An Intelligent System for Structural Analysis-Based Design Improvements

The goal of the research work presented in this paper was to collect, organize, and write the knowledge and experience about structural analysis-based design improvements into a knowledge base for a consultative advisory intelligent decision support system. The prototype of the system presented proposes possible design changes that should be taken into consideration to improve the design candidate according to the results of a prior stress-strain or thermal analysis. The system can be applied either in the design of new products or as an educational tool.

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.

ERGONOMIC DESIGN RECOMMENDATIONS BASED ON AN ACTUAL CHAINSAW DESIGN

<p>ENGLISH ABSTRACT: To develop high quality products, a designer has to consider various influential factors, one of which is ergonomics. And to fashion a specific product for the user, a designer needs expert knowledge of the user’s requirements. However, expert knowledge can also be accessed through an intelligent advisory system for ergonomic design support. The effectiveness of such an expert system depends mainly on the quality of the knowledge base and on the appropriateness of the system's inference engine. Data for the system’s knowledge base can be collected in different ways. One approach is to study relevant projects to collect appropriate ergonomic solutions; another is to recognise bottlenecks in ergonomic design. This paper presents a case study of the design of an actual chainsaw – with emphasis on ergonomic design solutions – that can be transformed into ergonomic design recommendations. At the end of the paper, an application of one of the derived recommendations within the knowledge base of the intelligent advisory system is presented.</p><p>AFRIKAANSE OPSOMMING: By die ontwerp van gehaltegoedere moet aandag gegee word aan verskeie faktore soos die Ergonomie. Die produkontwerper moet deeglike kennis dra van die verbruikersbehoeftes. Daarbenewens moet hy liefs ook gebruik maak van ’n intelligente sisteem vir ontwerphulp. Die navorsing is toegespits op datasteun vir ’n kettingsaagontwerp en toon hoe die intelligente sisteem betekenisvolle ondersteuning verleen.</p&gt

An Intelligent System for Structural Analysis-Based Design Improvements

The goal of the research work presented in this paper was to collect, organize, and write the knowledge and experience about structural analysis-based design improvements into a knowledge base for a consultative advisory intelligent decision support system. The prototype of the system presented proposes possible design changes that should be taken into consideration to improve the design candidate according to the results of a prior stress-strain or thermal analysis. The system can be applied either in the design of new products or as an educational tool.

Cosine Similarity-Based Pruning for Concept Discovery

In this work we focus on improving the time efficiency of Inductive Logic Programming (ILP)-based concept discovery systems. Such systems have scalability issues mainly due to the evaluation of large search spaces. Evaluation of the search space cosists translating candidate concept descriptor into SQL queries, which involve a number of equijoins on several tables, and running them against the dataset. We aim to improve time efficiency of such systems by reducing the number of queries executed on a DBMS. To this aim, we utilize cosine similarity to measure the similarity of arguments that go through equijoins and prune those with 0 similarity. The proposed method is implemented as an extension to an existing ILP-based concept discovery system called Tabular Cris w-EF and experimental results show that the poposed method reduces the number of queries executed around 15 %