With the increasing maturity of automated guided vehicles(AGV)technology and the widespread application of flexible manufacturing systems,enhancing the efficiency of AGVs in complex environments has become crucial.Thi...With the increasing maturity of automated guided vehicles(AGV)technology and the widespread application of flexible manufacturing systems,enhancing the efficiency of AGVs in complex environments has become crucial.This paper analyzes the challenges of path planning and scheduling in multi-AGV systems,introduces a map-based path search algorithm,and proposes the BFS algorithm for shortest path planning.Through optimization using the breadth-first search(BFS)algorithm,efficient scheduling of multiple AGVs in complex environments is achieved.In addition,this paper validated the effectiveness of the proposed method in a production workshop experiment.The experimental results show that the BFS algorithm can quickly search for the shortest path,reduce the running time of AGVs,and significantly improve the performance of multi-AGV scheduling systems.展开更多
首先介绍了真空衰减检漏机的结构和具体工作流程,然后给出了其差压法检测原理,实现BFS类药品既定瓶型的密封完整性检测。现以一种0.4 mL BFS滴眼剂产品为例,根据漏率计算公式,在满足客户生产要求速度和5μm检测精度前提下,进行检测模腔...首先介绍了真空衰减检漏机的结构和具体工作流程,然后给出了其差压法检测原理,实现BFS类药品既定瓶型的密封完整性检测。现以一种0.4 mL BFS滴眼剂产品为例,根据漏率计算公式,在满足客户生产要求速度和5μm检测精度前提下,进行检测模腔和标准模腔的仿形设计。在完成被检测阴性样品、3D打印基准物和5μm漏孔阳性样品等准备工作后,按照设定的参数进行检测,得到泄漏判定阈值范围,通过多组样品的测试证明,采用真空衰减检漏机设备能够有效检测BFS药品包装密封完整性,保证产品质量。展开更多
In cloud computing Resource allocation is a very complex task.Handling the customer demand makes the challenges of on-demand resource allocation.Many challenges are faced by conventional methods for resource allocatio...In cloud computing Resource allocation is a very complex task.Handling the customer demand makes the challenges of on-demand resource allocation.Many challenges are faced by conventional methods for resource allocation in order tomeet the Quality of Service(QoS)requirements of users.For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work.The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection(BFS)in the proposed work,this further reduces the inappropriate features from the data.The similarities that were hidden can be demoralized by the Support Vector Machine(SVM)classifier which is also determine the subspace vector and then a new feature vector can be predicted by using SVM.For an unexpected circumstance SVM model can make a resource allocation decision.The efficiency of proposed SVM classifier of resource allocation can be highlighted by using a singlecell multiuser massive Multiple-Input Multiple Output(MIMO)system,with beam allocation problem as an example.The proposed resource allocation based on SVM performs efficiently than the existing conventional methods;this has been proven by analysing its results.展开更多
文摘With the increasing maturity of automated guided vehicles(AGV)technology and the widespread application of flexible manufacturing systems,enhancing the efficiency of AGVs in complex environments has become crucial.This paper analyzes the challenges of path planning and scheduling in multi-AGV systems,introduces a map-based path search algorithm,and proposes the BFS algorithm for shortest path planning.Through optimization using the breadth-first search(BFS)algorithm,efficient scheduling of multiple AGVs in complex environments is achieved.In addition,this paper validated the effectiveness of the proposed method in a production workshop experiment.The experimental results show that the BFS algorithm can quickly search for the shortest path,reduce the running time of AGVs,and significantly improve the performance of multi-AGV scheduling systems.
文摘首先介绍了真空衰减检漏机的结构和具体工作流程,然后给出了其差压法检测原理,实现BFS类药品既定瓶型的密封完整性检测。现以一种0.4 mL BFS滴眼剂产品为例,根据漏率计算公式,在满足客户生产要求速度和5μm检测精度前提下,进行检测模腔和标准模腔的仿形设计。在完成被检测阴性样品、3D打印基准物和5μm漏孔阳性样品等准备工作后,按照设定的参数进行检测,得到泄漏判定阈值范围,通过多组样品的测试证明,采用真空衰减检漏机设备能够有效检测BFS药品包装密封完整性,保证产品质量。
文摘In cloud computing Resource allocation is a very complex task.Handling the customer demand makes the challenges of on-demand resource allocation.Many challenges are faced by conventional methods for resource allocation in order tomeet the Quality of Service(QoS)requirements of users.For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work.The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection(BFS)in the proposed work,this further reduces the inappropriate features from the data.The similarities that were hidden can be demoralized by the Support Vector Machine(SVM)classifier which is also determine the subspace vector and then a new feature vector can be predicted by using SVM.For an unexpected circumstance SVM model can make a resource allocation decision.The efficiency of proposed SVM classifier of resource allocation can be highlighted by using a singlecell multiuser massive Multiple-Input Multiple Output(MIMO)system,with beam allocation problem as an example.The proposed resource allocation based on SVM performs efficiently than the existing conventional methods;this has been proven by analysing its results.
