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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|4495||2000||19 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 18, Issue 2, February 2000, Pages 133–151
This paper describes the basic actions proposed for quality inspection. These actions involve structuring a Decision Supporting Expert System (DSES) to help with those decisions related to the preliminary activities for inspection development—most of them relating to determining of the need or convenience of carrying out the inspection itself. Once the opportunity to carry it out is defined, the expert system helps the user to select the type of inspection to adopt from amongst: (1) automatic or sensorial inspection; (2) inspection by samples or complete; (3) acceptance or rectifying and, in the most relevant module, (4) inspection by attributes or by variables. The complementary documentation of the DSES contains the directions to operate it, the rules and qualifiers that make up the system, as well as the results achieved through its experimental implementation.
Having the current concept of quality in mind (and the context of Total Quality Management itself), the feasibility process of basic quality control actions is nowadays considered to take place within a well-defined structure, known as quality evaluation system. Inspection, in turn, is the most important activity in the quality evaluation system of an industrial process. When correctly developed, the inspection makes possible to carry out a precise analysis of how the process operates and serves as a basis for a set of decisions that directly affect it, such as corrective and preventive actions which must be complied with in order to guarantee acceptable quality levels. Quality inspection has got a number of effective techniques with a wide range of applicability. Since there are several techniques available, there are many options for those who intend to devise an inspection process. Nevertheless, this situation poses difficulties as to the correct use of the different techniques, since most of such techniques have their own utilization particularities and yield results valid only within certain contexts. The need of choosing the most adequate technique for each situation shows that it is necessary to organize the information related to quality inspection, or else the whole quality evaluation process could be seriously compromised. The present paper highlights this question, which is considered to be a relevant restriction to the perfect use of quality evaluation. A more efficient way of optimizing quality evaluation development is proposed. We dedicate special attention to quality inspection by attributes, a much more difficult area when it comes to making the correct decision about quality evaluation of services, products and processes.
نتیجه گیری انگلیسی
In addition to attaining to the practical results expected, this paper makes possible to draw conclusions regarding the adequacy of the techniques used to solve the problem in question. Indeed, the characteristics of the tools related to the artificial intelligence (AI) field determined its full applicability to the situation under investigation and were fundamental to the achievement of those results. Besides the adequacy observed and the contribution toward the achievement of the expected results, it is equally important to stress the effectiveness of AI techniques for the treatment of the problem. In fact, the use of AI made possible to structure a reliable, fast and practical procedure for executing quality evaluation. This can be seen through its programming easiness, possibility of a critical analysis of the results and reliability of the information obtained. In a cost–benefit analysis, this aspect may pay off the system implementation costs. Thus, considering the adequacy and effectiveness aspects, we conclude that the application of the selected tools to the problem was correct, allowing the expected results to be attained. Some other considerations are also noteworthy at this point. When studying the concepts of AI and its more usual tools, some authors (like Fu, 1999, Nebendahal, 1987 and Waterman, 1995) have established basic criteria, upon whose effective compliance depends the adequacy of the problem under investigation to the techniques and methodologies in question. Firstly, let us draw attention to the fact that this study involved computer techniques whose characteristics are not found in usual programs. Further new knowledge was brought into the problem and there was a high degree of flexibility in the programs developed as a result thereof. In addition there is no way of predicting the results of the evaluation for many of the cases which were studied.