Simulation Engineer 3

DENSO•Southfield, 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.

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.