A tool-supported approach to inter-tabular verification.

The use of decision tables to verify KBS has been advocated several times in the V&V literature. However, one of the main drawbacks of those system is that they fail to detect anomalies which occur over rule chains. In a decision table based context this means that anomalies which occur due to interactions between tables are neglected. These anomalies are called inter-tabular anomalies. In this paper we investigate an approach that deals with inter-tabular anomalies. One of the prerequisites for the approach was that it could be used by the knowledge engineer during the development of the KBS. This requires that the anomaly check can be performed on-line. As a result, the approach partly uses heuristics where exhaustive checks would be too inefficient. All detection facilities that will be described, have been implemented in a table-based development tool called PROLOGA. The use of this tool will be briefly illustrated. In addition, some experiences in verifying large knowledge bases are discussed.

Unpacking Ambiguity in Building Requirements to Support Automated Compliance Checking

In the architecture, engineering, and construction (AEC) industry, manual compliance checking is labor-intensive, time-consuming, expensive, and error-prone. Automated compliance checking (ACC) has been extensively studied in the past 50 years to improve the productivity and accuracy of the compliance checking process. While numerous ACC systems have been proposed, these systems can only deal with requirements that include quantitative metrics or specified properties. This leaves the remaining 53% of building requirements to be checked manually, mainly due to the ambiguity embedded in them. In the literature, little is known about the ambiguity of building requirements, which impedes their accurate interpretation and automated checking. This research thus aims to address this issue and establish a taxonomy of ambiguity. Building requirements in health building notes (HBNs) are analyzed using an inductive approach. The results show that some ambiguous clauses in building requirements reflect regulators’ intention while others are unintentional, resulting from the use of language, tacit knowledge, and ACC-specific reasons. This research is valuable for compliance-checking researchers and practitioners because it unpacks ambiguity in building requirements, laying a solid foundation for addressing ambiguity appropriately

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

A novel qualitative prospective methodology to assess human error during accident sequences

Numerous theoretical models and techniques to assess human error were developed since the 60's. Most of these models were developed for the nuclear, military, and aviation sectors. These methods have the following weaknesses that limit their use in industry: the lack of analysis of underlying causal cognitive mechanisms, need of retrospective data for implementation, strong dependence on expert judgment, focus on a particular type of error, and/or analysis of operator behaviour and decision-making without considering the role of the system in such decisions. The purpose of the present research is to develop a qualitative prospective methodology that does not depend exclusively on retrospective information, that does not require expert judgment for implementation and that allows predicting potential sequences of accidents before they occur. It has been proposed for new (or existent) small and medium- scale facilities, whose processes are simple. To the best of our knowledge, a methodology that meets these requirements has not been reported in literature thus far. The methodology proposed in this study was applied to the methanol storage area of a biodiesel facility. It could predict potential sequences of accidents, through the analysis of information provided by different system devices and the study of the possible deviations of operators in decision-making. It also enabled the identification of the shortcomings in the human-machine interface and proposed an optimization of the current configuration.Fil: Calvo Olivares, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Rivera, Selva Soledad. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Núñez Mc Leod, Jorge Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentin

A branch and bound algorithm to optimize the representation of tabular decision processe.

Decision situations have various aspects: knowledge acquisition and structuring, knowledge representation, knowledge validation and decision making. It has been recognized in literature that decision tables can play an important role in each of these stages. It is however not necessary to use only one representation formalism during the whole life cycle of an intelligent system. Likewise it is possible that different formats of the same formalism serve different purposes in the development process.Important in this respect is the search for automated and, if possible, optimized transitions between different formats of a formalism and between various formalisms. In this paper a branch and bound algorithm is presented that transforms expanded decision tables, that, because of their explicit enumeration of all decision cases primarily serve an acquisition and verification function, into optimized contracted decision tables, primarily used as target representation of a decision process. An optimal contracted decision table is a contracted decision table with a condition order which results in the minimum number of contracted decision columns.

Uncertainty analysis in product service system: Bayesian network modelling for availability contract

There is an emerging trend of manufacturing companies offering combined products and services to customers as integrated solutions. Availability contracts are an apt instance of such offerings, where product use is guaranteed to customer and is enforced by incentive-penalty schemes. Uncertainties in such an industry setting, where all stakeholders are striving to achieve their respective performance goals and at the same time collaborating intensively, is increased. Understanding through-life uncertainties and their impact on cost is critical to ensure sustainability and profitability of the industries offering such solutions. In an effort to address this challenge, the aim of this research study is to provide an approach for the analysis of uncertainties in Product Service System (PSS) delivered in business-to-business application by specifying a procedure to identify, characterise and model uncertainties with an emphasis to provide decision support and prioritisation of key uncertainties affecting the performance outcomes. The thesis presents a literature review in research areas which are at the interface of topics such as uncertainty, PSS and availability contracts. From this seven requirements that are vital to enhance the understanding and quantification of uncertainties in Product Service System are drawn. These requirements are synthesised into a conceptual uncertainty framework. The framework prescribes four elements, which include identifying a set of uncertainties, discerning the relationships between uncertainties, tools and techniques to treat uncertainties and finally, results that could ease uncertainty management and analysis efforts. The conceptual uncertainty framework was applied to an industry case study in availability contracts, where each of the four elements was realised. This application phase of the research included the identification of uncertainties in PSS, development of a multi-layer uncertainty classification, deriving the structure of Bayesian Network and finally, evaluation and validation of the Bayesian Network. The findings suggest that understanding uncertainties from a system perspective is essential to capture the network aspect of PSS. This network comprises of several stakeholders, where there is increased flux of information and material flows and this could be effectively represented using Bayesian Networks