Scheduling mobile robots in part feeding systems

Emilio Morett, Elena Tappia and Marco Melacini

A chapter in Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management, 2021, pp 129-149 from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management

Abstract: Purpose: Industry 4.0 has increased the availability of real-time data in manufacturing systems, but scientific evidence about the value stemming from such data is still lacking in several fields. This paper studies data-driven approaches for the assignment of tasks to a fleet of mobile robots transporting parts to the stations of a mixed model assembly line. The approaches exploit real-time data concerning the robots and assembly stations state. Methodology: An agent-based simulation model of the system, including factory warehouses, assembly stations, and robots, is developed and validated through a real case in the automotive industry. Findings: The paper proposes a model that measures the part feeding system performance in terms of transportation tasks completion time, idle time of the assembly stations due to lack of materials, and amount of inventories at the assembly line. Different data-driven approaches are considered, differing among each other for the type of real-time data used and for the update frequency of the task assignment. Originality: The developed model enriches the ones presented in previous literature by including new information (e.g., robots failures) and new data-driven approaches, such as the dynamic assignment of tasks to robots.

Keywords: Advanced Manufacturing; Industry 4.0 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/249614/1/hicl-2021-31-129.pdf (application/pdf)

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:zbw:hiclch:249614

DOI: 10.15480/882.3979

Access Statistics for this chapter

More chapters in Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL) from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().