Process Optimization Engineer

Purpose:

To analyze, design, and continuously improve assembly processes and systems integration to enhance productivity, improve first-pass quality, and reduce operational costs. The role focuses on leveraging data analytics, digitalization, and automation tools to drive assembly process excellence and standardization.

Key Area of Responsibilities:

• Analyze current assembly processes and line layouts to identify inefficiencies, bottlenecks, and imbalance.
• Develop and implement assembly process optimization initiatives to improve line efficiency, throughput, and cycle time.
• Design, maintain, and standardize assembly process flows, routing, and work instructions to ensure consistency across lines.
• Conduct time studies and establish standard operation times for assembly workstations.
• Optimize manpower allocation, line balancing, tooling, and equipment utilization within assembly operations.
• Introduce and bring new method of technology to fit assembly operation.
• Support root cause analysis (RCA, 8D) for assembly-related defects and implement corrective actions.
• Implement SPC and process control methodologies at critical assembly process steps.
• Develop systems to track, analyze, and reduce repetitive assembly non-conformance issues.
• Apply PFMEA, MSA, and 4M methodologies to mitigate assembly process risks.
• Develop and deploy digital tools using Microsoft 365 (Power Apps, Power Automate, Power BI) to improve assembly process visibility and execution.
• Create dashboards to monitor assembly KPIs such as FPY, line efficiency, UPH, and capacity.
• Develop assembly capacity models and simple forecasting tools to support production planning.
• Collaborate with Manufacturing Engineering, Production, Quality, and T&D teams on assembly process improvement initiatives.
• Support NPI transfer to mass production, focusing on assembly readiness, standardization, and operator training.
• Create and maintain assembly-related technical documentation, SOPs, visual aids, and process guidelines.

• Bachelor’s degree in Mechanical, Manufacturing, Industrial Engineering, or related field.
• 3-5 years of experience in manufacturing or process engineering.
• Experience in process optimization, data analysis, and digitalization projects.
• Proficiency in Microsoft 365 tools (Power Apps, Power Automate, Power BI).
• Strong knowledge of SPC, PFMEA, MSA, 4M methodology and GD&T.
• Programming knowledge (Python, VBA, or similar) is an advantage.
• Strong analytical and problem-solving skills.
• Good communication and teamwork skills.
• Experience in semiconductor or high-mix manufacturing environment is preferred.