Data Quality and the Control of Automotive Manufacturing

Project Picture - Data Quality and the Control of Automotive Manufacturing

Project Description

The automotive manufacturing domain of this day and age is faced with a number of challenges. According to Maslow’s (1908-1970) hierarchy of needs, the desire for individuality will steadily increase along with the growing prosperity of people. As a consequence, the concept of mass customization has been evolving since the 1990s, i.e. producing goods and services to meet individual customer’s needs with near mass production efficiency. The progressing globalization, furthermore, yields new competitors on the one hand, and saturated markets, especially in Europe and Northern America, on the other hand. This leads to a high pressure to be innovative while at the same time the time to market (TTM) is expected to be reduced. Therefore, in the last decades, car manufacturers adopted simultaneous engineering (SE) approaches for the development cycles of their products; on that score, well-performing flows of information are considered to be among the fundamental prerequisites. In order to implement them, a high degree of standardization is required. As a side effect, many enterprises have lost some of their flexibility; but flexibility is essential to be able to efficiently react to the rapidly changing environmental circumstances.
Against this background the Audi AG has launched the project Elektronische Wagenbegleitkarte (eWBK) to replace the paper media by an IT system (Figure 1). The necessary input data, with respect to a product model and an assembly line, is given by

  • Product Configuration Data
  • Bill Of Materials
  • Assembly Process Plan

These components are combined in a manufacturing execution system (MES) which performs a resolving procedure to determine the required tasks and parts for each workstation and customer order, respectively. By doing so, the complicated interpretation processes for the operators will be dispensable in the future. In addition to that, firstly, paper won’t be wasted any longer and, secondly, the cycle times can be reduced. On the whole, not only the risk of misinterpretation will be minimized but also the degree of flexibility will increase. This, in turn, allows for new paradigms like late-time changes of customer orders or an even more efficient regulation of repair and restoring work.

MDD-based Verification of Automotive Manufacturing Data
In the course of this project, a new approach to verify consistency of the input data has been developed. For this purpose, Multi-Valued Decision Diagrams (MDDs) (Figure 2) are deployed to efficiently encode large sets of product configurations. The verification approach is based upon the set of all valid product configurations, which is why a compilation of the knowledge of feasible and infeasible combinations of equipment features is required. Since the data structure yielded by this compilation procedure often consumes high amounts of memory, it will be attempted to decrease these by choosing an adequate variable ordering. Therefore, new methods for the search of both proper variable orderings and efficient compilation sequences are investigated. In addition to that, we develop a methodology to increase the data quality of the product configuration data (PCD) by using meta-rules. The expert knowledge on valid and invalid product configurations is encoded by a set of constraints. Our approach makes it possible to formalize this expert knowledge and to define design patterns which the set of constraints must adhere to.

Project Period

    2009-11-01 – 2012-10-31

Project Members

Involved Institutions

Related Publications

  1. Rüdiger Berndt, Peter Bazan, Kai-Steffen Jens Hielscher und Reinhard German, “Construction Methods for MDD-based State Space Representations of Unstructured Systems,” Proceedings of the 17th International GI/ITG Conference on “Measurement, Modelling and Evaluation of Computing Systems and “Dependability and Fault-Tolerance, Bamberg, Germany, pp. 43-56, März 2014
  2. Rüdiger Berndt und Dirk Zitterell, “Towards High-Quality Automotive Product Configuration Data using Meta-Rules,” Proceedings of the 17th International Conference on Information Quality, Paris, November 2012
  3. Rüdiger Berndt, Peter Bazan, Kai-Steffen Jens Hielscher, Reinhard German und Martin Lukasiewycz, “Multi-Valued Decision Diagrams for the Verification of Consistency in Automotive Product Data,” Proceedings of 12th International Conference on Quality Software (IEEE), Xi’an, pp. 189-192, August 2012  
  4. Rüdiger Berndt, Peter Bazan und Kai-Steffen Jens Hielscher, “MDD-based Verification of Car Manufacturing Data,” Third International Conference on Computational Intelligence, Modelling & Simulation (IEEE), Malaysia, pp. 187-193, September 2011  
  5. Rüdiger Berndt, Peter Bazan und Kai-Steffen Jens Hielscher, “On the Ordering of Variables of Multi-Valued Decision Diagrams,” Leistungs-, Zuverlässigkeits- und Verlässlichkeitsbewertung von Kommunikationsnetzen und Verteilten Systemen, Hamburg, pp. 89-98, September 2011
  6. Rüdiger Berndt und Juliane Blechinger, “Der Weg ist das Ziel – Fahrplan zur Entdeckung von datenqualitätsgefährdenden Ursachen,” in Wirtschaftsinformatik & Management (04), pp. 40-45, 2011
  7. Florian Risch, Rüdiger Berndt und Jörg Franke, “Schlanke Informationsflüsse für eine effiziente Produktion,” in Zeitschrift für wirtschaftlichen Fabrikbetrieb (10), pp. 706-710, 2011