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IE Chapter 1 Unit3

IE Chapter 1 Unit3


Unit3

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Disciplines of Industrial Engineering

Five Big Major Engineering Disciplines and Their Development

In United States, there are five big major of engineering disciplines(civil, chemical, electrical, industrial, and mechanical) that were the branches of engineering that emerged prior to he time of World War I. These developments were part of the industrial revolution that was occurring worldwide, and the beginning of the technological revolution is still occurring. Development following World War II led other engineering disciplines, such as nuclear engineering, electronic engineering, and even computer engineering. The Space Age led to astronautical engineering. Recent concerns with the environment have led to environmental engineering and bioengineering. These newer engineering disciplines of civil, chemical, electrical, industrial, and mechanical engineering It is different with situations of Unit States that industrial engineering belongs to the secondary level of subjects under the first disciplines of management science and engineering in China The Beginning of IE Subjects Topics that later evolved into industrial engineering subjects were initially taught as special courses in mechanical engineering departments. The first separate departments of industrial engineering were established at State and at University in 1908 . (The program at Syracuse was

short-lived, but it was reestablished in 1925.)An IE option in mechanical engineering was established at Pennsylvania University in 1911. A rather complete history of industrial engineering academic programs may be in the reference. The practice of having an IE option within mechanical engineering departments was the predominant pattern until the end of War Ⅱ,and separate IE departments were established in colleges and universities throughout the last century. There was very litter graduate level work in prior to World War Ⅱ.Once separate departments were established ,master`s and doctor`s level program began to appear. Education of Modern IE–Sub-disciplines

Today , more than over, means difference things to different people. In fact, one of the ways to develop an understanding of modern is by gaining an understanding of both its subdisciplines and how it relates to other fields. It would be convenient, for purposes of explanation, if there were clearly defined boundaries between sub-disciplines and related fields to industrial engineering; unfortunately, that is not the case . The fields most commonly referred to today as sub-disciplines of or related to are management science, statistics, operations

research, ergonomics, manufacturing engineering, systems engineering and computer and information science. There are those in each of these disciplines who believe their field is separate and distinct from industrial engineering. The education of the modern engineers involves some combination of content from all the disciplines just mentioned. In any particular instance , the combination depends on the industrial engineering academic department and the company in which individuals gain work experience. What may or may not be apparent at this point is the diversity of course offerings in. Whereas depth in a single discipline is the primary strength of an electrical, mechancial, or civil degree program , breadth of understanding across a broad rang of related topic areas , both within and outside the college of engineering, as well as industrial engineering in subjects, is the primary strength of an industrial engineering degree program. The following introduction to each of these sub-and related disciplines is intended to offer both relevant history and a limited comparative understanding of the present nature of each discipline.

Management Science

Of all the disciplines mentioned above, management science, simply called management , was one of the earliest to human history. If management is the art and science of directing human effect, then it have begun when one person attempted to get another person to work . There is considerably less than unanimity of opinion today as to how best to do that. Recognition of the need for planning, organizing , leading , rendering , and controlling human effort can be traced back at least as far as early Egyptian times, The execution of these function is essential if ,for example, one is to build a pyramid in a reasonable amount time . With the possible exception of an introductory statement or paragraph about pre-twenties-century management thought, most modern texts in management being their development with a discussion of scientific concepts of . Many authors refer to Taylor as the “science management “, whereas others call him the father of”. There is litter question that the subdivision of management commonly referred to as production management has a great deal in common with industrial engineering . In most business colleges , production management is a sequence of one to two course at the undergratduate level that attempt to familiarize

management students with concepts and techniques specific to the analysis and management of production activity ., on the other hand , is an engineering degree curriculum concerned with analysis, design, and control of a service. A productive system is any system that produce either a product with teaching management students how to manage (i.e. ,direct human effects)in a production environment, with less attention paid to analysis and design of productive systems. Industrial engineering students, on the other hand , are taught primarily how to analyze and design productive systems and the control procedures for efficiently operating such systems. Except for a possible course or two concerned with fundamental understanding of management concept for directing the human effort associated with such systems, it is generally assumed that industrial engineers will not operate the systems they design. The training of a race car driver is management education: the design of the car is analogous to engineering education, The race car driver wants to know first and foremost how to drive the car and its less concerned with a detailed understanding of how it works. The industrial engineer designs the car with a driver in mind but with no intention of getting behind the wheel on the day of the race.

The engineer does intend to be there, however, to observe the performance of the car and assist with appropriate adjustments. The engineer`s concern after the initial design is with design improvement or the continued development of procedures that result in optimum performance In industrial engineering program, the course include: ● Management science. ● Production management. ● Logistic management./Supply chain management. ● Management information system. ● Human resource management. ● Project management. ● Quality management.

Operation Research (O.R.)

Operation research has been defined by the Operation Research Society of the United Kingdom as follow: The attack of modern science on complex problem arising in the direction management of large system of man , machines, and money in industrial, business, government, and defense. The distinctive approach is to develop a

scientific model of the system, incorporating measurement of factors such as chance and risk, with which to predict and compare the outcomes of alterative decisions,

strategies, or controls. The purpose is to help management determine its policies and scientifically. The definition says that O.R. is applicable just about anywhere there are systems that need to be managed. A “scientific model” is perhaps the key phrase in the definition. This implies that unless a scientific model (usually mathematical) is developed, it cannot be called operation research. The next phrase says that the objectives are to “predict and compare the outcomes of alterative are decisions, strategies or controls”. This implies that any scientific model that predicts or evaluates the results of decisions or policies is operations research. Finally, the overall objective of operations research is to “help management determine its policies and actions scientifically”. It is significant that we say to help management. No O.R. tool “makes” decisions. It is only an aid to the decision maker. Let us review the definition of IE in the unit. It is obvious that IE and O.R. have commonalities. O.R. and IE

indeed do have many of the same objectives and work on many of the same problems. The primary difference is that O.R. has a higher level of theoretical and mathematical orientation, providing a major portion of the science base of IE. O.R. carries a connotation of mathematical orientation, but IE does not restrict itself to any specific approach. Figure 1.2 illustrates the relationship between the two disciplines in terms of mathematical sophistication. Many industrial engineers work in the area of operations research, as do mathematicians, statisticians, physicist, sociologists, and others. It is significant to observe that many O.R. programs in universities are taught by industrial engineering faculty, or by mathematics and statistics faculty, or by Operations Research faculty. Nature of O.R. is in mathematical involvement. Research into new mathematical techniques could be called O.R. but not IE, although the research is often done by industrial engineers. Let’s explore nature of O.R. in an attempt to categorize the techniques. In every situation that we wish to model using an O.R. approach we encounter the problem

of estimating the values of the parameters ( factors such as the price raw material or time to produce a part). Those parameters may not be constant over time. That is, they may behave as random variables or perhaps change in some predictable fashion. One approach is to forget that they are random variables and use a mathematical model that does not recognize variation. This approach is called the deterministic approach and is often used. Actually, all models we have seen thus far have been deterministic. If the model recognizes this random variation, the approach is called probabilistic approach.

System Concept We repeat a word “system” during our discussion.

What is a system? A system may be defined as a set of components which are related by some form of interaction, and which act together to achieve some objective or purpose. In this definition, components are simply the individual parts, or elements, that collectively make up a system. Relationships are the cause-effect dependencies between components. The objective or purpose of a system is the desired state or outcome which the system is attempting to

achieve. Systems may be classified in a number of different ways. We discuss a few classifications that illustrate the similarities and dissimilarities of systems. Natural vs. Man-made Systems—Natural systems are those that exist as a result of processes occurring in the natural world. A river is an example of a natural system. Man-made systems are those that own their origin to human activity. A bridge built to cross a river is an example of a man-made system. Static vs. Dynamic Systems--A static system is one that has structure but no associated activity. The bridge crossing a river is a static system. A dynamic system is one that involves time varying behavior. The Chinese economy is an example of a dynamic system. Physical vs. Abstract Systems—A physical system is one that involves physically existing components. A factory is an example of a physical system, because it involves machines, buildings, people, and so on. Abstract systems are those in which symbols represent the system components. An architect’s drawing of a factory is an abstract system, consisting of lines, shading, and

dimensioning. Open vs. Closed Systems—An open system is one that interacts with its environment, allowing material (matter), information, and energy to cross its boundaries. A closed system operates with very little interchange with its environment. Industrial engineers design systems at two levels. The first level is called human activity systems and is concerned with management control systems and is concerned with procedures for planning, measuring, and controlling all activities within the organization.

Cybernetics Two highly significant works were publish in 1948; one was Norbert Wiener’s Cybernetics, or Control and Wiener’ Communication in the Animal and the Machine, and the other was Claude Shannon’s The Mathematical Theory of

Communication. Wiener derived the word Cybernetics from a Greek word meaning steersman, and his subject was the generality of negative feedback in systems spanning the biological and physical world. The most commonly used example of negative feedback

is the thermostat. When the temperature drops sufficiently below some desired value, the thermostat initiates the heating portion of the cycle, and the heat is added until a temperature is reached that is greater than the desired temperature. Heating is then stopped to permit cooling to negate the overheating. Negative feedback means that some action is taken to oppose or negate an unacceptable difference. Figure 1.3 is a conceptual model of negative feedback in management systems. An apparent condition is compared with a goal, and if a sufficient difference ( i.e., error)exist, management action is taken to reduce the difference. The action should result in a change in the apparent condition so that later comparison of the apparent condition with the goal will cause the controlling action to cease. Assume that a manufacturer wishes to have 100 units of inventory on hand. After reviewing his inventory status he notes that he has only 80. If 20 is a sufficient difference, he would probably perform the management action of ordering more material in an attempt to raise his inventory level closer to the desired level. The order, after a purchase delay, should bring the apparent condition

closer the goal, removing the need for additional management action. This concept is consistent with the exception principle of managerial control, which says that management attention should be directed to situations in which abnormal values are known to exist. It is

management’s job to cause an undesired value to return to a normal or steady-state level. It is the generality of this concept and other characteristics of systems that make Wiener’s text significant. Homeostasis is a word commonly employed in the biological sciences in connection with the regulatory processes in living organisms. Analogous regulation can be identified in such diverse systems as water flow in irrigation and current flow in electrical networks.

A General Systems Theory Wiener’s work is generally to be the starting point of what is now commonly referred to as general systems theory. Schlager reported in 1956 on the basis of a review of a nationwide survey, that the first known use of the term systems engineering was in the Bell Telephone Laboratories

in the early 1940s. Considering the problems the Bell System faced at that time in expanding its system, it is understandable that the term might well have been received there. The RCA (Radio Corporation of America) Corporation, in the yeas just preceding this, had recognized the need for a systems engineering point of view in the development of a television broadcasting system. In 1946 the newly created RAND Corporation developed a methodology that they labeled systems analysis. Quade and Boucher in Systems Analysis and Policy Planning defined systems analysis as “a systematic approach to helping a decision-maker choose a course of action by investigating his full problem, searching out objectives and

alternatives, and comparing them in the light of their consequences, using an appropriate framework—in so far as possible analytic—to bring expert judgment and intuition to bear on the problem”.

Systems Engineering Some fairly clear differences have emerged over the years between operations research and systems engineering. Although the early philosophers of operations research

believed it to be the beginning of an analytical attack, via mathematics, on large-scale problems, a review of the operations research literature shows that for most problems, the number and complexity of representations must be limited if analytically sound solutions are to be reached. Some operations research problems involve a large number of equations—some linear programming solutions, for example—but the complexities of representation in

any one of the many equations may, and often do, make the entire set of equations unsolvable. For many problems today the techniques of operations research offer solutions that were unavailable in the recent past. Systems engineering seems to have developed with less dependence on “hard” mathematical representation of all aspects of a system. Digital simulation is a much more frequently employed technique in systems engineering, particularly if the system cannot be tightly represented and solved analytically because there is no appropriate analytical technique or the data are not in the form required for a specific operations research technique. Systems demand that a macro perspective be attained in effectively dealing with any significant problem. There is

a considerable danger to attempting to solve a problem without first getting the big picture of the total system in which the problem is embedded. You may mess up the system in the process of fixing the problem—it is commonly called “wining the battle, but losing the war”.

Management statistics Management statistics comes from statistics and it is applications of statistics in industrial engineering. Statistics has been and will continue to be distinct from industrial industrial engineering. engineering However, has the approach of

changed

significantly;

the world around us is viewed as probabilistic in nature rather than deterministic. By deterministic it is meant that all actions under consideration in a particular study situation are assumed to be certain. Probabilistic implies that at least one aspect of the study situation has a probability of occurrence associated with it that must be considered. In a deterministic problem you may assume, for example, that the cost of a used car is $20,000. All calculations concerning buying the car would assume the fixed $20.000

cost. In a similar probabilistic problem, you may assume that there is an 80 precent chance that the car can be purchased for $ 20.000, and a 20 percent chance that it can be bought for $15,000. The probabilistic view of the world has so pervaded industrial engineering practice and education that a beginning course in probability and statistic has now become the most important prerequisite in a typical industrial engineering disciplines in this development, and it seems likely that the improved insight it offers to problems will ultimately result in all disciplines shifting toward a more probabilistic view of the world.

Ergonomics Ergonomics, previously called human factors, is one of the sub-disciplines of industrial engineering, closely associated with both industrial and experiment psychology. The field of psychology has produced a wealth of information and theory about the human body and mind that is readily available to human factors engineers.

Industrial engineering systems by nature are often human-machine systems, in contrast to hardware systems in

determining the best combination of human and machine elements. A typical course summaries the considerable research that has been performed to date in national ergonomics laboratories ( i.e., Wright Patterson Air Force Base) and in universities (e.g., Texas Technological University, Virginia Polytechnic Institute and Tsinghua University of China-mainland). These ergonomics

accomplishments assist in familiarizing the industrial engineering student with human-machine systems design. The text Human Factors Engineering by McCormick has been used extensively for this purpose. A significant amount of ergonomics research is now being performed in industrial engineering departments, complementing the continuing research that has been underway for many years in industrial psychology. Ergonomics studies physiological aspects and

psychological aspects of human beings. Physiological aspects of human beings include anthropometry and impacts of working environment. Psychological aspects of human beings include industrial psychology, mental health, and incentive mechanism.

Manufacturing Engineering Manufacturing engineering may be defined as designing the production process for a product. The Society of Manufacturing Engineers has represented manufacturing engineers in the Unite States since 1932. Manufacturing engineering is a familiar industrial

function name in manufacturing organizations but has never been as well established as an academic degree program in U.S. universities and 10 manufacturing engineering

academic degree programs in the United States. However, it is very popular and almost every engineering university or college has manufacturing engineering academic program in China. Industrial engineering and manufacturing engineering are distinct and typical complementary functions in a manufacturing organization. Most firms need both functions represented in their organizations to be truly effective. If one tries to substitute one function for the other, the function omitted typically represents a weakness in that manufacturing organization that will likely limit the overall capacity of the technical effort in that

organization,

A typical manufacturing engineering department is composed of numerous technical professionals ( mechanical engineers, thermodynamicists, material engineers,

computer scientists, etc). Each professional represents some part of the technical process in use at that manufacturing plant. For example, the thermodynamicists may concern himself with product fin design for dissipating heat, an electrical engineer may worry about test sets and related procedures, and the chemical engineer may concern himself with solution concentrations and related

specifications for plating processes. The processes function, as they were intended to function of technical expertise necessary to keep all the manufacturing

processes under control. If that is what the manufacturing engineering

department does, why do we need an industrial engineering department as well? The core of a typical industrial engineering department is a more homogeneous collection of professionals, typically make up of industrial engineers, with and without degrees, and technicians/technologists. It may well include other specialists, however, with degrees or experience in psychology, management, computer

science, and statistics, as well as other engineering disciplines. The smallest entity that an industrial engineer typically deals with is a machine. The machine to an industrial engineer is a black box that has a production rate, yield rate, required operator skills, process capabilities, and other production system attributes. The industrial engineer is concerned with developing a production system that produces the required quantity of products at an appropriate cost and quality. If a machine does not work properly, he may refer the problem to maintenance cost and quality. If a machine does work properly, he may refer the problem to maintenance, and if they cannot fix it, they should design a machine that will work for the required step in the production system under design.


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