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公开(公告)号：US20200073641A1
公开(公告)日：2020-03-05
申请号：US16451042
申请日：2019-06-25
Applicant: HITACHI, LTD.
Inventor： Kei IMAZAWA
Abstract: The software generation method uses a computer, wherein the computer includes a control unit and a storage unit; the storage unit stores manufacturing log data that includes sensor data acquired in one or both of a manufacturing process and an inspection process, and environmental configuration information that relates to a manufacturing device or an inspection device from which the sensor data are acquired for each component or product; and the control unit reads the manufacturing log data from the storage unit, reads the environment configuration information from the storage unit, constructs a causal inference model based on the manufacturing log data, constructs an expanded causal inference model by expanding the causal inference model using the environment configuration information, generates a contracted model by contracting the expanded causal inference model to a causal relation of prescribed target data of interest, and generates prescribed application software by reading the contracted model.
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公开(公告)号：US20200160047A1
公开(公告)日：2020-05-21
申请号：US16676528
申请日：2019-11-07
Applicant: HITACHI, LTD.
Inventor： Kaichiro NISHI , Akihisa TSUJIBE , Kei IMAZAWA
Abstract: A work skill supporting device include a storage unit that stores non-standard work model information including a condition of non-standard work, work procedure information including information indicating a work content and information indicating a part to be used in work, and a workplace internal image obtained by photographing an inside of a workplace; a time series skeleton information acquisition unit that acquires time series skeleton information of one or a plurality of workers from the workplace internal image; a non-standard work extraction unit that determines whether or not the time series skeleton information satisfies the condition; a part specification unit that specifies a part serving as a work target using the workplace internal image for the non-standard work determined as satisfying the condition; and a work content specification unit that specifies a work content of the non-standard work with reference to the work procedure information.
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公开(公告)号：US20200005176A1
公开(公告)日：2020-01-02
申请号：US16448748
申请日：2019-06-21
Applicant: HITACHI, LTD.
Inventor： Kei IMAZAWA
Abstract: A causal inference model construction method is performed using a computer. The computer includes a control unit and a storage unit, and the control unit implements: a result value reception step of reading manufacturing log data acquired in a manufacturing process and an inspection process; a correlation model construction step of constructing a correlation model using the manufacturing log data; a physical model reception step of receiving an input of a physical model; a probability distribution computation step of calculating probability distributions of the correlation model and the physical model; a probability distribution convergence processing step of performing convergence computation on the probability distribution of the correlation model, approximating a result of the convergence computation to the probability distribution of the physical model, and overwriting the correlation model; and a causal inference model holding step of storing a correlation model as a causal inference model in the storage unit.
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公开(公告)号：US20200159197A1
公开(公告)日：2020-05-21
申请号：US16571471
申请日：2019-09-16
Applicant: HITACHI, LTD.
Inventor： Kazuki HORIWAKI , Kei IMAZAWA
IPC: G05B19/418 , G06N3/08
Abstract: Specifying a suitable manufacturing condition and maintaining product quality is provided when there is a manufacturing state change. A computer in a manufacturing condition specifying system uses manufacturing condition data and quality data at a plurality of time points from a manufacturing flow to build models for each manufacturing state change in each manufacturing process of the flow. The computer uses the model and a quality target value to calculate a predicted value of a manufacturing condition at a next time point as first data based on a first learning model. The computer uses the model as well as the manufacturing condition data and quality data at the current time point to predict quality data at a next time point and calculate a quality error, and uses the first data and the quality error to specify manufacturing condition data at the next time point based on a learning model.
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Patent Agency Ranking
公开(公告)号：US20190217472A1
公开(公告)日：2019-07-18
申请号：US16237156
申请日：2018-12-31
Applicant: Hitachi, Ltd.
Inventor： Nobuaki NAKASU , Kei IMAZAWA
CPC classification number: B25J9/1666 , B23P19/04
Abstract: A robot controlling device inputs an operation state of a worker from a sensor. The robot controlling device calculates a position vector and a velocity vector of each of the robot and the worker from the operation state of the robot and the operation state of the worker, generates a risk determination area (an area where the robot is stopped, an area where the robot is evacuated, and an area where the robot is decelerated) around each of the robot and the worker, determines a risk based on overlapping between the generated risk determination area of the robot and the generated risk determination area of the worker, generates a collision avoidance trajectory in which collision between the robot and the worker is avoided from a result of the determination, and controls the robot based on the generated collision avoidance trajectory.
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公开(公告)号：US20190129397A1
公开(公告)日：2019-05-02
申请号：US16147923
申请日：2018-10-01
Applicant: HITACHI, LTD.
Inventor： Kazuki HORIWAKI , Kei IMAZAWA
IPC: G05B19/418
Abstract: A causal relationship model building system includes a computer which processes information for building a causal relationship model relating to a manufacturing flow of an object to be controlled. The computer builds the causal relationship model by using monitor data representing a state of each of a plurality of steps of the manufacturing flow, and quality data as a result of an inspection step, and specifies an allowable range of the monitor data so as to satisfy a target value of the quality data, by using the causal relationship model and the target value, from prediction based on a causal relationship between a plurality of pieces of the monitor data. The computer graphically displays information including the causal relationship model and the allowable range of the monitor data on a display screen.
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公开(公告)号：US20190103006A1
公开(公告)日：2019-04-04
申请号：US16118545
申请日：2018-08-31
Applicant: Hitachi, Ltd.
Inventor： Kei IMAZAWA , Takaharu MATSUI
CPC classification number: G08B21/0423 , G06K9/00664 , G06K9/00771 , G08B21/0476
Abstract: The monitoring apparatus includes: a processing unit and a data storage unit, in which the data storage unit stores image data of a work situation including a worker and a work object and model data including data indicating that a combination of a positional relationship between an area of the worker and an area of the work object has appeared in the past, and in which the processing unit includes a recognition unit that recognizes the areas of the worker and the work object from the input image, a combination area specification unit that specifies the combination of the positional relationship of the recognized areas of the worker and the work object, a model acquisition unit that acquires the model data from the data storage unit, and an abnormality degree calculation unit that calculates an abnormality degree in the combination of the areas of the worker and the work object.
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8.发明申请公开(公告)号：US20180307219A1
公开(公告)日：2018-10-25
申请号：US15911610
申请日：2018-03-05
Applicant: Hitachi, Ltd.
Inventor： Kazuki HORIWAKI , Kei IMAZAWA
CPC classification number: G05B23/0248 , G06N5/022
Abstract: A system is provided in which a causal relation model acquired according to a manufacturing process data is efficiently used and verification according to domain knowledge is easily performed. There is provided a causal relation model verification method in an information processing device which includes an input device, a display device, a processing device, and a storage device. In the method, a first step is performed in which quality data which is an evaluation result of a resulting product, monitor data which indicates a parameter in a case where the resulting product is generated, and domain knowledge which indicates a mutual relation between the quality data and the monitor data are acquired from the input device or the storage device. In addition, a second step is performed in which the processing device constructs the causal relation model which defines a relation between nodes by setting the quality data and the monitor data to the nodes, using a causal relation model construction condition, which is acquired from the input device or the storage device. In addition, a third step is performed in which at least one of a comparison processing performed by the processing device and a comparison display performed by the display device is performed on the causal relation model and the domain knowledge.
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公开(公告)号：US20160253618A1
公开(公告)日：2016-09-01
申请号：US14963502
申请日：2015-12-09
Applicant: Hitachi, Ltd.
Inventor： Kei IMAZAWA , Yuichi HAMAMURA , Shigenori TANAKA , Kouichirou TADA , Isamu MOMOSE , Yusaku FUKAYA
CPC classification number: G06Q10/063114 , G06K9/00771 , G06K9/6284 , G06K9/6296 , G06Q10/06395 , G06T7/73 , G06T7/77 , G06T2207/20076 , G06T2207/30196
Abstract: A method for work quality control of a worker in work where repetitive operation is performed which includes: a model construction step of statistically constructing, from past path data of the worker, past intermediate quality data on a product to be subjected to the work, and past final quality data on the product to be subjected to the work, a prediction model that receives the path data and the intermediate quality data and outputs the final quality data; a worker position recognition step of recognizing a position of the worker from image data on the work captured; and an unusual worker position determining step of substituting the position of the worker recognized in the worker position recognition step into the model constructed in the model construction step, to determine whether the position of the target worker is a usual one or an unusual one.
Abstract translation: 一种在重复操作的工作中对工作人员进行工作质量控制的方法，包括：从工作人员的过去路径数据统计构建过去对要进行工作的产品的中间质量数据的模型构建步骤，以及 过去要进行工作的产品的最终质量数据，接收路径数据和中间质量数据并输出最终质量数据的预测模型; 工作人员位置识别步骤，用于从所捕获的作品的图像数据中识别工作者的位置; 以及异常的工人位置确定步骤，将在工人位置识别步骤中识别的工作人员的位置替换到在模型构建步骤中构建的模型中，以确定目标工作者的位置是否是通常的或不寻常的。
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