Introduction to Manufacturing Systems / Operations Research

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Introduction to Manufacturing Systems /
Operations Research
What is Operations Research? Management
Science? Operations research is concerned with
scientifically deciding how to best design and
operate man-machine systems, usually under
conditions requiring the allocation of scarce
resources. (Operations Research Society of
America, 1976).  
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What is Operations Research? Management
Science?Management Science is the application
of a scientific approach to solving management
problems in order to help managers make better
decisions. (Intorduction to Management Science,
B.W.Taylor III, 1999). OR is the abstraction of
real world problems into mathematical models, and
the development of techniques to optimally (or
attempt to optimally) solve these problems. The
application of OR is using the models and methods
to aid decision makers (Schultz, 2002). Key
Phrase Management Science / Operations Research
aides decision makers.
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History of MS/OR Origins in World War II-
radar deployment policies- anti-aircraft fire
control- fleet convoy sizing - detection of
enemy submarine Early MS/OR Efforts - Large
Industries- automotive- oilgas-
airlines Additional MS/OR sectors-
telecommunications- financial planning- health
care- public service
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Nature of OR / Approach to Problem Solving  -
observe situation - define / formulate the
problem - construct a model that attempts to
sufficiently represent the situation - solve
/ validate the model - apply the model (aid
decision maker)
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Why is OR Important?  - Company
profitability - Overseas competition (trade
deficit article) - Erosion of US manufacturing
. Can't compete on labor cost  MS/OR
Today Continental Airlines articles 
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Definition - "simplified representation of
something real" www.dictionary.com -
Modeling

1. A small object, usually built to scale, that
   represents in detail another, often larger
   object.
2. a. A preliminary work or construction that
   serves as a plan from which a final product is to
   be made a clay model ready for casting.
   b. Such a work or construction used in testing or
   perfecting a final product a test model of a
   solar-powered vehicle.
3. A schematic description of a system, theory, or
   phenomenon that accounts for its known or
   inferred properties and may be used for further
   study of its characteristics

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Why Model?  - reduce cost - save time - too
much complexity - avoid disrupting production
system
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Types of models  - Math programming (Linear,
Integer, non-Linear) - Network - Queueing -
MDP (Markov Decision Processes) - Regression -
Forecasting - Inventory - Dynamic
programming - Simulation 
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Principles of Modeling (Ravindran, Phillips,
Solberg)

1. Do not build a complicated model when a simple
   one will suffice.
2. Beware of modeling the problem to fit the
   technique.
3. The deduction phase of modeling must be conducted
   rigorously (conclusions one draws from results).
4. Models should be validated prior to
   implementation.
5. A model should never be taken too literally.

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Principles of Modeling (Ravindran, Phillips,
Solberg) cont.

• A model should never be pressed to do, nor
  criticized for failing to do, that for which it
  was never intended.
• Beware of overselling a model.
• Some of the primary benefits of modeling are
  associated with the process of developing the
  model.
• A model cannot be any better than the information
  going into it.
• Models cannot replace decision makers.
•