As Maintenance Planning Engineer, you'll be the strategic data architect and systems specialist driving our manufacturing reliability excellence through comprehensive maintenance planning, advanced analytics, and systematic process optimization. You'll serve as the technical expert responsible for maintaining our Computerized Maintenance Management System, developing data-driven reliability strategies, and ensuring seamless integration between maintenance operations and business performance metrics to maximize equipment effectiveness and operational efficiency.
You'll design and implement maintenance planning frameworks, establishing standardized work management practices and performance measurement systems for all maintenance execution. Your expertise will encompass maintenance optimization, EAM system administration, materials management (MRO), and continuous improvement initiatives. You'll be instrumental in driving operational excellence through strategic planning, advanced analytics, and systematic process improvements that support data-driven decision making and cost optimization.
Education: • bachelor's degree in industrial engineering, Reliability Engineering, Mechanical, Electrical, Mechatronics, Electronics, Robotics Engineering, or related technical field • Professional certifications preferred (CMRP, CRE, Six Sigma, or equivalent reliability engineering certifications desirable)
Experience: • Minimum 1 year of maintenance planning experience in manufacturing environments • Proven experience with EAM/CMMS system administration (IBM Maximo, SAP PM) • Experience in materials management and inventory optimization (MRO) • Background in statistical analysis and reliability modeling • Experience with cross-functional teams
Software Proficiency: • Advanced EAM/CMMS expertise (IBM Maximo, SAP PM) for system administration and optimization • Advanced data analytics (Python, SQL, R) for reliability analysis and predictive modeling • Statistical analysis software (Minitab,) for reliability engineering and failure analysis • Microsoft Office Suite (Advanced Excel for data analysis, Power BI for dashboard creation)
DISCLAIMER: Ford Motor Company is an Equal Opportunity Employer, as we are committed with a diverse workforce, and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran and basis of disability
Develop comprehensive equipment reliability strategies by analyzing failure patterns, Mean Time Between Failures (MTBF), Mean Time To Repair (MTTR), and Overall Equipment Effectiveness (OEE) metrics to optimize maintenance interventions and maximize asset performance
Measure key performance indicators for monitor the maintenance execution, delivering actionable recommendations based on comprehensive reliability analysis and trend identification (backlog, wrench time, technical utilization, maintenance compliance)
Develop and maintain accurate equipment metadata by systematically collecting and inputting critical information including manufacturer specifications, model numbers, serial numbers, and hierarchical system structure data within the CMMS Platform (Maximo MFM)
Implement and maintain equipment identification systems ensuring all assets are properly labeled, barcoded, and traceable within the facility through standardized asset management protocols
Design and maintain work order data accuracy by systematically adding equipment to Preventive Maintenance (PM) plans, developing optimized schedules and work packages, and defining scheduled due dates and initial meter points for system-generated work orders
Develop facility-specific PM plans, schedules, routes, and work packages based on manufacturer recommendations, operational history, and reliability data to optimize maintenance effectiveness and resource utilization
Support management in work order data validation including equipment assignments, booked hours tracking (employee and vendor), parts usage analysis, work order classification, closing code accuracy, and comprehensive work order documentation
Manage comprehensive work order lifecycle ensuring proper creation, detailed planning, real-time updates, and systematic closure of all maintenance activities within the CMMS system
Coordinate maintenance scheduling and resource assignment by optimizing work distribution, balancing workload, and ensuring proper skill matching for maximum efficiency and quality outcomes
Develop and maintain spare parts metadata accuracy by systematically collecting supplier information, catalog numbers, min/max quantities, pricing data, manufacturer details, and standardized part numbering systems
Drive comprehensive materials management processes including requisition creation, purchase order generation, receipt processing, implementing 5S methodology in stores, and developing critical spares inventories
Execute systematic inventory control through regularly scheduled cycle counts, audit materials management processes, and support management with data-driven corrective actions based on KPI analysis and EAM data insights
Cost Optimization & Quality Improvement • Collaborate with facilities teams to implement cost reduction initiatives and improve parts quality through strategic sourcing, standardization efforts, and supplier performance optimization
Analyze maintenance costs and identify optimization opportunities through comprehensive data analysis, benchmarking, and process improvement recommendations
Provide comprehensive software training to end users and maintenance supervisors, serving as primary liaison for problem resolution and technical escalation support
Coach and educate maintenance staff on CMMS functions and best practices, ensuring optimal system utilization and data quality across all maintenance operations
This role offers the opportunity to leverage advanced reliability and maintenance engineering principles to drive manufacturing excellence. You'll apply your analytical expertise and systems knowledge to optimize our competitive advantage through superior maintenance planning and data-driven operational excellence.