Industrial Technology Research Institute

Sen-Chia Chang

Shih-Chieh Chien

Te-Ming Chen

Po-Yu Huang

Tsung-Jung Hsieh

Hong-Chi Ku

Yao-Chung Hsu

Chuang-Hua Chueh

Jia-Jang Tu

Chung-Wei Lin

Hsiang-Tsung Kung

Yao-Yuan Chang

Hsien-Cheng Liao

Yuan-Fu Liao

Jiang-Chun Chen

Chien-Liang Lai

Jia-Min Ren

Che-Ming Kuo

Pei-Yi Lo

Chi-Ting Day

Jeng-Shien Lin

Shih-Chien Chien

Chung-Mou Penwu

Chun-Fang Chen

I-Hsuan Chung

A system and a method for parameter optimization with adaptive search space and a user interface using the same are provided. The system includes a data acquisition unit, an adaptive adjustment unit and an optimization search unit. The data acquisition unit obtains a set of executed values of several operating parameters and a target parameter. The adaptive adjustment unit includes a parameter space transformer and a search range definer. The parameter space transformer performs a space transformation on a parameter space of the operating parameters according to the executed values. The search range definer defines a parameter search range in a transformed parameter space based on the sets of the executed values. The optimization search unit takes the parameter search range as a limiting condition and takes optimizing the target parameter as a target to search for a set of recommended values of the operating parameters.

System and method for parameter optimization with adaptive search space and user interface using the same

A dynamic prediction model establishment method, an electric device and a user interface are provided. The dynamic prediction model establishment method includes the following steps. An integration model is established by a processing device according to at least one auxiliary data set. The integration model is modified as a dynamic prediction model by the processing device according to a target data set. A sampling point recommendation information is provided by the processing device according to an error degree or an uncertainty degree between the at least one auxiliary data set and the target data set.

Dynamic prediction model establishment method, electric device, and user interface

A parameter optimization method includes: a parameter search is performed on an input parameter, an output response value and a target value through a plurality of optimization schemes to search for a plurality of candidate recommended parameters. Each optimization scheme is assigned to a weight value according to user historical decision information. At least one recommended parameter is selected from the candidate recommended parameters according to the weight values. An user interface is provided for a user to input a decision instruction. A new input parameter is selected from the at least one recommended parameter according to the decision instruction; the new input parameter is inputted into the target system; and a new output response value is evaluated whether meets a specification condition. The user historical decision information is updated based on the decision instruction to adjust the weight values.

Methods, devices and non-transitory computer-readable medium for parameter optimization

A tree search-based scheduling method and an electronic apparatus are provided. In the method, multiple order lists are received and a schedule is initialized, wherein each order list includes multiple production operations. In each order list, a first production operation which has not been joined into the schedule yet is selected, such that multiple prior operations are selected. An execution priority of the prior operations is calculated according to multiple dispatching rules, and multiple candidate operations are selected from the prior operations according to the execution priority. Afterwards, the candidate operations are listed as a next operation of the schedule respectively, and a scheduling simulation is performed according to the dispatching rules to obtain multiple scheduling indicators of the candidate operations. Scheduling is performed according to the scheduling indicators.

Tree search-based scheduling method and electronic apparatus using the same

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.

Health assessment method and health assessment device for workpiece processing apparatus

An abnormality measuring method and an abnormality measuring apparatus of equipment are provided. The abnormality measuring method includes the following steps: acquiring a feature sequence corresponding to a life cycle according to recipe information and sensing information, wherein the feature sequence includes a plurality of feature subset sequences, and the life cycle is relative to a plurality of process runs; performing repeatedly a life segment analyzing process to acquire a plurality of life segments of the life cycle and each of the plurality of the feature subset sequences corresponding to one of the plurality of life segments; building a corresponding trending distribution of each of the plurality of life segments according to a corresponding feature subset sequence of the life segment; and determining whether to send an alarm message according to a plurality of trending distributions.

Abnormality measuring method and abnormality measuring apparatus

A breakdown measuring method and a breakdown measuring device are disclosed. The breakdown measuring method includes the following steps: capturing a plurality of process flows, each of the process flows includes at least one recipe step; analyzing a flow attribute corresponding to each of the process flows; capturing sensing data corresponding to the at least one recipe step; generating a local feature in a time interval corresponding to each of the process flows according to the corresponding flow attribute, the corresponding at least one recipe step and the corresponding sensing data; generating a trend distribution according to the local features of the process flows; determining whether to send an alarm information based on the trend distribution.

Method and device of measuring breakdown status of equipment

A system and a method for predicting a remaining useful life (RUL) of a component of an equipment are provided. The system for predicting the RUL of the component of the equipment includes a data acquisition unit, a feature capturing unit, a mapping function generating unit, a similarity analyzing unit and a RUL calculating unit. The feature capturing unit obtains an estimation feature according to a real time sensing record, and obtains a plurality of training features according to a set of history sensing records. The similarity analyzing unit obtains k similar features which are similar to the estimation feature according to the training features. The RUL calculating unit obtains at least one of k predicting information via a mapping function according to the k similar features and calculates an estimation RUL according to at least one predicting value.

System and method for predicting remaining useful life of component of equipment

A method for monitoring a manufacturing apparatus includes collecting a control signal, of a controller and a corresponding sensing signal, of the manufacturing apparatus over a predetermined period of time; segmenting the control signal and the corresponding sensing signal to obtain at least one control step; calculating a character of the controller based on at least one of the control signal, the sensing signal, the at least one control step, or information from a user manual; generating, based on the character, a health index indicating health of the controller; and generating a warning signal when the health index exceeds a predetermined threshold.

Method, apparatus, and system for monitoring manufacturing equipment

A language learning system including a storage module, a feature extraction module, and an assessment and diagnosis module is provided. The storage module stores training data and an assessment decision tree generated according to the training data. The feature extraction module extracts pronunciation features of a pronunciation given by a language learner. The assessment and diagnosis module identifies a diagnosis path corresponding to the pronunciation of the language learner in the assessment decision tree and outputs feedback information corresponding to the diagnosis path. Thereby, the language learning system can assess and provide feedback information regarding words, phrases or sentences pronounced by the language learner.

Language learning system, language learning method, and computer program product thereof

The present invention relates to a speech interactive system and method. The system comprises a target information receiving module, an interactive mode setting and speech processing module, an interactive information update module, a decision module, and an output response module. It receives target information and sets corresponding target text sentence information. It also receives a user's speech signal, sets an interactive mode, decides the speech's target text sentence information, and generates an assessment for the target text sentence. Under the set interactive mode, the system updates the information in an interactive information recording table according to the assessment and a timing count. According to the interactive mode and the recorded information, an output mode for the target text sentence information is generated. According to the output mode and the recorded information, the response information is generated.

Speech interactive system and method

A system and method for detecting the recognizability of input speech signal is provided. It is designed in the pre-stage of speech recognition or a dialog system. The invention detects the user's environmental condition and verifies if the input speech signal can be recognized. It mainly comprises an environment parameter generator, a signal recognition verifier, and a strategy response processor. Through the use of the invention in the pre-stage of speech recognition or a dialog system, it can precisely verify the recognizability of the input speech signal and receives the input speech signals of high recognition probability in a noisy environment. This reduces the impact caused by receiving the input speech signals of low recognition probability. This invention thus increases the recognition probability for a recognizer.

System and method for detecting the recognizability of input speech signals

A method and system for utterance verification is disclosed. It first extracts a sequence of feature vectors from speech signal. At least one candidate string is obtained after speech recognition. Then, speech signal is segmented into speech segments according to the verification-unit-specified structure of candidate string for making each speech segment corresponding to a verification unit. After calculating the verification feature vectors of speech segments, these verification feature vectors are sequentially used to generate verification scores of speech segments in verification process. This invention uses neural networks for calculating verification scores, where each neural network is a Multi-Layer Perceptron (MLP) developed for each verification unit. Verification score is obtained through using feed-forward process of MLP. Finally, utterance verification score is obtained by combining all verification scores of speech segments and is used to compare with a pre-defined threshold for the decision of acceptance or rejection of the candidate string.

Method and system for utterance verification

A speech recognition system is used to receive a speech signal and output an output language word with respect to the speech signal. The speech recognition system has preset quantities for a first threshold, a second threshold, and a third threshold. The speech recognition system includes a first speech recognition device that is used to receive the speech signal and generate a first candidate language word and a first confidence measurement of the first candidate language word, according to the speech signal. A second speech recognition device is used to receive the speech signal and generate a second candidate language word and a second confidence measurement of the second candidate language word, according to the speech signal. A confidence measurement judging unit is used to output the language word, by comparing the first confidence measurement and the second confidence measurement to the above thresholds.

Speech recognition with plural confidence measures

A method for generating candidate word strings in speech recognition is provided, which is based on the nodes in the word lattice to search candidate word strings. The associated maximum string score for each node is first determined. Next, all nodes are sorted based on the associated maximum string score to group the nodes with the same string score into the same node set. Then, the node sets with relative high string scores are selected to connect the nodes by their starting time frame and ending time frame, thereby generating the candidate word strings.

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Hsinchu, Taiwan

Sen-Chia Chang