Associate Reliability Engineer: Predictive Maintenance

PT Cabot Indonesia; Cilegon; On-site; IDR 120,000,000 - 180,000,000; Full time

Job summary

PT Cabot Indonesia seeks an Engineering Technician to support predictive maintenance and reliability programs across our facilities. You will assist in deploying vibration analysis, thermal imaging, oil analysis, and data-driven improvements to sustainment.

The role requires a Bachelor's degree in engineering and up to 2 years of relevant experience, with a focus on applying statistical methods to improve equipment performance and process reliability.

Qualifications

• Bachelor's degree in an engineering discipline.
• 0–2 years of relevant experience.
• Familiar with statistical methods and quality tools such as RCA and SPC.

Responsibilities

• Check and act upon predictive maintenance results.
• Perform thermal imaging, oil analysis and vibration monitoring.
• Assist in design, procurement, and installation of new equipment for product development and process improvements.
• Determine and implement technically feasible and economically viable sustainment alternatives.
• Analyze and evaluate how to improve system sustainability during operations and changes.
• Collect and evaluate service use and maintenance data; conduct root-cause analyses and implement corrective actions.
• Ensure all product and process changes follow Management of Change principles.
• Support Responsible Care Management System implementation per RC14001 where applicable.

Skills

Statistical methods

Equipment calibration

Data interpretation

Education

Bachelor's degree in Engineering

Tools

Statistical tools

Job description

PT Cabot Indonesia seeks an Engineering Technician to support predictive maintenance and reliability programs across our facilities. You will assist in deploying vibration analysis, thermal imaging, oil analysis, and data-driven improvements to sustainment.

The role requires a Bachelor's degree in engineering and up to 2 years of relevant experience, with a focus on applying statistical methods to improve equipment performance and process reliability.