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Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).ORCID iD: 0000-0003-4616-189X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0002-0006-283X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-8679-8049
2017 (English)In: Procedia Manufacturing, ISSN 2351-9789, Vol. 11, p. 1279-1287Article in journal (Refereed) Published
Abstract [en]

This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.

Place, publisher, year, edition, pages
2017. Vol. 11, p. 1279-1287
Keywords [en]
Adaptive Production, Augmented Reality, Human-Robot Collaboration, Industry 4.0, Robotics, Unity Game Engine, Virtual Reality
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-216563DOI: 10.1016/j.promfg.2017.07.255ISI: 000419072100151Scopus ID: 2-s2.0-85029856140OAI: oai:DiVA.org:kth-216563DiVA, id: diva2:1155635
Note

QC 20171108

Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2022-06-26Bibliographically approved
In thesis
1. Introducing a procedural knowledge model for enhancing industrial process adaptiveness
Open this publication in new window or tab >>Introducing a procedural knowledge model for enhancing industrial process adaptiveness
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial processes are mainly based on procedural knowledge that must be continually elicited from experienced operators and learned by novice operators. In the context of Industry 4.0, machines already play a key role in knowledge transfer; however, new models and methods based on the artificial intelligence advances of the past few years need to be developed and applied. The future of human-machine collaboration is not limited to physical applications, but it has the potential to harness both the strength of human skills, experience and the computational power provided by the surrounding machines for truly adaptive industrial processes. The winning recipe is a balance between letting humans exploit their inherent experience and letting machines integrate the missing skills to preserve production standards. This work introduces a procedural knowledge model to be used for the design of industrial and scientific adaptive processes and it paves the way to transforming human-machine collaboration into an efficient solution to make industrial and scientific processes resilient to a constantly changing world.

Abstract [sv]

Industriella processer baseras huvudsakligen på den procedurella kunskapen som fortlöpande måste tas fram och anpassas av erfarna operatörer och läras in av nybörjare. Inom ramen för Industri 4.0 spelar maskiner redan en nyckelroll i kunskapsöverföring; dock behöver nya modeller och metoder utvecklas och användas, som baseras på de senaste årens framsteg inom artificiell intelligens. Framtiden för samarbete mellan människa och maskin är inte begränsad till fysiska applikationer, utan den har potential att utnyttja såväl styrkan i mänsklig kompetens och erfarenhet som den beräkningskraft som de omgivande maskinerna tillhandahåller, för att åstadkomma verkligt anpassningsbara industriella processer. Det vinnande receptet är att hitta en balans mellan att låta människor utnyttja sina egna erfarenheter och att låta maskiner tillhandahålla de saknade färdigheterna för att kunna följa produktionsstandarder. I detta arbete introduceras en procedurell kunskapsmodell som kan användas för utformning av industriella och vetenskapliga, anpassningsbara processer och banar väg för att omvandla samarbete mellan människor och maskiner till effektiva lösningar för att göra industriella och vetenskapliga processer följsamma i en ständigt föränderlig värld.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2021. p. 184
Series
TRITA-ITM-AVL ; 2021:35
Keywords
procedural knowledge, industrial process, industry 4.0, adaptiveness, human-machine collaboration
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-300208 (URN)978-91-7873-963-9 (ISBN)
Public defence
2021-09-17, https://kth-se.zoom.us/j/63998476971, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2021-08-30 Created: 2021-08-27 Last updated: 2022-06-25Bibliographically approved

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de Giorgio, AndreaRomero, MarioOnori, MauroWang, Lihui

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