Knowledge Based System

Surface mount technology (SMT) is one of the most important developments in electronic industry. A surface mount assembly (SMA) has three consecutive manufacturing steps: solder paste stencil printing, component placement, and solder reflow. Stencil printing process (SPP) involves highly operation complexity and has multiple quality characteristics, and averagely accounts for 60% of soldering defects in SMA. This work presents a knowledgebased system for SPP planning and control to upgrade soldering quality level and system performance. A hybrid data set contains a 3 8-3 experimental design and statistical process control (SPC) records was collected firstly, and followed by data processing for removing conflicted, inconsistent, and redundant samples through a fuzzycluster algorithm. The output columns of the clustered data were then transformed using fuzzy quality loss function (FQLF) with respect to the dissatisfaction of printing performance. The neuro-fuzzy technique was adapted to model and learn SPP knowledge from the transformed data set into a SPP knowledge base. Finally, a GUI man-machine interface was developed to help engineers in predicting responses and evaluating the overall SPP performance. The empirical evaluations of soldering quality and productivity demonstrate the effectiveness and efficiency of this proposed system.

For the treatment of industrial wastewater a multitude of processes is available. It is the task of the chemical engineer to choose processes and to build up a treatment sequence suitable for the actual problem. Because of the large number of processes and process combinations, a knowledge-based system may be helpful during process selection and sequencing. The introduced knowledge based system delivers a treatment sequence based on heuristics and cost estimation. Depending on the supplied information a more or less detailed treatment sequence is suggested by the program. The article describes the aim and development of the knowledge based system, gives an overview on the program functions and presents the result of an example program consultation.

This paper describes the development of a Knowledge Based System for predicting strategic maintenance in residential property. An initial feasibility study identified a need for the long term strategic planning of building maintenance in Housing Associations. However, conventional Maintenance Management programs require too much data input, are too inflexible, do not explain their results, and do not permit their users to explore potential alternatives. The application of Knowledge Based System's technology to this area directly addresses these problems. This paper examines the need for such systems, and describes the implementation of one such system using a Client Centred Methodology. The paper concludes by discussing some of the problems that were encountered during the system's development, how they were overcome, and what lessons may be learned for future system developments.

ADDS (Approach to Document-based Development of Software) is an approach to the development of applications based on a document-oriented paradigm. According to this paradigm, applications are described by means of documents that are marked up using descriptive domain-specific markup languages. Afterwards, applications are produced processing these marked up documents. Formulation of domain-specific markup languages in ADDS is a dynamic and eminently pragmatic activity since these languages evolve in accordance with the authoring needs of the main actors that participate in the development process (i.e. domain experts and developers). OADDS (Operationalization in ADDS) is a processing model that promotes the construction of modular language processors and their incremental evolution. Thus, OADDS is specifically designed to cope with the evolutionary nature of the domain-specific markup languages encouraged by ADDS. ADDS and OADDS have successfully been applied to the development of applications in knowledge-intensive domains (i.e. transport networks and educational hypermedias). This paper also describes the advantages (incremental development and maintenance improvement) that this approach supposes for the development of knowledge-based systems.

New wireless communications, user mobility and the growing need of taking into account the characteristics of the context make feasible the development of advanced frameworks to support context-aware knowledge systems. In this paper we present the design of the contextual information for an airport domain using a platform that exploits the modular and distributed architecture to develop context-aware applications.

Geo-deformation failures leading to landslides cause huge loss to socio-economic infrastructures and personal life and property all over the world, specifically in hilly terrains. It is a localized phenomenon which usually gets triggered by rainfall. In this paper, a framework for a warning system based on prediction of failure of geo-deformation has been proposed. The system warns against rainfall-triggered landslides making use of a Knowledge Based System including a warning module. The system consists of the input module, the understanding module, rainfall prediction module, the expert module, the output module and the warning module. The input module accepts scanned images of thematic maps of contributing factors of landslides as well as output from rainfall prediction module, based on field observed GPS data. The understanding module interprets input information to extract relevant information as required by expert module. The expert module consists of a Knowledge Base (KB) and Inference strategy to categorize the given region into different intensities of landslide hazard, output module communicates a warning message to warning module provided by the inference module and finally, warning module proclaim the warning message to user. At present, the system has the capability to prepare a Landslide Susceptibility Zone map of a region and its extension to a prediction system is under development. The major outcomes of the proposed system will be towards development of a warning system towards local geo-hazard analyses and provide a support system for landslide disaster preparedness and mitigation activities.

If it is true that good problems produce good science, then it will be worthwhile to identify good problems, and even more worthwhile to discover the attributes that make them good problems. This discovery process is necessarily empirical, so we examine several challenge problems, beginning with Turing's famous test, and more than a dozen attributes that challenge problems might have. We are led to a contrast between research strategies-the successful "divide and conquer" strategy and the promising but largely untested "developmental" strategy-and we conclude that good challenge problems encourage the latter strategy.

Although activated sludge process is a very widely used biological process in wastewater treatment plants (WWTP), and there are properly functioning control loops such as that of dissolved oxygen, in practice, this type of plant requires a major time investment on the part of the operator, involving many manual operations. Treatment plants work well most of the time, as long as there are not unforeseen occurrences. Normal operating situations (generally similar to design conditions) can be treated mathematically by using efficient control algorithms. However, there are situations in which the control system cannot properly manage the plant, and in which the process can only be efficiently managed thanks to the operator's experience. This is a case in which a knowledgebased system may be useful. One of the difficulties inherent to the development of a knowledge-based system is to obtain the knowledge base (i.e., knowledge acquisition), specially when dealing with a wide, complic...

Although substantial advances have been achieved in last twenty years, in practice we are still far from taking full advantage of the potential of knowledge-based systems (KBS). Very few KBS have survived their evaluation period and only one third of those that were initially reported as successful are still in use. The primary purpose of the paper is to report on three KBS applications that have been developed for research purposes in the field of civil engineering. The main challenge underlying all three projects has been to develop computer support systems that would induce changes and improvements to the way that engineers solve their everyday problems. A great deal of effort has been put into eliciting knowledge and reasoning strategies from engineering experts with the aim of building up a computer model of their expertise in order to assist engineers in their decision-making processes. The paper closes by highlighting the principal achievements and the main issues concerning the future development of KBS for solving real life problems.

Design of concrete mixtures is the process of selecting the most economical and practical proportions of all the ingredients to produce quality concrete. Because of the nature of the mix design process and all the heuristic knowledge that is associated with it, concrete mix design lends itself well to a knowledge-based application. This paper describes a prototype knowledge-based system called HPCMIX that can be used to load the experimental data, develop several statistical models to determine the responses, evaluate the predicted models, and predict the 28 days strength and slump. It can also be used to design HPC mix proportions that are subjected to specified constraints (e.g. strength and slump). It is capable of selecting proportions of mixing water, cement, supplementary cementitious materials, aggregates and superplasticizer, with consideration being given to the effects of air content as well as water contributed by superplasticizer and moisture conditions of aggregates. As most of knowledge-based systems, this system has explanation facilities, can be incrementally expanded, and has an easy to understand knowledge base. The system was tested on a sample project. The system's selection of the concrete proportions compared favourably with the expert's selection. The system is very useful for civil engineering students as well as practicing engineers.

Social security legislation plays an important role in the Dutch society. In view of this, the effects of social security legislation have to be analysed carefully before new legislation can be made. Due to the growing complexity of legislation on the social security domain, this analysis has become a demanding task. ExpertiSZe is a knowledge-based system developed to support the process of analysing juridical and socioeconomic effects of social security legislation. The ExpertiSZe system consists of three modules: a consultation module, a consistency module and a simulation module. These modules, which all work on the basis of the same rule-based model, provide the legislator with more insight into the impact of legislation. This article describes the potential of ExpertiSZe to support the analysis of effects of legislation.

This paper outlines the development of a knowledge-based system (KBS) which integrates environmental factors into the supplier selection process. The system employs both case-based reasoning (CBR) and decision support components including multi-attribute analysis (MAA). Traditionally, when evaluating supplier performance, companies have considered factors such as price, quality, flexibility etc. However, with environmental pressures increasing, many companies have begun to consider environmental issues and the measurement of their suppliers' environmental performance. The framework presented in this paper was developed from an analysis of environmental management practices in a number of companies along with a thorough literature survey. The paper then outlines how the most important parts of the framework were computerised using KBS techniques. An evaluation of the system implemented in a multinational company is presented along with proposals for future system enhancements. q

This work presents a brief review of some selected knowledge-based approaches to electrocardiographic (ECG) pattern interpretation for diagnosing various malfunctions of the human heart. The knowledge-based approaches discussed here include modeling an ECG pattern through an AND/OR graph, a rule-based approach and a procedural semantic network (PSN) based approach for ECG interpretation. However, certain syntactic approaches to ECG interpretation are also covered, considering their precursory roles to knowledge-based ECG interpretation. A fuzzy-logic-based approach is included in the discussion to show how imprecision can be dealt with in modeling cardiological knowledge. A domain-dependent control algorithm is discussed to show how the production level parallelism can be exploited to reduce the length of the match}resolve}act cycle of a rule based ECG interpretation system. The review also contains a brief description of some recent applications of connectionist approaches to ECG interpretation. This discussion "nally ends with a comparative assessment of performances of all the above-mentioned knowledge-based approaches to ECG interpretation and some hints about the future directions of work in this "eld. : S 0 0 3 1 -3 2 0 3 ( 9 9 ) 0 0 0 6 5 -5

This paper introduces PROSIM, a knowledge-based system for modeling processes, analyzing them using simulation and project management tools, and designing improved processes. Domain experts who are familiar with the various aspects of the system may be interviewed and process models can be developed based on the evidence collected using PROSIM. The tutorial focuses on the built-in simulation design support environment of PROSIM that enables building simulation models automatically from process models. The later part of the tutorial briefly covers extensions to PROSIM which permit information captured in PROSIM models to be leveraged for other analysis-project planning in a project management tool such as Microsoft ® Project ™ . A purchase order processing system example is described to demonstrate the utility of PROSIM.

A ubiquitous Knowledge Base (u-KB) is a distributed and decentralized knowledge base where the factual knowledge (i.e. individuals) is scattered between objects disseminated within a given environment with no centralized coordination. Such a vision enables a truly pervasive environment where autonomous objects set up a self-organized discovery architecture. This paper presents an extended framework to set-up u-KBs. An advanced semantic matchmaking makes possible resource discovery based on metadata stored in RFID (Radio Frequency IDentification) tags without pre-stored and fixed repositories and a dissemination protocol allows an ondemand retrieval of suitable resource descriptions directly from tags located on the objects.

The need for flexible and well understood knowledge representations which are capable of capturing clinical guidelines and protocols for decision support systems is widely recognised. The PROforma method for specifying clinical guidelines and protocols comprises a graphical notation for their design, and a formal knowledge representation language to enable them to be executed by a computer to support the management of medical procedures and clinical decision making. PROforma technology consists of a graphical knowledge editor for the creation of guidelines, and an enactment engine for testing and executing them. This paper provides an overview of the motivation and structure of PROforma, and illustrates its use in the development of clinical applications.

Abstract: MIX is an ESPRIT project aimed at developing strategies and tools for integrating symbolic and neural methods in hybrid systems. The project arose from the observation that current hybrid systems are generally small-scale experimental systems which couple one symbolic and ...

Although there is not a complete agreement on the causes of foaming in anaerobic digestion, experts and operators do have valuable empirical knowledge of key factors. Based on this knowledge, a model for calculating the risk of foaming in anaerobic digestion systems due to microbiological causes has been developed. Organic loading rate, variation in organic loading rate, and the presence of filamentous microorganisms in the activated sludge system, used as a feed source for the digester, have been selected as the inputs of a knowledge-based model designed to provide as output the risk of foaming in an anaerobic digester. The performance of the model is demonstrated by means of a case study using the IWA Benchmark Simulation Model No. 2 as a framework, where risk of foaming is used as a new evaluation criterion. The simulated results of an open-loop configuration and two closed-loop control strategies illustrate the usefulness of this knowledge-based approach as a means of estimating the risk of foaming in anaerobic digestion.

A complete knowledge based procedure for the design and manufacture of a round hole broach tool is described. The knowledge based design system (KBDS) produces a tool specification from user inputs describing the task to be performed. These design results are then used by the knowledge base to generate a geometric CAD/CAM representation, which can be utilized directly to display a drawing of the tool or to generate a CNC program for producing it. The process of formulating a knowledge-based design system demonstrates: the integration of expertise from experts, handbooks and theory; the awareness of restrictions on the scope of design that can be handled by a given system: the use of failure handling mechanisms to detect design failures and either adjust the emerging design or indicate infeasibility.

A computerized Urine Protein Expert System (UPES) measuring creatinine, total protein, albumin, IgG, α 1 -microglobulin, α 2 -macroglobulin, and N-acetyl-β-Dglucosaminidase, together with urine dipstick testing for granulocyte esterase and hemoglobin pseudoperoxidase, and measurement of serum creatinine had been found to be useful in adults for differentiating between renal disorders. The objective of this study was to investigate UPES for identifying the different types of proteinuria and their underlying prerenal, glomerular, tubular, and postrenal causes in 146 children characterized by routine and invasive nephrological investigations. UPES proved to be a useful tool in pediatric renal patients after refinements were implemented in the program. Comparing UPES with the pediatric nephrologist's interpretation of all available clinical and laboratory data, UPES diagnosed glomerulopathies in 46 (75%) of 61 patients. In a further 23% it suggested glomerular involvement by indicating either a disturbed glomerular permeability or increased excretion of albumin. Tubular proteinuria was correctly described by UPES in 23 (100%) patients with different tubulopathies. UPES revealed normal kidney function in all healthy children and all children with remission of renal disorders. Therefore, UPES can be regarded as a useful tool in the automated differentiation of renal diseases in children.

Algorithmic research is an established knowledge engineering process that has allowed researchers to identify new or significant problems, to better understand existing approaches and experimental results, and to obtain new, effective and efficient solutions. While algorithmic researchers regularly contribute to this knowledge base by proposing new problems and novel solutions, the processes currently used to share this knowledge are inefficient,

Over the past four years there has been a tremendous resurgence of "public" interest inside and outside of IBM in APL and especially APL2 as a result of 1. an awareness of the importance of for technical computing, rapid prototyping, array algorithms for parallel computing, and advanced decision support 2. state-of-the-art work being done with APL in such diverse areas as medical imaging, finance, manufacturing scheduling, spot market oil buying and selling, computer design, chip design, mathematics, knowledge based systems statistics, etc. 3. IBM establishing APL2 as its strategic interactive language and making it a key player in its technical computing strategy Due to this renewed interest, I have compiled a list of some APL-related articles on Modeling and on Knowledge-Based Expert Systems .(KBES).

With the aging population increasing at a faster rate the muscular skeletal system disorder caused by falling is becoming a challenging problem to health providers. In Thailand there is lack of training of therapists to assist the elderly people following fall injuries. The need for innovative approaches to help with the care of elderly is required. This paper addresses this issue by describing a decision support system based on a case based reasoning paradigm to support the physiotherapists in their care for the elderly.

This case analysis contributes to the academic development of knowledge management by questioning the widely accepted data-information-knowledge hierarchy. It examines the practical use the hierarchy during the development of a knowledge-based system in a large utility company. The data-informationknowledge hierarchy was found to be of limited practical use. The literature related to the hierarchy sheds little light on separating the concepts of data, information and knowledge. This case uses empirical data from an in-depth study to present a counterpoint to the conventional data-information-knowledge hierarchy. It contributes to theory in two distinct ways. First, it introduces the knowledge-informationdata model, which proposes a top-down perspective rather than the traditional bottom-up approach. Second, the case suggests that the terms knowledge and information can be understood in terms of their purpose and location. r

Laser forming is a relatively new technique which is beginning to find applications in a number of areas. The technique involves passing a high powered laser beam over the surface of a material to induce thermal deformation. If the technique is to find widespread commercial application then control of the process will be crucial. The case is made for using feedback control as opposed to a knowledge based system to counter the difficulties arising from the range and unpredictability of the process variables. The development of a basic feedback system is described and the results for forming operations with the system implemented are presented. These indicate the success of the system in producing deformations of predetermined magnitude. Recommendations for future developments and refinements are proposed. ,~ 1997

Information and computer technology popularizes in blood banks for its potentials in working efficiency as well as service quality. But, in the face of the explosive data and information, one of the challenges in blood bank information systems is how to make good use of them for decision making support. In this paper, we desire to explore the mechanisms of decision making support in blood bank information systems. Firstly, the properties of data and decisions in a blood bank are examined carefully; then, we introduce the development of computerized decision making support with special concerns on blood donation and transfusion service; finally, a case study is presented to evidence our understanding on decision making support in blood bank information systems.

Good performance within a company is the result of correct interaction of business management with its internal and external environment. The recognition of internal strengths and weaknesses, as well as external opportunities and threats, takes place on the basis of a SWOT-analysis. However, despite their importance, many companies often only have vague ideas of their competitive strengths and weaknesses, opportunities and threats. In this paper, the development of a knowledge-based system is described that can assist managers of small and medium sized companies in performing a SWOT-analysis. For our research purposes, we concentrated only on the identification of internal strengths and weaknesses. q commence with the identification and evaluation of these strategic factors which assist or hinder the company in reaching its full potential. Because every company is confronted with a dynamic environment, the relative importance of a strategic factor will change constantly, so this analysis is accordingly to be of a permanent nature.

The World Wide Web facilitates user access to knowledge-based decision support systems. Such web-enabled systems can provide users with advice about how decision-makers exercise discretion. GetAid, developed using the web-based shell environment WebShell, is an example of a web-based decision support system operating in a discretionary legal domain. This paper presents the Context, Criteria, Contingency evaluation framework for knowled- ge-based

Validation and verification of expert systems or knowledge-based systems is a critical issue in the development and deployment of robust systems. This article is a comprehensive survey of the developments and trends in this field. More than 300 references are included in the References and Additional Readings at the end of this article.

This paper surveys knowledge management (KM) development using a literature review and classification of articles from 1995 to 2002 with keyword index in order to explore how KM technologies and applications have developed in this period. Based on the scope of 234 articles of knowledge management applications, this paper surveys and classifies KM technologies using the seven categories as: KM framework, knowledge-based systems, data mining, information and communication technology, artificial intelligence/expert systems, database technology, and modeling, together with their applications for different research and problem domains. Some discussion is presented, indicating future development for knowledge management technologies and applications as the followings: (1) KM technologies tend to develop towards expert orientation, and KM applications development is a problem-oriented domain. (2) Different social studies methodologies, such as statistical method, are suggested to implement in KM as another kind of technology. (3) Integration of qualitative and quantitative methods, and integration of KM technologies studies may broaden our horizon on this subject. (4) The ability to continually change and obtain new understanding is the power of KM technologies and will be the application of future works. q

Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results. Keywords—Expert system, car failure diagnosis, knowledge- based system, CLIPS.

. Business process reengineering BPR has become the buzzword representing dramatic changes to the business processes of organizations trying to quickly preempt or react to market opportunities and competition. Much of the changes are enabled by computer-based technology such as Ž . expert systems ES providing a unique opportunity to study significant implementations of the technology within a relatively short time. Eight ES implementation success factors proposed in the literature were empirically tested in this study in terms of their direct and indirect importance to the benefits from using ES in BPR. Sixty-two ES applications within E.I. Dupont de Nemours dealing with business process changes significant enough to be called BPR were used. Despite the relatively small sample size, four of the eight success factors were corroborated: user satisfaction with the ES, the difficulty of the business problem addressed, the degree of user involvement in the ES implementation process, and characteristics of the ES shells. q 1998 Elsevier Science B.V. All rights reserved.

Validation and verification of expert systems or knowledge-based systems is a critical issue in the development and deployment of robust systems. This article is a comprehensive survey of the developments and trends in this field. More than 300 references are included in the References and Additional Readings at the end of this article.

Clouds are distributed Internet-based platforms that provide highly resilient and scalable environments to be used by enterprises in a multitude of ways. Cloud computing offers enterprises technology innovation that business leaders and IT infrastructure managers can choose to apply based on how and to what extent it helps them fulfil their business requirements. It is crucial that all technical consultants have a rigorous understanding of the ramifications of cloud computing as its influence is likely to spread the complete IT landscape. Security is one of the major concerns that is of practical interest to decision makers when they are making critical strategic operational decisions. Distributed Denial of Service (DDoS) attacks are becoming more frequent and effective over the past few years, since the widely publicised DDoS attacks on the financial services industry that came to light in September and October 2012 and resurfaced in the past two years. In this paper, we introduce advanced cloud security technologies and practices as a series of concepts and technology architectures, from an industry-centric point of view. This is followed by classification of intrusion detection and prevention mechanisms that can be part of an overall strategy to help understand identify and mitigate potential DDoS attacks on business networks. The paper establishes solid coverage of security issues related to DDoS and virtualisation with a focus on structure, clarity, and well-defined blocks for mainstream cloud computing security solutions and platforms. In doing so, we aim to provide industry technologists, who may not be necessarily cloud or security experts, with an effective tool to help them understand the security implications associated with cloud adoption in their transition towards more knowledge-based systems.

Truth maintenance systems (TMSs) were introduced more than ten years ago, but recently there is an explosion of interest in them and their possible applications in different areas. In this paper we discuss truth maintenance from three perspectives: • Truth maintenance as a data base management facility, which was in fact the original intention of the TMS. • Truth maintenance as an infei'ence facility, which provides a way to extend the role of the TMS in solving problems. • Truth maintenance as a verification facility, which illustrates a new and promising application of TMSs in the area of expert systems design. This paper is not intended to provide a complete survey on TMSs, rather it aims to present the basic ideas and functionality of TMS, and to show how different kinds of TMS can be used as a meta-environment for testing Expert System Knowledge Bases, represented as sets of production rules, for anomalies.

The authors review and categorize the research in applications of arti®cial intelligence (AI) and expert systems (ES) in new product development (NPD) activities. A brief overview of NPD process and AI is presented. This is followed by a literature survey in regard to AI and ES applications in NPD, which revealed twenty four articles (twenty two applications) in the 1990±1997 period. The applications are categorized into ®ve areas: expert decision support systems for NPD project evaluation, knowledge-based systems (KBS) for product and process design, KBS for QFD, AI support for conceptual design and AI support for group decision making in concurrent engineering. Brief review of each application is provided. The articles are also grouped by NPD stages and seven NPD core elements (competencies and abilities). Further research areas are pointed out.

Abstract. The goal of the PIF Project is to develop an interchange format to help automatically exchange process descriptions among a wide variety of business process modelling and support systems such as workflow software, flow charting tools, process simulation systems, and process repositories. As an example of such an exchange, a demonstration scenario has been created which describes the use of PIF in the modelling and simulation of an integrated supply chain where different companies co-operate ...

The monitoring and detection of nosocomial infections is a very important problem arising in hospitals. A hospitalacquired or nosocomial infection is a disease that develops after admission into the hospital and it is the consequence of a treatment, not necessarily a surgical one, performed by the medical staff. Nosocomial infections are dangerous because they are caused by bacteria which have dangerous (critical) resistance to antibiotics. This problem is very serious all over the world. In Italy, almost 5-8% of the patients admitted into hospitals develop this kind of infection. In order to reduce this figure, policies for controlling infections should be adopted by medical practitioners. In order to support them in this complex task, we have developed a system, called MERCURIO, capable of managing different aspects of the problem. The objectives of this system are the validation of microbiological data and the creation of a real time epidemiological information system. The system is useful for laboratory physicians, because it supports them in the execution of the microbiological analyses; for clinicians, because it supports them in the definition of the prophylaxis, of the most suitable antibi-otic therapy and in monitoring patients' infections; and for epidemiologists, because it allows them to identify outbreaks and to study infection dynamics. In order to achieve these objectives, we have adopted expert system and data mining techniques. We have also integrated a statistical module that monitors the diffusion of nosocomial infections over time in the hospital, and that strictly interacts with the knowledge based module. Data mining techniques have been used for improving the system knowledge base. The knowledge discovery process is not antithetic, but complementary to the one based on manual knowledge elicitation. In order to verify the reliability of the tasks performed by MERCURIO and the usefulness of the knowledge discovery approach, we performed a test based on a dataset of real infection events. In the validation task MERCURIO achieved an accuracy of 98.5%, a sensitivity of 98.5% and a specificity of 99%. In the therapy suggestion task, MERCURIO achieved very high accuracy and specificity as well. The executed test provided many insights to experts, too (we discovered some of their mistakes). The knowledge discovery approach was very effective in validating part of the MERCURIO knowledge base, and also in extending it with new validation rules, confirmed by interviewed microbiologists and specific to the hospital laboratory under consideration.

Product design and optimisation today involves so many fields of expertise, many of which are in rapid evolution, that it can be very difficult for the designer to manage them. This paper describes the development of the DGLs (Design Guidelines), a knowledge-based tool that could be of great help to designers and engineers in modifying their products to get compatibility with different manufacturing and verification technologies. The current release of the DGLs, heavily influenced by the adoption of some ISO-GPS (Geometrical Product Specification) concepts, has been validated using the Rapid Prototyping technique called FDM (Fluid Deposition Modelling) and the CMM (Coordinate Measuring Machine) verification technique.

Assuring the quality of an expert system is critical. A poor quality system may make costly errors resulting in considerable damage to the user or owner of the system, such as financial loss or human suffering. Hence verification and validation, methods and techniques aimed at ensuring quality, are fundamentally important.