Manufacturing & Industrial • Stokesdale, North Carolina, United States
Coordinator III-HAC (103497)
Stokesdale, North Carolina, United StatesPosted 11 hours ago
Manufacturing & Industrial
About the Role
Job Purpose
The Operations Research & Simulation Engineer is responsible for the predictive modeling, algorithmic optimization, and business analytics of the master production schedule and manufacturing assembly line. This role builds discrete-event simulation models ("digital twins") and AI/ML-driven heuristic engines to mathematically optimize build sequences, balance assembly station capacities, and run dynamic "what-if" line scenarios. A key focus is utilizing basic business analytics to track key floor metrics while deploying predictive algorithms to mitigate external supply chain volatility and other external factors
Key Accountabilities
Simulation & Digital Twin Development: Develop, scale, and maintain discrete-event simulation (DES) models of the aircraft assembly line to evaluate cycle times, station footprints, labor capacities, and tooling constraints.
Scenario & "What-If" Optimization: Run advanced manufacturing line scenarios to predict the downstream impacts of major disruptions (e.g., late tier-1 fuselage arrivals, engineering change orders, or labor drops) and generate mathematically optimized recovery schedules.
AI/ML & Constraint Programming: Build and deploy basic AI models, stochastic networks, and heuristic algorithms (such as constraint satisfaction solvers) to automate line balancing and buffer against delivery swings.
Business Analytics & Dashboarding: Design, build, and audit cross-functional business intelligence dashboards (e.g., Power BI) to synthesize historical performance, track schedule "thrashing," and report out diagnostic KPIs to leadership.
Data Integration & Systems Architecture: Act as a technical liaison between Manufacturing Engineering, IT, and Supply Chain to cleanly ingest raw data from SAP/MES platforms into simulation and analytics models.
Statistical Process Analysis: Analyze statistical operational data—including process capability studies, machine/labor through-put rates, and supplier lead-time drift patterns.
Continuous Improvement Support: Provide technical root-cause analysis on schedule variances and floor bottlenecks to support physical line optimization and lean implementation goals
Qualifications, Experience, and Skills
Bachelor’s or master’s degree in industrial engineering, Operations Research, Data Science, Aerospace Engineering, or a highly quantitative technical field.
5+ years in a manufacturing environment (aerospace or highly structured assembly preferred).
Core Simulation Software: Strong hands-on experience building complex operational models using discrete-event simulation platforms (e.g., FlexSim, AnyLogic, Arena, Simio).
Business Analytics & ERP Stack: Proven experience with descriptive data analytics tools (Power BI, Tableau) layered over standard ERP/MES ecosystems (e.g., SAP, PLEX, Siemens).
Scheduling Foundations: Deep grasp of traditional manufacturing logic, including Critical Path Method (CPM), Material Requirements Planning (MRP), Takt time balancing, Gantt charts, and resource allocation.
Communication & Presentation: Excellent oral, written communication, and presentation skills. Proven ability to translate abstract algorithmic data into clear, actionable executive trade-offs for production managers and upper management.
Aviation Frameworks (Preferred): General exposure to aircraft assembly sequencing, manufacturing flows, and strict quality frameworks.
Professional Traits: Self-starter able to work under minimal supervision in a fast-paced environment while fostering overall team harmony
Working Conditions
Incumbents may be routinely exposed to equipment operational noise heat-cold-dust, and/or aircraft equipment, parts, or fuel odors.
Incumbents may be required to stand, sit, squat, walk, bend, climb ladders, move, reach, or stretch for prolonged time periods with no restrictions, as required by job duties.
Work in a safe and professional manner while adhering to all regulatory requirements (FAA, OSHA, DOT, EPA, State, and Federal regulations, etc.).
Read, hear, speak, and see with no restrictions, as required by job duties.
Comprehend and adhere to management directions and/or safety instructions with no restrictions.
Effectively communicate in Business English language.
Pull, push, carry, lift, or move items up to 10 lbs. throughout the work shift without assistance, as required by job duties. 8. Pull, push, carry, lift or move materials/people/items/equipment weighing up to 50lbs or more during the work shift, with the use of Company provided “reach assistance technology” or “movement assist technology” (fork-lifts, pallet jacks, pulleys, dolly’s, robotics reach equipment, people movers etc.), as required by job duties.
What You'll Do
Simulation & Digital Twin Development: Develop, scale, and maintain discrete-event simulation (DES) models of the aircraft assembly line to evaluate cycle times, station footprints, labor capacities, and tooling constraints.
Scenario & "What-If" Optimization: Run advanced manufacturing line scenarios to predict the downstream impacts of major disruptions (e.g., late tier-1 fuselage arrivals, engineering change orders, or labor drops) and generate mathematically optimized recovery schedules.
AI/ML & Constraint Programming: Build and deploy basic AI models, stochastic networks, and heuristic algorithms (such as constraint satisfaction solvers) to automate line balancing and buffer against delivery swings.
Business Analytics & Dashboarding: Design, build, and audit cross-functional business intelligence dashboards (e.g., Power BI) to synthesize historical performance, track schedule "thrashing," and report out diagnostic KPIs to leadership.
Data Integration & Systems Architecture: Act as a technical liaison between Manufacturing Engineering, IT, and Supply Chain to cleanly ingest raw data from SAP/MES platforms into simulation and analytics models.
Statistical Process Analysis: Analyze statistical operational data—including process capability studies, machine/labor through-put rates, and supplier lead-time drift patterns.