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TOMAI Factory System – Effective Management of Production Processes and Industrial Infrastructure

The TOMAI Factory System is a dedicated, flexible, and scalable solution tailored to the specific needs of various applications for monitoring and controlling production processes in a factory. It functions as a digital twin, capturing, storing, and analyzing data from production processes and industrial machines. This enables improvements in OEE (Overall Equipment Effectiveness), identification of failure points and low-quality production areas, and reduction of overproduction and material or component waste.

Developed based on the Industry 4.0 concept, the TOMAI Factory System incorporates the principles of the Internet of Things (IoT), Augmented Reality, Cloud Computing, Big Data, Automation, Additive Manufacturing, Connectivity, and System Integration. This comprehensive approach allows real-time monitoring of production lines, rapid response to changes in production parameters, and simultaneous tracking of media consumption. A critical aspect is the analysis of machine failures and performance declines.

The system’s flexibility (Connectivity & System Integration) allows integration with other factory systems such as ERP, MES, CMMS, WMS, SCM, etc. The TOMAI Factory System can communicate bidirectionally with PLC controllers from various manufacturers. Data is collected in real-time, enabling immediate implementation of preventive actions within the ongoing process.

The TOMAI Factory System (Web application) can be operated locally using touch panels and computers, or remotely via web browsers or mobile devices (Android, iOS). User authorization management is also noteworthy, for example through RFID card logins, enhancing monitoring, control, and security of the production process.

The system is built on four functional modules: data collection, line status monitoring, historical diagnostics and analysis, and performance and failure analysis.

Data Collection Module

The TOMAI Factory System hardware infrastructure collects data from all PLC controllers, servers, and IT systems. The gathered information is stored in a local MSSQL database.

A significant feature of the system is media consumption analysis—electricity, compressed air, water, technical gases, etc.—which leads to optimized production costs and precise allocation (e.g., per produced item). Additionally, it enables quick responses to potential media losses (e.g., leaks) and detailed production cost breakdowns. By analyzing media consumption, the system can forecast usage based on trends, examining the relationship between media consumption and production downtimes.

Current Line Status Monitoring Module
The TOMAI Factory System’s functionality allows for real-time data monitoring from production lines. This results in real-time tracking of the manufacturing process, both for the entire production line and individual stations. Parameters are presented clearly using graphs. The system also provides a view of the current production items. Both operational time and alarms on the line or individual stations are recorded. The system ensures centralized recipe management, which can be exported and imported from various systems. Recipes can also be compared—for example, in terms of raw material quantities—and synchronized between different machines, preventing production quality drops.

Historical Diagnostics and Analysis Module

This module generates reports with selected criteria, ensuring quick analysis of large amounts of process data.

The system can not only compile materials used in production but also monitor their usage. Furthermore, it verifies the correctness of material usage in components. Analysis and modification of stock levels are crucial aspects.

The TOMAI Factory System supports historical data management. Thus, both the entire production history and the history of each item can be analyzed.

If necessary, results for multiple stations can be compiled. Additionally, the system analyzes relationships between production parameters, line, and operator performance, and downtime causes.

In terms of production serialization, the TOMAI Factory System allows for setting production and production boards and tracking manufacturing progress in real-time on custom-designed charts and reports.

It provides a view of reference parameters changed by users. A very useful feature is the Pareto Diagram of statuses divided by references for stations within a given timeframe. Production can be summarized considering the pallet/socket number. Moreover, reports of global parameters and station status summaries are generated. Collected data can be exported (CSV).

Performance and Failure Analysis Module

This module defines relationships between alarms on production modules and identifies bottlenecks, common causes of downtimes, delays, jams, etc. All machine parameters are recorded and configured via the TOMAI Factory System. Considering the working time of the production line and other machines, the maintenance department can schedule inspections and overhauls, reducing the risk of unplanned downtimes.

Optionally, a KPI module can be implemented to analyze operator performance, including their average working times. This module’s functionality is closely tailored to user needs.

Summary

The TOMAI Factory System is a flexible solution for real-time monitoring of the production process. Designed from scratch by ELPLC S.A. engineers, it ensures functionality tailored to the specific needs of a factory. Integration with existing production lines, machines, and IT systems such as ERP, MRP, MES, CMMS, WMS, etc., is vital. This includes data exchange at both the IT and OT levels. During implementation, ELPLC S.A. engineers can modify the software of existing control devices.

Implementing the TOMAI Factory System primarily provides financial benefits for the factory. These arise from effective management of raw materials used in production, ensuring appropriate production quality, and overseeing manufacturing with performance analysis of machines and operators. Additionally, it identifies bottlenecks, common causes of downtimes, delays, jams, and reduces the risk of unplanned machine downtimes.

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