Expert systems for vendor selection

The survival of organisations, especially SMEs, depends, to the greatest extent, on those who supply them with the required material input. This is because if the supplier fails to deliver the right materials at the right time and place, and at the right price, then the recipient organisation is bound to fail in its obligations to satisfy the needs of its customers, and to stay in business. Hence, the task of choosing a supplier(s) from a list of vendors, that an organisation will trust with its very existence, is not an easy one. This project investigated how purchasing personnel in organisations solve the problem of vendor selection. The investigation went further to ascertain whether an Expert Systems model could be developed and used as a plausible solution to the problem. An extensive literature review indicated that very scanty research has been conducted in the area of Expert Systems for Vendor Selection, whereas many research theories in expert systems and in purchasing and supply management chain, respectively, had been reported. A survey questionnaire was designed and circulated to people in the industries who actually perform the vendor selection tasks. Analysis of the collected data confirmed the various factors which are considered during the selection process, and established the order in which those factors are ranked. Five of the factors, namely, Production Methods Used, Vendors Financial Background, Manufacturing Capacity, Size of Vendor Organisations, and Suppliers Position in the Industry; appeared to have similar patterns in the way organisations ranked them. These patterns suggested that the bigger the organisation, the more importantly they regarded the above factors. Further investigations revealed that respondents agreed that the most important factors were: Product Quality, Product Price and Delivery Date. The most apparent pattern was observed for the Vendors Financial Background. This generated curiosity which led to the design and development of a prototype expert system for assessing the financial profile of a potential supplier(s). This prototype was called ESfNS. It determines whether a prospective supplier(s) has good financial background or not. ESNS was tested by the potential users who then confirmed that expert systems have great prospects and commercial viability in the domain for solving vendor selection problems.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

The use of expert systems for decision making in organizations

The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.

Computer integrated system for form-roll manufacture

Computer integrated manufacture has brought about great advances in manufacturing technology and its recognition is world wide. Cold roll forming of thin-walled sections, and in particular the design and manufacture of form-rolls, the special tooling used in the cold roll forming process, is but one such area where computer integrated manufacture can make a positive contribution. The work reported in this thesis, concerned with the development of an integrated manufacturing system for assisting the design and manufacture of form-rolls, was undertaken in collaboration with a leading manufacturer of thin-walled sections. A suit of computer programs, written in FORTRAN 77, have been developed to provide computer aids for every aspect of work in form-roll design and manufacture including cost estimation and stock control aids. The first phase of the development programme dealt with the establishment of CAD facilities for form-roll design, comprising the design of the finished section, the flower pattern, the roll design and the interactive roll editor program. Concerning the CAM facilities, dealt with in the second phase, an expert system roll machining processor and a general post-processor have been developed for considering the roll geometry and automatically generating NC tape programs for any required CNC lathe system. These programs have been successfully implemented, as an integrated manufacturing software system, on the VAX 11/750 super-minicomputer with graphics facilities for displaying drawings interactively on the terminal screen. The development of the integrated system has been found beneficial in all aspects of form-roll design and manufacture. Design and manufacturing lead times have been reduced by several weeks, quality has improved considerably and productivity has increased. The work has also demonstrated the promising nature of the expert systems approach to computer integrated manufacture.

Developing a model for consumer product safety evaluation

Safety enforcement practitioners within Europe and marketers, designers or manufacturers of consumer products need to determine compliance with the legal test of "reasonable safety" for consumer goods, to reduce the "risks" of injury to the minimum. To enable freedom of movement of products, a method for safety appraisal is required for use as an "expert" system of hazard analysis by non-experts in safety testing of consumer goods for implementation consistently throughout Europe. Safety testing approaches and the concept of risk assessment and hazard analysis are reviewed in developing a model for appraising consumer product safety which seeks to integrate the human factors contribution of risk assessment, hazard perception, and information processing. The model develops a system of hazard identification, hazard analysis and risk assessment which can be applied to a wide range of consumer products through use of a series of systematic checklists and matrices and applies alternative numerical and graphical methods for calculating a final product safety risk assessment score. It is then applied in its pilot form by selected "volunteer" Trading Standards Departments to a sample of consumer products. A series of questionnaires is used to select participating Trading Standards Departments, to explore the contribution of potential subjective influences, to establish views regarding the usability and reliability of the model and any preferences for the risk assessment scoring system used. The outcome of the two stage hazard analysis and risk assessment process is considered to determine consistency in results of hazard analysis, final decisions regarding the safety of the sample product and to determine any correlation in the decisions made using the model and alternative scoring methods of risk assessment. The research also identifies a number of opportunities for future work, and indicates a number of areas where further work has already begun.

Computer automation of land evaluation procedures

This study was concerned with the computer automation of land evaluation. This is a broad subject with many issues to be resolved, so the study concentrated on three key problems: knowledge based programming; the integration of spatial information from remote sensing and other sources; and the inclusion of socio-economic information into the land evaluation analysis. Land evaluation and land use planning were considered in the context of overseas projects in the developing world. Knowledge based systems were found to provide significant advantages over conventional programming techniques for some aspects of the land evaluation process. Declarative languages, in particular Prolog, were ideally suited to integration of social information which changes with every situation. Rule-based expert system shells were also found to be suitable for this role, including knowledge acquisition at the interview stage. All the expert system shells examined suffered from very limited constraints to problem size, but new products now overcome this. Inductive expert system shells were useful as a guide to knowledge gaps and possible relationships, but the number of examples required was unrealistic for typical land use planning situations. The accuracy of classified satellite imagery was significantly enhanced by integrating spatial information on soil distribution for Thailand data. Estimates of the rice producing area were substantially improved (30% change in area) by the addition of soil information. Image processing work on Mozambique showed that satellite remote sensing was a useful tool in stratifying vegetation cover at provincial level to identify key development areas, but its full utility could not be realised on typical planning projects, without treatment as part of a complete spatial information system.

An approach to the development of expert systems within production planning and control

The thesis presents an account of an attempt to utilize expert systems within the domain of production planning and control. The use of expert systems was proposed due to the problematical nature of a particular function within British Steel Strip Products' Operations Department: the function of Order Allocation, allocating customer orders to a production week and site. Approaches to tackling problems within production planning and control are reviewed, as are the general capabilities of expert systems. The conclusions drawn are that the domain of production planning and control contains both `soft' and `hard' problems, and that while expert systems appear to be a useful technology for this domain, this usefulness has by no means yet been demonstrated. Also, it is argued that the main stream methodology for developing expert systems is unsuited for the domain. A problem-driven approach is developed and used to tackle the Order Allocation function. The resulting system, UAAMS, contained two expert components. One of these, the scheduling procedure was not fully implemented due to inadequate software. The second expert component, the product routing procedure, was untroubled by such difficulties, though it was unusable on its own; thus a second system was developed. This system, MICRO-X10, duplicated the function of X10, a complex database query routine used daily by Order Allocation. A prototype version of MICRO-X10 proved too slow to be useful but allowed implementation and maintenance issues to be analysed. In conclusion, the usefulness of the problem-driven approach to expert systems development within production planning and control is demonstrated but restrictions imposed by current expert system software are highlighted in that the abilities of such software to cope with `hard' scheduling constructs and also the slow processing speeds of such software can restrict the current usefulness of expert systems within production planning and control.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

RELAX:a language to address uncertainty in self-adaptive systems requirement

Self-adaptive systems have the capability to autonomously modify their behavior at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In order to support the rigorous specification of adaptive systems requirements, this paper introduces RELAX, a new requirements language for self-adaptive systems that explicitly addresses uncertainty inherent in adaptive systems. We present the formal semantics for RELAX in terms of fuzzy logic, thus enabling a rigorous treatment of requirements that include uncertainty. RELAX enables developers to identify uncertainty in the requirements, thereby facilitating the design of systems that are, by definition, more flexible and amenable to adaptation in a systematic fashion. We illustrate the use of RELAX on smart home applications, including an adaptive assisted living system.

On the use of software models during software execution

Increasingly software systems are required to survive variations in their execution environment without or with only little human intervention. Such systems are called "eternal software systems". In contrast to the traditional view of development and execution as separate cycles, these modern software systems should not present such a separation. Research in MDE has been primarily concerned with the use of models during the first cycle or development (i.e. during the design, implementation, and deployment) and has shown excellent results. In this paper the author argues that an eternal software system must have a first-class representation of itself available to enable change. These runtime representations (or runtime models) will depend on the kind of dynamic changes that we want to make available during execution or on the kind of analysis we want the system to support. Hence, different models can be conceived. Self-representation inevitably implies the use of reflection. In this paper the author briefly summarizes research that supports the use of runtime models, and points out different issues and research questions. © 2009 IEEE.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Intonation contour realisation for Standard Yorùbá text-to-speech synthesis:a fuzzy computational approach

This paper presents a novel intonation modelling approach and demonstrates its applicability using the Standard Yorùbá language. Our approach is motivated by the theory that abstract and realised forms of intonation and other dimensions of prosody should be modelled within a modular and unified framework. In our model, this framework is implemented using the Relational Tree (R-Tree) technique. The R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. Our R-Tree for an utterance is generated in two steps. First, the abstract structure of the waveform, called the Skeletal Tree (S-Tree), is generated using tone phonological rules for the target language. Second, the numerical values of the perceptually significant peaks and valleys on the S-Tree are computed using a fuzzy logic based model. The resulting points are then joined by applying interpolation techniques. The actual intonation contour is synthesised by Pitch Synchronous Overlap Technique (PSOLA) using the Praat software. We performed both quantitative and qualitative evaluations of our model. The preliminary results suggest that, although the model does not predict the numerical speech data as accurately as contemporary data-driven approaches, it produces synthetic speech with comparable intelligibility and naturalness. Furthermore, our model is easy to implement, interpret and adapt to other tone languages.

Knowledge-based system for casting process selection

Design of casting entails the knowledge of various interacting factors that are unique to casting process, and, quite often, product designers do not have the required foundry-specific knowledge. Casting designers normally have to liaise with casting experts in order to ensure the product designed is castable and the optimum casting method is selected. This two-way communication results in long design lead times, and lack of it can easily lead to incorrect casting design. A computer-based system at the discretion of a design engineer can, however, alleviate this problem and enhance the prospect of casting design for manufacture. This paper proposes a knowledge-based expert system approach to assist casting product designers in selecting the most suitable casting process for specified casting design requirements, during the design phase of product manufacture. A prototype expert system has been developed, based on production rules knowledge representation technique. The proposed system consists of a number of autonomous but interconnected levels, each dealing with a specific group of factors, namely, casting alloy, shape and complexity parameters, accuracy requirements and comparative costs, based on production quantity. The user interface has been so designed to allow the user to have a clear view of how casting design parameters affect the selection of various casting processes at each level; if necessary, the appropriate design changes can be made to facilitate the castability of the product being designed, or to suit the design to a preferred casting method.

Logic Based Pattern Recognition - Ontology Content (2)

Logic based Pattern Recognition extends the well known similarity models, where the distance measure is the base instrument for recognition. Initial part (1) of current publication in iTECH-06 reduces the logic based recognition models to the reduced disjunctive normal forms of partially defined Boolean functions. This step appears as a way to alternative pattern recognition instruments through combining metric and logic hypotheses and features, leading to studies of logic forms, hypotheses, hierarchies of hypotheses and effective algorithmic solutions. Current part (2) provides probabilistic conclusions on effective recognition by logic means in a model environment of binary attributes.

The Fuzzy-Neuro Classifier for Decision Support

This paper aims at development of procedures and algorithms for application of artificial intelligence tools to acquire process and analyze various types of knowledge. The proposed environment integrates techniques of knowledge and decision process modeling such as neural networks and fuzzy logic-based reasoning methods. The problem of an identification of complex processes with the use of neuro-fuzzy systems is solved. The proposed classifier has been successfully applied for building one decision support systems for solving managerial problem.