Centering on Humans - Intersectionality in Vision Systems for Human Order Picking
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| Názov: | Centering on Humans - Intersectionality in Vision Systems for Human Order Picking |
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| Autori: | Flores-García, Erik, Jeong, Yongkuk, Ruiz Zúñiga, Enrique, Wiktorsson, Magnus |
| Informácie o vydavateľovi: | Högskolan i Skövde, Institutionen för ingenjörsvetenskap Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling Department of Production Engineering, KTH Royal Institute of Technology, Södertälje, Sweden Department of Production Engineering, KTH Royal Institute of Technology, Södertälje, Sweden Department of Production Engineering, KTH Royal Institute of Technology, Södertälje, Sweden Cham 2024 |
| Druh dokumentu: | Electronic Resource |
| Abstrakt: | This study applies an intersectional approach to address concerns about diversity of data acquisition when applying computer vision systems in human order picking. The study draws empirical data from a single case study conducted at an automotive manufacturer. It identifies critical factors of intersectionality for the use of vision systems to enrich data collection in human order picking at four levels including form and function, experience and services, systems and infrastructure, and paradigm and purpose. These findings are helpful for mitigating bias and ensuring accurate representation of the target population in training datasets. The results of our study are indispensable for enhancing human-centricity when applying computer vision systems, and facilitating the acquisition of unstructured data in human order picking. The study contributes to enhancing diversity in human order picking, a situation that is highly relevant because of the variations in age, gender, cultural background, and language of staff. The study discusses theoretical and managerial implications of findings, alongside suggestions for future research. The authors would like to acknowledge the support of Swedish Innovation Agency (VINNOVA) project number 2022–02413. This study is part of the Dynamic Scheduling of Assembly and Logistics Systems using AI (Dynamic SALSA) project. This project is funded under SMART EUREKA CLUSTER on Advanced Manufacturing program. Dynamic Scheduling of Assembly and Logistics Systems using AI (Dynamic SALSA) |
| Témy: | Production Engineering, Human Work Science and Ergonomics, Produktionsteknik, arbetsvetenskap och ergonomi, Conference paper, info:eu-repo/semantics/conferenceObject, text |
| DOI: | 10.1007.978-3-031-71633-1_30 |
| URL: | IFIP Advances in Information and Communication Technology, 1868-422X ; 731 Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments : 43rd IFIP WG 5.7 International Conference, APMS 2024, Chemnitz, Germany, September 8-12, 2024, Proceedings, Part IV, p. 421-434 |
| Dostupnosť: | Open access content. Open access content info:eu-repo/semantics/restrictedAccess |
| Poznámka: | English |
| Other Numbers: | UPE oai:DiVA.org:his-24590 0000-0003-0798-0753 0000-0003-1878-773X 0000-0003-4180-6003 0000-0001-7935-8811 urn:isbn:978-3-031-71632-4 urn:isbn:978-3-031-71635-5 urn:isbn:978-3-031-71633-1 doi:10.1007/978-3-031-71633-1_30 ISI:001356136900030 Scopus 2-s2.0-85204635335 1482252603 |
| Prispievajúcí zdroj: | UPPSALA UNIV LIBR From OAIster®, provided by the OCLC Cooperative. |
| Prístupové číslo: | edsoai.on1482252603 |
| Databáza: | OAIster |
Nájsť tento článok vo Web of Science | Abstrakt: | This study applies an intersectional approach to address concerns about diversity of data acquisition when applying computer vision systems in human order picking. The study draws empirical data from a single case study conducted at an automotive manufacturer. It identifies critical factors of intersectionality for the use of vision systems to enrich data collection in human order picking at four levels including form and function, experience and services, systems and infrastructure, and paradigm and purpose. These findings are helpful for mitigating bias and ensuring accurate representation of the target population in training datasets. The results of our study are indispensable for enhancing human-centricity when applying computer vision systems, and facilitating the acquisition of unstructured data in human order picking. The study contributes to enhancing diversity in human order picking, a situation that is highly relevant because of the variations in age, gender, cultural background, and language of staff. The study discusses theoretical and managerial implications of findings, alongside suggestions for future research.<br />The authors would like to acknowledge the support of Swedish Innovation Agency (VINNOVA) project number 2022–02413. This study is part of the Dynamic Scheduling of Assembly and Logistics Systems using AI (Dynamic SALSA) project. This project is funded under SMART EUREKA CLUSTER on Advanced Manufacturing program.<br />Dynamic Scheduling of Assembly and Logistics Systems using AI (Dynamic SALSA) |
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| DOI: | 10.1007.978-3-031-71633-1_30 |