1. Industrial Engineering
4th Edition
Chapter 11
Industrial Engineering

2. What is Industrial Engineering?
Industrial Engineering involves the production of any economic goods within an economy.  Because there are so many different kinds of “industries” they are divided into the following categories. 
Primary industries: These industries deal with the extraction of resources directly from the Earth such as farming, mining, petroleum, and logging.
Secondary industries: These industries are involved in manufacturing products from the resources provided by the primary industries. They include the manufacture of automobiles, furniture, electronics, and so forth.
Tertiary industries: These industries compose the service industry. They include education, health care, package delivery, software development, financial institutions, government organizations, and so forth.
Originally the name “industrial engineering” applied only to manufacturing. Today it has grown to encompass any procedure that includes how any process, system, or organization operates. Some universities have changed the name “industrial engineering” to a broader term such as "production engineering" or "systems engineering".
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3. What is Industrial Engineering?
In general, Industrial Engineers develop integrated systems consisting of people, knowledge, equipment, energy, and materials. Examples of activities where industrial engineering is used include
designing assembly lines and workstations
process efficiency analysis
streamlining emergency room use in a hospital
planning distribution schemes for materials or products, and
shortening lines at a bank, hospital, or a theme park.
When Industrial Engineers work in one of the Secondary industries, they are often called Manufacturing Engineers. When they work in one of the Primary or Tertiary industries they are called Industrial Engineers.
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4. What is Industrial Engineering?
Today Industrial Engineering can be broken down into the following categories:
Manufacturing and Quality Control
Methods Engineering
Simulation Analysis and Operations Research
Ergonomics
Material Handling
When Industrial Engineers work in one of the Secondary industries, they are often called Manufacturing Engineers. When they work in one of the Primary or Tertiary industries they are called Industrial Engineers.
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5. Manufacturing & Quality Control
Quality control in manufacturing processes can be broken down into the areas of
Statistical Analysis
Probability Theory
Reliability Analysis and
Design of Experiments.
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6. Statistical Analysis
Statistics is a branch of mathematics in which groups of measurements or observations are studied. Some of the more common descriptive terms used in statistics are defined below:
Population - a group of items that is being studied.
Sample - a small group of items selected from a population.
Random samples - occur when members have an equal chance of being selected.
Data - numbers or measurements that are collected in a population.
Variables - characteristics that allow us to distinguish one individual from another.
Constants - items whose value never changes
The word “data” is plural (therefore we should say “data are” “not data is”). Data represents a set of measurements. A single element of that set is called a “datum” as in “there is only one datum point”.
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7. Statistical Analysis Some common statistical terms
The mean or average is 1 divided by the number of samples N multiplied by the sum of all the data points.
The median M is the middle value of a set of data containing an odd number of values, or the average of the two middle values of a set of data with an even number of values.
The standard deviation σ is the square root of 1 divided by the number of samples (data) minus 1, multiplied by the sum of the data points subtracted from the mean and then squared.
The word “data” is plural (therefore we should say “data are” “not data is”). Data represents a set of measurements. A single element of that set is called a “datum” as in “there is only one datum point”.
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8. Statistical Analysis Example
Five employees of a department store earn the following weekly wages: $400, $650, $660, $625, and $660.
a.) Find the median weekly wage.
b.) What is the mean weekly wage?
c.) Find the standard deviation of the set of wages.
Solution:
Need: The employee wage median, mean, and standard deviation.
Know: The set of wages in question.
How: Use the equations for median, mean and standard deviation,
The word “data” is plural (therefore we should say “data are” “not data is”). Data represents a set of measurements. A single element of that set is called a “datum” as in “there is only one datum point”.
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9. Statistical Analysis Example cont.
The wages can be listed in order as: $400, $625, $650, $660, and $660. Since this set has an odd number of items, the median as the middle values, or $650.
The mean (or average) weekly wage is computed as
The standard deviation of the set of wages is computed as
The word “data” is plural (therefore we should say “data are” “not data is”). Data represents a set of measurements. A single element of that set is called a “datum” as in “there is only one datum point”.
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10. Probability Theory
Probability is a number that represents the likelihood that a specific event will occur. It is the ratio of the number of actual occurrences to the number of possible occurrences.
When P(A) = 0 event A cannot occur (e.g., the probability that you will grow younger rather than older is zero), and when P(A) = 1 event A is certain to occur (e.g., the probability that you will grow older and not younger).
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11. Probability Theory Probability Addition
When we have independent ‘or’ events A or B or C or …, then the probability of any one of them occurring is
P(A or B or C or …) = P(A) + P(B) + P(C) + …
Probability Multiplication
When we have independent ‘and’ events A and B and C and … then the probability of all of them occurring is
P(A and B and C and …) = P(A) × P(B) × P(C) × ….
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12. Probability Theory Example
If you draw just two cards from a complete deck of 52 cards, what is the probability you will get either an ace or a queen?
Solution:
Need: The probability of drawing an ace or a queen.
Know: There are four aces and four queens in a 52 card deck.
How: Use the equation for probability addition.
Solve: P(ace or queen) = (4 aces)/52 + (4 queens)/ = 8/52 = = 15.4%
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13. Probability Theory Example
Now suppose you draw just two cards from a complete deck of 52 cards, what is the probability you will get both an ace and a queen?
Solution:
Need: The probability of drawing an ace and a queen.
Know: There are four aces and four queens in a 52 card deck.
How: Use the equation for probability multiplication.
Solve: P(ace or queen) = [(4 aces)/52] × [(4 queens)/52] = (4/52)2 = 5.92×10-3 = 0.592%
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14. Reliability Analysis
The reliability of a product (or a system) is defined as the probability that a product will perform its required function under specified conditions for a certain period of time. If we have a large number of a certain product that we can test over time, then the reliability of that product at time t is given by
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15. Reliability Analysis
The failure rate F(t) of a product at time t is defined as the probability of a product failing at time t. Let NF = number of products that failed during the time interval t + Δt and NS = number of products that have NOT failed by time t. If Δt is small and the failure rate does not change during this time interval, then the failure rate at time t, can be calculated as:
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16. Reliability Analysis Failure rate bath tub curve
Early Failure: This is the early failure (or break-in) stage. During this period failures typically occur because products were not designed properly or manufacturing flaws occurred.
Useful life: This is the center stage of the bath-tub curve and is characterized by a constant failure rate. This stage is the most significant stage for reliability prediction and evaluation activities.
Wear out stage: This is the final stage where the failure rate increases as the products begin to wear out and break down.
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17. Reliability Analysis
When the failure rate is constant it represents the middle phase of a bath tub curve. When there is very little break-in failure (early failure), a constant failure rate can be effectively used to predict the reliability of a product to a particular time. If the failure rate F is a constant (i.e., independent of t), then the reliability R(t) at time t is given by
R(t) = e -F t
where F = constant failure rate
For example, if there are initially 1000 components and their failure rate is constant at F = 10% per hour, then the reliability after 3 hours, with F = 0.1 failures/hour, is R(t) = e-3F = e-0.3 = = 74.1%
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18. Reliability Analysis
The Mean Time to Failure (MTTF) is the average time an item may be expected to function before failure, and applies to non-repairable items. The MTTF is simply the average of all the times to failure.
The Mean Time Between Failures (MTBF) applies to repairable items. Since this refers to the mean time “between” failures it is defined as
For example, if there are initially 1000 components and their failure rate is constant at F = 10% per hour, then the reliability after 3 hours, with F = 0.1 failures/hour, is R(t) = e-3F = e-0.3 = = 74.1% Note that the MTTF and MTBF are actually the same. Which term is used depends on the circumstances - is the item repairable (a car) or not (a light bulb).
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19. Design of Experiments (DOE)
Design of Experiments (DOE) deals with designing, conducting, and statistically analyzing data to determine how the input variables influence the desired outcome. It allows changing more than one input variable at a time to speed up the experimentation, and it will indicate when variables interact with each other.
The four steps of a DOE are:
1) Design the experiment
2) Collection of data
3) Statistical analysis of the data, and
4) Conclusions and recommendations made as a result of the experiment
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20. Design of Experiments (DOE)
In general, the number of experiments (tests) required for a DOE with N variables tested at M levels of each variable is:
Number of DOE Experiments = NM
So if you have 2 variables and want to test them over 2 levels of each variable you will need 22 = 4 experiments.
Similarly, if you have 3 variables to be tested over 2 levels you need 32 = 9 experiments.
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21. Methods Engineering
Methods engineering is concerned with the selection, development, and documentation of the methods by which work is to be done. It includes workplace design, tool and equipment selection, human motion analysis and standardization, and the establishment of work time standards.
A methods engineering procedure utilizes five separate stages to ensure that an existing process is fully analyzed before a new process is introduced. The five stages are: 1) project selection; 2) data acquisition; 3) analysis; 4) development; 5) implementation.
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22. Methods Engineering
Stage one (project selection) a project is identified that either requires an efficiency enhancement or is a new production process where reliability, accuracy, and efficiency are of particular importance.
Stages two and three (data acquisition and analysis) are concerned with collecting and analyzing data from an existing activity or a production line. Data that are collected during the second stage is analyzed in stage three to establish the optimum man-to-machine ratio and production line outputs.
Stage four (development) man-to-machine ratios and the number of operators allocated to a machine or the number of machines to a single operator are established and developed into a workable process.
Stage five (implementation) results are presented to management for implementation of the resulting method of operation.
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23. Simulation Analysis
Simulation analysis is an analytical tool used to evaluate the performance of an existing or proposed system under different operating conditions. It can be used to answer questions like:
What is the best design for a new communications network?
What are the material resource requirements?
How will a highway perform when the traffic increases by 50%?
What will be the impact of a failure?
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24. Operations Research
Operations Research (OR) is the application of scientific principles to business management, providing a quantitative basis for complex decisions.
Industrial engineers today use OR methods to produce optimal solutions to complex human-technology interaction problems. These problems often require dealing with a large number of variables and constraints.
Rather than using trial and error methods on the system itself, a mathematical model of the system is developed and then manipulated to find optimum operating conditions.
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25. Ergonomics
Industrial engineers also design the work area in which humans interact with machines. This is known as ergonomic engineering. There are two general divisions of ergonomics:
Occupational ergonomics (human factors) is concerned with the strength capabilities of the human body in performing manual work (such as lifting, turning, and stretching), and with the environmental effects of temperature, humidity, vibration, and so forth on the human worker.
Cognitive ergonomics (task analysis) is concerned with understanding the behavior of humans as they interact with machines. This information is used to design machine display interfaces and controls to support operator needs, to limit their workload, and to promote awareness of the operation.
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26. Occupational Ergonomics
Occupational ergonomics provides methods for optimizing tasks in the workplace.
Worker posture and movement is dictated by the task and the body’s muscles, ligaments and joints needed in carrying out the task.
Poor posture and movement can produce stress that results in damage to the neck, back, shoulder, wrist and other work related injuries.
For example, a poorly-designed tool can adversely impact overall worker performance, create injuries, and produce human task error. Industrial engineers evaluate these tools to determine potential sources of injury and attempt to improve them to fit the needs and workflow of workers.
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27. Cognitive Ergonomics
Cognitive ergonomics often involves a time and motion study for repetitive tasks. This study results in a method for establishing worker productivity standards in which a complex task is broken into small, simple steps, that will keep the worker safe from injury and increase their productivity. This can be done as follows:
List the steps needed to perform the task
Discuss them with the worker
Measure each step with a stopwatch as the worker performs the task
Repeat the complete process at least 10 times
Compute the mean and standard deviation of each step and of the complete task
Be aware of worker disruptions and learning curves
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28. Materials Handling
Material Handling is the field concerned with solving the problems of movement, storage, control, and protection of materials throughout the processes of cleaning, preparation, manufacturing, distribution, consumption and disposal of all related goods and their packaging.
The focus of material handling is on the methods, mechanical equipment, systems and controls used to achieve these functions.
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29. Materials Handling
The primary objective of a material handling system is to reduce the unit cost of production. Other objectives are:
Reduce manufacturing cycle time
Reduce delays and damage
Promote safety and improve working conditions
Maintain or improve product quality
Promote productivity by having material move short distances, in a straight line, and use the force of gravity whenever possible
Encourage increased use of facilities by purchasing adaptable equipment and developing a preventive maintenance program
Control inventory
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30. Summary
Industrial Engineering is the field of engineering concerned with the design, analysis, and operation of systems that range from a single piece of equipment to large businesses. 
Industrial engineers serve in areas that range from the production of raw materials to manufacturing to the service industry.
Industrial engineers determine the most effective way to utilize people, machines, materials, information, and energy to make a product or provide a service. 
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