Contents
Business
Logistics Management
Rationale
Logistics is the art and science of managing and controlling the flow of goods,
energy, information and other resources like products, services,
and people, from the source of production to the marketplace. It
is difficult to accomplish any marketing or manufacturing without logistical support. It involves the integration of information, transportation, inventory, warehousing,
material handling, and packaging.
The operating responsibility of logistics is the geographical repositioning
of raw
materials, work in process, and finished inventories where required
at the lowest cost possible.
This
course provides an introduction to Logistics Management. Logistics
management is the planning, implementation and control of the processes
involved in the flow and storage of materials from the point of
origin (as raw materials) through the various value-added stages
to the point of consumption (as finished goods). It has been estimated
that logistics costs account for 30% of the cost of doing business.
Effective logistics management can lower costs, provide better customer
service and quality, which translate into strategic competitive
advantage and profitability for the company.
Topics
covered include the strategic importance of logistics management,
international logistics issues, logistics network design,
location and layout planning, demand forecasting, the management
of materials and inventories, production planning and control,
and transportation/distribution issues. The is a course
designed to give students the knowledge and experience of
logistics problem solving. Attention is given to such
problems as transportation and network planning, inventory
decision making, facility location planning, vehicle routing,
and logistics forecasting. Students will use several
quantitative tools commonly seen in the filed of logistics,
which include algebra, geometry, differential calculus, and
mathematical programming. The course emphasises the
use of PC-based spreadsheet programs. However, no prior
experience in spreadsheet or advanced mathematics/statistics
is required.
Through
this course, we hope that the student will develop an appreciation
of the practical significance and complexities of logistics
management, gain an understanding of the key processes involved,
and master some analytical tools useful in the designing,
operating and improving of a logistics system.
The
course has been scheduled for a 10-week period. |
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Learning
Outcomes
Upon
successful completion of this course, the student will be able to
understand
- the
role of the logistics process in national and multi-national businesses
and government activity;
- understand
the characteristics of logistics elements and their interrelationships
within the supply chain;
- develop
analytical and problem solving skills necessary to develop and
analyze solutions for a variety of logistical problems;
- learn
to recognize areas in which logistics process can be improved
to gain competitive advantage in the marketplace.
Teaching
and Learning Resources
Click
on titles
Introduction
to Logistics Management
Tutorials
Readings
 |
Machine
Learning, Tom
Mitchell, McGraw Hill, 1997.
Machine
Learning is the study of computer algorithms that improve
automatically through experience. Applications range from
datamining programs that discover general rules in large data
sets, to information filtering systems that automatically
learn users' interests.
This book provides a single source introduction to the field.
It is written for advanced undergraduate and graduate students,
and for developers and researchers in the field. No prior
background in artificial intelligence or statistics is assumed.
Lecture
slides
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Brief
Review of Logistics Concept. The
Logistics Planning Process & Tools
Tutorials
Readings
Channels
Management/Logistics and Supply Channel Management. Logistics Network Design
Tutorials
Readings
International
Journal of Logistics Management
Award
Winning Papers
Benchmarking
Costing Issues
Customer Service
E-Business
Exporting/Importing
Globalization/Global Logistics
Information Systems
Inventory Management
Logistics in the Automotive Industry
Logistics in Europe
Logistics in Latin America
Logistics in North America |
Logistics
Management
Logistics Organization
Manufacturing Related Issues
Outsourcing/Third-Party Logistics
Partnerships
Performance Measurement
Purchasing/Materials Supply
Re-engineering/Network Design
Retail Logistics
Strategic Planning
Supply Chain Management
Transportation
Warehousing |
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Inventory
in Logistics System. Warehouse Layout and Material Handling
1. Overview of Inventory Management
2. MRP
3. DRP - Multi-echlon System
4. DRP - Cost Trade-off Analysis
Tutorials
Readings
Inventory
Management
- Deterministic
demand models
- Newsvendor
model
- Probabilistic
demand models
One
of the mechanisms that almost all operations use to mitigate the detrimental
impact of variability is inventory. The Just In Time (JIT) philosophy
calls for the elimination of all waste (called muda in Japanese),
and the elimination of inventory is enemy number 1 in the JIT philosophy.
A lean plant is a good thing, but anyone in retail understands that
inventory is a necessary evil. We provide three fundamental
models of inventory:
(1)
Given the reality of a fixed order cost (a set-up cost, deliver
fee, transaction cost, purchasing overhead, etc.) as well
as the reality that it costs me to hold inventory, how large should
my orders be to minimize the sum of ordering costs and holding costs?
The is the Economic Order Quantity.
(2)
Given that my demand is uncertain and the lead time from my supplier
is uncertain, how do I determine when to place an order (the Reorder
Point, ROP)? How much Safety Stock (SS) should I carry to
avoid stockouts?
(3)
The above models assume inventory can be handled indefinitely.
What if I sell produce, newspapers, magazines, current information,
blood products, or some other perishable item? The newsvendor
helps us set the tradeoff between ordering too much (the case of
excess stock, where we can at best salvage the leftovers) and ordering
too little (the case of shortages/stockouts), both of which erode
our profits. The newsvendor model quantifies the Service Level
(SL) that maximizes profit.
Tutorials
Readings
Transportation
Planning. Vehicle Routing & Scheduling
Tutorials
Readings
Facility
Layout and Location
1. Overview of Location Analysis and Evaluation
2. Heuristic Model - Grid Technique
3. Optimization Model
4. Least Number of Branches Problem
Tutorials
Challenges
in Supply Chain Management
Most
of the preceding material did not specifically focus on what happens
between firms that are part of the same supply chain. That is a
huge area of effort now as firms are recognizing large gains to
be made from reengineering of their supply chains. Details about
inventory management and reordering policies at each echelon or
level of the supply chain are important issues. The larger
issue, however, is the way in which the different firms and levels
of the supply chain interact. When information is not shared,
inherent demand uncertainty at the lowest levels of the chain propagates
up the chain, and is amplified at each level. The result is greatly
degraded efficiency that hurts every member of the chain, but especially
the suppliers. Even when a firm is integrated, this is a problem
when there is no one responsible for end-to-end system performance.
Today's environment is increasingly characterized by vertical dis-integration.
The result is that no single firm does or can take responsibility
for the total supply chain system performance. Poor
forecasting, lack of information (secrecy), ill-conceived marketing
efforts, and simplistic inventory management approaches all compound
the problem. We present actions that counteract these debilitating
factors. The most fundamental of them all is the need for
all members of the supply chain to work together toward the common
causes of end-to-end supply chain performance. This often
involves strategic alliances across the firms of the supply chain,
information sharing, and common forecasts.
Tutorials
Readings
Information
Technology
Tutorials
Readings
Product
Packages
Process
Management Transformation and Improvement. ERP, MRP, BPR, JIT
This
topic builds upon our understanding of fundamental operational models
and issues together with the concepts of transformation. Here
we take a look at where the rubber meets the road. ERP systems
go hand-in-hand with transformation and they support (or limit!)
the operational mechanisms and practices.
The
Transformation module above alerts us to the sad fact that ERP systems
and application software are not actually soft. They should
be called "concreteware" because of their rigidity within an organization.
The book "Why ERP?" tells us to ask the very question in the title
before rushing to buy and install one. These notes critically
examine the strengths and weaknesses of ERP systems with emphasis
on their effectiveness in production planning. The huge attraction
of ERP systems is their ability to automate business process across
business functions, facilities, and countries. The greatest
problem with ERP systems is that they require the firm to completely
reengineer its business processes from top to bottom so that they
conform to the software. This transformation is utterly gut-wrenching
for most organizations. Unfortunately, the ERP software once
installed keeps the organization locked into specific business processes
that work against flexibility over time.
Tutorials
Readings
Recommended
Text
 |
Fundamentals
of Logistics Management: European Edition
David
B Grant, Heriot-Watt University, UK
Douglas M Lambert, Ohio State University, USA
James R Stock, University of Southern Florida, USA
Lisa M Ellram, Arizona State University, USA
ISBN: 0077108949
Copyright year: 2006
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Resources
Logistics
Systems Analysis
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