Simulation Engineer 3

Key Responsibilities

• Develop and deploy digital twin models to replicate physical manufacturing processes, enabling real-time monitoring, simulations, and predictive analytics.
• Collaborate with cross-functional teams, including operations, process engineering, and IT, to design data-driven solutions that enhance process efficiency and product quality.
• Identify opportunities for process optimization, material flow improvements, and line balancing by leveraging digital twin simulations.
• Use predictive analytics to simulate different production scenarios and anticipate potential bottlenecks or inefficiencies.
• Integrate data from various systems, such as MES, ERP, and IoT devices, into digital twin models to provide accurate, real-time insights.
• Analyze digital twin outputs to recommend process changes, reduce downtime, optimize material management, and improve overall productivity.
• Ensure the scalability and adaptability of digital twin models across multiple production lines and facilities.
• Collaborate with the IT department to ensure secure, efficient data flow between physical systems and their digital counterparts.
• Support continuous improvement initiatives by identifying areas for cost reduction, yield improvement, and process reliability.
• Stay up-to-date with industry trends and advancements in digital twin technology, automation, and smart manufacturing.

Qualifications

• Bachelor’s degree in mechanical engineering, Industrial Engineering, or a related field.
• Advanced degree (master’s) is a plus.
• 8+ years of experience in manufacturing, with a focus on process optimization, material management, and line optimization.
• Hands-on experience with digital twin technologies, simulation software (e.g., AnyLogic, Simio, or Siemens Tecnomatix), and data analytics tools.
• Proficiency in using IoT, AI, and machine learning to support digital transformation in manufacturing.
• Solid knowledge of lean manufacturing, Six Sigma, and other process improvement methodologies.
• Experience in integrating digital twin models with ERP/MES systems.
• Strong analytical and problem-solving skills with the ability to interpret complex data sets and recommend actionable solutions.
• Excellent communication and interpersonal skills, with the ability to work effectively across teams.