Designing and implementation of an intelligent manufacturing system
Abstract: Purpose: The goal of
XPRESS is to establish a breakthrough for the factory of the future with a new
flexible production concept based on the generic idea of “specialized
intelligent process units” (“Manufactrons”) integrated in cross-sectoral
learning networks for a customized production. XPRESS meets the challenge to
integrate intelligence and flexibility at the “highest” level of the production
control system as well as at the “lowest” level of the singular machine.
Design/methodology/approach: Architecture of a manufactronic networked
factory is presented, making it possible to generate particular manufactrons
for the specific tasks, based on the automatic analysis of its required
features.
Findings: The manufactronic factory concept meets the challenge to
integrate intelligence and flexibility at the “highest” level of the production
control system as well as at the “lowest” level of the singular machine. The
quality assurance system provided a 100% inline quality monitoring, destructive
costs reduced 30%-49%, the ramp-up time for the set-up of production lines decreased
up to 50% and the changeover time decreased up to 80%.
Research limitations/implications: Specific features of the designed
manufactronic architecture, namely the transport manufactrons, have been tested
as separate mechanisms which can be merged into the final comprehensive at a
later stage.
Practical implications: This concept is demonstrated in the automotive
and aeronautics industries, but can be easily transferred to nearly all
production processes. Using the manufactronic approach, industrial players will
be able to anticipate and to respond to rapidly changing consumer needs,
producing high-quality products in adequate quantities while reducing costs.
Originality/value: Assembly units composed of manufactrons can flexibly
perform varying types of complex tasks, whereas today this is limited to a few
pre-defined tasks. Additionally, radical innovations of the manufactronic
networked factory include the knowledge and responsibility segregation and
trans-sectoral process learning in specialist knowledge networks.
Author: Michael Peschl,
Norbert Link, Michael Hoffmeister, Gil Gonçalves, Fernando L. F. Almeida
Journal Code: jptindustrigg110034
