HCM TOTAL QUALITY MANAGEMENT AND SIX SIGMA

Artificial Intelligence Tools and Case Base Reasoning Approach for Improvement Business Process Performance Aleksandar Vujovic, Zdravko Krivokapic and Jelena Jovanovic Additional information is available at the end of the chapter 1. Introduction Contemporary and every day more perfect information achievement, becomes available for everybody, and simply, very quickly become a necessity. It is necessary that organizations use information technology as a tool for developing a sense of learning, acquire and use knowledge. Information tools should not be use like tools for automation of existing processes. There should be another aspect or already obsolete category. With this aspects, thinking and attitudes, it can be said that we living in the century of knowledge and that we have already overcome period of information technology which should be, simply, implemented like support in the way for achieving knowledge. This informational environment has been recognized in the world and because of there are significant rising in the use of artificial intelligence tools. There is evidence that is a great number of eligible to use and easily available software for needs of the development of such as systems in the field of artificial intelligence. Also, in [1] states that investment and implementation of artificial intelligence show significant results, particularly in attempt of to get higher profit. The artificial intelligence, like the word itself says is the area that deals with the development of systems that mimic human intelligence and a man with tend to replace him in some activities based on knowledge. That is way for over viewing problem of human absence, cost of services, disinclination of people to provide knowledge and similar. Specified conditions, particularly from the standpoint of the necessities of knowledge, and also the fact that in area of research topic for the purposes of quality management systems, there are evident gap [2, 3-10, 11]. That facts justifying the author's striving to be in this research and accept to use artificial intelligence tools for developing systems oriented to knowledge. These views and attitudes were in agreement: that there is no correct programming software that has a strong base of knowledge that could assist in © 2012 Vujovic et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License ( identification of a problem, that has not developed a single expert system that deals with the measurement, evaluation, corrective and preventive action to improve organizational performance and the like [12, 13-16, 10]. It is also an incentive to be based on such analogies create a foundation set up and entered the field of artificial intelligence in order to obtain knowledge as one of the most important factors for creating competitiveness in the market [17-19, 20]. Everything above can be understand like introduction for developing an research whit main aim for developing a system in the field of artificial intelligence that would be based on the analysis in the quality management system and that has given recommendations for achieving business excellence and improve the financial performance of the organization. The main parts and activities of that research stay in the basis of this chapter. 2. The main targets, methods and contribution Based on the introduction and results of researching literature source and practice, in the scope of this research, it can be set up main targets, and that are: • to find (regardless of size or type of organization) area in organization which have priority from the standpoint of improvement, • to establish new concept of Degree of Readiness and Coefficient of Significance which can show intensity and type of action which should be provide in direction of achieving business excellence and • to develop and testing in real condition an expert system for improvement business process performances even those of financial character base on analogy with human body function. In this sense, it can be use science method for inductive and deductive way of deciding and concluding. First one was used for collecting, estimating and analyzing of experimental data, or to making general knowledge by using specific knowledge and particular facts. The second one was used for applying and checking specific conclusion in real condition. Also, like science approaches it was used: analogy method, expert decision and “ex post facto” or previous case and facts. Beside that, many other methods and tools were conducted like: knowledge discovery in data base, data mining, case base reasoning-CBR, object oriented programming, artificial intelligence tools, Analytic Hierarchy Process-AHP, expert choice, testing in real condition, Visual Basic and Select Query Language. Through a detailed analysis of literature sources and software, it was found evident gap in applying artificial intelligence tools for improvement business process performances based on Quality Management System-QMS and especially in experience of other and case reasoning. In this research, analogy between human body function and process oriented organization were established, and areas in organization which is prior from the standpoint of improvement were identified. Two unique data bases and significant number of company and data, make original experimental value and bases for research. Also, new concept of Degree of Readiness and Coefficient of Significance for achieving business excellence stay in the basis of new expert system for achieving business excellence. By applying this expert system, especially on prior area, employees should drive they process performances to excellent condition, even those of financial character. Also, many actions for improvement with appropriate coefficients which show theirs intensity where found. This action should be understood also like preventive action for strengthening organizational condition to avoid some failure in the system. This expert system was tested in real conditions in one very successful organization which will be participant in competition for European Award for business excellence. This test and verification showed that the system could be useful and also the efficient and effective 3. Experimental research, areas for research and reasons for developing expert systems The basic facts of this research are attempted to define two levels of experimental data. The first level of the data is related to quality management systems and nonconformities that have emerged. This is a basic level of data which reflects the situation in the quality management systems and identify critical places that are subject to improvement. The base of these data is unique and consists of the 1009 nonconformities (cases), identified in over than 350 organizations. If we know that in our area in the field of competent certification body has, approximately 500 certificates, then the number of 350 is about 70% of the total number. That fact points out to the significance of sample for analysis. The term nonconformities refer to any non-conformance of requirements of ISO 9001, nonconformity non-fulfilment of a requirement [21]. During the external audits of quality management system, competent and trained auditors can identify several types of nonconformities (Figure 1). We are using most significant data from highest level of pyramid at which were collected at the level of many country like external estimation and evaluation of they performance and condition. Distribution of nonconformities depends on the rules that define the certification body itself. However, for the purposes of this research is used classification which is the most common in the literature, which is favour by the authoritative schools in the world in the field of management system and that is clearly recommended by European guidelines in the subject area, which is split into three levels. The first level is the disagreements that are evaluated as insignificant deviations from the standards and requirements which are interpreted as an oversight or random error. The other two categories are interpreted as nonconformities that represent a great deviation from the essential requirements, which are reflected in the frequent discrepancies in individual requirements, representing a deviation that brings into doubt the stability of the management system and threatening the operations of the organization. Data base of nonconformities which is under consideration in this research contains only nonconformities in the domain of the other two categories, and that giving greater importance to this research and gives greater significance results. Figure 1. Data source (highest level of data significance) Non-conformances are identified in accordance with the structure requirements defined in the ISO 9001 standard as follows: - Quality management systems: 4.1 general requirements, 4.2 documentation requirements, - Management responsibility (module 5): 5.1 management commitment, 5.2 customer focus, 5.3 quality policy, 5.4 planning, 5.5 responsibility, authority and communication, 5.6 management review, - Resource management (module 6): 6.1 provision of resource, 6.2 human resources, 6.3 infrastructure, 6.4 work environment, - Product realization (module 7): 7.1 Planning of product realization, 7.2 customer related processes, 7.3 design and development, 7.4 purchasing, 7.5 production and service provision, 7.6 control of monitoring and measuring devices, - Measurement, analysis and improvement (module 8): 8.1 general, 8.2.1 customer satisfaction, 8.2.2 internal audit, 8.2.3 monitoring and measurement of processes, 8.2.4 monitoring and measurements of product, 8.3 control of nonconforming product, 8.4 analysis of data, 8.5 improvement. Accordingly, for example in the field of 8.2.1 from the standpoint of the appearance of non- conformances organizations have a significant and frequent or large deviations in the sense that it does not follow the information about the observations of users, it did not define the methods for obtaining this information, they do not have strong communication with customers and similar. Or for example in the field of 8.2.3 with the observed aspect, organizations do not apply appropriate methods for monitoring and performance measurement processes, have not mechanisms for implementation of corrective measures in cases that have not achieved the planned performance of processes and the like. This data will be used like the basis of CBR approach or approach where it is possible to make significant conclusion in the sense of main target of this research. This approach is shown in figure 2. Figure 2. Case based approach The second level of data consist data from evaluation organizations that participated in the competition for the quality award based on European Quality Award criteria. This database is unique, as well as in the previous case. Data were transferred in encoded form in order to secure the identity of the organization. Data were collected in 100% extent (34 organizations) and thus are significant and give a real picture of the situation in our organizations. These data are used for comparison with previous, basic level data. That is way for making improvement or exalt from basic level on the level of business excellence and way for making knowledge which reproduce expert system on his output. That is also comply with literature more existent attitude, and natural way that organization should first implement Quality Management System and after that system which is based on Total Quality Management concept [22, 23-26, 27]. In order to show the current directions and trends in the field of development of software for quality, and to select under researched areas in the field of software quality, it was conducted a detailed review and analysis of a total of 143 software. All necessities information for that analysis are available in site () where are publish updated software items which are related to quality. The results of the analysis are shown in the figure 3. Figure 3. Results of analysis of existent software for quality On the x axis diagrams are shown the software ability and orientation. Obviously is that the software in the field of quality is usually oriented to the control of documentation, statistical control and analysis, six sigma model, concept of total quality management, FMEA and QFD methodology, corrective action, flowchart and process mapping. However, there are specific tools for automation: the implementation of the quality management system documentation, description of information flow, implementation methods and techniques of quality, and more. Therefore, it can be concluded that there is no software that is based on the application of artificial intelligence tools in the sense of the definition of preventive actions for the purpose of improving the process. The greatest number of software is related to the application of statistical methods in the process of monitoring and improving quality. It is obviously that a large number of software is based on total quality management systems concept. The facts point out present approach which we develop in this research and also justify further research in this area. It is interesting that a large number of software are base on the corrective actions and on the other hand there is not any registered software that has application for output preventive action what is, of course, main recommendation of ISO 9000 series. This fact also gives stimulus in terms of development of software that emphasis to the prevention. That approach is unique in the field of software for quality and makes this research more significant. Beside this analysis, in this research were analyzed huge amounts of available books in order to point out the justification of applying expert system. Expert systems are different from other artificial intelligence systems in that, they attempt to explicitly and unequivocally embody expertise and knowledge with the software [28]. Expert systems are also identified as one of the most commercial branches and in most number of projects used artificial intelligence tools [29, 30]. For example, it is estimated that in the first half of 21st century, even 75% of all legal documents be written with the assistance of expert systems [31]. Also expert systems will be of vital importance for measuring the quality of products and services [32-34]. Expert systems are an area of special importance with rise trends in modern business conditions [35, 36-38]. They have special significance in a highly developed countries where is actual knowledge based economy. This research highlight trends, significance and justification of developing and implementing expert systems. Main idea and approach for developing expert system come from analogy between human body functions and process in some organization which was organized based on process modelling from ISO 9000 respect. This approach is present on figure 4. This research tries to deal with perfection of functioning of the human body compare with a process modelling structures of the implemented quality management system. The challenge made in this way, tried to create a system that is universal for all sizes of organization, which incorporates a large number of gathered data, in fact a large number of experiences, in order to get a better image of the system status. This should be added to the primary goal which is to develop a model for improvement of management system, oriented to achieve BE according to show off how to maintain and improve the performance of the human body. However, the goal is also, to develop a system for measuring performance and capacity of each activity in the QMS, in order to obtain a true picture of the systems and capabilities in order to define the areas where improvements should be made, with clearly defined intensity of improvement. On the basis, thus established the analogy is made to compare elements of implemented QMS to the systems that have applied for Quality award for BE as a system with high performance.