vehicle. Therefore， the main question is how to extract customer needs and consumer-relevant information within this data using the process of data mining （DM）. Consequently， in this paper， a literature review on the aforementioned use case is conducted. Based on the literature research， a DM simulation game is conducted to determine the suitability of existing DM processes in the area of requirements elicitation. Finally， a process extension is proposed that helps to systematically focus the DM process on customer-relevant information and thus accelerate the overall process.