Metrology Equipment Use Case

Summary

Metrological equipment is essential for quality control and in-line inspection in manufacturing processes. To maintain products as competitive as possible, the detection of flaws or maintenance needs must be performed in a cost and time-effective approach, keeping the cost of the final product as low as possible. Furthermore, the early detection of machines’ errors would be essential for the customer of TRIMEK and the owner of the measuring equipment, to avoid wrong measurements and loss of efficiency and performance.

The testbed aims to monitor the performance of a coordinate measuring machine to correlate the results of the verification and calibration processes with the values of the operational condition. Data acquisition is performed via the SERENA databox, serving as a gateway and providing data from the edge to the SERENA cloud platform. Moreover, the RUL calculation is performed on the cloud triggering maintenance activities. SERENA AR operator support services are included as well to support the operator during the inspection and maintenance activities. Cloud deployment of the SERENA system is included in this demonstrator. The addition of predictive support as a service with the corresponding business model facilitate the reduction of maintenance costs, hardware problems, predictive scheduling of corrective activities, and increased customer satisfaction.

The business-wise objectives for TRIMEK, as well as the KPIs selected for the measure, are listed below:

  • Improve the portfolio of services provided with the sale of TRIMEK’s products, strengthening its market position and increasing its competitiveness
  • Increase customer satisfaction with the overall functioning of the machine, its state monitoring, and new maintenance approach
  • Facilitate the knowledge of TRIMEK’s different types of client machine’s state and maintenance related data management
  • Assess a shift from proactive and reactive maintenance strategies to predictive, at least in a partial manner
  • Reduce the soft and hard number of machine breakdowns per year
  • Reduce the cost associated with repairing and maintenance activities
  • Extend the CMM machine lifecycle
  • Improve the accurateness of the maintenance personnel sent to customers for problem solution and maintenance activities

As a result of applying SERENA solutions, all the tools and services functioning, correlation, assessment, and validation from our TRIMEK’s perspective as end-user can be transduced into the following:

  • Increment of operator satisfaction in 2 points on a scale from 1 to 10
  • Reduction of person hour per maintenance process in 10-20 %
  • Reduction of total maintenance cost in 10-20%
  • Increment of availability of the machine in 5-10%
  • Reduction of unexpected failures in 5-10%
  • Reduction of maintenance procedure time in 20-30%
  • The lifetime of components extended by 0.5 years
  • Increment of turnover in 5-10%

 

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D6.4_final.pdf PDF
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Country: ES
Address: Altube 01139
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Data analytics.png
Databox dashboard.png
Databox.png
SERENA dashboard UI.png
Databox architecture.png
CMM SPARK model.png
Scheduler UI.png
OPerator support service UI.png
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Comment:

From the activities developed within the SERENA project, it became clearer the relation between the accuracy and good performance of a CMM machine and the good functioning of the air bearings system. It was proved or confirmed by TRIMEK’s machine operators and personnel that airflow or pressure inputs and values out of the defined threshold directly affects the machine accuracy. This outcome was possible from the correlation made with the datasets collected from the sensors installed in the machine axes and the use of the tetrahedron artifact to make a verification of the accuracy of the machine, thanks to the remote real-time monitoring system deployed for TRIMEK’s pilot. This has helped to reflect the importance of a cost and time-effective maintenance approach and the need to be able to monitor critical parameters of the machine, both for TRIMEK as a company and for the client’s perspective.

 

Another lesson learned throughout the project development is related to the AI maintenance-based techniques, as it is required multiple large datasets besides the requirement of having failure data to develop accurate algorithms; and based on that CMM machine are usually very stable this makes difficult to develop algorithms for a fully predictive maintenance approach in metrology sector, at least with a short period for collection and assessment.

 

In another sense, it became visible that an operator’s support system is a valuable tool for TRIMEK’s personnel, mainly the operators (and new operators), as an intuitive and interacting guide for performing maintenance task that can be more exploited by adding more workflows to other maintenance activities apart from the air bearings system. Additionally, a more customized scheduler could also represent a useful tool for daily use with customers.

 

As with any software service or package of software, it needs to be learned to implement it and use it, however, TRIMEK’s personnel is accustomed to managing digital tools.