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Outline of Lectures

 

Outline of Lectures

1.

Supply Chain Management (3 credits)

 

This course explores fundamental and emerging topics in global supply chain management, including inventory management, network planning, information visibility, supply contract, integration, alliances, procurement, product design, global logistics, risk management, pricing, IT and standards. Contents will be suitable for students pursuing research and/or professional career in this discipline. In addition to the text, simulation games, cases will also be used for presentation and discussion.

2.

Lean Production and Management (3 credits)

 

Course Introduction and Grouping, Overview, Crisis and Opportunity, Business Process Reengineering, Profit and Performance Indicator, Principle, Seven Wastes and Improvement, Standardization and Multi-Skill Worker, Five S and Visual Management, Lean House and Organization, Procedure, Value Stream, Quick Changeover, Push and Pull, Kanban System, Autonomation and Error-Proofing, Design of Manufacturing Process, Total Productive Management, Total Quality Management and Six-Sigma, Journal Paper Review, Case Practice and Report.

3.

Global Logistics Management (3 credits)

 

Supply Chain (or Value Chain) integrates suppliers, manufacturers, inventory and distribution activities to provide variability, fast, reliable and high service level for their customers. Well-designed of Logistics systems and operations management are essential to lower Logistics cost and enhance global competitivity. We will go through these issues from Harvard Business School and Richard Ivey School of Business cases study.

4.

Inventory Management Systems with Application (3 credits)

 

This course is designed to (a) develop a familiarity with inventory control and management; (b) understand the important issues in inventory management; (c) develop the ability in modeling problems and analyzing results obtained; (d) develop skills in applying a variety of techniques to deal with inventory problems.

5.

Scheduling Theory (3 credits)

 

This course centers on deterministic scheduling problems, including single machine models, parallel machine models, flow shop, job shop and open shop.

6.

Applied Probability Models (3 credits)

 

This course aims to provide students a board fundamental knowledge of probability theory and probability models. For more subsequent courses such as stochastic processes, reliability analysis, and decision process can be built on these basic probability models.

7.

Mathematical Programming (3 credits)

 

This course is to teach the students the formulation and algorithmic aspects underlying Linear Programming, Network Flows and Nonlinear Programming. Topics to be covered include: problem formulation, simplex method in tableau and revised form, duality theory, an introduction to the geometry of the simplex method, sensitivity analysis, the simplex method for the transportation and network flow problems, optimality conditions and numerical methods for nonlinear programs.

8.

Dynamic Programming (3 credits)

 

The art of formulation illustrated by Dynamic Programming is useful in learning creative thought rather than rote repetition of formulas and proofs. It stimulates thought rather than memory. The techniques can be applied in elementary path problems, equipment replacement, resource allocation, general path problems, traveling salesman problems, problems with linear dynamics and quadratic criteria, discrete-time optimal control, cargo-loading (or knapsack) problems.

9.

Network Reliability (3 credits)

 

This course focuses on system performance evaluation and decision making for both deterministic and stochastic models. The classmates can apply the methodologies and models to the practical systems such as computer networks, telecommunication networks, urban traffic systems, power transmission system, and manufacturing systems. In this course, we will discuss quickest path problem, multicommodity reliability problem, performance evaluation for stochastic project, routing problem in computer networks, and the loading problem in power transmission systems.

10.

Enterprise Modeling and Analysis (3 credits)

 

Currently, there is an increasing need in industries for precise modeling enterprise. Enterprise modeling is perceived as a prerequisite to enterprise integration. People need to better understand their business operations, re-engineer their business processes, and share data and knowledge or develop common applications with partner companies. Enterprise modeling must therefore provide a set of common languages to describe various aspects of the enterprise at different abstraction levels (e.g. business level, engineering level, or operational level) and from different angles (e.g. function view, information view, or organization view).

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