Nov 28, 2021  
2019-2020 Graduate Catalog 
    
2019-2020 Graduate Catalog [ARCHIVED CATALOG]

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ETSC 541 - Industrial Operations Management


Description:
Operations Management within the context of Industrial Engineering. Topics include, but are not limited to, forecasting, scheduling, lean production, capacity management, inventory management, aggregate planning, supply chain management, logistics, maintenance and reliability, and decision making. Formerly IET 541, students may not receive credit for both.

Prerequisites:
Prerequisite: ETSC 540 or permission of instructor.

Credits:
(4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

  • Select appropriate forecasting methods and correctly apply those methods to generate product demand forecasts.
  • Assess the capacity of work processes, equipment, and facilities, to compare this assessment with forecasted demands for the work in question, and to suggest appropriate decisions about matching capacity with demand.
  • Create aggregate plans that specify the production capacity, inventory, labor, overtime, and subcontracting needs for given product mixes and demand levels and to compute the costs associated with resource selection options available to meet demand.
  • Calculate system reliability and mean time between failures for various system components, and they will be able to suggest appropriate strategies for improving system performance.
  • Select appropriate maintenance methods matching the needs placed on production by market demand with constraints presented by capacity and by the condition of a facility and its equipment and systems.
  • Configure storage facilities and specify material handling systems to accommodate the needs presented in various scenarios, given the inventory management practices being used in that facility .
  • Identify how quality requirements such as ISO9001 and how engineering standards impact the collaboration between partners in a supply chain in terms of everyday operations and in terms of governing the product development process.
  • Apply decision making tools such as decision tables, decision trees coupled with expected monetary value.
  • Determine optimal solutions for constrained problems using linear programming techniques and Monte Carlo analysis.

Learner Outcomes Approval Date:
10/16/2013

Anticipated Course Offering Terms and Locations:



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