The study investigates the effects of the pandemic brought about by Covid-19 on Ilocos businesses and establishments on its business operations and supply chain. The study participants were the 352 owners of the micro, small, medium, and large businesses in Ilocos Norte, and they were selected using a convenience sampling technique. The study employed a quantitative research design, and the entrepreneurs were asked about the perceived impact of Covid-19 on the supply chain. Using descriptive statistics, the findings divulged that the impact of the Covid-19 pandemic on the businesses ranged from retrenchment of employees, disruption in the supply chain, and temporary to permanent shutdown. The impact of the pandemic includes uncertainties, the decline in productivity, demand, and sales. This study implies that COVID-19 significantly affects operations, primarily supply chain management. Numerous organizations are pursuing local sourcing as a result of supply chain disruptions.
{"title":"Impacts of Covid-19 on Supply Chain and Business Operations on Enterprises in the Province of Ilocos Norte","authors":"Eric S Parilla, M. E. Abadilla","doi":"10.31098/lomr.v1i1.927","DOIUrl":"https://doi.org/10.31098/lomr.v1i1.927","url":null,"abstract":"\u0000\u0000\u0000The study investigates the effects of the pandemic brought about by Covid-19 on Ilocos businesses and establishments on its business operations and supply chain. The study participants were the 352 owners of the micro, small, medium, and large businesses in Ilocos Norte, and they were selected using a convenience sampling technique. The study employed a quantitative research design, and the entrepreneurs were asked about the perceived impact of Covid-19 on the supply chain. Using descriptive statistics, the findings divulged that the impact of the Covid-19 pandemic on the businesses ranged from retrenchment of employees, disruption in the supply chain, and temporary to permanent shutdown. The impact of the pandemic includes uncertainties, the decline in productivity, demand, and sales. This study implies that COVID-19 significantly affects operations, primarily supply chain management. Numerous organizations are pursuing local sourcing as a result of supply chain disruptions.\u0000\u0000\u0000","PeriodicalId":247331,"journal":{"name":"Logistic and Operation Management Research (LOMR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125065619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Technology nowadays is always changing very fast. Automated tools are used to face the advanced technology in the warehouse industry, such as automated guided vehicles (AGV). It becomes a common daily vehicle when working in the warehouse, especially on the shop floor. It means collaboration between AGVs is needed and has become important. This paper suggests how to avoid collisions between AGVs and how to avoid obstacles is a practical problem if two or more AGVs interact with each other. This is a common need that should be addressed. As a result, a more effective system design should be created and implemented. This paper used a three-tier internet of things (IoT) structure to avoid collisions and reduce path deviation to design an AGV collaboration system. The IoT was used to authorize AGVs to communicate with each other by transmitting position messages. In this situation, AGV would be aware of other AGV positions and would decide what to do next. According to the findings, two AGVs can avoid colliding by knowing each other's positions in any path scenario by recognizing obstacles through Light Detection and Ranging (LIDAR) detection. This paper designed an AGV collaboration system using the Robot Operating System (ROS) and conducted an experiment to test its practicality. The experiment simulated a warehouse intersection in the real world. This study used the statistical ANOVA method to identify motion planning parameters concerning final AGV position error values.
{"title":"A Study of AGV Collaboration with IoT Concept to Avoid a Collision at Warehouse Intersection","authors":"R. Muftygendhis, W. Shiang, Chia-Hung Hsu","doi":"10.31098/lomr.v1i1.957","DOIUrl":"https://doi.org/10.31098/lomr.v1i1.957","url":null,"abstract":"Technology nowadays is always changing very fast. Automated tools are used to face the advanced technology in the warehouse industry, such as automated guided vehicles (AGV). It becomes a common daily vehicle when working in the warehouse, especially on the shop floor. It means collaboration between AGVs is needed and has become important. This paper suggests how to avoid collisions between AGVs and how to avoid obstacles is a practical problem if two or more AGVs interact with each other. This is a common need that should be addressed. As a result, a more effective system design should be created and implemented. This paper used a three-tier internet of things (IoT) structure to avoid collisions and reduce path deviation to design an AGV collaboration system. The IoT was used to authorize AGVs to communicate with each other by transmitting position messages. In this situation, AGV would be aware of other AGV positions and would decide what to do next. According to the findings, two AGVs can avoid colliding by knowing each other's positions in any path scenario by recognizing obstacles through Light Detection and Ranging (LIDAR) detection. This paper designed an AGV collaboration system using the Robot Operating System (ROS) and conducted an experiment to test its practicality. The experiment simulated a warehouse intersection in the real world. This study used the statistical ANOVA method to identify motion planning parameters concerning final AGV position error values.","PeriodicalId":247331,"journal":{"name":"Logistic and Operation Management Research (LOMR)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115844341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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