Curricular Internship in Predictive Maintenance (f/m/d)

Do you want to anticipate failures and transform industrial maintenance?

Are you looking to apply your engineering knowledge to a project with a real impact on equipment reliability?

• This internship is an opportunity to develop predictive maintenance solutions, using data and condition monitoring techniques to anticipate failures, reduce unplanned downtime, and optimize the performance of production equipment;
• Integrated into a TPM (Total Productive Maintenance) and continuous improvement approach, you will play an active role in evolving from reactive maintenance to a more preventive, predictive, and data-driven strategy.

Main responsibilities

• Analyze historical failure and performance data to identify patterns and anticipate failures;
• Identify critical equipment and opportunities for implementing predictive maintenance;
• Explore condition monitoring techniques, such as vibration analysis, thermography, and monitoring of operational parameters;
• Optimize existing maintenance plans, applying Lean and TPM methodologies;
• Define reliability indicators, such as MTBF, MTTR, and availability, and evaluate the impact of the implemented improvements;
• Collaborate with maintenance and production teams in the implementation and validation of proposed solutions.

What you will gain

• Practical experience in predictive maintenance, reliability, and continuous improvement;
• Contact with condition monitoring technologies and industrial data analysis.
• Opportunity to develop a project with a real impact on reducing failures, increasing availability, and optimizing maintenance costs.

Join us and contribute to a smarter, more efficient, and future-oriented maintenance for the industry!

• Student of Mechanical Engineering, Electrical Engineering, Automation, Mechatronics, Industrial Management, or an equivalent field;
• Interest in industrial maintenance, equipment reliability, and Industry 4.0 technologies.;
• Curiosity about predictive maintenance, condition monitoring, and data analysis;
• Analytical capacity, critical thinking, and structured problem-solving;
• Knowledge of Excel and interest in data analysis and visualization tools, such as Power BI, Python, or equivalent tools;
• Willingness to learn, initiative, and ability to work in a team;
• Availability to have direct contact with equipment and follow activities on the ground.

🔀 Hybrid working system

🌐 Sharing experiences with colleagues from all over the world

🧑‍⚕️ Medical clinic (psychology and general practice) & social service office on-site

📚 Training opportunities (e.g., technical training, foreign language training) 

📈 Continuous professional development

💲 Access to great discounts on partnerships and Bosch products

🏋️ Sports and health-related activities

🚉 Great access to public transport

🚌 Free transport from Porto

🅿️ Free parking

🍽️ Canteen

Success stories don't happen by chance...

Make them happen. Apply now!