Case Study on Hybrid Predictive Maintenance of CNC Tool Using Digital Twin (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

15 minutes

Workload:

Array hour

Proficiency:

Advanced

Target:

Professionals, Workers, Manager

SUMMARY

This lesson covers a case study on hybrid predictive maintenance for CNC tools, which integrates both data-driven and model-based approaches with the aid of Digital Twin technology. Through this case study, students will learn about the process of developing a Digital Twin model, the role of data collection and predictive analytics in maintenance, and the benefits and challenges of implementing such a system in industrial settings. This lesson emphasizes the shift from fixed maintenance schedules to dynamic, condition-based strategies that align maintenance activities with actual tool wear and usage patterns.

About The Author

The public establishment INTECHCENTRAS was established by the Engineering and Technology Industries Association of Lithuania (LINPRA). As an independent business organization, LINPRA represents the interests of companies in the metal products, machinery and equipment, electromechanics and electronics, plastics, and rubber industries at both the international and national levels. InTechCentras is a Smart Manufacturing competence center. We serve as the coordinators for the Advanced Manufacturing Digital Innovation Hub and were one of the initiators of the EDIH4LT in Lithuania. Intechcentras is the only independent certified RecyClass.

Learning outcomes

By the end of this lesson, students will be able to evaluate the effectiveness of predictive maintenance strategies in CNC machining by examining the integration of data-driven and model-based approaches within the Digital Twin framework.
By the end of this lesson, students will be able to analyze the process of data collection from CNC machine sensors, focusing on how parameters such as vibration, temperature, and operational metrics contribute to predictive maintenance insights.
By the end of this lesson, students will be able to evaluate the benefits and challenges of hybrid predictive maintenance, particularly in terms of cost efficiency, operational productivity, and CNC tool lifespan.