Simulation Engineer 3

DensoSouthfield, MI

About The Position

We are seeking an experienced Simulation Engineer with manufacturing experience, specializing in process optimization, material management, and line optimization. The ideal candidate will play a key role in developing and implementing digital twin models to optimize manufacturing processes, increase efficiency, and reduce costs. This position requires a deep understanding of manufacturing systems, data integration, and the application of simulation technologies.

Requirements

  • Bachelor’s degree in mechanical engineering, Industrial Engineering, or a related field.
  • 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.
  • Bachelor's degree in Engineering, Computer Science, or a related field.
  • Minimum 5 years of experience in manufacturing engineering or a related field.
  • Proven experience in digital twin model development and application.
  • Strong knowledge of manufacturing processes and material flow analysis.
  • Experience with MES/ERP systems and data integration.
  • Proficiency in simulation software and tools.
  • Excellent problem-solving and analytical skills.
  • Ability to work independently and manage multiple projects.
  • Effective communication and collaboration skills.
  • Willingness to stay updated with industry trends and best practices.

Nice To Haves

  • Advanced degree (master’s) is a plus.

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.
  • Lead the development and maintenance of digital twin models representing manufacturing processes.
  • Conduct simulation studies for production scenarios, material flow, and line balancing.
  • Support MES/ERP data integration into digital models.
  • Participate in continuous improvement initiatives.
  • Document models, assumptions, and results for future reference and knowledge sharing.
  • Provide technical expertise and guidance to junior team members.
  • Ensure compliance with industry standards and best practices.
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