| INDUSTRIAL PRODUCTION MANAGEMENT
(objectives)
This course is aimed at providing the basic methodological tools required for production planning and control in manufacturing systems. Specific methods used in make to stock, assemble to order, make to order, and engineering to order are analyzed, also discussing the differences between push and pull production systems. The course follows the traditional hierarchical approach including aggregate production and capacity planning, master production scheduling, materials and manufacturing resources requirements planning (MRP and CRP techniques), order release planning and job scheduling. furthermore, techniques for demand forecasting and implementation of just in time lean manufacturing systems are presented. The course also provides tools to estimate the performances of manufacturing systems, i.e. the links between work in process, throughput and cycle time, including variability effects and lot sizing decisions. finally, production planning decisions are put in perspective with strategic decisions, with capacity planning issues and with inventory management problems.
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Derived from
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20801966 INDUSTRIAL PRODUCTION MANAGEMENT in Management and automation engineering LM-32 CAPUTO ANTONIO CASIMIRO
(syllabus)
The industrial enterprise
Organization and scope of industrial enterprise. Classification of production systems. Analysis of production processes (process mapping and performance estimation). Little’s law. Impact of flow and process variability on main performance measures. Analysis of lot size effects on capacity, lead time and manufacturing cost. Lot sizing criteria in repetitive manufacturing.
Demand forecast
Analysis of demand variability components (random fluctuations, trends, seasonality). Classification of quantitative and qualitative forecasting methods. Linear regression causal models, time series methods (moving averages, exponential smoothing) and seasonal forecasting methods. Estimation of forecast error. Demand estimation for new products: market size and market penetration dynamics (Bass model).
Fundamentals of production planning and control
Analysis of P-Time and D-Time. Push and Pull production systems. Make to Stock, Assemble to Order, Make to Order ed Engineering to Order systems. The hierarchical production planning framework.
Aggregate planning
Alternatives to match production and demand. Trial and error aggregate planning methods (chase, level and mixed plans). LP models for the aggregate planning problem.
Master production scheduling
Criteria to disaggregate an aggregate plan and methods to develop a Master Production Schedule (MPS) based on items forecast and firm orders. Etsimation of Available to Promise capacity. Difference of MPS in MTS and ATO settings.
Requirements planning
MRPI and II methods. Capacity Requirements Planning. Lot sizing criteria for materials requirements planning. Limitations of MRP systems.
Operational planning and manufacturing execution
Final Assembly Schedule and operational plans. Criteria for job release and queues control. Heuristic rules for job scheduling and priority assignment. Production advancement and control systems.
Pull production systems
Kanban method and production leveling techniques. Methods for sequencing mixed model assembly lines. CONWIP. Comparison of push and pull systems.
Inventory management
Classification and scope of inventories. Relevant costs in inventory management. Management of dependent demand materials: economic order quantitym reorder cycle and reorder level policies. Service level and computation of safety stock. Benefits of safety stock pooling. Management of dependent demand items: lot by lot and dynamic lot sizing techniques. Newsboy model and single period order sizing. ABC classification and warehouse performance measures.
(reference books)
Lecture notes provided by instructor and uploaded on Moodle web site.
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Dates of beginning and end of teaching activities
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From 01/03/2023 to 12/06/2023 |
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Delivery mode
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Traditional
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Attendance
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not mandatory
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Evaluation methods
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Oral exam
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Università Roma Tre