Abstract:
A stereo camera apparatus including an image capturing device, an optical axis controlling module and a calculating module is provided. The image capturing device is suitable for obtaining a stereo image, and the image capturing device includes a plurality of image capturing units. The optical axis controlling module is coupled to the image capturing device. The calculating module is coupled to the image capturing device and the optical axis controlling module, wherein the calculating module calculates a calibration condition according to the stereo image. The optical axis controlling module adjusts directions of imaging optical axes of the image capturing units. After being adjusted by the optical axis controlling modules, the imaging optical axes of the image capturing units are aligned. Besides, a self-calibration apparatus and a method of calibration are also provided.
Abstract:
A stereo camera apparatus including an image capturing device, an optical axis controlling module and a calculating module is provided. The image capturing device is suitable for obtaining a stereo image, and the image capturing device includes a plurality of image capturing units. The optical axis controlling module is coupled to the image capturing device. The calculating module is coupled to the image capturing device and the optical axis controlling module, wherein the calculating module calculates a calibration condition according to the stereo image. The optical axis controlling module adjusts directions of imaging optical axes of the image capturing units. After being adjusted by the optical axis controlling modules, the imaging optical axes of the image capturing units are aligned. Besides, a self-calibration apparatus and a method of calibration are also provided.
Abstract:
A prediction model building method for a processing machine is provided. While a workpiece is manufactured by the processing machine, a machine parameter set is generated. After the workpiece is manufactured, the workpiece is measured and a workpiece quality parameter set is generated. Then, a component status is determined according to the machine parameter set. Then, a workpiece quality prediction model in the component status is built according to the machine parameter set, the workpiece quality parameter set and the component status.
Abstract:
A management system, a smart meter, a server, an operation method and a management method are provided. The management system includes a remote server and at least one smart meter. The smart meter is coupled to the remote server via a communication network. The smart meter measures electrical energy of at least one power line to obtain at least one batch of electricity data. The smart meter detects whether the loading event occurs. If the loading event occurs, the smart meter performs data compression on the electricity data obtained during an event period corresponding to the loading event to obtain compressed data, and uploads the compressed data to the remote server. The remote server performs data decompression on the compressed data to obtain decompressed data. The remote server performs load identification according to the decompressed data.
Abstract:
A production line operation forecast method and a production line operation forecast system are provided. The production line operation forecast method includes the following steps: obtaining an online production line work-in-process map at a time point, generating candidate simulated dispatch decisions based on the online production line work-in-process map, and inferring production-line work-in-process map changes of the candidate simulated dispatch decisions at a next time point; inputting the production-line work-in-process map changes to a forecast model, such that the forecast model outputs simulated production line operation health indicators of the candidate simulated dispatch decisions at the next time point; and selecting one of the candidate simulated dispatch decisions as a scheduling dispatch decision.
Abstract:
A production line scheduling method, adapted to a plurality of jobs passing a bottleneck station having at least one manufacturing machine, the jobs respectively correspond to a plurality of job conditions, and the method includes: performing a plurality of times of a schedule simulation algorithm on the jobs to sequentially establish a plurality of schedule simulation trees, and obtaining a job schedule and a simulated finishing period of each job based on the schedule simulation trees; and calculating a plurality of expected feeding times of each job at a plurality of stations including the bottleneck station, each schedule simulation tree includes at least one scheduling route, and each scheduling route is generated from one schedule simulation algorithm, the schedule simulation algorithm includes: performing a node expansion step based on at least one node expansion condition and the job conditions to obtain the scheduling route.
Abstract:
A prediction model building method for a processing machine is provided. While a workpiece is manufactured by the processing machine, a machine parameter set is generated. After the workpiece is manufactured, the workpiece is measured and a workpiece quality parameter set is generated. Then, a component status is determined according to the machine parameter set. Then, a workpiece quality prediction model in the component status is built according to the machine parameter set, the workpiece quality parameter set and the component status.
Abstract:
A production line operation forecast method and a production line operation forecast system are provided. The production line operation forecast method includes the following steps: obtaining an online production line work-in-process map at a time point, generating candidate simulated dispatch decisions based on the online production line work-in-process map, and inferring production-line work-in-process map changes of the candidate simulated dispatch decisions at a next time point; inputting the production-line work-in-process map changes to a forecast model, such that the forecast model outputs simulated production line operation health indicators of the candidate simulated dispatch decisions at the next time point; and selecting one of the candidate simulated dispatch decisions as a scheduling dispatch decision.
Abstract:
A health assessment method and a health assessment device of a workpiece processing apparatus are disclosed. The health assessment method includes the following steps. Acquire a first sensing data related to the workpiece processing apparatus at an operation stage of the workpiece processing apparatus. Set the first sensing data as a substitution of a first transform model to acquire a virtual workpiece quality. Set the virtual workpiece quality as a substitution of a second transform model to acquire a first virtual apparatus health index.
Abstract:
A management system, a smart meter, a server, an operation method and a management method are provided. The management system includes a remote server and at least one smart meter. The smart meter is coupled to the remote server via a communication network. The smart meter measures electrical energy of at least one power line to obtain at least one batch of electricity data. The smart meter detects whether the loading event occurs. If the loading event occurs, the smart meter performs data compression on the electricity data obtained during an event period corresponding to the loading event to obtain compressed data, and uploads the compressed data to the remote server. The remote server performs data decompression on the compressed data to obtain decompressed data. The remote server performs load identification according to the decompressed data.