MANAGEMENT FOR ENGINEERS
EMIS 8364
Fall 2004 @ Lockheed Martin
Day # 1, Friday, August 13, 2004; 8:00 am to 5:00 pm
Chapters 1-5:
1.
2.
3.
4.
5.
Engineering and Management Basics
History of Engineering Management
Planning and Forecasting
Decision Making & Statistical Analysis
Organizing
Chapter 1: Engineering and Management Basics
Origin of word Engineer - Latin for a talent, natural capacity, or clever invention.
According to Webster Dictionary – (1) The art of managing engines, (2) The application
of science and mathematics by which the properties of matter and sources of energy in
nature are made useful to man in structures, machines, products, systems, and processes.
Engineering as a Profession:
The profession in which a knowledge of the mathematical and natural sciences gained by
study, experience, and practice is applied with judgement to develop ways to utilize,
economically, the materials and forces of nature for the benefit of mankind.
Engineers:

Individuals with baccalaureate or higher degrees in engineering, science, or
mathematics who have acquired status as engineers.

People whose highest degree is an associate engineering or technologist degree and
who have acquired status through experience as engineers or as engineering
technicians or technologists.

Individuals who over years of experience and/or non-collegiate training have acquired
the skills and knowledge to be bona fide engineering work.

Professional engineers licensed by State regulatory agencies.
Engineering Degrees:
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Science vs. Engineering:
Engineering Disciplines:
Management:
Young engineers or scientists’ narrow viewpoint: Management is something “they” do, a
world full of time-wasting effort spent mainly on useless meetings and covering up one’s
mistakes and stabbing peers in the back in a bid to reach the top of the corporate ladder.
Is this viewpoint correct?
Management is –
1. An organizational or administrative process
2. A science, an art or a discipline
3. The group of people running an organization
4. An occupational career
From academic view point Management is a process:

The work of creating and maintaining environment in which people can accomplish
goals efficiently and effectively.

The process of achieving desired results through efficient utilization of human and
material resources.

The process of reaching organizational goals by working with and through people and
other organizational resources.

A set of activities (including planning and decision making, organizing, leading and
controlling) directed at an organization’s resources (human, financial, physical and
information) with the aim of achieving organizational goals in an efficient and
effective manner.

The process by which managers create, direct, maintain and operate purposive
organizations through coordinated, cooperative human effort.
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
The process of acquiring and combining human, financial, informational and physical
resources to attain the organization’s primary goal of producing a product or service
desired by some segment of society.
Are Managers Bosses?
An engineer who goes into management expecting to be a leader, to issue commands and
have subordinates follow without question, will be disappointed.
From business executives view point Management is:

Being a respected and responsible representative of the company to your subordinate

The ability to achieve willing and effective accomplishments from others toward a
common business objective

Organizing and coordinating a profitable effort through good decision making and
people motivation

Getting things done through people

The means by which an organization grows and dies

The overall planning, evaluating and enforcement that goes into bringing about “the
name of the game” - profit

Keeping your customers happy by delivering a quality product at a reasonable cost

Directing the actions of a group to accomplish a desired goal or objective in the most
efficient manner
Is Management a Science or an Art?
It is not an exact science, like engineering. There are no fixed answers in management.
All that one can hope to do is to learn the basic principles. The aspiring manager must use
common sense in applying these principles to real life situations.
What is Engineering Management?
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Narrow Definition: Direct supervision of engineers or of engineering functions, e.g.,
supervision of engineering research or design activities.
Broader Definition: The engineering manager is distinguished from other managers
because he/she possesses both an ability to apply engineering principles and a skill in
organizing and directing people and projects. He/she is uniquely qualified for two types
of jobs: the management of technical functions, for example, design or production or the
management of broader functions, for example, marketing or top management.
Engineers can be especially effective in the general management of technically oriented
organizations, such as high-technology enterprises due to the following:

Understand both the technology that is driving the business today and the technology
that will change the business in the future.

Treat research and development as an investment to be nurtured, rather than an
expense to be minimized.

Place a premium on innovation

Strategic thinking with future technologies
Management Levels & Skills:
First-line managers are generally responsible for carrying out the plans and objectives of
higher management, using the personnel and other resources assigned to them.
Middle managers carry titles such as plant manager, division head, chief engineer or
operations manager. They make plans of intermediate range to achieve the long-range
goals set by top management, establish departmental policies, and evaluate the
performance of subordinate work units and their managers.
Top managers bear titles such as chairman of the board, president, or executive vice
president; one of these will normally be designated “chief executive office” (CEO). While
they may report to some policy-making group (the board of directors, legislature, our
council, they have no full-time manager above them.
Managerial Skills
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


Technical
Interpersonal
Conceptual
Lowest level of manager has the greatest need for technical skills, such as engineering,
accounting, machining or word processing. Interpersonal skills are important at every
management level. Conceptual skills represent the ability to "see the forest in spite of the
trees”. This ability is essential to the top manager’s responsibility for setting king-term
objectives for the enterprise.
Managerial Roles and Functions:
Roles



Interpersonal – figurehead, leader, liaison
Informational – monitor, disseminator, spokesperson
Decisional – resource allocator, negotiator, disturbance handler,
entrepreneurial
Functions
 Planning
 Organizing
 Staffing
 Leading
 Controlling






Requirements for PE License in Texas
Order of the Engineer – Obligation of the Engineer
Engineering Ethics, NSPE Code of Ethics
Technical vs. Non-Technical Content of Job
Personal/Regulatory/Legal/HR/Personnel Issues “Day Care”
Delegate Authority not Responsibility
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MOTIVATION
Figuring out why people don't do what you want them to do at work*
We've all been there, mystified by the behavior of each other, asking ourselves questions like:
"Why are they doing it that way?" "Why aren't they doing their job?" "Why can't I get him/her to
cooperate?" "I thought I was clear about what I wanted, I guess not!"
Often we make faulty conclusions based upon our own untested assumptions, e.g.:
"They don't have the capability to do the job." "They aren't motivated enough." "They have a bad
attitude about their job."
***********************
Below are some questions to ask to help diagnose such situations. With the proper diagnosis of
root cause, you have a better shot at resolving the situation to everyone's benefit and growth.
For whatever behavior is not being demonstrated by someone:
1. Do they know WHY they should be doing it? [Provide people with an understanding of the big
picture and the importance of their specific contribution]
2. Do they know HOW to do it? [Provide people with proper training to do their jobs and ask if
they feel comfortable with their job. Some people are hesitant to say "I don't know."]
3. Do they know it's a PART OF THEIR JOB? [Ensure that job descriptions and objectives reflect
the full scope of their responsibilities]
4. Do they know how IMPORTANT it is? [Be clear about priorities within a person's job. Don't
assume they will prioritize their activities the way that you would]
5. Is there a POSITIVE CONSEQUENCE for doing it, or a NEGATIVE CONSEQUENCE for NOT
doing it? [Are they acknowledged/rewarded when they do it or coached when they don't do it?]
6. Are they PUNISHED when they do it? [e.g. the productive person who keeps getting new
assignments because the boss knows he/she can rely on him/her, or the employee who gets
labeled a troublemaker when they try to bring management's attention to a problem]
7. Do they think they are ALREADY DOING IT?! [Without frequent communication and feedback
a person may think they're doing just fine -- the old "no news is good news!"]
8. Are there OBSTACLES beyond their control? [Best way to uncover this is to ask the person in
the job]
9. Do they have the CAPABILITY to do it? [Have they had the proper education and/or
experience, and coaching to perform in the job]
10. Are they experiencing PERSONAL PROBLEMS [Perhaps they did it before but stopped doing
it due to special circumstances. Find out by asking.]
11. Can ANYONE do it? [Is the task in question even humanly possible - has anyone ever done it
before?]
Using the above questions to explore performance situations will help focus on the right solution.
Often we immediately prescribe training which really only addresses a couple of the above root
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causes. The rest is about good supervisor/employee communication and "tuning in" to the
individuals with whom your work.
***********************
* Excerpted from Why Employees Don't Do What They're Supposed to Do and What to Do About
It, by Ferdinand F. Fournies
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Chapter 2: History of Engineering Management
Even the earliest civilization required management skills whenever groups of people
shared a common purpose. Today, the word “scientific management” is used for finding
better, more efficient ways to do things, orderly and systematically.
Masons/Military (fortifications/weapons)
The old Cottage Industry and Industrial Revolution of the 18th Century
A series of labor saving inventions in the late 18th century changed the society completely
Cottage industry replaced by factories.
Explosive growth of Mill Towns led to:
 Filthy and overcrowded living
 Child labor
 Crime & Brutality
 Falling wages
 Unemployment
 Rising food prices
Luddite Rebellion (1811-1816)
A “worst case” scenario of public resistance to Modern Manufacturing Methods and
Practices.
Setting:
British Industrial Revolution concluded
Laws regulating the wool industry repealed
British on the verge of war
Depression
Luddites used guerrilla tactics to destroy labor saving textile machinery throughout
England. Like Robin Hood, “General Ludd” or “Ned Ludd” took on mythical proportions
and received general public support.
The 18th Century factory managers faced many of the same problems we face today:
 Recruiting
 Training
 Discipline
 Motivation
 Regular attendance
 Labor unrest
This needed a professional manager
Industrial Engineering:
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Industrial Engineering is concerned with the design, improvement, and installation of
integrated systems of people, material, information, equipment and energy. It draws upon
specialized knowledge and skills in the mathematical, physical and social sciences
together with the principles and methods of engineering analysis and design to specify,
predict and evaluate the results to be obtained from such systems.
Pioneers in the evolution of Industrial Engineering:
Charles Babbage
Frederick Winslow Taylor
Frank and Lilian Gilbreth
Henry Gantt
1908 - First autonomous Industrial Engineering Department established at Pennsylvania
State College.
Scientific Management:
Frederick W. Taylor is considered the father of Scientific Management. Taylor’s goal:
Maximum efficiency in manufacturing organization.
Taylor argued that people understand the need for efficiency because “we can see and feel
the waste of material things, “But” our larger waste of human effort, “ brought on by the
“awkward, inefficient, or ill directed movement of men, “are” less visible, less tangible,
and ...but vaguely appreciated.” The fundamental cause of this waste of human effort was
unscientific management: mangers focused too much on the output of work and not
enough on the processes by which the work was done.
Taylor’s approach: The substitution of a science for the individual judgment of the
workman. (In most early nineteenth century workplaces, managers left it to work crews to
determine the actual methods of work.)
Principles of Scientific Management:
First: Develop a science for each element of a man’s work, which replaces the old ruleof-thumb method.
Second: Scientifically select, then train, teach, and develop the workmen, whereas in the
past he chose his own work and trained himself as best as he could.
Third: Heartily cooperate with the men so as to ensure all of the work being done in
accordance with the principles of the science which has been developed.
Fourth: There is an almost equal division of work and the responsibility between the
management and the workmen. the management take over all work for which they are
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better fitted than the workman (defining how work is to be done), while in the past almost
all of the work and the greater part of the responsibility were thrown upon the men.”
Hawthorne Studies
W. Edwards Deming – The Quality Guru & TQM
Deming Cycle P-D-C-A
1. Plan
2. Do
3. Check
4. Act
Deming’s Philosophy - The most important changes that an organization must make in
order to produce successfully are (from book - Out of the Crises):
1. Create consistency of purpose toward improvement of product and service
2. Adopt the new philosophy: we are in a new economic age
3. Cease dependence on mass inspection as a way to achieve quality
4. End the practice of awarding business on the basis of price tag
5. Constantly and forever improve the system of production and service; the
system includes people
6. Institute training on the job
7. Institute leadership to help people and machines to do a better job
8. Drive out fear
9. Break down barriers between departments
10. Eliminate slogans and targets for zero defects and new levels of productivity
11. Eliminate work standards and management by objectives
12. Remove barriers that rob people of their rights to pride of workmanship
13. Institute a vigorous program of education and self-improvement
14. Put everybody in the company to work to accomplish the transformation
How would you go about instilling commitment to Deming’s philosophy in your
company?
Chapter 3: Planning and Forecasting
Five Fundamental Functions of Management:
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
Planning

Organizing

Staffing - Service Relationships – Supportive of main mission

Leading (or directing or motivating)

Controlling
Planning and forecasting are the key results areas on which the survival of the
organization depends.
Planning provides a method of identifying objectives and designing a sequence of
programs and activities to achieve these objectives.
The basic, logical method for solving problems is called:

Planning process, or

Decision making process, or

Scientific Method
A clear vision of the basic purpose or mission for which it exists is essential to the long
term success of any enterprise. Where there is no vision, the people parish.
Three components of a good “vision framework”:



Core Values and Beliefs: A system of guiding principles
Purpose: The fundamental reason for existence
Mission: A goal with a clear finish line and a specific time frame
Planning Involves:

Goals and Objectives

Strategies

Planning Horizon

Policies and Procedures
Establishment of Objectives (Peter Drucker):
 Market Share

Innovation
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
Productivity

Physical and Financial Resources

Manager Performance and Development

Worker Performance and Attitude

Profitability

Social Responsibility
Management by Objective (MBO):
Have an understanding of the goals and objectives of the overall organization and those
of the superior’s group

Goals must be quantifiable and verifiable

Individual goals must be consistent with the organization goals

At the end of the period, evaluate the success in meeting assigned goals
Strategic planning:
Identify the businesses a company is in and the ones it wants to be in the future, and to
define a strategy for getting from the first to the second. Business Portfolio Matrix.
Strategic Management of Technology:
The management of technology encompasses the management of research, product and
process development and manufacturing engineering.
Three Broad Classes of technologies:

Basic technologies – Firm must master to exist

Key technologies – For competitive advantage

Pacing Technologies - Tomorrow’s key technologies
Forecasting
An essential requirement to effective planning is forecasting what the future will be like.
Future markets and future technology forecasting:
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Market and Sales Forecasting:
Common Forecasting Methods:

Jury of executives

Sales force composite

User’s expectation
Quantitative forecasting methods:

Simple moving average

Weighted moving average

Exponential smoothing

Simple Regression model

Multiple regression model
Choice of method: Combination of many of the above
Technological Forecasting:
Based on three premises:
1. Technological events and capabilities grow in a very organized manner
2. Technology responds to needs, opportunities and provision of resources
3. New technology can be anticipated by understanding the process of innovation
Types of technological forecasting:

Normative – starts with desired future goals and develop it

Exploratory - extrapolates in to future from present
Delphi Method:
This technique is based on using the judgement of a panel of experts to arrive at a
convergence regard the forecast of a new technology.
Chapter 4: Decision Making & Statistical Analysis
Decision Making: Managerial decision making is the process of making a conscious
choice between two or more rational alternatives in order to select the one that will
produce the most desirable consequences (benefits) relative to unwanted consequences
(costs). Decision making is an essential part of planning.
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Occasions for Decision Making



Authoritative communication
Referred by subordinates
Own initiative
Types of Decisions:


Routine
Non-routine
Rational decision making process consists of optimizing, or maximizing, the
outcome by choosing the single best alternative from among all possible ones.
Objective Rational decisions are made by:
(a) Viewing the behavior alternatives prior to decision in panoramic fashion
(b) Considering the whole complex of consequences that would follow on each
choice
(c) With the system values as criterion singling out one from the whole set of
alternatives.
Actual decisions (Bounded Rational Decisions) are made by:



Fragmentary knowledge of consequences
Imperfectly anticipated values
Few of the possible alternatives ever come to mind
Management Science/ Operations research
Five step Process:
1. Formulate the problem (Real world)
2. Construct a mathematical model
3. Test the model
4. Derive a solution
5. Apply the model solution to the real problem
Decision Making Under certainty:
Linear Programming
Characteristics of LP Problems:

A well defined single objective must be stated
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


There must be alternative courses of action
The total achievement of the objective must be constrained by scarce
resources or other restraints
The objective and each of the constraints must be expressed as linear
mathematical functions
Example #1 Linear Programming Problem:
Consider a factory producing two products, product X and product Y. If you can
realize $10 profit per unit of product X and $14 per unit of product Y, what is the
production level x of product X and y units of product Y that maximizes the profit
P?
Your factory is subject to following resource limitations or constraints: it can
employ only five workers, three machinists and two assemblers, that each works
only 40 hours a week and products X and/or Y can be produced by these workers
subject to following constraints: Product X requires three hours of machining and
one hour of assembly per unit and Product Y requires two hours of machining and
two hours of assembly per unit.
Profit Function:
P = 10 X + 14 Y
Constraints:
3 Machinists = 120 hrs. Machine time
2 Assemblers = 80 hrs Assembly time
1. 3X + 2Y <= 120
2. X + 2Y <= 80
Solution: Graphical
Solution: Analytical
3X + 2Y = 120
X + 2Y = 80
2X = 40, X = 20
20 + 2Y = 80,
2Y = 60, Y = 30
P = 10 X + 14 Y
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P = 10 x 20 + 14 x 30
P = 620
Example #2 The Secret formula
The two main items which go into the manufacturing of Zing ( a component of a floroll)
are known simply as Formula X and Formula Y. The composition of these two
ingredients is a closely guarded secret, but both are produced by two processes, Upper
and Lower. To produce one gallon of Formula X requires 4 hours in the Upper process
and 2 hours in the Lower process. To produce one gallon of Formula Y requires 1 hour in
the Upper process and 3 hours in the Lower process. The total amount of time available,
in a day, in the Upper process is 80 hours, and in the Lower process it is 120 hours. The
manufacturing makes a profit of $10.00 by selling one gallon of Formula X and $15.00 by
selling Formula Y. The objective is to maximize profits, while working within the
constraints of the processes.
P = 10 X + 15 Y
1. 4X + Y <= 80
2. 2X + 3Y <= 120
3. X >= 0
4. Y >= 0
Solution: Graphical
Solution: Analytical
4X + Y = 80
2X + 3Y = 120
12X + 3Y = 240
10X = 120, X = 12
4 x 12 + Y = 80
Y = 80 – 48 = 32
P = 10 x 12 + 15 x 32
P = 120 + 480 = 600
If suppose Process Y had 180 hours
i.e., 2X + 3Y <=180
12X + 3Y = 240
2X + 3Y = 180
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10X = 60, X = 6
2 x 6 + 3Y = 180
3Y = 168,
10X = 60, X = 6
2 x 6 + 3Y = 180
3Y = 168, Y = 56
P = 10 x 6 + 15 x 56
P = 60 + 840 = 900
Steps in Formulating LP Problems:
1. Define the objective
2. Define the decision variables
3. Write the mathematical function for the objective (objective function)
4. Write a one or two word description of each constraint
5. Write the right-hand side (RHS) for each constraint, including the units of
measure
6. Write<, =, or >, = for each constraint
7. Write all the decision variables on the left-hand side of each constraint
8. Write the coefficient for each decision variable in each constraint
Steps in the Graphical LP Solution method:
1. Formulate the objective and constraint functions
2. Draw a graph with one variable on the horizontal axis and one on the vertical
axis
3. Plot each of the constraints as if they were lines or equalities
4. Outline the feasible solution space
5. Circle the potential solution points. These are the intersections of the
constraints or axes on the inner (minimization) or outer (maximization)
perimeter of the feasible solution space
6. substitute each of the potential solution point values of the two decision
variables into the objective function and solve for Z
7. Select the solution point that optimizes Z
Computer solutions:


Simplex Method - George Danzig of Stanford University
Projective Geometry - N. Karmakar of Bell Laboratories
Inventory Control:
How large should the inventory be and how often should it be replaced to minimize the
cost and meet the demand?
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Economic Order Quantity (EOQ)
Assume:
R = Total requirement for the period
Q = No. of units per batch
S = Order or set-up cost per batch
I = Investment of storing cost per Unit
Investment cost = ( I x Q ) /2
Set-up or ordering cost = S (R /Q)
Total cost = Inv. Cost + Order cost
Objective: Minimize Total cost
EOQ = Sqrt ( 2 R S / I )
Example:
I = $ 2 / Unit
S = $40 per order
R = 1000 Units / Yr
EOQ = Sqrt ( 2 . 1000. 40 / 2)
= Sqrt ( 40,000)
= 200 Units
If set-up or ordering cost is reduced to $10 ( one fourth)
EOQ = Sqrt ( 2. 1000 . 10 / 2)
= Sqrt (10,000)
= 100 Units / Yr
Queuing Theory Models:
Arrival rate = a
Serving rate = s
Traffic intensity = p
p=a/s
Traffic intensity is the probability that an arrival will have to queue.
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Many assumptions are involved in an analytical solution
For a single service channel:
Average number in queue = p2 / ( 1 – p)
Average waiting time in queue = p / ( s – a )
Simulation Techniques
Decision Making Under Risk:




Nature of Risk
Expected Value
Decision Trees
Risk as Variance
Decision Making under Uncertainty:
Competitive Strategy
Theory of Games
Zero- sum games
Computer Based Information Systems:




Integrated Data Bases
Management Information Systems (MIS)
Decision Support Systems (DSS)
Expert Systems
Artificial Intelligence:
A form of computer reasoning designed to mimic that of the human reasoning
process. Artificial intelligence may be thought of as the umbrella term for many
forms of evolving technology (expert system, fuzzy logic, neural network) that in
some manner attempts to embody the computer with human-like capabilities be
they thinking, seeing, hearing etc.
Soft computing consciously exploits the tolerance for imprecision to solve
problems that could not otherwise be solved. Soft computing incorporates three
main constituents: fuzzy logic, neural networks, and probabilistic reasoning.
Expert Systems:
An expert system is an information system which provides the user with a facility
for posing and obtaining answers to questions relating to the information stored in
its knowledge base. The knowledge base of an expert systems is a repository of
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human knowledge. Typically, such systems possess a user-invisible, nontrivial
inferential capability and have the capability to infer from premises which are
imprecise, incomplete or not totally reliable.
The idea behind the use of an expert system is to capture in a computer program
the knowledge and skills of a person who is an expert in a given field.
Fuzzy Logic:
Fuzzy logic is an attempt at formalization of approximate reasoning, which is
characteristic of the way in which humans reason in an environment of uncertainty
and approximation. Fuzzy logic holds that all things are a matter of degree.
Fuzzy logic has been used in applications areas such as project management,
product pricing models, sales forecasting, criminal identification, process control
and signal processing.
It is important to realize that fuzzy logic is a logic of fuzziness, not a logic which
is itself fuzzy; analogous to probability - laws of probability are not random, just
as laws of fuzziness are not vague.
Implementation:
Decisions, no matter how well conceived, are of little value until they are put to
use.
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