Dürr Delivers One of the Biggest Paint Shops to SAIC Volkswagen

Date: 21/04/2021
Categories: Success stories

Despite all the restrictions caused by the coronavirus pandemic, Dürr handed over one of the biggest paint shops in China to SAIC Volkswagen right on schedule.

Dürr has supplied to SAIC Volkswagen joint venture (SVW) plant near Shanghai all of the plant engineering as well as the most comprehensive portfolio yet of its proprietary DXQ software products.

The new plant in Anting, which produces various electric models and conventionally powered vehicles, has a production capacity of 120 bodies per hour – twice that of a standard paint shop – and features a smart painting line that records around 3,500 digital data points for every individual body alone. Moreover, sensors supply many gigabytes of data in the form of process values for, i.e., temperature, pressure, and humidity – information that is useful to increase the overall equipment effectiveness (OEE) of a paint shop.

How the project came to be

In order to bring this project to life, mechanical engineering and the IT department worked in synergy right from the beginning: the digital solutions were developed in parallel with planning and implementing the comprehensive plant engineering – from the RoDip® dip coating system through paint booths with EcoDryScrubber dry separation to the oven and the air pollution control.

Over the 18-month project duration, six international product development teams from Dürr worked with up to ten developers in each case on the new technologies. To ensure a smooth IT installation in China, all the software functions were first tested in the Dürr headquarters in Bietigheim-Bissingen in a test environment that faithfully replicated the conditions in Anting.

DXQcontrol: one software to control the paint shop

SVW uses nearly all modules from the DXQcontrol software solution for higher-level plant control. It enables the life cycle of each body to be tracked from beginning to end. This starts with receipt of a production order, whereby the order information is translated into concrete production steps. In addition to order data management, the DXQbusiness.intelligence module is also used in a new form: for the first time, consumption data such as energy, water, or air usage can be evaluated historically over long periods. This lays the foundation for sustainable plant operation.

A further innovation is the use of mobile apps provided by various DXQ products. For example, employees can manage and filter alarm functions directly at the point of origin in the plant using tablets if the line comes to a stop.

Maintenance data, as well, can be accessed by employees using tablets by scanning QR codes on plant components. In this way, information can be called up directly at the point of origin. This enables the employees to work more flexibly than is possible with stationary PCs. At SVW in Anting, the DXQequipment.maintenance maintenance software is being used for the first time for a complete paint shop, and as a mobile version as well. The software has interfaces to the plant equipment’s almost 130 controllers, and uses them to determine each piece of equipment’s need for maintenance based on up-to-date information like operating hours or counter readings. SVW can also incorporate plant components from other suppliers here.

Several terabytes of digital data per year are collected, saved, and evaluated by the algorithms of the DXQplant.analytics application. If, for example, an employee detects an irregularity on the paint surface during the quality inspection, he enters it into the tablet. DXQplant.analytics correlates recorded quality results with order data (production number, derivative, color, etc.) and process data on the basis of artificial intelligence to identify patterns. A broad base of data makes it possible to track the fault causes in a targeted way and define measures. In this way, the system can be permanently optimized. For the first time, process data from other suppliers’ components and systems is also evaluated at SVW in Anting using DXQplant.analytics, for example in Application Technology.