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Characterizing Digital Dashboards for Smart Production Logistics
KTH, School of Industrial Engineering and Management (ITM), Sustainable production development, Avancerad underhållsteknik och produktionslogistik.ORCID iD: 0000-0003-0798-0753
KTH, School of Industrial Engineering and Management (ITM), Sustainable production development, Avancerad underhållsteknik och produktionslogistik.ORCID iD: 0000-0003-1878-773x
KTH, School of Industrial Engineering and Management (ITM), Sustainable production development, Avancerad underhållsteknik och produktionslogistik.ORCID iD: 0000-0001-7935-8811
Seoul National University.ORCID iD: 0000-0003-3792-0022
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2022 (English)In: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action / [ed] Kim, D.Y., von Cieminski, G., Romero, D., Seou, Korea, 2022, Vol. 664, p. 521-528Conference paper, Published paper (Refereed)
Abstract [en]

Developing digital dashboards (DD) that support staff in monitoring, identifying anomalies, and facilitating corrective actions are decisive for achieving the benefits of Smart Production Logistics (SPL). However, existing literature about SPL has not sufficiently investigated the characteristics of DD allowing staff to enhance operational performance. This conceptual study identifies the characteristics of DD in SPL for enhancing operational performance of material handling. The study presents preliminary findings from an ongoing laboratory development, and identifies six characteristics of DD. These include monitoring, analysis, prediction, identification, recommendation, and control. The study discusses the implications of these characteristics when applied to energy consumption, makespan, on-time delivery, and status for material handling. The study proposes the prototype of a DD in a laboratory environment involving Autonomous Mobile Robots.

Place, publisher, year, edition, pages
Seou, Korea, 2022. Vol. 664, p. 521-528
Keywords [en]
digital dashboards, smart production logistics, autonomous mobile robots
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Engineering and Management
Identifiers
URN: urn:nbn:se:kth:diva-320766DOI: 10.1007/978-3-031-16411-8_60ISI: 000869729400060Scopus ID: 2-s2.0-85138813083OAI: oai:DiVA.org:kth-320766DiVA, id: diva2:1707476
Conference
APMS 2022
Projects
EXPLAIN
Funder
Vinnova, S5014
Note

QC 20221101

Available from: 2022-10-31 Created: 2022-10-31 Last updated: 2022-11-04Bibliographically approved

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Flores-García, ErikJeong, YongkukWiktorsson, Magnus

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Production Engineering, Human Work Science and Ergonomics

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