
Optimize Production
1 day ago
The Manufacturing Optimization Specialist is responsible for analyzing, designing, and optimizing manufacturing processes to improve efficiency, reduce waste, and ensure quality.
- Leading Improvement Projects: Lead complex projects using Six Sigma methods (e.g., DMAIC) to achieve strategic objectives such as process optimization, waste reduction, and quality enhancement.
- Process Assessment & Improvement Identification: Partner with leadership to evaluate current processes, metrics, and customer requirements to identify areas ripe for improvement.
- Project Management & Reporting: Define goals and boundaries, secure resources, identify stakeholders, create detailed project plans and charters, and track project progress, milestones, and savings.
- Cross-functional Collaboration: Work with cross-functional teams to ensure successful implementation of improvement initiatives.
- Analysis and Problem Solving: Expertise in Lean methodologies and Six Sigma principles is used to identify, analyze, and solve complex problems affecting business operations and customer satisfaction.
- Associate's degree in Mechanical Engineering, Industrial Engineering, or related field.
- Bachelor's degree but not required.
- Minimum of 5 – 10 years experience.
- Lean Six Sigma Black Belt Certification: Strong background and certification in Lean Six Sigma are expected.
- Strong Analytical Skills: Ability to conduct root cause analyses, analyze data, and apply statistical tools to identify trends and potential issues.
- Leadership and Coaching: Process Engineers must be able to effectively lead cross-functional teams, assign roles, provide coaching and development, and foster collaboration to drive organizational change.
- Problem-solving: Ability to understand the problem, analyze the data, develop projects, and implement solutions.
- Ability to work in a manufacturing environment, including exposure to noise, heat, and moving machinery.
- Ability to lift up to 50 pounds occasionally and stand for extended periods during process observation.
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