{"title":"Automated Pallet Racking Examination in Edge Platform Based on MobileNetV2: Towards Smart Manufacturing","authors":"","doi":"10.1007/s10723-023-09738-y","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Pallet racking is a critical element of the production, storage, and distribution networks businesses worldwide use. Ongoing inspections and maintenance are required to ensure the workforce's safety and the stock's protection. Currently, certified inspectors manually examine racks, which causes operational delays, service charges, and missing damages because of human error. As businesses move beyond smart manufacturing, we describe an automated racking assessment method utilizing an integrated framework, MobileNetV2-you only look once (YOLOv5). The proposed method examines the automated pallet tracking system and detects multiple damages based on edge platforms during pallet racking. It employs YOLOv5 in conjunction with the Block Development Mechanism (BDM), which detects defective pallet racks. We propose a device that attaches to the moveable cage of the forklift truck and provides adequate coverage for the neighboring racks. Also, we classify any damage as significant or minor so that floor supervisors can decide whether a replacement is necessary immediately in each circumstance. Instead of conducting annual or quarterly racking inspections, this would give the racking industry a way to continuously monitor the racking, creating a more secure workplace environment. Our suggested method generates a classifier tailored for installation onto edge devices, providing forklift operators.</p>","PeriodicalId":54817,"journal":{"name":"Journal of Grid Computing","volume":"21 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grid Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10723-023-09738-y","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Pallet racking is a critical element of the production, storage, and distribution networks businesses worldwide use. Ongoing inspections and maintenance are required to ensure the workforce's safety and the stock's protection. Currently, certified inspectors manually examine racks, which causes operational delays, service charges, and missing damages because of human error. As businesses move beyond smart manufacturing, we describe an automated racking assessment method utilizing an integrated framework, MobileNetV2-you only look once (YOLOv5). The proposed method examines the automated pallet tracking system and detects multiple damages based on edge platforms during pallet racking. It employs YOLOv5 in conjunction with the Block Development Mechanism (BDM), which detects defective pallet racks. We propose a device that attaches to the moveable cage of the forklift truck and provides adequate coverage for the neighboring racks. Also, we classify any damage as significant or minor so that floor supervisors can decide whether a replacement is necessary immediately in each circumstance. Instead of conducting annual or quarterly racking inspections, this would give the racking industry a way to continuously monitor the racking, creating a more secure workplace environment. Our suggested method generates a classifier tailored for installation onto edge devices, providing forklift operators.
期刊介绍：
Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures.
Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.
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