Advanced Facilities Design

Study of the theoretical and applied aspects of facility logistics. Topics include location, layout, material handling systems, storage and warehouse systems, and cellular systems.

IE58200

Credit Hours:

3

Learning Objective:

Be able to describe and understand fundamental definitions and models related to each course module; Be able to describe the relationships between fundamental models across the course modules; Identify similarities and differences between common modeling approaches in facility design within each area and across areas; Be able to develop a decision model for facility-level logistic system design; Be able to create an appropriate decision model for a design problem within each module; Be able to critique available approaches that exist in popular and theoretical literature related to facility design; Be interested in the critical evaluation and improvement of logistics system (specifically, facility) designs; Understand the need for multiple perspectives about a facility design problem in order to construct a deeper understanding of its importance and intricacies; Be able to identify sources of knowledge in logistics system (specifically, facility) design; Be able to inform others about how to recognize opportunities for improvement in logistics system (specifically, facility) design; Connect concepts of the course to everyday scenarios, either at work or in personal life; Become confident in assessing usage of space and interaction design among elements within a physical environment.

Description:

Study of the theoretical and applied aspects of facility logistics. Topics include location, layout, material handling systems, storage and warehouse systems, and cellular systems.

Topics Covered:

  1. Foundational Knowledge
  2. Location
  3. Layout
  4. Material Handling Systems
  5. Storage and Warehouse Systems
  6. Cellular Systems Design

Prerequisites:

Graduate Standing, or IE 484, or undergraduate standing and a course in production systems. Informal: Comfort with developing and solving optimization problems. Basic probability (some queueing is helpful, but not mandatory). MS Excel skills.

Applied / Theory:

50 / 50

Web Address:

https://mycourses.purdue.edu/

Web Content:

A link to current course website, syllabus, grades, lecture notes, homework assignments, solutions, and quizzes.

Homework:

All homework will be facilitated through D2L Brightspace

Projects:

Each student (either as an individual or in a group) will complete a semester project. The topic of the project will be up to each student/group, with instructor consent, and must follow one of the following 4 tracks: (1) Survey scholarly articles within a particular focus area/theme; (2) Implement (program) one or more algorithms discussed in class or from a scholarly article; (3) Study a real problem from one of the topic areas and propose an improvement using the analytical tools discussed in the course.

Exams:

There are no exams in this course.

Textbooks:

Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.
All textbooks will be available as eBooks via Purdue Libraries, or through another site.

Computer Requirements:

ProEd minimum computer requirements.
Students must install the AMPL IDE on their personal computers (https://ampl.com/products/IDE/) and install the Kestrel client for the NEOS Server (https://ampl.com/try-ampl/run-ampl-on-neos/)

ProEd Minimum Requirements:

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