Gq Ops Ie Modeling And Automation Manager

As Manager, GQ Ops IE Modeling & Automation, you will lead the transformation of GQ Ops into a more automated, data-driven, and scalable operation. This role owns automation strategy, system enablement, IE modeling, planning tools, and data governance, with a strong focus on reducing manual touchpoints, improving operational reliability, and enabling a future-ready reliability lab operating model. You will work closely with cross-functional teams—including GQ Ops, Process Engineering, Planning, IE, Central and Site Automation, IT, Facilities, and external partners—to identify high-impact opportunities, translate operational needs into practical solutions, and drive standardized, scalable execution across sites. Key Responsibilities 1. Lab Automation Strategy & Deployment Lead the GQ Ops automation roadmap to improve productivity, quality, safety, and operational consistency. W Evaluate and benchmark industry solutions; translate relevant technologies into scalable lab automation strategies. Drive equipment and process automation (e.g., laser mark, ALU, robotics, vision systems, workflow digitization) to reduce manual work. Partner with stakeholders to define requirements, assess ROI, support vendor engagement, and execute FAT/SAT/PAC. Standardize automation designs across sites based on best-known methods and operational needs. Drive AI Transformation for speed, innovation and productivity. 2. MES & AMHS Enablement Drive automation of key workflows and ensure MES readiness across development, UAT, deployment, and sustainment. Enable AMHS integration to improve material flow, throughput, and system reliability. Act as the central GQ Ops interface for MES, AMHS, and lab automation systems. Partner with IT, Automation, and Operations teams to improve system uptime, performance, and issue resolution. Support AMHS solutioning including layout optimization, tool interface readiness, and operational integration. 3. IE Modeling & Planning Systems Develop and sustain scalable, automated planning systems to support GQ Ops operations. Build IE models covering capacity, throughput, utilization (PeakUtil%), cycle time, and bottleneck analysis. Translate business inputs (ramp plans, loading, tool availability) into actionable planning scenarios for decision-making. Improve planning tool adoption, model accuracy, and cross-site standardization. Develop digital tools, dashboards, and decision-support systems for operations. Bridge the Plan-to-Performance (P2P) gap through modeling insights and feedback loops with operations teams. Explore and deploy advanced analytics/AI use cases to improve prediction, automation, and decision quality. 4. MSH Greenfield Lab Enablement Lead planning and enablement of MSH greenfield reliability lab for future ramp requirements. Translate business needs into layout design, process flow, automation readiness, and execution plans. Drive alignment on equipment selection, utilities, infrastructure readiness, and ODD requirements. Coordinate across GEL, Process Engineering, Planning, Facilities, Automation, and vendors to ensure readiness and timelines. Integrate automation, AMHS, MES, and data considerations early to ensure scalability and minimize rework. 5. Central Team Leadership & Cross-Site Execution Lead and develop a high-performing central team. Set priorities, manage deliverables, and ensure timely execution of automation and system initiatives. Communicate insights clearly to stakeholders, including automation impact, system risks, and model outputs. Drive cross-site alignment to standardize best-known methods and scale successful solutions. Foster a culture of innovation, accountability, and data-driven decision-making. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. Minimum Requirement Bachelor’s degree or higher in Industrial Engineering, Automation, Mechatronics, Electrical/Electronics, Mechanical Engineering, Computer Science, Data Science, or a related technical discipline. Minimum 7 years of experience. Relevant experience in automation, industrial engineering, manufacturing systems, planning, capacity modeling, data analytics, process improvement, or system implementation. Strong working knowledg…