kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Data flow structure for multimodal human-robot collaboration in material handling
KTH, School of Industrial Engineering and Management (ITM), Production engineering.ORCID iD: 0000-0002-6090-7187
KTH, School of Industrial Engineering and Management (ITM), Production engineering.ORCID iD: 0000-0003-1878-773x
KTH, School of Industrial Engineering and Management (ITM), Production engineering.ORCID iD: 0000-0001-7935-8811
2023 (English)In: 29th IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Shaping the future - Data-driven Engineering, Innovation and Entrepreneurship, Edinburgh, 2023, 2023Conference paper, Oral presentation only (Refereed)
Abstract [en]

Material handling systems are challenges by ever increasing complexity due to customization, new product technologies, circularity requirements and increasing supply network interactions. In such a dynamic environment, proper use of robots can boost the efficiency of material handling systems. However, human-robot collaboration in material handling has not been in focus as a research agenda. Thus, it is not clear how the different requirements of human and robots from a data flow perspective should be addressed. In addition, human-robot collaboration in material handling should take into account some specific characteristics such as low visibility caused by constant movement for people, robots, and materials. This paper aims to take a step to cover this gap by proposing a framework that uses multimodal technologies to serve the purpose of safe and efficient human-robot collaboration in material handling. The proposed framework includes aspects such as human thoughts, robot assistance, real-time sensing, and human knowledge. A material handling scenario in a tested environment is presented for demonstration and verification purposes of the proposed framework. The results show that the proposed framework is beneficial to address the different requirements of human and robot in material handling. In addition, it is argued that efficient human-robot collaboration in material handling requires close attention to the monitoring of the work environment to ensure safe and efficient co-existence and collaboration.

Place, publisher, year, edition, pages
2023.
Keywords [en]
data-driven, Industry 4.0, IoT, human-robot collaboration, AMR
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Production Engineering
Identifiers
URN: urn:nbn:se:kth:diva-339601DOI: 10.1109/ICE/ITMC58018.2023.10332275Scopus ID: 2-s2.0-85181085063OAI: oai:DiVA.org:kth-339601DiVA, id: diva2:1812069
Conference
29th International Conference on Engineering, Technology, and Innovation, ICE 2023, Edinburgh, United Kingdom of Great Britain and Northern Ireland, Jun 19 2023 - Jun 22 2023
Note

Part of ISBN 9798350315172

QC 20231121

Available from: 2023-11-15 Created: 2023-11-15 Last updated: 2024-02-22Bibliographically approved
In thesis
1. Data-driven Production Logistics: A value-oriented transition approach
Open this publication in new window or tab >>Data-driven Production Logistics: A value-oriented transition approach
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In the current manufacturing environment, the constant evolution ofproducts and services creates complexities in managing the flow ofinformation. Production logistics (PL), as a vital element of manufacturingsystems, are highly influenced by these dynamics. Earlier research hasemphasised the need for seamless data flow from start to finish to cope withthese dynamics through digitalisation transition projects. However, earlierresearch argue that these projects are often technology-oriented and lack avalue-oriented perspective.Earlier research has indicated that digitalisation initiatives such asIndustry 4.0 emphasise the technological aspects of transitioning to a datadrivenfuture for production logistics. Thus, it is argued by earlier researchthat value creation is not solely technical but also socio-technical,highlighting the interplay between technology and social factors in shapingindustrial outcomes. Existing literature often overlooks the critical aspectof value orientation. This thesis contends that it is crucial for companies toadopt frameworks that guide the transition from data to value. Theseframeworks are designed to emphasise a value-oriented perspective, whichis particularly important when advancing towards data-driven productionlogistics.However, three major areas require further research. Firstly, it isimportant to understand the characteristics of a data-driven PL system.Secondly, there is an absence of tools or systematic methods to assess theflow of information in production logistics for the purpose of mapping valueand pinpointing waste resulting from data inefficiencies. Thirdly, it isnecessary to understand how to align data-driven solutions with the sociotechnicalenvironment and user-centric considerations.This thesis begins by identifying PL system requirements through asystematic literature review, case studies, and experiments, establishing asystematic foundation for value creation in the transition to data-driven PL.It also proposed a method for detection of waste on the shopfloor caused byinformation flow inefficiencies.The major contribution to the literature is the proposed framework forvalue-oriented transition to data-driven production logistics. Thisframework includes several findings of the thesis. The findings offerpractical tools for waste detection, digital service design, and acomprehensive framework for a value-oriented transition in data-drivenproduction logistics, providing valuable guidance to industry practitioners.

Abstract [sv]

Dagens tillverkande miljöer präglas av komplexa informationsflöden med kontinuerlig utveckling och lansering av produkter och tjänster.  Produktionslogistik (PL), som ett viktigt element i tillverkningssystem, påverkas starkt av denna komplexa och dynamiska miljö. Tidigare forskning har betonat behovet av ett sömlöst flöde av data från början till slut för att hantera denna dynamik inom digitaliseringsprojekt. Forskningen har dock också visat att dessa projekt, inom ramen för Industri 4.0, riskerar att bli teknikorienterade och sakna ett värdeorienterat perspektiv, i detta fall vid övergången till en datadriven produktionslogistik. I dessa sammanhang måste värdeskapandet ses som inte enbart tekniskt utan också sociotekniskt, vilket framhäver samspelet mellan teknik och sociala faktorer i formandet av industriella resultat. Denna avhandling fokuserar den kritiska aspekten av värde och utgår från att det är avgörande för företag att anta ramverk som knyter data till värde och tar ett värdeorienterat perspektiv, vilket är särskilt viktigt i utvecklingen mot datadriven produktionslogistik (PL). Det finns dock tre områden som kräver ytterligare forskning. För det första är det viktigt att förstå egenskaperna hos ett datadrivet PL-system. För det andra finns det en brist på verktyg eller systematiska metoder för att bedöma informationsflöden inom produktionslogistik i syfte att kartlägga värde och identifiera slöserier orsakade av ineffektiv datahantering. För det tredje är det nödvändigt att förstå hur man anpassar datadrivna lösningar till den sociotekniska miljön och användarcentrerade överväganden. Denna avhandling börjar med att identifiera krav på PL-system genom en systematisk litteraturöversikt, fallstudier och experiment, vilket etablerar en systematisk grund för värdeskapande i övergången till datadriven PL. Den beskriver också en metod för att upptäcka slöserier på verkstadsgolvet som orsakas av ineffektiviteter i informationsflödet. Slutligen presenterar avhandlingen ett ramverk för en värdeorienterad övergång till datadriven produktionslogistik. Det största bidraget till litteraturen är det föreslagna ramverket för värdeorienterad övergång till datadriven produktionslogistik. Detta ramverk innehåller flera resultat av avhandlingen. Resultaten sammanfattas även i praktiska verktyg för att identifiera slöserier, utveckling av digitala tjänster och ett omfattande ramverk för en värdeorienterad övergång mot datadriven produktionslogistik, vilket framförallt riktar sig mot en användning av industrins praktiker.

Nyckelord Intern logistik, Smart, Värde, Tillverkning, Teknologi

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2023. p. 101
Keywords
Internal logistics, Smart, Value, Manufacturing, Technology
National Category
Engineering and Technology
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-339865 (URN)978-91-8040-782-3 (ISBN)
Public defence
2023-12-13, C1 / https://kth-se.zoom.us/j/69895972941, Kvarbergagatan 12, Södertälje, 10:00 (English)
Opponent
Supervisors
Available from: 2023-11-22 Created: 2023-11-21 Last updated: 2024-01-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopusConference website

Authority records

Zafarzadeh, MasoudJeong, YongkukWiktorsson, Magnus

Search in DiVA

By author/editor
Zafarzadeh, MasoudJeong, YongkukWiktorsson, Magnus
By organisation
Production engineering
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 113 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf