Paradigms for knowledge-based systems in industrial engineering

When developing expert systems, expertise lies not only in formulating the knowledge to be put into the knowledge base, but also in deciding upon the knowledge representation and inference mechanism most suited to the application. Six detailed knowledge bases demonstrate the application of various AI-based systems to industrial engineering problems. They illustrate a number of approaches: expert systems, which are based upon practical experience; decision systems, which derive from modelling skills; and situation-action systems, which rely on production process design skills. The six paradigms presented describe a logical expert system for selecting material handling equipment; a multi-valued expert system for selecting a dispatching rule for automatic guided vehicles; a profile matching expert system for selecting project management software; a confidence building expert system for selecting a machine feeder; a tandem decision system for developing a production schedule; and a situation-action system for controlling job allocation in a flexible manufacturing cell. The relationships between these various paradigms and the characteristics of problems to which they can be applied are categorized by the nature of the expert and his expertise; the features of the environment; the decision or decisions to be taken; and the manner in which AI-system performance can be evaluated. A knowledge base is proposed for determining which architecture is most appropriate for a given application.     

A tandem architecture for cooperating knowledge-based concurrent engineering systems

This paper proposes a tandem architecture for cooperating heterogeneous expert systems. Two levels of meta and working expert systems are involved. The working-level expert systems (W-ES), which may be implemented in their own computational environments and in private proof languages, are mainly for application computations. The meta-level expert systems (M-ES), using a common argument language, are mainly responsible for cooperation. The prototype AGENTS system is described for constructing M-ES. Interaction among W-ES has been transformed into two forms: communication between M-ES through ordinary AGENTS messages and communication between M-ES and the corresponding W-ES using the Deductive Inference Language (DIL). DIL predicates are provided for defining DIL: messages, actuators and converters for interpreting DIL queries and instantiating variables. By this approach, stand-alone capability of infividual systems is retained at the working-level and cooperation is achieved effectively with minimum embellishment at the meta-level.     

Formalizing an engineering approach to cooperating knowledge-based systems

A theoretical grounding is provided for a cooperating knowledge-based systems (CKBS) model which is based upon agents, cooperation blocks, and cooperation block hierarchies. Our model describes the requirements for task decomposition, negotiation, cooperation and coordination, fault tolerance, and recoverability, these requirements in turn defining a holonic system. The behavioral properties of our model are described using state transition diagrams and properties of correctness and termination are proven.     

ECDEX: A knowledge-based approach to conceptual design of engineering systems

This paper describes a knowledge-based approach to the domain independent conceptual design phase. We describe the development of “ECDEX”, the “Engineering Conceptual Design Expert” that generates concept variants (concept alternatives) during the conceptual design phase of engineering systems. ECDEX was developed using an expert system shell called CLIPS (C Language Integrated Production System) and a C-program interface to aid the quantitative phase of concept evaluation. ECDEX internally develops function structures that are dependent on the number of solution principles for each sub-function selected during the process. After the function structures are developed, ECDEX searches for solution principles for each of the sub-functions considering that every combination needs to begin with the system input and end with the system output. After all combinations are developed, ECDEX performs the concept evaluation using evaluation criteria defined by the designer providing a set of ‘concept variants’. ECDEX is applied to three test cases; an impulse loading test rig, a hydro-electric generation plant and a fishing reel. The results from these three test cases demonstrate that ECDEX generates satisfactory conceptual designs of engineering systems.     

Critics for knowledge-based design systems

Expert critics have been built to critique human performance in various areas such as engineering design, decision making, etc. We suggest that critics can also be useful in the building and use of knowledge based design systems (KBDSs). Knowledge engineers elicit knowledge from domain experts and build a knowledge based design system. The system generates designs. The amount of knowledge the system possesses and the way it applies the knowledge directly influence the performance of its designs. Therefore, critics are proposed to assist in: acquiring sufficient knowledge for constructing a desirable system; and applying proper knowledge to generating designs. Methodologies of equipping a KBDS with critics are developed. Our practice in building and using a KBDS shows the applicability and capability of these critics     

A knowledge-based system for postgraduate engineering courses

This paper describes a novel approach to the development and implementation of an educational tool based on knowledge-based technology employing an expert system shell. Software has been developed which, after providing basic background information, proceeds to analyse the student's learning pattern to establish which next question, explanation, or topic to propound in order to aid the learning process and ensure that fundamental knowledge is gained by the student at his/her own pace. While the system described has been designed and implemented specifically to supplement, rather than supplant, the taught part of an MSc. course in Manufacturing Systems Engineering and Management, the methodology formulated can be used to develop similar knowledge-based systems for other technical as well as non-technical subjects at both undergraduate and postgraduate levels in Higher Education.     

Rule-based consistency enforcement for knowledge-based systems

A rule-based approach for the automatic enforcement of consistency constraints is presented. In contrast to existing approaches that compile consistency checks into application programs, the approach centralizes consistency enforcement in a separate module called a knowledge-base management system. Exception handlers for constraint violations are represented as rule entities in the knowledge base. For this purpose, a new form of production rule called the activation pattern controlled rule is introduced: in contrast to classical forward chaining schemes, activation pattern controlled rules are triggered by the intent to apply a specific operation but not necessarily by the result of applying this operation. Techniques for implementing this approach are discussed, and experiments in speeding up the system performance are described. Furthermore, an argument is made for more tolerant consistency enforcement strategies, and how they can be integrated into the rule-based approach to consistency enforcement is discussed     

Constructing knowledge-based systems

Vital, a four-and-a-half-year ESPRIT II research and development project that involves nine organizations in five countries is discussed. It addresses the problems of effective process modeling for knowledge-based systems, providing guidelines on when to use various knowledge-engineering methods and techniques, and reducing the bottleneck in acquiring expert knowledge by providing both methodological and software support for developing large, industrial, knowledge-based system applications. The project goals, approach, and workbench are outlined, and a case study is described     

Prototyping strategies for multisensory product experience engineering

The paper deals with prototyping strategies aimed at supporting engineers in the design of the multisensory experience of products. It is widely recognised that the most effective strategy to design it is to create working prototypes and analyse user’s reactions when interacting with them. Starting from this consciousness, we will discuss of how virtual reality (VR) technologies can support engineers to build prototypes suitable to this aim. Furthermore we will demonstrate how VR-based prototypes do not only represent a valid alternative to physical prototypes, but also a step forward thanks to the possibility of simulating and rendering multisensory and real-time modifiable interactions between the user and the prototype. These characteristics of VR-based prototypes enable engineers to rapidly test with users different variants and to optimise the multisensory experience perceived by them during the interaction. The discussion is supported both by examples available in literature and by case studies we have developed over the years on this topic. Specifically, in our research we have concentrated on what happens in the physical contact between the user and the product. Such contact strongly influences the user’s impression about the product.     

Design of knowledge-based systems with a knowledge-based assistant

The authors propose a model for an intelligent assistant to aid in building knowledge-based systems (KBSs) and discuss a preliminary implementation. The assistant participates in KBS construction, including acquisition of an initial model of a problem domain, acquisition of control and task-specific inference knowledge, testing and validation, and long-term maintenance of encoded knowledge. The authors present a hypothetical scenario in which the assistant and a KBS designer cooperate to create an initial domain model and then discuss five categories of knowledge the assistant requires to offer such help. They discuss two software technologies on which the assistant is based: an object-oriented programming language, and a user-interface framework     

Rethinking competence systems for knowledge-based organizations

Existing competence systems are based on a rationalistic view of competence. While these competence systems might work in job-based organizations, we argue that in more dynamic settings, such as in knowledge-based organizations, the interest-informed actions that capture the emergent competencies of tomorrow require different types of information technology support. The main objective of this paper is to elaborate on the possibilities and implications of using interest-activated technology as a design rationale for competence systems. This paper is based on an action case study of an implemented interest-activated Intranet recommender system prototype at Volvo Information Technology AB in Gothenburg, Sweden. On the basis of how organizational members used this prototype to find information they were interested in, our research team was able to inquire into how personal interest, embodied in information-seeking activities, could be a means for identifying competence. Building on the relation between personal interest and competence, we discuss competence systems design and spell out explicit implications for managerial practice in knowledge-based organizations.     

Critical success factors for knowledge-based software engineering applications

A key problem in KBSE is evaluating the prospective utility of proposed KBSA tools. This paper analyzes the utility of ten KBSA prototype applications that were developed as part of an advanced course. Based on such an analysis, we hypothesize three new critical success factors for explaining their utility. The factors identify key elements of KBSA tools that serve as indicators of their likely utility.     

Structural design language for coupled knowledge-based systems

A Structal Design Language (SDL) has been developed in INTERLISP environment for building coupled knowledge-based expert systems for integrated design of a class of structures. The integrated design includes the preliminary design, structural analysis, design of members, design of connections, and computer-aided drafting of the final design. The complex body of knowledge needed for detailed design of a structure is fractionated into smaller and more manageable knowledge sources which are organized into a hierarchy of cooperating conceptual specialists. SDL provides a multiwindow graphics interface capable of displaying both the orthographic and isometric views of the frame structure and beam-column connections. A three-dimensional face frame representation sentation is used for the graphic display of the beam-column connections. SDL has been used to develop a prototype knowledge-based system for integrated design of steel building structures consisting of moment-resisting frames.     

A knowledge-based approach for multi-factory production systems

This paper investigates scheduling of jobs with deadlines across a serial multi-factory supply chain which involves minimizing sum of total tardiness and total transportation costs. Jobs can be transported among factories and can be delivered to the customer in batches which have limited capacity. The aim of this optimization problem is threefold: (1) determining the number of batches, (2) assigning jobs to batches, and (3) scheduling the batches production and delivery in each factory. The proposed problem formulated as a mixed-integer linear program. Then the model's performance is analyzed and evaluated through two examples. Moreover, a knowledge-based imperialistic competitive algorithm (KBICA) is also presented to find an approximate optimum solution for the problem. Computational experiments of the proposed problem investigate the efficiency of the method through different sizes of the test problems.     

A formal model for knowledge-based systems verification

A logico-algebraic model for verification of Knowledge Based Systems, based on Abraham Robinson's meta-algebra, is presented in this article. the set of rules of Knowledge Based System is considered to be the set of axioms of a theory “T”. the model consists of: (i) the collection “P” of all well formed formulas of the language of T, (ii) a subset P₀ of P that has as its elements the axioms of a given logic (bivalued, intuitionistic, or other), plus all the theorems that can be deduced from this logic inside the language of T, (iii) some distinguished subsets of P, to be called m-ideals and m-filters, that depend on T and P₀. Important concepts that are involved in the verification of Knowledge Based Systems are considered, such as forward and backward reasoning consistencies. Appropriate characterizations are obtained by using properties of m-ideals and m-filters. © 1994 John Wiley & Sons, Inc.     

A knowledge-based experimental design system for nucleic acid engineering

Presented in this paper is a knowledge-based experimental design system that incorporates the domain expertise used in nucleic acid engineering, thus automating the processing of error-prone, laborious low-level work, and many decision-making steps, and guiding the biologist toward a workable plan. This allows the biologist to work at a higher abstraction level, concentrating on more fundamental, difficult and challenging problems directly related to protein structure - function relationships. Cassette-based site-directed mutagenesis and synthetic gene designs are used as examples to illustrate the utility of the knowledge-based system approach to experimental design.     

A knowledge-based system for performing reverse engineering of relational databases

A knowledge-based system, called the Knowledge Extraction System (KES), is presented which performs the process of reverse engineering of relational databases. KES generates an extended entity-relationship (EER) model from a relational database. Within its extraction procedure, domain semantics are obtained by analyzing the data schema and data instances of an existing database, by using heuristics, or asking the user. Relations and attributes are classified into several categories and then converted into the corresponding modelling structures of the EER model. KES demonstrates how knowledge-based system technology can be applied to ease the work of database reverse engineering. It also illustrates that the reverse engineering process can be implemented at a high level of automation. To do so, KES is integrated with the target database management system so that data can be analyzed directly through dynamic SQL queries.     

A model of explanation for financial knowledge-based systems

In this paper we describe a method for explanation generation in financial knowledge-based systems. The underlying financial model consists of a mixture of quantitative and qualitative relations. The method described can be embedded in a theory of scientific explanation. In a case-study we compare textbook analyses with the output of a program which implements our theory of explanation.