Approach to developing expert system

Approach to developing expert system

At the market today, we can find many tools for creating expert systems. These systems can be developed in a programmable environment through tools of type C + +, Visual Basic or some other programs which are related to development of expert systems. However, today are developed specialized tools for creating expert systems which allow a high degree of automation in process of developing expert systems. There are called expert system shells. From the standpoint of this research it was carried out choice of expert system shell from the aspect of next four criteria [43-45, Personal communication with group for consulting from London South Bank University, Business, Computing & Information Management, 2011):

- programmability,

- comprehensiveness,

- universality,

- price.

During the election, it was analyzed 58 shells. All information about shells are available on the Internet [2], and classified in a group of commercial shell. Detailed analyses were conducted separately for each tool through analyzing belonging site. For evaluation on the basis of the criteria it was adopted the scale of 1 to 5 where 1 is unsatisfactory grade. According to defined criteria as a most distinguished tool for the needs of the research was adopted ACQUIRE shell. That tool is non programming oriented and it has affordable price. This is a tool that supports the work of the Windows operational environment. It has possibility to develop all elements of expert system and supports forward, backward and combined chaining. For the presentation of knowledge it can be used production rules, the action table, or combined techniques. During a process of developing expert system, the role of engineer for knowledge took up first author, and the role of one expert took up second author. Also, as sources of knowledge were used following:

- experience from eleven prestigious organizations in the world of field of quality management systems, business excellence and organizational performance [46],

- guidelines from standards for improving organizational performance [47 ],

- best practices from auditing of ISO 9001 oriented system [48],

- experience and practice of organizations that participated in the competition for the Oscar of quality award [49],

- theory and principles of TQM [50],

- experiences that are listed in [51] and indicate the path to business excellence.

The expert systems are included and knowledge gained through many concrete practical projects of quality management systems implementation, and many training on that topic. That knowledge is next:

- knowledge that are specific to certain companies,

- knowledge derived from specific experiences and on specific way of solving problem,

- knowledge of those that are best for certain jobs and are passed special training,

- knowledge of those that is proven in practice for the specific job and similar.

For the purposes of this research, expert system was develop for modules 5 (management responsibility) and module 8 (measurement, analyses and improvement) of ISO 9001 standard. The reason for that is that these areas have the greatest importance in achieving business excellence [1] and therefore they should be considerate from the standpoint of improvement. Also, another reason is that module 8 has requirements that are oriented to the improvement and that is essence and priority.

The idea of this research is to make the integration of decision support systems (DSS) which is operate on first level of experimental data, and expert system. That is modern approach of integration a number of tools with the aim of acquiring a larger volume of better knowledge [52] and make system with higher level of intelligence. Today trends are integration expert systems and traditional decision support systems which as output give data and information [53].

Integration of expert systems and decision support system can be achieved in two ways [54]. The purpose of this research is to use model which is present on figure 5. based on the collection and analysis of data obtained at the output of the decision support system and it provide important information like one of inputs for expert system and its knowledge base. This is the model which is completely compatible with previous remarked analogy with human body. This two approach stay in base of this analogy integrative model for improvement business process performance.

For the purposes of this research, we developed a decision support system in the MS Access, Select Query Language and Visual Basic environment.

Applying Pareto method and rules of 70/30 it can be identified area which is crucial from the standpoint of improvement. Also, this system like support for making decision provides written presentation of nonconformities which can be shown as experience of other companies. That could be use like important data for the definition of knowledge in expert system. In addition, this system provides, and comparative analysis with the period of the four years before, which also has significance for the definition of knowledge in the expert system.

Connection between data from the first and data from the second level was achieved through the introduction of the concept of "Degree of readiness (Si)" in achieving business excellence, in accordance with the following expression:

Si = Nz [%] * Kz , i=1,2,...,26

where:

Si        Degree of readiness for all type of organizations for all requests of ISO 9001

Nz      Power of a standard clause in terms of percentage. Nz = ƒ (number of nonconformities from experimental database)

Kz      Coefficient of significance for achieving business excellence

That degree is applies to every single request of ISO 9001 and showing the willingness or the ability of organizations (both manufacturing and service sector) to attain business excellence in some areas. To find this degree, we are using method Analytic Hierarchy Process (AHP) and corresponding software Expert Choice. 

It is important to emphasize this because it was used and it is very important during definition of preventive measures in terms of defining their priorities and "power". Also, “power” of prevention was related with number of nonconformities in particular area. That means, larger number of nonconformities, or larger number of experience, make possibilities for defining more effective and efficient preventive action like output of expert system.

Through application of Pareto method, based on coefficient of significance following requests were identified as the most significant for achieving business excellence:

requests - 821, 823, 85, 84, 54, 824, 56, 53, 71, 41, 51, 72, 55

At the same time, this is important areas, and have high level of priority for improvement from the standpoint of achieving business excellence and it is very important for defining preventive action of expert system and intensity of that action. If we take a look at the list of "Coefficients of significance" for business excellence achieving, especially the most important ones and perform comparison with the list of variables and their significance in terms of: Business Process Reengineering (BPR), manufacturing strategy, benchmarking and performance measurement, being the result of the appreciated research [55] and [56] it may be found significant intercompatibility.

The concerned compatibility is especially reflected in the following variables, evaluated in the relative research as highly significant for the following four projects, i.e.: customer satisfaction, quality, employee satisfaction and personal growth, customer adaptability, identification of top managers with BPR goals, strong process orientation, results orientation, direct customer cooperation. On the other hand, the above mentioned four areas are considered as highly important for any market-oriented organization, thence it can be concluded that organizations by strengthening their capacities in areas of presented "Coefficients of significance" (especially the most important ones), are not only strengthened in terms of the business excellence achieving as per European Award model, but also in the stated four areas.

But some of these areas are much more important then other. Because that, the research was further elaborated in order to indicate most important area for improvement and area where should be focus attention and where should be provide very intensive action in order to achieve best organizational condition and results. This research was conduct from the standpoint of occurrence of nonconformities in all type of organisation regardless of they size or type (both for manufacturing and service organisation). Parallel the Pareto method (70/30) was carried out in that direction and based on that, it was identified next areas:

requests - 56, 75, 62, 822, 74, 76, 54, 72, 85, 821, 55, 63

Now we are search for common requests (area) that are most important and where should be oriented focus and where should be provide extensively action in terms of achieving business excellence regardless of type or size of organization. And they are:

1. 821 – customer satisfaction,

2. 72 - customer related processes,

3. 54 – planning,

4. 85 – continual improvement,

5. 56 – management review and

6. 55 – responsibility, authority and communication.

This area is most important for defining output of expert system and for defining intensity of action for improvement.

Objects were defined during the process of expert system developing. That were depend of problem which should be solved, base on ISO 9001 oriented check list an based on experience which can be find on DSS output. Base on results of DSS system, it is defined value of the object and relation between them.

At the end, after starting the program, in a short time, system introduce user in a set of dialog boxes.

Data obtained from this report, user can use and implement knowledge that an expert system produces. However, users can improve performance of an organization in the field where such as performance are on lower level. Also, it can be improvement performances of other, non critical, area and can be reach level of business excellence.

This expert system was developed in three iterative steps. Each of them resulted of the improvement, for example improvement of the definition of objects, set the input data, the relation between objects depending on the priorities of execution and more.

The expert system was implemented and tested in practical, real conditions in the organization that has a clear commitment to participate in the competition for the European Award for Business Excellence, also providing important measures in that direction. Evaluation was done on the basis of technical and ergonomic characteristics based on guidelines in standards ISO/IEC 9126/1:2001 for evaluation quality of software.

Software was evaluated positive in terms of technical characteristics and in terms of ergonomic. In

this sense, product has small time of response, it is compatible with most used operating system, it has an excellent user’s oriented interface, and it has easy data entry and a good view of the output, installation is simple and the software is very competitive. Also, in this sense, within the organization, it was carried out the reorganization of the priority areas from the viewpoint of improvement, implemented preventive measures for the potentially unstable areas and also applied the measures for the improvement (offered by this system) leading to business excellence achieving.

10 Common Questions about Six Sigma

10 Common Questions about Six Sigma

Our consulting organization has been associated with Six Sigma since its inception in the 1980s. During the last 20 years, we have heard virtually every question asked about both the concept and application of this cutting edge management philosophy.

In our final chapter, we address 10 common questions asked about Six Sigma and provide our insight into their answers. It should be noted that in some cases, these questions are honest forms of curiosity about the topic. In other cases, these questions are forms of resistance on the part of the questioner. For purposes of this chapter, we assume the best-case scenario about the intentions behind each question.

Question #1 Isn’t Six Sigma just like other quality initiatives in the past, almost all of which were failures?

By far, this is the most common question we hear. As we have already alluded, Six Sigma uses many of the same tools and techniques as other quality initiatives, but there are huge differences between Six Sigma and previous efforts.

First, other quality initiatives never gained the attention of top management. Whether the quality initiative was Statistical Process Control, Total Quality Management, Hoisin Planning, or other quality initiatives, it was a rarity for management to actually be involved. What typically happened was project teams were immediately formed among those that had an interest in improvement. These teams attempted to utilize quality tools and techniques, but without the support of management. Thus, the effort was halfhearted as were the results.

Six Sigma is different because of management’s active involvement. Jack Welch at General Electric said that Six Sigma was the most important initiative he brought to General Electric in the 20 years he was at the helm. His successor, Jeffery Immelt, mentioned expanding Six Sigma four times in his first interview with the Wall Street Journal. The other two finalists for Jack Welch’s succession, James McNerney and Robert Nardelli brought Six Sigma to their new organizations (3M and Home Depot, respectively) in the first month after leaving General Electric.

Why has Six Sigma garnered such support from such highlevel executives? Because the executives use Six Sigma strategically, as an enabler to achieving the business objectives of the organization (see Chapter 2). With the support, encouragement, and resource allocation of management, Six Sigma has become a way of doing business in the organizations that embrace it, something that never happened with other quality initiatives. How many other quality initiatives have had the support of management like Six Sigma?

With that management support, results follow. In recent months, our consulting firm has assisted our clients generate multimillion dollar cost savings while improving customer satisfaction and improving the bottom line. One financial services client reduced dispute resolution time for a credit card process from over 38 days to less than 3. Another client, a health care provider, reduced unexpected complications and improved patient registration. If something is successful, it is used. These kinds of results attract the active involvement of management. When management supports something, it will work. Therein lies the difference between Six Sigma and other quality initiatives.

Question #2 How will I know if my organization is successfully implementing Six Sigma?

There are several signs you should be looking for if your organization

is becoming successful in its efforts to implement Six Sigma.

First, management in your organization will begin to become more fact-based. Attending a meeting will result in decisions made by data rather than the person with the loudest voice. Someone in those meetings will ask to see the data, whether that data is a Pareto chart, a histogram, or a survey from a customer.

Second, you will start to become more familiar with the concept of process. As we described earlier in this book, a process is a series of steps or activities that takes inputs, adds value, and produces outputs for a customer. While everyone talks about being customer focused, only those that begin to measure, manage, and improve the processes of their organization will truly be customer focused. Thus, if your organization is successfully implementing Six Sigma, you and others in your organization will become more familiar with the processes you either work in or are affected by. In addition, you will become aware of the key measures of effectiveness and efficiency for those processes.

Third, you could expect to see and participate in more improvement teams. When an organization starts a Six Sigma initiative, the first teams will appear to be a novelty. After some period of time, improvement will become an expectation of every employee in the organization. Thus, the concept of improvement teams and your periodic participation on them will become standard fare rather than a novelty.

Fourth, the focus of energy of a Six Sigma organization changes. Reward and recognition migrates from the fire fighter to the arsonist catcher. What this means is that the organization you work in will become proactive rather than reactive.

Question #3 Isn’t Six Sigma going to rob me of my creativity?

This question has become more prevalent since National Public Radio (NPR) ran a segment on this very topic. NPR indicated that many employees are concerned that their creativity will be limited by having to be in an organization that manages with facts and data.

Just the opposite will happen. Employees will have far greater opportunity to exhibit their creativity in a Six Sigma organization. There are two major ways that a Six Sigma culture encourages creativity rather than hampers it.

First, while on a DMAIC project team, the success or failure of the team is directly related to how well project team members tap into their creativity. Recognize that while decisions are made based on data, the team enters the root causation phase of Analysis with the responsibility to generate root causes through brainstorming. This, by definition, will cause project team members to use both their experience and creativity relative to the project. Again, in Improve, project team members must brainstorm ideas that will generate improvement in sigma performance. Time and again, I have seen that teams with great ideas (that are tested and verified) dramatically improve sigma performance.

Second, there is another tactical methodology that helps to create new processes or products. This design for Six Sigma methodology is known by its initials DMADV, which stands for Define, Measure, Analyze, Design, and Verify. DMADV is used when a process or product does not currently exist that is needed to positively impact a strategic business objective of the organization. The creativity of DMADV project team members is pivotal toward the success of its goals.

Therefore, whether the team is using DMAIC or DMADV, creativity is a must if the team is going to be successful.

Question #4 Will I lose my job if Six Sigma is successful?

One of the problems with a quality improvement approach years ago called Process Re-engineering was that virtually all of the benefits touted to management were workforce reductions.

The goal of Six Sigma is to improve both effectiveness and efficiency. Efforts that focus exclusively on efficiency (like process reengineering) often can appear like a workforce reduction effort. When efforts like Six Sigma work on effectiveness (which you will remember is improving how well you meet your customer’s needs and requirements) properly, it is typical for the business to grow and expand, not contract.

You should also remember our discussion of business process management in Chapter 2. Six Sigma should always be structured in a way to achieve the business objectives of the company. I haven’t yet seen Six Sigma be exclusively devoted to just the reduction of employees engaged in inefficiency.

Having said that Six Sigma is not an employee reduction program, the following also has to be said: If your job is exclusively devoted to work around inefficiency, ultimately your job is a target for possible change or elimination. To not acknowledge this fact would be deceptive. If this is the case, you want to expand your work knowledge into other areas of the business. In the best case, as your organization improves both effectiveness and efficiency, your skills could be used elsewhere in the organization. Additionally, if your current work is focused on inefficiency, it is even more important to work on a Six Sigma team. The skills you master as part of a Six Sigma team will dramatically assist your career development, whether those skills will be used in your current position, a new position in your current organization, or some other company.

Question #5 We have tried improvement before, why should Six Sigma be any different?

Since the 1980s, many organizations have made half-hearted attempts at improving their organization through quality. I would be the first to say that whether the effort was Statistical Process Control, Total Quality Management, a Just-In-Time effort, or some other well-intentioned program, it probably failed.

Have you ever considered why it failed? I have spent considerable time and money studying why quality efforts have failed. What I and others in my organization have found is that previous efforts failed for the following reasons:

• Little or no management support and involvement.

• There was not a strategic element associated with previous efforts.

• Management of the acceptance of other initiatives never occurred.

Let’s briefly discuss how Six Sigma properly addresses each of these failures. First, management historically has not been involved in quality efforts because they didn’t see the connection between those quality activities and how their business was conducted. To them, quality was the domain of engineering or technical types, similar to the reputation of Information Technology. Fortunately, Six Sigma clearly defines how management becomes involved using Six Sigma as a philosophy and strategy of helping them achieve business objectives.

Second, this strategy, called Business Process Management, dictates how management will be involved with Six Sigma quality activities both during the initiation and the maintenance of the strategy of Six Sigma.

Third, if you have been a part of a quality initiative that failed, think of how well (or more likely, poorly) the acceptance of the quality effort was managed. In all likelihood, there was little or no management of the acceptance of the quality effort.

Once again, Six Sigma is different in this regard. As we discussed in the previous chapter, a series of “soft” tools are used in a Six Sigma initiative that are totally directed toward gaining acceptance to Six Sigma whether it be directed at management or an individual contributor.

Question #6 I’m not good at math. Isn’t this going to be difficult for me?

I often say that if I can make my living teaching Six Sigma, anyone can learn it. I even have grade transcripts from school that prove I am not the smartest mathematician. However, the good news is that much of the math associated with Six Sigma is simple, direct, and useful.

In school, I always felt that the math was about theory. Or to put it another way, in school I felt I was learning the intricacies of how a carburetor worked but never how to drive a car. To me, the math associated with Six Sigma that you have to learn is more along the path of how to drive a car. Most of the math in Six Sigma is adding, subtracting, simple multiplication, and division.

We have worked with many Six Sigma project teams. Most project teams tell us after the completion of their project how they had dreaded the math involved but that overall the statistical calculations were the least of the problems they encountered. Between computer programs like Mini-tab and the assistance of Master Black Belts, the math associated with project work is not as bad as they thought it would be.

Instead, project teams frequently cite other issues they struggled with much more than math. Our next series of questions deal with these more important problems.

Question #7 What do I need to know so I don’t become a part of failed Six Sigma team?

Teams rarely fail because they use the wrong tool or technique. This is even more so after individuals have been part of a few teams. They quickly learn to master the concepts and tools of Six Sigma. At Eckes and Associates we have gathered data on both our successes and our failures. The data shows that the biggest problem teams face will be in dealing with the concept of team dynamics.

In our third Six Sigma book, Six Sigma Team Dynamics: The Elusive Key to Project Success we reviewed many of the pitfalls that teams encounter. Like so many other initiatives in life, the issue of leadership is a crucial variable in either the success or failure of a Six Sigma team.

As we indicated in Six Sigma Team Dynamics, leadership comes in many forms. First, executive management must create an environment where they actively and demonstratively endorse Six Sigma as their management philosophy. Without this active endorsement, Six Sigma will, at best, end up being a short-lived cost savings initiative. In addition, in Chapter 2 we discussed how management must create the Six Sigma strategy through identifying and measuring processes and ultimately picking highprofile, low-performing processes. Next, leadership manifests itself through the project Champions who sponsor and guide the project to completion.

Leadership is an important aspect of team dynamics. The project Champion will have a variety of responsibilities from before the team is formed, through the four to six months they exist as a team, and even after the team is disbanded.

However, as we discussed in our previous chapter, there are a series of “soft” tools that assist a team in creating and maintaining team dynamics. These tools fall into two major areas. Tools associated with preventing maladaptive behaviors and intervention tools to assure that maladaptive behaviors don’t occur again. As stated in our previous chapter, such tools as agendas, ground rules, and setting specific roles and responsibilities for each team member are virtual guarantees for increased team dynamics. Knowing how and when to intervene when team dynamics go awry is yet another key to successful team dynamics.

Question #8 My plate is already full. How will I have the time to implement a Six Sigma initiative?

For those who are younger than 40 years of age, you may not remember the I Love Lucy Show. There is an episode where Lucy and her friend Ethel decide to get a job at a local candy manufacturer. They are placed on a production line where they are expected to pack individual candies into a box. The problem occurs when the production line is going too fast and they simply can’t keep up with the work. Both Lucy and Ethel are well intended and trying the best they can, but this is a broken process. They are exhausted. They clearly would think their plates are full. But this also is a process in need of improvement. Yes, the responsibility for fixing this process is that of management. But smart management will enlist the support and involvement of those that live in the process to get information and ideas as to how the process can be improved.

There is considerable variation in the amount of time team members spend on a Six Sigma project. Those team members who have previous experience or current skills associated with project management spend considerably less than the average 20 percent of work time associated with Six Sigma project time. We have seen some teams spend upwards of 50 percent or more of their time on Six Sigma project work but these teams tend to be more disorganized and rarely achieve their project goals of improved sigma performance.

Someone who asks the question above apparently has developed a tolerance for the current level of ineffectiveness and inefficiency in their work. They have lived and worked in processes so broken they have come to believe that inefficiency is their work. When done properly, what falls off the plate is all the empty calories in the organization that deal with being ineffective and inefficient.

Having said this, it is also important to note that it is management’s responsibility to send the clear message that process improvement is part of the job description.

Question #9 Is Six Sigma a guarantee of success? I heard Motorola is having problems with Six Sigma.

Six Sigma is not a guarantee of success in your business. Think of the analogy of preventive medicine. You can take all the precautions of eating right, exercising regularly, not smoking or drinking to excess and yet still experience illness. However, with Six Sigma as your management philosophy, the odds are that you will be sick as an organization less often and less severely.

Remember, at the highest level, Six Sigma is attempting to improve the effectiveness and efficiency of an organization. A problem many organizations encounter is the bias toward improvement of efficiency in the organization at the expense of effectiveness.

There are two major reasons for this bias toward improvement of efficiency, which is particularly acute in the first year of implementation. First, management typically is unaware of the cost associated with their current levels of ineffectiveness and inefficiency. Therefore, they are anxious to see a dramatic as possible return on their investment of outside resources, which are typically needed in the first year or two of implementation. Therefore, where does the short term cost benefits exist for quicker ROI? Clearly, it is in the current level of inefficiencies within the processes of the organization.

Second, it is much easier to quantify the costs associated with inefficiency versus improving effectiveness. What do you think is easier to measure, machine downtime or the longer term benefits of a happy customer? It is obviously the efficiency measure of machine downtime.

Ultimately, if Six Sigma is going to be a success in your organization, it needs a balance between improvement of effectiveness and efficiency. If your focus is on improving the efficiency of a process that produces Porsches and your customers desire a Chevrolet, Six Sigma will not work the way it could for you.

Question #10 Are there good consultants who will waive their fee and take a percentage of the cost savings they claim to generate for their clients?

Are there consultants who do this, yes. Are they good, no. Let’s examine why.

What would you think of a surgeon who would say, “Look, I will waive my fee for doing surgery on you and you get back to me with a percentage of your earnings from me saving your life?” If I had this proposal from a surgeon I would immediately question how good he or she is. I would feel it was a marketing ploy from a less than successful surgeon trying to drum up some new business. I want a surgeon with a proven track record of competency who will charge top dollar if they are worth it. And something tells me if your life was in jeopardy, you would make the same decision.

As a Six Sigma consultant, I feel confident in my skills. But much like the surgeon, there are no guarantees. Data we accumulated over the years indicate there is an 80 percent likelihood of either a dramatic shift in your culture or at least generating a significant ROI. For example, in recent years, our client base has been generating anywhere from a 2 to 1 to a 20 to 1 ROI for their first year Six Sigma implementation efforts.

Having said all this, our data still indicates 20 percent of our clients have failed to generate ROI. A consultant should not be responsible for lackluster effort, not paying attention to consultant advice, or populating project teams with the equivalent of the roster of a bad baseball team.

Final considerations

4. Final considerations

Nowadays, very small number (a few per cent) of the scientific research activities in area of quality management systems are based on topic of the collection and analysis of information with aim to improvement business results. That fact justify author’s effort to make preventive actions for improvement business performances through establishing synergy between area of quality management and artificial intelligence like area which is strictly oriented on producing knowledge. Also, through analysis of the available software for quality managemnt, it can be concluded that there are no any software from field of artificial intelligence that was developed for quality management systems improvement. That means that each further step in this direction brings positive scientific research results. The research point out necessity of making connection between more software solutions and tools in order to make the system with a higher level of intelligence. For this purpose, it is best to apply the integration of decision support systems and expert system. That is best world experience. With this approach it can be make system that producing knowledge and that is greatest resource which can make organization more competitive and can ensure improvement of organizations performances. Based on those facts in this research we developed unique analogy integrative approach which stays in the basis of model for improvement business process performance in the direction for achieving best organizational performances.

As the most important requests for achieving business excellences were identified requests which are mostly related to: measurement, analysis and improvement (module 8 - ISO 9001) and management responsibility (module 5-ISO 9001). The next area is most important for excellence organizational condition and at the same time area where should make very intensive action for improvement and strengthening: 821 – customer satisfaction, 72 - customer related processes, 54 – planning, 85 – continual improvement, 56 – management review and 55 – responsibility, authority and communication. It is interesting to highlight, that all activities and process which is related with customer and achieving his satisfaction and anticipation his needs, are in the focus and that should be direction and guidelines for all employees.

Also, it is shown that the strengthening, especially in these areas is used to lead to the significant progress in terms of: business process reengineering, manufacturing strategy, performance measurement and benchmarking, as very important aspects of market-oriented organization.

This research present interesting and useful results which should be use for defining measurement for improvement business performance in way for achieving business excellence. Those results are related with term of Degree of readiness which show part (every request) of ISO 9001 certified model and they ability for achieving top business form. Also, interesting results are present through values of Coefficient of significance. This two indexes show direction about area and intensity of action which should be provide to make best organisational condition.

In organizations that have specific information through database and information systems, it is necessary to develop systems that will assist staff in decision making. These systems provide data and output information on the basis of which, in accordance with the principle of decision making base on fact, the employees make business decisions that certainly contribute to improve organizational performance. However, in the today complex business condition, organization must make stride from level of data and information to level of knowledge. That is way for ensuring prestigious position on the market. That could be achieving through development expert system base on expert knowledge and base on output of decision support system.

This approach could be related with one modern approach, which calls case base reasoning. This approach is base on experience of other companies, and that approach could be use for defining preventive action. In this sense, it can be use a system that was developed in this work. That system was testing in real condition and proved to be very useful and that showed great level of efficiency and effectiveness for real business conditions. According to process of testing and estimation, users of the system were put ratings that are present in table 2. They indicate that this system can: make financial benefits, provide better organisation of job, stimulate all employees to improving own process, synchronise function in organisation, identify priority area for improvement, define intensity of action for improvement, stimulate preventive versus corrective action, encourage better involvement of new staff in to the activities, bring higher level of flexibility and other.

Author details

Aleksandar Vujovic, Zdravko Krivokapic and Jelena Jovanovic

Faculty of Mechanical Engineering, University of Montenegro,

Department for Production Engineering, Podgorica

Approach to developing expert system

3. Approach to developing expert system

At the market today, we can find many tools for creating expert systems. These systems can be developed in a programmable environment through tools of type C + +, Visual Basic or some other programs which are related to development of expert systems. However, today are developed specialized tools for creating expert systems which allow a high degree of automation in process of developing expert systems. There are called expert system shells. From the standpoint of this research it was carried out choice of expert system shell from the aspect of next four criteria [43-45, Personal communication with group for consulting from London South Bank University, Business, Computing & Information Management, 2011):

- programmability,

- comprehensiveness,

- universality,

- price.

During the election, it was analyzed 58 shells. All information about shells are available on the Internet [2], and classified in a group of commercial shell. Detailed analyses were conducted separately for each tool through analyzing belonging site. For evaluation on the basis of the criteria it was adopted the scale of 1 to 5 where 1 is unsatisfactory grade. According to defined criteria as a most distinguished tool for the needs of the research was adopted ACQUIRE shell. That tool is non programming oriented and it has affordable price. This is a tool that supports the work of the Windows operational environment. It has possibility to develop all elements of expert system and supports forward, backward and combined chaining. For the presentation of knowledge it can be used production rules, the action table, or combined techniques. During a process of developing expert system, the role of engineer for knowledge took up first author, and the role of one expert took up second author. Also, as sources of knowledge were used following:

- experience from eleven prestigious organizations in the world of field of quality management systems, business excellence and organizational performance [46],

- guidelines from standards for improving organizational performance [47 ],

- best practices from auditing of ISO 9001 oriented system [48],

- experience and practice of organizations that participated in the competition for the Oscar of quality award [49],

- theory and principles of TQM [50],

- experiences that are listed in [51] and indicate the path to business excellence.

The expert systems are included and knowledge gained through many concrete practical projects of quality management systems implementation, and many training on that topic. 

That knowledge is next:

- knowledge that are specific to certain companies,

- knowledge derived from specific experiences and on specific way of solving problem,

- knowledge of those that are best for certain jobs and are passed special training,

- knowledge of those that is proven in practice for the specific job and similar.

For the purposes of this research, expert system was develop for modules 5 (management responsibility) and module 8 (measurement, analyses and improvement) of ISO 9001 standard. The reason for that is that these areas have the greatest importance in achieving business excellence [1] and therefore they should be considerate from the standpoint of improvement. Also, another reason is that module 8 has requirements that are oriented to the improvement and that is essence and priority.

The idea of this research is to make the integration of decision support systems (DSS) which is operate on first level of experimental data, and expert system. That is modern approach of integration a number of tools with the aim of acquiring a larger volume of better knowledge [52] and make system with higher level of intelligence. Today trends are integration expert systems and traditional decision support systems which as output give data and information [53].

Integration of expert systems and decision support system can be achieved in two ways [54]. The purpose of this research is to use model which is present on figure 5. based on the collection and analysis of data obtained at the output of the decision support system and it provide important information like one of inputs for expert system and its knowledge base. This is the model which is completely compatible with previous remarked analogy with human body. This two approach stay in base of this analogy integrative model for improvement business process performance.

For the purposes of this research, we developed a decision support system in the MS Access, Select Query Language and Visual Basic environment. This system is base on the first level of experimental data, and like one of outputs it gives results which are present on figure 6 (for module 8).

Applying Pareto method and rules of 70/30 it can be identified area which is crucial from the standpoint of improvement. Also, this system like support for making decision provides written presentation of nonconformities which can be shown as experience of other companies. That could be use like important data for the definition of knowledge in expert system. In addition, this system provides, and comparative analysis with the period of the four years before, which also has significance for the definition of knowledge in the expert system.

Connection between data from the first and data from the second level was achieved through the introduction of the concept of "Degree of readiness (Si)" in achieving business excellence, in accordance with the following expression:

Si = Nz [%] * Kz , i=1,2,...,26 

where:

Si Degree of readiness for all type of organizations for all requests of ISO 9001 Nz Power of a standard clause in terms of percentage. 

Nz = ƒ (number of nonconformities from experimental database) 

Kz Coefficient of significance for achieving business excellence

That degree is applies to every single request of ISO 9001 and showing the willingness or the ability of organizations (both manufacturing and service sector) to attain business excellence in some areas. To find this degree, we are using method Analytic Hierarchy Process (AHP) and corresponding software Expert Choice. Results are shown in table 1.

It is important to emphasize this because it was used and it is very important during definition of preventive measures in terms of defining their priorities and "power". Also, “power” of prevention was related with number of nonconformities in particular area. That means, larger number of nonconformities, or larger number of experience, make possibilities for defining more effective and efficient preventive action like output of expert system.

Through application of Pareto method, based on coefficient of significance following requests were identified as the most significant for achieving business excellence:

requests - 821, 823, 85, 84, 54, 824, 56, 53, 71, 41, 51, 72, 55

At the same time, this is important areas, and have high level of priority for improvement from the standpoint of achieving business excellence and it is very important for defining preventive action of expert system and intensity of that action. If we take a look at the list of "Coefficients of significance" for business excellence achieving, especially the most important ones and perform comparison with the list of variables and their significance in terms of: Business Process Reengineering (BPR), manufacturing strategy, benchmarking and performance measurement, being the result of the appreciated research [55] and [56] it may be found significant intercompatibility.

The concerned compatibility is especially reflected in the following variables, evaluated in the relative research as highly significant for the following four projects, i.e.: customer satisfaction, quality, employee satisfaction and personal growth, customer adaptability, identification of top managers with BPR goals, strong process orientation, results orientation, direct customer cooperation. On the other hand, the above mentioned four areas are considered as highly important for any market-oriented organization, thence it can be concluded that organizations by strengthening their capacities in areas of presented "Coefficients of significance" (especially the most important ones), are not only strengthened in terms of the business excellence achieving as per European Award model, but also in the stated four areas.

But some of these areas are much more important then other. Because that, the research was further elaborated in order to indicate most important area for improvement and area where should be focus attention and where should be provide very intensive action in order to achieve best organizational condition and results. This research was conduct from the standpoint of occurrence of nonconformities in all type of organisation regardless of they size or type (both for manufacturing and service organisation). Parallel the Pareto method (70/30) was carried out in that direction and based on that, it was identified next areas:

requests - 56, 75, 62, 822, 74, 76, 54, 72, 85, 821, 55, 63

Now we are search for common requests (area) that are most important and where should be oriented focus and where should be provide extensively action in terms of achieving business excellence regardless of type or size of organization. And they are:

1. 821 – customer satisfaction,

2. 72 - customer related processes,

3. 54 – planning,

4. 85 – continual improvement,

5. 56 – management review and

6. 55 – responsibility, authority and communication.

This area is most important for defining output of expert system and for defining intensity of action for improvement.

Objects were defined during the process of expert system developing. That were depend of problem which should be solved, base on ISO 9001 oriented check list an based on experience which can be find on DSS output. Base on results of DSS system, it is defined value of the object and relation between them. In that way, it is created decision tree, which is present on figure 7.

At the end, after starting the program, in a short time, system introduce user in a set of dialog boxes. One of them is shown on figure 8.

Depend on the answers, expert system produce user’s report, like one which is presented on figure 9.

Data obtained from this report, user can use and implement knowledge that an expert system produces. However, users can improve performance of an organization in the field where such as performance are on lower level. Also, it can be improvement performances of other, non critical, area and can be reach level of business excellence.

This expert system was developed in three iterative steps. Each of them resulted of the improvement, for example improvement of the definition of objects, set the input data, the relation between objects depending on the priorities of execution and more.

The expert system was implemented and tested in practical, real conditions in the organization that has a clear commitment to participate in the competition for the European Award for Business Excellence, also providing important measures in that direction. Evaluation was done on the basis of technical and ergonomic characteristics based on guidelines in standards ISO/IEC 9126/1:2001 for evaluation quality of software. The results are shown in Table 2.

Figures showed significant high mark by categories, and thus the total amount. Software was evaluated positive in terms of technical characteristics and in terms of ergonomic. In this sense, product has small time of response, it is compatible with most used operating system, it has an excellent user’s oriented interface, and it has easy data entry and a good view of the output, installation is simple and the software is very competitive. Also, in this sense, within the organization, it was carried out the reorganization of the priority areas from the viewpoint of improvement, implemented preventive measures for the potentially unstable areas and also applied the measures for the improvement (offered by this system) leading to business excellence achieving.

Experimental research, areas for research and reasons for developing expert systems

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.

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 nonconformances 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.

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 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 (http://www.qualitymag.com) where are publish updated software items which are related to quality. The results of the analysis are shown in the figure 3.

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.

To establish the analogy between the process modulated organizational structure and the human organism, so as to create the system that is independent from organizational functions and based only on the process model, following division of man functions was made [39, 40]:

- willing and

- unwilling functions.

Willing functions (term “functions” is used in medical terminology, although it is equally correct, to use a term “activities” in view of ISO 9000 standard terminology. For reasons of consistent referencing and use of theories from the field of medicine, the author has chosen to use the term functions.) are those dependent on man’s profession and performed by man’s will. They are variable and dictated by a central control of the organism. For example, when a worker at the construction site lifts his hand, it is not the same as when a referee at the game lifts his hand and etc. Willing functions refer to functions of external motoric organs.

Second category is made of unwilling or automated functions and their use is given by their existence. There are functions that are same in all professions and all people (considering that they exist, i.e. that human body is in good health) and do not depend on the man will but are simply executed. For example, those are functions of secreting enzymes, hormones, heartbeats, and similar, like ordinary body functions, and functions that cannot be controlled [41, 42].

With such a ratio of functions in the human body, we can establish the analogy of the system with implemented quality management system. Analogy in term of willing function goes in direction to developed all data in to two category, production and service organization and make some analyses, which is not subject of this research.

In order to meet requirements of this research, only analogy in terms of unwilling functions has been considered. The idea is to use all nonconformities (undependable of organization type or size) and base on case base reasoning approach, make conclusion about readiness of systems to making some top form.

Six Sigma Class Introduction

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 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