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  6. [Case Study] Improving Work Quality through Hand Movement Assessment during Picking Operations

[Case Study] Improving Work Quality through Hand Movement Assessment during Picking Operations

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last updated:May 16, 2023

アキュイティー
アキュイティー
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Improvements in operations for preventing recurrence are possible! It captures the movements of the worker's hands in real time.

In the assembly and picking processes at manufacturing sites, issues such as human errors, variability in work, productivity, and work management are present. The "Two-Hand Mode" feature included in the 'Human Tracker' captures the movements of the worker's hands in real-time, allowing for the recording and judgment of movements and the areas entered and exited. It can record where parts were taken from, and by linking with lamps and speakers, it can notify the worker with colors or sounds when their hands enter the wrong area, thereby reducing work mistakes. [Challenges and Requests Before Implementation] ■ We want to manage hand operations, such as whether parts were taken from or placed in designated areas, to reduce variability in human work and work errors. *For more details, please refer to the PDF document or feel free to contact us.

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[Case Study] Improving Work Quality through Hand Movement Assessment during Picking Operations

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  • Related Link - https://www.acuity-inc.co.jp/pickups/cases/place/2…

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【Effects After Implementation】 ■ Assurance of work quality and improvement of productivity through work log management ■ Reduction of work errors through real-time feedback to workers by linking with lamps and sounds *For more details, please refer to the PDF document or feel free to contact us.

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Acuity Inc. Company Profile

Acuity Inc. Company Profile

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アキュイティー

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Acuity Inc. thoroughly decomposes and analyzes elements based on a wide range of sensing technology options and numerous implementation cases. By identifying the essence of challenges, we select the optimal methods to solve current issues and create new value. "Seeing is changing." Our solutions address challenges by observing people, objects, and systems, using quantified data as a basis for resolution. For example, in performance testing of manufactured products, we provide systems for displacement measurement, static testing, and 3D measurement as methods to solve issues related to reducing man-hours, improving efficiency, automation, and traceability. We consistently handle factory digital transformation with manufacturing-specific solutions, including AI-based appearance inspection and image processing systems, as well as human detection systems for motion analysis, gaze analysis, and automation of visual inspections.

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