Decision Performance and Safety Performance: A Value-Focused Thinking Study in the Oil Industry

Considerable research has been performed to develop leading indicators of safety performance. We use value-focused thinking to understand the objectives and evaluation measures that frame a particular safety-related decision within an organization. These decisions are part of the safety culture. Our research partners were two oil shipping companies; we surveyed crewmembers on their tankers to evaluate performance in each decision objective on their vessel. We demonstrate that measurements of the achievement of these objectives are related to future safety performance and thus provide leading indicators of safety

KNOWLEDGE ACQUISITION METHODOLOGIES: SURVEY AND EMPIRICAL ASSESSMENT

Knowledge acquisition, the process of extracting information from human experts, is one of the challenges in building expert systems. Modern practitioners and researchers need more guidance than is provided by existing knowledge acquisition guidelines. However, there has been little empirical research upon which to base the needed guidelines. This paper surveys the available knowledge acquisition techniques and describes a knowledge acquisition experiment which contrasts three of these methods. A framework was developed to categorize the types of heuristic which can be elicited with different means of knowledge acquisition. This research represents the initial steps in a research program focused on the development of empirically evaluated, generalized guidelines for effecting .knowledge acquisition

Impact of a Distributed Intelligent System in a Large Scale Safety Critical System

Safety critical large scale systems are complex, physically extensive socio-technical systems, extending over a range of domains, and are of interest because of the enormous catastrophic potential on their constituents, bystanders and the environment. Often, failures in such systems are traced to human error, as well as to unforeseen and unanticipated combinations of causal factors arising from the size, scope and complexity of the systems. Technologies developed to support these systems are often distributed, supporting subsystems with specific local requirements

Assessment of Intelligence Complexity in Embedded Intelligent Real Time Systems

Intelligent systems and their applications are proliferating. Embedded Intelligent Real-Time Systems (EIRTS) are one type of intelligent system. Defining and measuring the complexity of this kind of system may help with better design, development, maintenance, and performance of EIRTS. In this paper, we propose a set of evaluation criteria to measure the complexity of Embedded Intelligent Real-Time Systems (EIRTS). We show an operationalization of the criteria with a sample EIRTS