[Other Materials] Free: Methods to Eliminate Tacit Knowledge and Personalization in Manufacturing Engineers
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DX transformation with operator analysis AI: Visualizing work processes and converting "tacit knowledge" into "explicit knowledge." We will streamline and optimize the manufacturing process!
We will clarify the tasks in manufacturing and logistics that are prone to errors and time-consuming, and achieve appropriate personnel placement, training, workload verification, and improvement of work mistakes. To this end, we will promote the digital transformation (DX) of operations, which can enhance productivity and quality. To address issues such as labor shortages and the transmission of skills, we will utilize the "Worker Analysis AI" to smoothly implement the SECI model (Socialization, Externalization, Combination, Internalization), promoting personnel training, efficient work, and knowledge sharing. The "Worker Analysis AI" strengthens corporate competitiveness and supports sustainable growth. **The Necessity of Converting Tacit Knowledge into Explicit Knowledge** In various operations, the experience of skilled workers tends to accumulate as tacit knowledge within individuals. Converting tacit knowledge into explicit knowledge offers the following benefits: - Standardization: Ensures consistency in work procedures and quality. - Efficient Training: Enables rapid training of new employees. - Knowledge Sharing: Shares knowledge across the organization, improving performance. - Risk Mitigation: Reduces risks associated with worker transfers and resignations. - Continuous Improvement: Promotes process improvements, optimizing efficiency and costs. *For more details, please refer to the "Related Catalog" and "Other Materials" and contact us.*
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basic information
【Feature Introduction】 1. Work Process Settings: Setting work areas and conditions for each action 2. Automatic Extraction of Improvement Tasks: Videos jump to cycles in the cycle count graph 3. Automatic Grouping of Cycle Counts: Cycle time measurement 4. Continuous Measurement of Cycle Time: Quality improvement through work omission detection alarms 5. Display of Worker Hand Trajectories: Visualization of worker hand movements 6. Work Omission Alarm: Real-time detection of work omissions with history display 7. Work Comparison: Comparing time, accuracy, and efficiency among workers 8. Easy Creation of Work Manuals: Automatic manual creation from videos and information 9. Behavioral Trajectory Analysis: Understanding differences between veterans and newcomers through behavioral data, reviewing 3M (Muri, Muda, Mura) 【Service Provision Format】 Service provided via subscription (cloud service) *Hardware (edge notebook PC and web camera) is required. This information is a reference structure. Please contact us for details.
Price information
Negotiable *Please contact us as the structure may vary depending on the requirements.
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Applications/Examples of results
Examples of Utilizing the SECI Model 1. Assembly Work in Factories: Visualizing the movements of veteran workers and converting tacit knowledge into explicit knowledge. This achieves standardization of work and provides an environment that is easy for newcomers to learn. By sharing the know-how of veterans with everyone, consistency in work is maintained. 2. Packaging Work: Conducting flow analysis to identify unnecessary movements. This reduces work time and cuts labor costs. Best practices are recorded as explicit knowledge and shared with everyone for efficient work methods. 3. Motion Comparison: Simultaneously observing the movements of veterans and newcomers to clearly identify areas for improvement. This strengthens newcomer training and allows for rapid skill enhancement. Specific feedback becomes possible, improving the effectiveness of training. 4. Manual Creation: Creating video manuals of veteran work and sharing key points of the tasks. This enables everyone to perform tasks in the same manner, achieving uniform quality. New staff can also quickly learn the tasks. 5. Utilization of Knowledge Management Tools and Groupware: Consolidating explicit knowledge into knowledge management tools and groupware to promote information sharing across the organization. This advances the collaboration and utilization of knowledge, leading to increased efficiency and productivity throughout the organization.
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Company information
Our company is an AI startup founded by researchers from the University of Tokyo and the French research institution Inria, with a mission to "improve quality and efficiency through advanced AI technology" specifically for the manufacturing and logistics industries. Our technology meets the needs of quality control, production technology, and DX promotion departments, enabling optimization of production processes and risk management. The founder, Yamamoto, has conducted AI research at Yahoo Japan and Inria, presenting results at top international conferences such as WWW and RecSys. Over 80% of our team consists of researchers who studied AI and computer science at world-class universities like the University of Tokyo, Cambridge, and Imperial College. With their international perspectives and advanced skills, we provide innovative solutions to quality control challenges. In particular, in mission-critical areas that emphasize the interpretability of AI, our XAI (explainable AI) technology brings transparency to the reasoning behind AI decisions for managers in quality control and production technology departments, supporting safer and more reliable system operations. This leads to improvements in production efficiency and quality, promoting sustainable growth in the manufacturing and logistics industries.