Prediction of problems in injection moulded plastic products with computer aided mould design software : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Technology in Manufacturing and Industrial Technology at Massey University

Several new technologies to assist plastic injection moulding companies have been developed in the last twenty years. A number of computer software programs are now available which could revolutionise mould design. The most exciting aspect of the Computer Aided Mould Design (CAMD) software is the effect it has on reducing the lead time required to produce a working mould from a product concept. The application of the new technology for designing moulds, however, has been slow in New Zealand. One of the main reasons for the slow progress is the perceived value of the software or consulting services. Many injection moulding companies who design and manufacture moulds do not realise the great potential of CAMD software to save many hours of mould changes and volume of polymer material, even when the program is used after the mould has been made. However, the true benefits are only seen when the mould is designed using CAMD before the mould has been manufactured. Moulds manufactured correctly the first time save a great deal of time, energy and money. The value of the software is not completely understood by injection moulding manufacturers. They perceive the immediate benefits, however, the ongoing benefits are not recognised. A project was carried out to demonstrate the potential of CAMD software in determining moulding problems in existing injection moulded products. Four products, two of which were supplied by an injection moulding company, that had moulding problems, were simulated using Moldflow, a CAMD software package. The results of the simulation were compared with the actual moulding problems. It was found that the Moldflow simulation results described the problems occurring in the moulds accurately. Moulding problems included warpage, air traps and weld lines in poor positions and flow marks. Warpage is a major problem in injection moulded products. Even simple products can warp if not designed correctly. The only problems Moldflow did not identify, and does not claim to, were the flow marks caused by jetting and splashing of plastic as it entered the cavity. The designer must be aware of the problems caused by jetting and design gates to avoid it. Moldflow, and other CAMD software, are beneficial tools for the mould designer. The advantages of CAMD include short mould development time, shorter lead times from concept to production, reduction in the amount of material used, fewer changes to machine settings and predictable, repeatable quality. These benefits are not only savings in the mould design and manufacture, they also continue on into the processing of the product since less material is used in the product and machine down time caused by moulding problems is greatly reduced

On The Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems

It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour’s recommendations

The Danger Theory and Its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems

'On the Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems'

It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour's recommendations

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques

A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques

An Artificial Immune System Based Recommender

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques. Notes: Uwe Aickelin, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, U