SeizoMind Tra - Manufacturing Data Platform
SeizoMind Tra is intended for the management of production data. It manages the production data collection and the assignment of production numbers. It effortlessly integrates data across the whole supply chain, from upstream to downstream, by connecting production data and master data with signals from industrial processes, equipment, and visual data like photographs and videos.
The goal of manufacturing data collection
Using production-related data is critical to manufacturing operations and management. Businesses can anticipate increased productivity in manufacturing management jobs, better processes, inventory management, and product design by utilizing production data effectively. Ultimately, this will lead to higher-quality executive decision-making.
Manufacturing data
Manufacturing management numbers assigned to each order or lot, production instructions, work logs, equipment signals, sensor data, and other information are examples of production data. These kinds of data must be linked and obtained properly because they are gathered at various times and places. Depending on the management model used, there are differences in the process for linking production data. Manufacturing numbers are used to control the manufacture and acquisition of parts required for each order under the manufacturing number management system, which tracks orders separately. Part numbers are employed in the MRP (Material Requirements Planning) approach to manage inventories overall. Production and procurement are based on the quantities specified in the production plan. Data can be kept in conjunction with timestamps, locations, or equipment numbers to ensure traceability in cases when manufacturing or part numbers are unavailable. The essential information for every form of data must be found and kept with the relevant data in order to handle production data effectively.
Data platform
Creating internal data platforms to encourage data use has become standard procedure in the IT sector. In the same way, an increasing number of companies are collecting manufacturing data and putting it on data platforms in the manufacturing sector. Depending on the goal and use case, several data platform design patterns, such as those for data lakes and data warehouses (DWH), are combined and employed. Although raw data can be gathered in its original form, it is typically converted or sampled using ETL/ELT technologies before being stored. The specifications of the data being stored as well as the appropriate design and management of the data storage techniques are critical components of any successful data platform construction.
Challenges in manufacturing data platform
The key challenges in manufacturing data platform are as follows:
- Necessary data is not properly linked.
- Audio, video, and picture files are not being used or stored effectively enough.
Solution utilizing SeizoMind Tra
SeizoMind Tra has all the features required to meet and overcome these challenges. Companies can improve their manufacturing and supply chain operations and address a variety of production data management challenges by putting SeizoMind Tra into practice.
Necessary data is not properly linked.
It's critical to plan ahead when gathering production data by determining what further information has to be obtained. This comprises environmental data from the work site as well as the operational state of equipment during the task, in addition to directly connected master data and production work records. Through careful data collection, you can efficiently construct an all-encompassing data platform.
It is difficult to properly link and take into account all relevant facts. Merely use IDs to connect data to master data may result in data discrepancies because master data can change, which may hinder precise analysis. Data extraction for a single production number may become unfeasible if numerous production processes are conducted on the same piece of equipment. Instead, it is necessary to integrate the data collection with the equipment usage and job schedule. Before integrating with external systems, appropriate interface design and data format agreements need to be created.
SeizoMind Tra offers the functionalities required to construct an appropriate framework for gathering data. You can save snapshots of the original master data that are connected to the relevant production data by utilizing the manufacturing number management function. SeizoMind Tra uses work center, BOM, and BOP information registered in SeizoMind Mas to link equipment information used in production. Based on user requests, interfaces can be built and made available for interaction with external systems or data spaces. Furthermore, it makes connection to data spaces for exchanging GHG emission data throughout the supply chain easier when combined with SeizoMind CFP.
Audio, video, and picture files are not being used or stored effectively enough.
Production data can be connected to object data, which includes information that cannot be expressed solely through text or signal data, like images, videos, and audio files. To advance data use in manufacturing, these kinds of data are crucial. However, object data is substantially greater in volume and in format variation than text or signal data, so careful consideration of storage methods is necessary to ensure efficient utilization.
To efficiently collect and utilize object data, an I/O interface that enables streaming and content delivery techniques is required. It's difficult to build an I/O interface that supports several data types. Thus, data collected frequently goes unutilized. Furthermore, the data platform requires search functionality, but building a search engine for object data is very difficult. It is possible that only low-performance search capabilities will be developed despite of the high cost.
Because SeizoMind Tra has capabilities for gathering several kinds of object data, you can begin gathering data right away. It offers methods for major media types' streaming and content delivery, making it possible to use audio, video, and image files right now. SeizoMind Tra indexes the content itself in addition to metadata, improving object data searchability. Its value can be further enhanced by applying it to knowledge utilization in conjunction with SeizoMind Age.
Toward the Success of Manufacturing Data Platform
Building a production data platform correctly raises the chances of a successful business transformation through digital transformation (DX), which is crucial for improving the use of manufacturing data. Effective data collection is dependent on a carefully planned approach, and the data must be designed and stored in a system that is suitable for production data. SeizoMind Tra is the best option for companies trying to increase the use of manufacturing data because it is specifically designed for production data.
As introduced in this article, implementing SeizoMind Tra can lead to the following benefits:
- Enhancement of traceability and consistency of data
- Completing data integration with external systems in a seamless manner
- Improved use of audio, image, and video data
- Decrease in the price of developing data gathering systems
- Decrease the price of developing media data delivery systems
If you are experiencing difficulties with manufacturing data management or related operations, we advise you to consider our SeizoMind-based solutions. For more extensive information, pricing, or casual consultations, please use the contact form on our website.