When considering implementing historical data management software, it's crucial to recognize the differences between factory-level data and the business environment. Many companies want to access production data archives in the same way they access corporate archives, using traditional relational databases. However, relational databases are often not the optimal approach for factory-level data management for various reasons. First, production operations are real-time, requiring extremely fast data acquisition speeds for optimized analysis. Factory-wide historical data management offers read/write speeds 10 to 20 times faster than relational databases, with true real-time data resolution down to microseconds. Furthermore, factory-wide historical data management is optimized for "time-series" data, while relational databases can only handle relational issues. For example, a relational database is best suited for questions like: "Which customer has the largest order?", but factory-wide historical data management is better suited for answering other types of questions, such as: "What is the standard deviation of production per unit per hour today?" With powerful compression algorithms, factory-wide process data processing can achieve convenient and secure online storage of multi-year data, which helps improve performance and reduce maintenance costs. [i]Assuming 500 floating-point operations per second, the plant-wide historical database uses less disk space and achieves faster read and write speeds. With a relational database, disk space must be carefully managed due to its poor compression algorithms, even with proprietary pre-compressed data workspaces. Source: GE Fanuc Automation[/i] As with any large software project, implementing production data archives and achieving effective results and return on investment can be time-consuming, especially with relational database architectures and the numerous custom interfaces required for real-time system implementation. Relational databases also require companies to manually create and manage custom tables, which is time-consuming. Using a standard interface for the plant-wide historical database reduces implementation time by approximately 50%, thus lowering overall costs. Furthermore, there is no need for data management or the creation of "plans," triggers, stored procedures, or views. The system can be installed and configured within hours due to ease of use, without the need for specialized services such as custom installation code or scripts. Long-term maintenance is also greatly simplified. With plant-wide historical data management, online maintenance is no longer required. However, using a relational database requires full-time maintenance due to the poor compression algorithm (as shown in the figure), forcing companies to manage files and disk space. Furthermore, we must schedule tag imports and maintenance during downtime, as online maintenance cannot perform these tasks. A factory-wide historical database helps companies collect and analyze vast amounts of information generated within the factory, achieving higher performance and reducing costs required to meet industry regulations. Data collection and analysis contribute to improved product quality and consistency. For example, we can compare past production processes, analyze data prior to downtime events, and plan ideal production processes based on current operations. Accumulated data also helps us prepare reports using standard web browser tools, enabling information sharing. Finally, a factory-wide historical database serves as a crucial bridge between factory operations and business operations, providing business systems with essential real-world data to obtain a clear and accurate picture of current production status or historical trends. This detailed information offers significant benefits, such as helping customers securely track order status.