‍Introduction

In the fast-paced textile industry, optimizing efficiency and maintaining high standards of quality are paramount. A digital time study is a crucial tool in achieving these goals. It involves using technology to observe, record, and analyze the time taken for various working steps within a process cycle. This data is invaluable for identifying bottlenecks, reducing inefficiencies, and ensuring consistent product quality. Implementing such studies in the textile industry can significantly enhance productivity and profitability by providing detailed insights into each step of the manufacturing process.

Understanding Digital Time Studies

A digital time study leverages advanced technologies such as cameras and AI to monitor and evaluate production processes in real-time. This method replaces traditional stopwatch-based time studies with a more accurate and comprehensive approach. By continuously capturing data and providing instant analysis,digital time studies enable manufacturers to make informed decisions quickly. In the textile industry, where precision and speed are critical, this technology can lead to substantial improvements in both efficiency and product quality.

Implementing a Camera-Based Time Study System

The system described in the provided documentation offers a robust solution for conducting camera-based time studies in textile manufacturing. Here’s an overview of how the system works and its key components:

System Setup

The solution involves setting up cameras at critical points in the production line. These cameras are connected to an AI model that analyzes the footage in real-time. To access the system, users need to create an account and log in via the provided URL. The interface displays an overview of all existing stations.

The user can set up and change the grabbing zones in the field of view of the camera in just a few minutes.

Improving Processes with Data Insights

The system provides an “Analytics” page, offering a comprehensive overview of production and error Key Performance Indicators (KPIs). This dashboard helps in monitoring and analyzing production efficiency over time. Historical data and classifications of past images are accessible through the “Images” section, allowing users to review and learn from previous production cycles.

The data collected through camera-based time studies is pivotal for continuous improvement in textile manufacturing. Here are some ways the gathered data can be utilized:

1.     Identifying Bottlenecks:

Analyzing cycle times and error frequencies helps in pinpointing specific stages in the production process that are causing delays or defects. Addressing these bottlenecks can lead to smoother operations and faster production cycles.

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2.     Training and Development:

Historical data serves as a valuable resource for training employees. By understanding common errors and their causes, workers can be better trained to avoid these mistakes, improving overall productivity.

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3.     Optimizing Resource Allocation:

Detailed analytics provide insights into resource usage and efficiency. This information can be used to optimize the allocation of materials and labor, reducing waste and lowering production costs.

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Conclusion

Implementing a camera-based time study system in textile manufacturing offers a multitude of benefits. From enhancing process efficiency and product quality to providing critical insights for continuous improvement, the impact of this technology is profound. By leveraging real-time data and advanced analytics, textile manufacturers can stay competitive in an increasingly demanding market, ensuring sustainable growth and success.

How we did it

Supported by Intel, we are proud to be bringing this solution to market. The solution is optimized for data-intensive workloads and is adaptable, vetted, and ready for immediate deployment.

The solution runs on Intel® Core™ i5 Processors, which are state-of-the-art processors, allowing for maximum flexibility and performance in Industrial Settings. Best in class Wi-Fi connectivity with Intel® Wi-Fi 6 (Gig +) ensures a responsive and reliable connection for immersive connectivity even in large factory spaces.

To create training data to pretrain a model for advanced hand-recognition even with working gloves, we use the Intel®RealSense™ Depth Camera D435f. With its advanced depth-sensing capabilities, this camera is designed to capture accurate 3D images and video in real-time, making it ideal for our industrial use case.

With the Intel® OpenVino™ Toolkit, we optimize our AI models to run efficiently on Intel hardware, unlocking unparalleled performance and accuracy. A lot of workstations need to be equipped, OpenVino™makes it easy to deploy our AI models at scale.

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