F. Bonavolontã, D. Dallet, E. Erra, A. Grassi, Valentina Popolo, A. Tedesco, Silvestro Vespoli
{"title":"在增强现实辅助的工业4.0程序中测量工人的绩效","authors":"F. Bonavolontã, D. Dallet, E. Erra, A. Grassi, Valentina Popolo, A. Tedesco, Silvestro Vespoli","doi":"10.1109/I2MTC43012.2020.9129320","DOIUrl":null,"url":null,"abstract":"Augmented Reality (AR) is considered as one of the enabling technologies offering the largest potential to improve the way in which modern factories operate, thus becoming an integral part of the Industry 4.0 paradigm. However, there are still some aspects that hinder the widespread adoption of AR. In particular, one limitation is the lack of a measurement methodology of the impact that AR has on the worker's performance in a manufacturing environment. In this regard, the present work addresses the assessment of the performance of workers when they carry out a task, supported by an AR system. To this purpose, comparative experimental tests were carried out on two groups of volunteers who were given a specific assembly task (one group followed paper instructions, whereas the other followed AR-administered instructions). To measure the worker's performance and assess the impact of AR, two figures of merit were used: the processing time required to complete a task and the number of errors made. The experimental tests showed that, while the processing times were comparable between the two groups, administering instructions through AR resulted in a lower error rate and hence an improved quality of the product.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Measuring Worker’s Performance in Augmented Reality-assisted Industry 4.0 Procedures\",\"authors\":\"F. Bonavolontã, D. Dallet, E. Erra, A. Grassi, Valentina Popolo, A. Tedesco, Silvestro Vespoli\",\"doi\":\"10.1109/I2MTC43012.2020.9129320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Augmented Reality (AR) is considered as one of the enabling technologies offering the largest potential to improve the way in which modern factories operate, thus becoming an integral part of the Industry 4.0 paradigm. However, there are still some aspects that hinder the widespread adoption of AR. In particular, one limitation is the lack of a measurement methodology of the impact that AR has on the worker's performance in a manufacturing environment. In this regard, the present work addresses the assessment of the performance of workers when they carry out a task, supported by an AR system. To this purpose, comparative experimental tests were carried out on two groups of volunteers who were given a specific assembly task (one group followed paper instructions, whereas the other followed AR-administered instructions). To measure the worker's performance and assess the impact of AR, two figures of merit were used: the processing time required to complete a task and the number of errors made. The experimental tests showed that, while the processing times were comparable between the two groups, administering instructions through AR resulted in a lower error rate and hence an improved quality of the product.\",\"PeriodicalId\":227967,\"journal\":{\"name\":\"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2MTC43012.2020.9129320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC43012.2020.9129320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring Worker’s Performance in Augmented Reality-assisted Industry 4.0 Procedures
Augmented Reality (AR) is considered as one of the enabling technologies offering the largest potential to improve the way in which modern factories operate, thus becoming an integral part of the Industry 4.0 paradigm. However, there are still some aspects that hinder the widespread adoption of AR. In particular, one limitation is the lack of a measurement methodology of the impact that AR has on the worker's performance in a manufacturing environment. In this regard, the present work addresses the assessment of the performance of workers when they carry out a task, supported by an AR system. To this purpose, comparative experimental tests were carried out on two groups of volunteers who were given a specific assembly task (one group followed paper instructions, whereas the other followed AR-administered instructions). To measure the worker's performance and assess the impact of AR, two figures of merit were used: the processing time required to complete a task and the number of errors made. The experimental tests showed that, while the processing times were comparable between the two groups, administering instructions through AR resulted in a lower error rate and hence an improved quality of the product.