Machining feature-based system for supporting step-compliant milling process

STEP standards aims at setting up a standard description method for product data and providing a neutral exchanging mechanism that is independent of all the information processing systems for product information model. STEP Part 21 is the first implementation method from EXPRESS language and implemented successfully in CAD data. However, this text file consists of purely geometrical and topological data is hardly to be applied in machining process planning which requires machining features enriched data. The aim of this research is developing a new methodology to translate the EXPRESS language model of CAD STEP data into a new product data representation and enriched in machining features which is more beneficial to machining process planning. In this research, a target Database Management System (DBMS) was proposed for developing this system by using its fourth-generation tools that allow rapid development of applications through the provision of nonprocedural query language, reports generators, form generators, graphics generators, and application generators. The use of fourth-generation tools can improve productivity significantly and produce program that are easier to maintain. From this research, a new product data representation in a compact new table format is generated. Then this new product data representation has gone through a series of data enrichment process, such as normal face direction generation, edge convexity/concavity determination and machining features with transition feature recognition. Lastly, this new enriched product data representation is verified by generating to a new STEP standard data format which is according to ISO1030-224 standard format and providing an important part of solution for supporting STEP-compliant process planning and applications in milling process

Intelligent Association Exploration and Exploitation of Fuzzy Agents in Ambient Intelligent Environments

This paper presents a novel fuzzy-based intelligent architecture that aims to find relevant and important associations between embedded-agent based services that form Ambient Intelligent Environments (AIEs). The embedded agents are used in two ways; first they monitor the inhabitants of the AIE, learning their behaviours in an online, non-intrusive and life-long fashion with the aim of pre-emptively setting the environment to the users preferred state. Secondly, they evaluate the relevance and significance of the associations to various services with the aim of eliminating redundant associations in order to minimize the agent computational latency within the AIE. The embedded agents employ fuzzy-logic due to its robustness to the uncertainties, noise and imprecision encountered in AIEs. We describe unique real world experiments that were conducted in the Essex intelligent Dormitory (iDorm) to evaluate and validate the significance of the proposed architecture and methods

Integration via Meaning: Using the Semantic Web to deliver Web Services

Presented at the CRIS2002 Conference in Kassel.-- 9 pages.-- Contains: Conference paper (PDF) + PPT presentation.The major developments of the World Wide Web (WWW) in the last two years have been Web Services and the Semantic Web. The former allows the construction of distributed systems across the WWW by providing a lightweight middleware architecture. The latter provides an infrastructure for accessing resources on the WWW via their relationships with respect to conceptual descriptions. In this paper, I shall review the progress undertaken in each of these two areas. Further, I shall argue that in order for the aims of both the Semantic Web and the Web Services activities to be successful, then the Web Service architecture needs to be augmented by concepts and tools of the Semantic Web. This infrastructure will allow resource discovery, brokering and access to be enabled in a standardised, integrated and interoperable manner. Finally, I survey the CLRC Information Technology R&D programme to show how it is contributing to the development of this future infrastructure

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

MACS: Multi-agent COTR system for Defense Contracting

The field of intelligent multi-agent systems has expanded rapidly in the recent past. Multi-agent architectures and systems are being investigated and continue to develop. To date, little has been accomplished in applying multi-agent systems to the defense acquisition domain. This paper describes the design, development, and related considerations of a multi-agent system in the area of procurement and contracting for the defense acquisition community