A method for planning industrial robot networks for automotive welding and assembly lines

Abstract

Automotive robot network planning needs sound methods, new management style, and practices that are based on co‐operation, respect and trust. This is fundamental because networking means sharing and exchanging quality information at all levels of the enterprise. Robots working in welding and assembly lines need to communicate with each other, with their cell/line control computer, with the factory production control systems, with quality control systems, assuring that quality is checked at process level in order to gain valuable feedback from the shop floor. In this paper, we introduce some of the most important network planning and engineering/technology management principles and rules that robot networkers should keep in mind. In the follow‐up paper we illustrate actual simulation case studies and results, based on our established methods.

A simulation method and distributed server balancing results of networked industrial robots for automotive welding and assembly lines

“…As discussed by Ranky (2002c), in such developments, staff involved in the networking project has to be educated in the scope of the selected network(s) and the related connectivity issues, implying the following. The existing suppliers and their support for the selected network must be evaluated.…”

“…Simulation, as a method, like most system analysis and design methods, involves systems and models of them. A system for our purposes can be defined as a robot welding or assembly facility in an automotive environment, or robotized welding, or assembly process, either actual, or planned, with all important automation and human resources, computer communication systems, sensors, tools and materials, and fail-safe systems (Banks and Carson, 1984;Carr, 2002;Dornan, 2002;Ranky, 2002c).…”

Reconfigurable robot tool designs and integration applications

“…The key with such projects, as always, is not to be carried away by the exciting technology, but to identify the requirements, the cycle times, the tasks and their precedence rules, the task control constraints, and then based on solid industrial and R&D experience, simulation and budget constraints, take/design the best possible solution (Ranky, 2003b, c, d).…”