1t數(shù)控座式焊接變位機設計【說明書+CAD】

1t數(shù)控座式焊接變位機設計【說明書+CAD】,說明書+CAD,1t數(shù)控座式焊接變位機設計【說明書+CAD】,數(shù)控,焊接,變位,設計,說明書,仿單,cad THE INDUSTRIAL ENGINEERING REVOLUTION by SAMUEL EILON, Ph.D., M.I.Prod.E. Associate Professor in Industrial Engineering, Israel Institute of Technology. Summary Classical industrial engineering was based on five main foundations: the rule of intuition, the philosophy of the one best way, the deterministic system, the principle of simplification and the classical methods of experimentation. Intuition rarely yields satisfactory results in complicated systems and is giving way to operational research techniques. The philosophy of the one best way has been replaced by the philosophy of the better way, and the deterministic methods by statistical analysis. We are increasingly aware of the inadequacy of the principle of simplification and believe that industrial operations are inherently complex and require a new approach to their study. The Hawthorne experiments demonstrated the effect of observation on the observed system and also emphasized the necessity of devising new methods for industrial engineering research and study of administrative behaviour. INDUSTRIAL engineering is a comparatively young subject, which grew with the rapid industrial development of Western Europe and America, until in recent years it began to occupy an honourable position in institutions of higher learning. The pioneers in this field endeavoured, at the beginning of the century, to establish it on scientific foundations, to formulate " laws" which would describe and explain phenomena and relations between cause and effect, and to outline principles for procedure and organisation in order to achieve a desirable level of performance. But, with all its “scientific" principles, industrial engineering remained more an art than a science. The success of experts in the field can perhaps be attributed more to a sixth sense based on accumulated experience than to the application of set laws and principles, which are supposed to lead the engineer step by step to the desirable solution. Like many other subjects, industrial engineering has experienced in the past two decades a rapid development, which led to a drastic change in views and outlook. The classical industrial engineering can be said to have been established on the following five foundations: the rule of intuition; the philosophy of the one best way; the deterministic system; the principle of simplification; and the classic methods of experimentation in physics. I shall try to review in this Paper the changes in our understanding of these basic concepts and the way they affect our whole approach to and evaluation of industrial engineering problems. We are now experiencing literally a revolution in this field of engineering, a revolution that will transform it into a completely new engineering science. The rule of intuition When an industrial engineer or a manager is supplied with specific data, on the basis of which he has to take a decision or to outline an engineering plan, what is the conventional method that guides him in his quest for a solution? He tries to digest the facts in his mind; he outlines several logical alternatives for a solution and proceeds to compare them in order to select the best. In this process of comparison, he tries to visualise the possible results that can be expected of each alternative and in this he is guided by his past experience, or by the experience of others, and he mainly uses his sense of intuition to assess these results qualitatively or quantitatively and to relate results of one method or system to those of another. What is intuition? Intuition is a process of thinking, which is difficult to dissect into individual factors or sequences. It is quite often based on the principle of identification of given data of a specific problem with previous experience, and is normally associated with rapid transfer from one sequence to another. This process, however, may be too closely attached to identification with past associations, rather than with the problem at hand. Thus, not all the relevant factors may play a relevant role in the procedure of arriving at a solution, and while intuition sometimes leads to the right answer for the wrong reasons, it should be remembered that an intuitive approach quite often results in a wrong solution, or in a solution which is not the best one. Those instances where the intuitive approach yields wrong answers are usually revealed when undesirable results are obtained. But in most cases, when the suggested solution is neither catastrophic nor the best one, we tend to regard the intuitive solution as a successful one, and if somebody suggests a better solution we usually say that "it is very easy to be clever in retrospect" or that " the conditions have changed in the meantime and we now have information which we did not have before ". It is true that sometimes changes in the nature of the problem do occur, but the significance of these changes, both qualitatively and quantitatively, is important in the evaluation of the solution. In many cases we can formulate in advance the nature of the changes that may arise, some of them even quantitatively, but the percentage of the cases in which the intuitive method provides a solution that takes such details into account, is almost negligible. How does intuition work and what is the relation between intuition and previous experience? To what extent are intuitive processes in the mind related to past associations and to what extent are they independent of the external world, forming so to speak an isolated system in which the computation yields absolute values? These are complicated problems which provide rich material for research on the structure and performance of the mind and it is not intended to enlarge on them here. But for the purpose of our discussion it is possible to say that every thinking process consists of several elements or steps, each one leading forward in the quest of a solution. The word " forward " is important here, since if the steps do not take us nearer to the target, it is necessary to have more steps from the starting point to get there, and the number of steps is significant in the actual attainment of the goal. Each element is fed with data from the previous element, then an operation based on the data takes place and the output is fed into the next element. Even if we assume that the computational operation itself at each element is free of errors, it is still doubtful whether the input to each element is always identical with the output of the previous one, because each input is accompanied by a suitable re-arrangement of the material and perhaps formulation of the facts in a form easily digestible by the computational operation. Putting the data in a new light or expressing it in different terms may lead to non-identification of input with preceding output. This is a second source of possible errors in the intuitive process, and the accumulated error increases with the number of elements. This is somewhat similar to several toy bricks put on top of each other. If the bricks are accurately located, the structure will be absolutely vertical. A small displacement of one brick in the structure causes a displacement of the top brick, while several displacements of several bricks may lead to an increased displacement of the top from its desirable location. the short cut Another aspect of the intuitive thought is the short cut, i.e., the elimination or combination of several elementary steps in the thinking process, based on an analogy of these elements with other known elements from past experience. This aspect is one of the amazing phenomena associated with the performance of the mind, but from the point of view of error making it has the same pitfalls of unidentical situations and distorted data. The process of analytical thinking is not always as simple as described above. Usually the process is divided into several sub-processes, which have to be carried out simultaneously, which are interconnected and which influence each other. The input to a certain element may not be unidirectional; that is, it may not be obtained from one previous element but from several elements belonging to different processes, and similarly the output may be multidirectional to several elements. Here we have two important aspects: first, the capacity of the mind to carry out assimilation of several inputs to one element without distorting their accuracy and contents; and, secondly, the amount of complexity of simultaneous processes and multidirectional inputs and outputs that the intuitive mind can carry out, without unwarrantably eliminating complete processes in order to achieve simplicity. Both aspects can become sources of appreciable errors. The intuitive processes have been mentioned at some length in order to point out the reasons for either their missing the target altogether, or for incurring accumulated errors of such a magnitude as to render the proposed solution unsatisfactory. The very fact that different intuitive minds give different solutions to the same problem, and that the solutions are usually not equivalent (i.e., it is possible to say that one solution should be preferred to another) would indicate the necessity of analysing methods that would yield a solution independent of intuitive faculties, and would therefore be free from the mistakes which might be attributed to them. New methods in analysis of situations and systems are provided by operational research techniques, which facilitate the study of intricate and complex systems when any intuitive attempt to a solution is doomed to failure for two reasons: first, many systems of this kind have specific characteristics and it is difficult or impossible to draw conclusions about their nature from previous experience of other systems; secondly, the complexity of the systems and the large number of variables on which they depend, make it impossible for the human mind to achieve an effective absorbtion of all the facts and the intricate relationship between them. The tools of operational research can be used for a systematic analysis and quantitative evaluation of the characteristics of the system, and though intuition can always be of some help, just as it is helpful in the solution of mathematical problems, the autocratic rule of intuition in the solution of classical industrial engineering problems is coming to an end. The first critical steps in the evaluation of industrial operations are the definition of the problem, the definition of the objective and the definition of criteria for measurement. It is often said that the definition of the problem is half-way to its solution ,and this is probably quite true, as the definition of the problem inevitably entails gathering of adequate and relevant information and precise understanding of the characteristics of the factors involved. The definitions of the objective and the criteria for measurement have undoubtedly been one of the major stumbling blocks of critical operational analysis in the past. Not only has there been a lack of agreement as to what objective is desirable; many managements have been trying to achieve several objectives at the same time, and quite often these objectives are not compatible with each other. It has often been asserted that the definition of objective is a matter for higher management and the task of the industrial engineer begins after that. In view of the confusion on this score in the past, and the different and sometimes conflicting criteria which have been applied in the study of operations, it would seem that a meticulous study of industrial objectives and criteria is warranted, if operational research methods are to be fully exploited. The philosophy of the one best way At the beginning of the century the pioneers in industrial engineering had already recognised the fact that there are large variations between different workers, between their methods of work and between their outputs. Frederick Taylor came to the conclusion that it is necessary to outline scientific methods in order to enable objective measurements with the aid of a clearly defined criterion. He asserted that the desirable maximum efficiency would be achieved if tasks in industry were undertaken by people trained for them. He wanted to solve the problem of existing variations by carefully selecting personnel, suitable in skill and aptitude for each particular job, and he called these people " first class men ", a definition that aroused severe criticism at the time. Frank Gilbreth put the emphasis on the work method. He said that for the attainment of maximum efficiency there exists one method for the execution of each job which is " the best way ", the acquisition of which should be the objective of operators' training. Gilbreth was prepared to admit that the existing variations between operators may cause deviations from the best method, even after the operators have been trained to use it, and he was prepared to allow such deviations, provided the output attained by the best method was not affected. This philosophy of Gilbreth was enlarged upon by Alford, who said that this view was identical with the philosophy of the engineering standard. The one best way should be regarded as a relative engineering concept, which describes the best method that can be found under the given circumstances. " It is not an ultimate best way but is in the line of progress, and may be changed or modified as soon as a better way is discovered. The new way then becomes the best way until it is superseded by something better. To the one who accepts and applies this philosophy comes the grace and rhythm and perfection of motion of him who knows, and knows that he knows, and does what he knows, no matter what his work may be." 1 This is quite a liberal interpretation of the philosophy of the one best way, but at the beginning of the century this philosophy was rigid, deterministic and static. Rigid, in that it implied that there exists only one method which is the best. Deterministic, in that it said that the method can be defined after suitable study and research. Static, in that it made the work system dependent on fixed parameters. But we are now beginning to understand that the three assumptions of this philosophy are unfounded. First, we are no longer confident that to every problem there is only one best solution, even when we overcome the obstacle of defining the criterion by means of which the solution should be evaluated. Many problems have several equivalent solutions and in the design of machinery and equipment, for instance, this phenomenon is well known. Secondly, we are now convinced that the deterministic outlook has no foundation either in theory or in practice. Theoretically, as we shall see later, we cannot be sure that the proposed method will really prove to be up to the mark, as hoped in advance, since the feeding of the method into the system may lead to some unexpected results. From the practical point of view, the classical assertion is that it is possible to find the method " after suitable study and research ", i.e., the search is a function of time and money, and these are not always available in abundance. And, lastly, no work system is static. It cannot be defined in static terms but by statistical parameters. It changes with time and with the many variables on which it depends. Its characteristics change fundamentally with changes of methods, with changes of processes or even with changes of views. Perhaps it is permissible to say that for the philosophy of the one best way has now been substituted the philosophy of the better way. The philosophy of the best way recognises one absolute idealistic method, a super target to be aimed at by every worker or engineer seeking perfection. The philosophy of the better way is the philosophy of reality. It asserts that every process of development is unlimited. In this process we are moving along an indefinite spiral which continuously transfers us into a new space and with each step the system is faced with new problems demanding their solution. In the search for a better method with limited facilities, it is of course possible to find several solutions, some of which will be better than others, and this is where the real test of the engineer lies. The average engineer, without imagination and initiative, will be satisfied with any better solution, with the pretext that there is no need to make any special effort because we are not after a final and absolute method. A good engineer will try to achieve the maximum with the facilities at his disposal, will not be deterred by the infinite process of development and will not be drawn into apathy, but will regard it as a constant challenge, a source of interest, vitality and action. And is this phenomenon not typical of what happens in other fields of human endeavour ? determinism and probability The first steps of industrial engineering were naturally based on the deterministic outlook and this view, to a certain extent, formed the background to the philosophy of the one best way. The deterministic approach was coupled with the belief that if a set of defined operations is followed, a certain result is obtained, and this same result can be expected to recur again and again from the same set. This view is reminiscent of a set of experiments in classical physics shown by a teacher to his students. He takes, for instance, a metal sphere, slightly smaller in diameter than the internal diameter of a ring at room temperature. He warms the sphere over a Bunsen burner and tries to push the hot sphere through the ring, exhibiting in this way the phenomenon of metal expansion with temperature. Each time it is sufficiently warmed, the teacher expects the sphere not to pass through the ring and he would be extremely surprised, and perhaps worried, if after proceeding with identical sets of operations the sphere would sometimes pass through the ring and sometimes not, and he would undoubtedly express the view that something had gone wrong in the structure or nature of the experimental apparatus. In fabrication processes it has been well known for some time that the result is not deterministic in this sense, i.e., that after a recurring set of operations, a large variation in results is obtained. This is the basis for specifications of tolerances in the design of machinery parts. But although this phenomenon of variation has been known for some time, the study and method of specifying tolerances has been a subject for intuitive decision for many years, until new methods based on statistical analysis were established. It is surprising that the process of recognising the fact that most industrial engineering operations, and not only manufacturing operations, are not deterministic, took such a long time, since many industrial operations are associated with very wide variations, because of their being dependent on or related to human factors, and in biology and medicine it is well known that many characteristics and phenomena are subject to wide variations. The results of fabrication processes are usually related to comparatively small statistical variations, and perhaps their qualitative and quantitative analysis, before other statistical phenomena in industrial engineering, can be attributed to the fact that they were easier to understand and to attack. The principle of simplification Another phenomenon connected with industrial operations is the large number of factors and variables affecting them. In many fields of physics we can carry out experiments by isolating the system. We disconnect the system from other phenomena and proceed with the experiment in a closed system unaffected by the outside, and usually the factors which we cut off have such a small influence, that we may draw conclusions from the experiment about the behavio