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iTAC highlights: A day in a factory – solving challenges with MOM

Achieve transparency and efficiency in manufacturing, minimize errors and increase overall equipment effectiveness (OEE) with Manufacturing Operations Management (MOM)

Montabaur, March 21, 2022 – Manufacturing companies face new challenges every day. For instance, they must meet the increasing demands for efficiency, quality and transparency – and at the same time digitize processes and much more. The MES/MOM specialist iTAC Software AG supports the solution of these tasks with the iTAC.MOM.Suite. The individual modules can be used for different use cases in everyday factory operations. iTAC shows examples of difficulties that can arise on a factory day and how these can be solved with Manufacturing Operations Management (MOM).

"Product development cycles are becoming increasingly shorter. In addition, they are undergoing ever greater individualization, tailored to the respective customer requirements. Production must be able to adapt flexibly and quickly to new requirements and run productively. There is little room for errors and malfunctions. Nevertheless, these can occur unexpectedly on a daily basis," explains Peter Bollinger, CEO of iTAC Software AG, a subsidiary of Dürr AG.

A practical example: The production manager suddenly discovers in the morning in the quality management module that an OEE figure for a machine was not in order. The reason: For a certain period of time, the machine did not deliver any output, which had a negative impact on the OEE figure. It is necessary to take a closer look at the data in the line's equipment.

Such challenges can be solved with a MOM solution. One component of the iTAC.MOM.Suite is iTAC.SMT.Edge, which is a machine integration platform based on an edge solution for the standardization and centralization of data in SMT production. The solution provides complete transparency in the plant for each line. "If the worker discovers a defective OEE figure, they can analyze the production performance in more depth using a comparison function by date, product part number and machine," explains Peter Bollinger.

Analyzing data in real time
A central role in the analysis is also the possibility of easily linking IIoT data, which is based on so-called unstructured data in the form of sensor data (e.g. vibration, temperature, etc.), with MES data to create flat data structures and analyzing this data almost in real time. Analysis tools such as iTAC.IIoT.Edge take care of this and enable different use cases according to the specific requirements of electronics production and other manufacturing areas. For example, the data from the sensors installed in the plants, which measure vibrations or humidity, can be easily integrated into the iTAC.IIoT.Edge and linked with MES data. In the process, the data packets can be forwarded to the iTAC.IIoT.Edge or other analysis tools. Due to local data processing, the Edge solution is more cost-effective than cloud computing and also increases performance.

Maintenance Manager facilitates maintenance
Once the machine responsible for the incorrect OEE figure has been identified, the next step is to repair it or, if necessary, carry out minor maintenance work during the shutdown. With iTAC's Maintenance Manager, a repair or maintenance order can be created and assigned to maintenance personnel. The Maintenance Manager is available for both workstations and mobile devices such as tablets. This means that maintenance tasks can be carried out on the spot in production and are easy to define or plan in the office.

Planning with the consideration of maintenance tasks
With the iTAC.APS.Service as an elementary part of the iTAC.MOM.Suite, precise planning via the Advanced Planning and Scheduling System is not only possible taking into account material, personnel and production orders, but also, for example, including repair or maintenance tasks – and all of this in real time. The data from the analytics service can be integrated into the Maintenance Manager so that the best repair and maintenance time can be predicted. "In this way, negative effects on quality and efficiency of production processes can be prevented in the long term, and overall plant effectiveness can be increased," explains Peter Bollinger.