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Titel: A new approach to plan manual assembly
VerfasserIn: Manns, Martin
Fischer, Klaus
Du, Han
Slusallek, Philipp
Alexopoulos, Kosmas
Sprache: Englisch
Titel: International journal of computer integrated manufacturing : IJCIM
Bandnummer: 31
Heft: 9
Seiten: 907-920
Verlag/Plattform: Taylor & Francis
Erscheinungsjahr: 2018
Freie Schlagwörter: Assembly planning
stochastic models
manual assembly
human motion modelling
DDC-Sachgruppe: 600 Technik
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: Today’s methods for planning manual assembly processes have been developed for many decades. Besides technical advances, organisational innovations such as concurrent engineering have made a major contribution to both cost and quality of the final product. However, mass customisation and personalisation of products have imposed additional requirements. Planning should be performed for many different product variants while at the same time planning cost and time to market should be kept at a minimum level. The objective of this paper is to present a new approach for planning of manual assembly processes that goes beyond established industry practices, which has the potential to provide planning teams with tools to evaluate different assembly process scenarios faster, eliminating the need for physical prototypes. The approach is based on controlled natural language textual descriptions of assembly tasks, automatic generation human motions from the textual descriptions based on data-driven, statistical motion models and interactive process optimisation. The proposed method is evaluated in a pilot case from automotive industry regarding ease of use, extensibility, adaptability, motion realism and motion diversity. Results suggest that while the approach addresses practical needs of production planning, technical challenges remain in order to make it ready to be implemented into digital planning environments.
DOI der Erstveröffentlichung: 10.1080/0951192X.2018.1466396
URL der Erstveröffentlichung: https://www.tandfonline.com/doi/full/10.1080/0951192X.2018.1466396
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-393469
hdl:20.500.11880/35477
http://dx.doi.org/10.22028/D291-39346
ISSN: 1362-3052
0951-192X
Datum des Eintrags: 22-Mär-2023
Fakultät: MI - Fakultät für Mathematik und Informatik
Fachrichtung: MI - Informatik
Professur: MI - Prof. Dr. Philipp Slusallek
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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