Productivity prediction method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention relates to a productivity prediction method and device, electronic equipment and a storage medium, and relates to the technical field of lean production. The method comprises the steps of: recognizing the current worker identity of each station on a production line; collecting the field operation process video of the current worker at each station through cameras assembled at each station; performing streaming media analysis on the video, and identifying duration information of each worker executing a predetermined process according to the position of a predetermined reference object in multiple frames of images of the video; and predicting the productivity of the production line according to the duration information of the predetermined process executed by each worker within the predetermined duration. The method can automatically and effectively predict the productivity of workers, can improve the accuracy of productivity prediction analysis, and can reduce manpower consumption.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of lean production, and specifically relate to a production capacity prediction method, device, electronic equipment, and storage medium. Background technique [0002] With the intensification of the market competition environment, enterprises have gradually developed from rough development to refined and systematic operation, which reversely requires manufacturing enterprises not only to increase market promotion / occupation, but also to seek benefits from within the enterprise to enhance enterprise competition to match the rapid development of the external market. [0003] Manufacturing enterprises are generally labor-intensive industries. In the stage of pursuing benefits within the transition of enterprise development, due to the large number of employees, employees have become the most important focus. Employee work is an important focus of enterprise product value-added. At th...

AI Technical Summary

Problems solved by technology

Employee work is an important focus of enterprise product value-added. At the same time, employee work is also a treasure that enterprises need to dig urgently. There are many hidden wastes of actions, unreasonable arrangements that lead to loss of efficiency, waste of cost, waste of quality, safety accidents and many other common problems. In the past, due to immature collection technology, outdated collection methods, and inaccurate collection information, it was impossible to effectively analyze employee productivity, resulting in a large amount of value loss at the employee operation level.

[0004] At present, the collection of staff actions generally adopts the method of wearing sensors, such as hand damage, sensor gloves, etc., but these will affect direct operations, and the cost is too high. PTS (prefabricated action time analysis) analysis methods, video analysis methods, and MOST are used. In the process, a professional IE (industrial engineer) uses a stopwatch to collect the action time, and then registers it in the register, then conducts an optimization analysis of the action, formulates a standard SOP operation process, and determines the best operating process and operating time

[0005] However, this collection and analysis method is discontinuous, has high requirements for personnel, high cost, poor timeliness, single application dimension, and cannot accurately predict the actual production capacity of the staff.

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