As part of its electric initiative, Volkswagen Sachsen GmbH is pursuing the goal of gradually producing several models of the so-called ID family. From November , the vehicle plant in Zwickau will produce these models for Volkswagen and other Group brands such as Audi and Seat.
The different requirements of MEB production and the expansion to a multi-brand plant demand comprehensive measures regarding modernization and digitalization. The vision is to build the "leading plants in the application of Industry 4.
This will enable the company to take the lead in the brownfield benchmark of the Volkswagen brand for the digitalization of large and small series production of electric vehicles and components. The "IoT Readiness" project assessed the current status of digitization in the individual trades of the automotive process chain, including logistics and quality assurance. The potential digitization topics are analyzed and evaluated together with the respective specialist departments and subsequently chronologically arranged in a roadmap.
A process model was developed specifically for the requirements of digitization in the automotive industry. It is based on a holistic regulatory framework that considers people, technology and organization at the physical, infrastructural and virtual levels. In order to meet the compact time frame, the process steps of maturity assessment, analysis of potential and competition were carried out in parallel. The aim of the project was to evaluate the status quo of the manufacturing system processes in terms of digitalization and IoT readiness by means of the Modular Transversal Kit MQB.
More than 50 meetings were held in nine areas, resulting in a total of 31 confirmed potentials. The defined and developed topics for the IoT readiness strategy of Volkswagen Sachsen GmbH offer tremendous potential and corresponding cost savings of several million euros. Examples include an intelligent sensor evaluation platform for carrying out root cause analyses. The aim is to improve the fault elimination process, and the use of IP cameras and artificial neural networks to increase the degree of automation in quality control.
