Optimised scheduling in human–robot collaboration – a use case in the assembly of printed circuit boards

Karin Bogner, Ulrich Pferschy, Roland Unterberger and Herwig Zeiner

International Journal of Production Research, 2018, vol. 56, issue 16, 5522-5540

Abstract: Advances in the technologies of sensors and lightweight robots increasingly enable direct physical interaction between humans and robots. This so-called human–robot collaboration is supposed to offer more flexibility in production processes, as opposed to fully automated processes. The aim of this contribution is to describe an integer linear programming model which optimally coordinates the distribution of tasks between humans and robots in a realistic production process of printed circuit boards (PCBs), where the objective is to minimise the completion time of a board. In addition, we discuss an extended case wherein a whole set of different boards is to be assembled, which is highly relevant for low volume production with a high degree of customisation. After stating an extended integer linear programming (ILP) formulation, we propose two practical approaches for solving the computationally more complex second scenario: an order-based heuristic approach and a matheuristic applying a truncated variant of the ILP model with different sequencing strategies. The computational evaluation based on a real-world use case from the PCB industry underlines the efficacy of the matheuristic approach for obtaining a good overall makespan.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2018.1470695 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:56:y:2018:i:16:p:5522-5540

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2018.1470695

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().