Job Description

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Perform routine and preventive maintenance on high-precision semiconductor assembly tools.
• Troubleshoot and repair mechanical, electrical, and software-related issues to minimize downtime.
• Ensure all tools are calibrated and functioning within specified parameters.
• Utilize AI and machine learning techniques to predict and prevent equipment failures.
• Implement and manage predictive maintenance programs to enhance tool reliability and reduce unplanned downtime.
• Monitor and analyze OEE metrics to identify areas for improvement.
• Implement strategies to increase equipment availability, performance, and quality output.
• Identify and implement process improvements to enhance tool performance, reliability, and efficiency.
• Collaborate with engineering and production teams to optimize tool utilization and reduce cycle times.
• Maintain accurate records of maintenance activities, tool performance, and spare parts inventory.
• Ensure all maintenance procedures comply with industry standards, safety regulations, and company policies.
• Lead or support the installation, qualification, and commissioning of new tools or tool upgrades.
• Provide technical expertise in the modification or retrofit of existing tools to meet production requirements.
• Provide technical training and support to junior maintenance staff and operators.
• Serve as the point of contact for complex tool-related issues and provide guidance on troubleshooting techniques.

Qualifications

REQUIRED

• Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or a related field. Advanced degree or relevant certifications are a plus.
• Minimum of 7-10 years of experience in maintenance engineering within the semiconductor industry, with a focus on high-precision tools.

Preferred

• Extensive experience with semiconductor assembly equipment, such as wire bonders, die bonders, flip-chip assembly tools, active alignment and laser soldering.
• Proven experience in AI-driven predictive maintenance and a strong understanding of OEE (Overall Equipment Effectiveness) principles.
• Experience in implementing and managing AI-driven predictive maintenance programs.
• Strong knowledge and practical experience in improving OEE within a semiconductor manufacturing environment.
• Familiarity with Industry 4.0 technologies and their application in manufacturing maintenance.
• Work is performed in a cleanroom environment with strict adherence to safety and contamination control procedures.
• May require occasional on-call or after-hours support in response to equipment breakdowns or emergencies.
• In-depth knowledge of semiconductor manufacturing processes, particularly related to assembly and packaging.
• Expertise in handling and maintaining high-precision tools used in semiconductor assembly, such as wire bonders, die bonders, and flip-chip assembly tools.
• Strong expertise in AI-driven predictive maintenance techniques, including data analysis, machine learning, and the application of predictive models.
• Ability to implement and optimize predictive maintenance systems to reduce equipment downtime and enhance operational efficiency.
• Deep understanding of OEE metrics and how they impact manufacturing performance.
• Expertise in Lean Manufacturing principles and their application to improve overall equipment effectiveness and production efficiency.
• Advanced troubleshooting skills for resolving mechanical, electrical, and software-related issues on high-precision equipment.
• Ability to diagnose and resolve complex equipment problems to minimize downtime and maintain tool performance.
• Knowledge of equipment automation, control systems, and their integration into manufacturing processes.
• Experience with CAD software and other engineering tools for designing and modifying equipment.
• Familiarity with cleanroom standards and contamination control procedures required in semiconductor manufacturing environments.

Skills

• Proficient in troubleshooting mechanical, electrical, and software issues on high-precision equipment.
• Strong understanding of semiconductor manufacturing processes and equipment calibration.
• Experience with CAD software and equipment automation systems is preferred.
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills in English.