Ensure process quality with quantity and needs-based maintenance

Advantages of quantity-based process monitoring

By changing your maintenance strategy from time-based to needs-based maintenance, your entire process will be optimised. The added value results from the use of the moneo IIoT platform and moneo LifetimeEstimator. moneo LifetimeEstimator is part of ifm’s moneo Industrial AI Assistant package, which offers intelligent, AI-powered additional features. The moneo Industrial AI Assistant in turn is part of the overall moneo IIoT Insights package. This package offers multiple solutions to optimise your processes. Needs-based replacement through quantity-based maintenance reduces resource consumption because the plant’s capacity utilisation is taken into account. Targeted analysis of historical data also makes it easier to calculate maintenance times. Overall, quantity-based maintenance makes for a transparent production process and guarantees quality assurance of the manufactured products. moneo can also be easily integrated into existing production processes – a minor effort with a major impact.

Value proposition

Process optimisation using a piece counter

Piece counting takes place in different quality control processes. This usually involves counting the batches produced or monitoring wear parts that wear out during production. Piece counters are also integrated into production processes to distinguish between good and bad parts. This is the basis for key metrics such as first-pass yield (FPY). Defects or failures in the production process are identified at an early stage. Based on the data collected, measures can then be taken to produce defect-free products and adjust maintenance accordingly.

Piece counters are also used in the final testing of sensors by recording strokes on a knuckle-joint press for pressing housings using position sensors. A warning is given when a certain level of wear is reached and the equipment needs to be replaced. This means the maintenance team still has time to replace the equipment. The collected piece count data can be used for documentation purposes for production analysis and other operational purposes.

This allows companies to track the production sequence and sustainably optimise their processes.

moneo simulation video

AI tool moneo LifetimeEstimator enables predictive maintenance

moneo LifetimeEstimator is a function block of ifm’s Industrial AI Assistant and encompasses all AI solutions. moneo LifetimeEstimator reliably predicts the remaining service life of critical wear parts. The intuitive application requires no expert AI knowledge. A 5-step wizard guides the user through the application.

First, precise data on the produced pieces is captured and processed in real time. The sensor values are automatically converted and analysed to generate process-relevant information, which is then clearly visualised in moneo. The processed data provides detailed insights into the plant’s capacity utilisation, the actual degree of wear of components and tools, and the remaining lifetime of the monitored process components or materials. Values that exceed defined thresholds are automatically detected. The integrated alarm management enables a targeted response. A defined lead time helps prevent unplanned downtimes and maintain product quality.

moneo LifetimeEstimator is the perfect addition to make quantity-based maintenance even more precise. As a result, no resources are wasted, maintenance can be planned optimally and machine downtime can be avoided.

Automated data transmission through versatile interface management

The combination of hardware and software – or, more precisely, the integrated solution including ifm sensors and the IIoT platform moneo – offers a wide variety of options and interfaces to various systems, and supports you in automating your processes. moneo and moneo LifetimeEstimator can be used as an on-premises solution as well as directly in the cloud. Depending on the selected application, an edgeGateway ensures data transfer to moneo|cloud, or a vAppliance enables data transfer to the on-premises solution. Numerous protocols such as MQTT and OPC UA can be used to extract data from moneo and integrate it into the downstream system.

Direct connection to SAP PM is only possible with the on-premises solution through the integration of the Shop Floor Integration (SFI) interface. If the count value is violated, a maintenance order is generated in the SAP system via the SFI interface in parallel to the message in moneo. The person responsible for the system has the opportunity to carry out the appropriate maintenance and then reset the counter. After completing the maintenance order, the replacement can be reported and the counter reset in the SAP system. This also automatically closes the threshold value violation in moneo.

By providing the appropriate interfaces, ifm also enables you to store your data in the cloud and use it for further analysis if necessary.

• moneo
  MQTT or OPC UA → AWS, Azure, SAP
• SAP Integration
  SFI (shop floor integration) → SAP PM
• Alarm
  Email notification (threshold)
• Spare parts
  Automatic ordering through SAP
• Cloud and on-premises
  Cloud and on-premises use

For engineers: how to integrate a piece counter into your production processes

Do you want to implement needs-based monitoring of your production process and ensure a consistently high level of quality of your processes and products? Then you should opt for the IIoT platform moneo. You can install the software centrally on a server or use it in moneo|cloud. For the on-premises solution, IO-Link masters are connected to the server via an internal network (VLAN).

The counter values are shown on a multifunction IO-Link display and forwarded from there to the IO-Link master. Depending on the application and your existing hardware, different counters such as VSE meters, controllers such as Siemens LOGO or other PLC controllers are connected to moneo via an interface such as the IO-Link master or ifm Agent. This enables data transfer to moneo. Dashboards are created in moneo and warning and alarm thresholds are set in moneo LifetimeEstimator. In the first step, two replacement intervals of the wear parts are recorded in moneo. In the second step, moneo LifetimeEstimator is trained and set up based on the recorded cycles.

Depending on the application, the analysed process values provide information about the ratio of good and bad parts, the quantity produced and the wear of machine parts, and allow conclusions to be drawn about the wear of components. If a replacement is necessary, this will be indicated by an alarm. The advance notification period for upcoming component replacements is set to 7 days before the threshold is reached, allowing the necessary replacement to be incorporated into the weekly personnel planning. A ticket processing rule can also be configured. If threshold violations occur, the SFI interface automatically sends an alarm to the ERP SAP PM system. After maintenance, the piece counter in the multifunction IO-Link display is reset via a key-operated switch depending on the application.

With its moneo solutions, ifm provides a variety of benefits, optimising process transparency, process and maintenance planning, and resource utilisation. As a result, downtimes are avoided and money is saved.

System structure – piece counting

1. IO-Link master (VLAN)
2. Power supply
3. Multifunction display for monitoring of analogue standard signals
4. Inductive sensor
5. Key-operated switch

moneo software

• Historical data
• Visualisation
• Monitoring
• Alarm function
• Threshold violations via SFI to SAP

System structure – good and bad parts

1. IO-Link master (VLAN)
2. Power supply
3. Multifunction display for monitoring of analogue standard signals
4. Inductive sensor
5. Key-operated switch

System structure – wear of machine parts

1. Power supply
2. Diagnostic electronics for vibration sensors
3. Inductive sensor
4. Key-operated switch