Open AccessGeneric Architecture for the Automatic Parametrization of Production Machine Assembly Programs
Author(s) -
Philipp Stephan,
Jessica Fisch,
Alperen Can,
Oliver Heimann,
Gregor Thiele,
Jörg Krüger
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1140/1/012025
Subject(s) - bottleneck , computer science , architecture , interface (matter) , industrial engineering , robot , information flow , process (computing) , data flow diagram , manufacturing engineering , software engineering , embedded system , engineering , artificial intelligence , database , programming language , operating system , linguistics , philosophy , art , bubble , maximum bubble pressure method , visual arts
In a high-mix low volume production environment, time to market is a key factor. However, one bottleneck lies in the often times manual parametrization of machines for new or modified designs. A truly flexible manufacturing environment therefore requires a continuous data flow from the design stages to the shop floor. This paper presents a concept for the automated parameterization of machines at a large automotive plant. Therefore, this paper initially discusses the results of a stakeholder analysis. The stakeholders comprise of different departments related to the product design and manufacturing processes. The requirements resulting from the interviews conducted with the stakeholders are grouped and ordered by priority. Secondly a general architecture for the control interface is presented. It includes multiple submodules, which model the continuous data flow between the departments and the production systems. The first main step of the data flow is the transformation of the information which is presented in various styles depending on the source departments to structured and standardized data. Thereafter machine parameters are generated automatically by a submodule using the structured input data and inference rules. Finally, the architecture supports the automatic transfer of the machine readable output data to the assembly line. To test the architecture a prototype comprising of more than 100 robots in a live production environment is implemented. It allows for a continuous data flow from the design and productions planning department to the robots. This enables a flexible process control, which up to today has supported the fast roll out of more than 100 new product variants. In contrast to the conventional manual setup of the machines for operation, the prototype was able to show that the monetary and time expenditure could be reduced by 95 percent.