Intelligent Support for a Computer Aided Design Optimisation Cycle

It is becoming more and more evident that  adding intelligence  to existing computer aids, such as computer aided design systems, can lead to significant improvements in the effective and reliable performance of various engineering tasks, including design optimisation. This paper presents three different intelligent modules to be applied within a computer aided design optimisation cycle to enable more intelligent and less experience-dependent design performance.

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications

Framework Programmable Platform for the Advanced Software Development Workstation (FPP/ASDW). Demonstration framework document. Volume 1: Concepts and activity descriptions

The Framework Programmable Software Development Platform (FPP) is a project aimed at effectively combining tool and data integration mechanisms with a model of the software development process to provide an intelligent integrated software development environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The Advanced Software Development Workstation (ASDW) program is conducting research into development of advanced technologies for Computer Aided Software Engineering (CASE)

The Definition of Intelligent Computer Aided Software Engineering (I-CASE) Tools

The growing complexity of the software systems being developed and the use of different methodologies indicate the need for more computer support for automating software development process and evolution activity. Currently, Computer-Aided Software Engineering (CASE), which is a set of software systems aimed to support set of software process activities, does this automation. While CASE tools prove its importance to develop high quality software, unfortunately CASE tools doesn’t cover all software development activities. This is because some activities need intellectual human skills, which are not currently available as computer software. To solve this shortcoming, Artificial Intelligence (AI) approaches are the ones that can be used to develop software tools imitating these intellectual skills. This paper presents the definition of Intelligent Computer Aided Software Engineering (I-CASE). The definition encompasses two steps. The first step is a clear decomposition of each basic software development activity to sub activities, and classify each one of them whether it is an intellectual or procedural job. The second step is the addressing of each intellectual (un-automated) one to proper AI-based approach. These tools may be integrated into a package as an Integrated Development Environment (IDE) or could be used individually. The discussion and the next implementation step are reported. Keywords: Software Engineering, CASE tools, Artificial Intelligenc

Genuine lab experiences for students in resource constrained environments: The RealLab with integrated intelligent assessment.

Laboratory activities are indispensable for developing engineering skills. Computer Aided Learning (CAL) tools can be used to enhance laboratory learning in various ways, the latest approach being the virtual laboratory technique that emulates traditional laboratory processes. This new approach makes it possible to give students complete and genuine laboratory experiences in situations constrained by limited resources in the provision of laboratory facilities and infrastructure and/or where there is need for laboratory education, for large classes, with only one laboratory stand. This may especially be the case in countries in transition. Most existing virtual laboratories are not available for purchase. Where they are, they may not be cost friendly for resource constrained environments. Also, most do not integrate any form of assessment structure. In this paper, we present a very cost friendly virtual laboratory solution for genuine laboratory experiences in resource constrained environments, with integrated intelligent assessment

An investigation into artificial intelligence based generative computer process planning

The process planning function can be further optimized with the introduction of an intelligent software package such as an Artificial Intelligence based Generative Computer Process Planning System. An AI based CAPP system, also categorized as an expert system, provides the vital link between design and manufacture, a bridge of knowledge in the information chain of manufacturing engineering. With the increasing role of computers in the process planning function, planning has become easier, faster, and more efficient. This thesis provides an explanation of the process planning function and how artificial intelligence will improve it. Topics in AI techniques and procedures, knowledge engineering, Computer Aided Design, and Group Technology (GT) are discussed. Utilizing the topics presented, a complete interactive software system is presented to illustrate the flexibility of an AI based CAPP system

Software life cycle methodologies and environments

Products of this project will significantly improve the quality and productivity of Space Station Freedom Program software processes by: improving software reliability and safety; and broadening the range of problems that can be solved with computational solutions. Projects brings in Computer Aided Software Engineering (CASE) technology for: Environments such as Engineering Script Language/Parts Composition System (ESL/PCS) application generator, Intelligent User Interface for cost avoidance in setting up operational computer runs, Framework programmable platform for defining process and software development work flow control, Process for bringing CASE technology into an organization's culture, and CLIPS/CLIPS Ada language for developing expert systems; and methodologies such as Method for developing fault tolerant, distributed systems and a method for developing systems for common sense reasoning and for solving expert systems problems when only approximate truths are known

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested