JOB DESCRIPTION:
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.
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.
- Lead the development and maintenance of digital twin models representing manufacturing processes.
- Conduct simulation studies for production scenarios, material flow, and line balancing.
- Collaborate with cross-functional teams to design data-driven solutions enhancing process efficiency and product quality.
- Analyze data to identify inefficiencies and improvement opportunities.
- Support MES/ERP data integration into digital models.
- Participate in continuous improvement initiatives.
- Document models, assumptions, and results for future reference and knowledge sharing.
- Stay updated with the latest digital twin and manufacturing technology trends.
- Provide technical expertise and guidance to junior team members.
- Ensure compliance with industry standards and best practices.
- 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.
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