Search results

Fused filament fabrication (FFF) is a common additive manufacturing method that is widely used owing to its low cost, environmental friendliness and safety. Colour models are needed because of their ability to express more information, but high printing quality and efficiency are difficult to achieve with the existing FFF colour printing methods because of the “inertia” of printing. Inertia refers to the feature of the former colour material remaining in the molten cavity when switching colours in colour FFF printing. The purpose of this paper is to propose a new FFF colour printing method to reduce printing material usage and printing time.

A new FFF colour printing method that uses transitioning waste to construct the part is proposed. Based on the freedom of the colour surface model’s interior space, the internal fill and support of the print model are generated using the transitioning waste to reduce printing material usage and printing time and to achieve environmentally friendly colour printing. The modified elite ant system (EAS) algorithm is used to construct and optimize this method based on the colour surface model.

A colour printing experiment is performed using a colour-mixing FFF printer platform with a special waste extrusion module. The experimental results show that this method can significantly reduce material and time consumption compared to the commonly used method. The printed part produced by this method also has high surface quality.

A new FFF colour printing method that uses transitioning waste to construct the part is proposed. Based on the freedom of the colour surface model’s interior space, the internal fill and support of the print model are generated using the transitioning waste to reduce printing material usage and printing time and to achieve environmentally friendly colour printing. The modified EAS algorithm is used to construct and optimize this method based on the colour surface model. A special waste extrusion module is developed.

Today, Jacquard woven fabric producers are able to digitally control each warp yarn individually, pre-program the variable pick density and speed for each filling yarn, and automatically change a pattern without stopping the weaving process. Jacquard CAD systems dramatically reduce the time to produce fabric from the artwork or target design The process of weave/color selection for each area of the pattern is, however, still highly dependent on the CAD system operator who works from a particular color gamut. Multiple weaving trials are required to get a sample that matches the original artwork since the process requires the designer‘s subjective evaluation. The lack of automatic selection of weaves/color matching prompts this research.

This paper addresses the development of a geometric model for predicting the color contribution of each warp and filling yarn on the fabric surface in terms of construction parameters. The combination of geometric modeling and existing color mixing equations enables the prediction of the final color of different areas of a Jacquard pattern. The model was verified experimentally and a close agreement was found between a color mixing equation and the experimental measurements.

ETL format is a newly proposed CAD format, which is both simple enough that CAD models in this format can be easily sliced, and capable of describing solids with arbitrarily complex surface details. This paper aims to provide a method for slicing CAD models in ETL format.

The proposed slicing method is based on a method for slicing CAD models in colour STL format. Affine mapping method is used to calculate the colour of the intersection polygon of a voxel in the slicing result volume dataset, and a triangular facet that constitutes the geometry of the described object, when the facet has texture mapping definition.

The proposed slicing method is simple and robust. Implementations have demonstrated its feasibility.

The proposed slicing method is meaningful to preparing data for the rapid formation of models with complex surface details, including colour and textures.

The objective of this paper is two‐fold: to share information about color and to solicit information about sound, with the ultimate goal of producing a simple formula for generating a cybernetic mixed reality environment; and to serve as a vehicle for inviting conversation at the “Cybernetics: Art, Design and Mathematics 2010” Conference.

The majority of research in color focuses on the perceptual, experiential, phenomenon. Conceptual color is a perceptual and non‐experiential. It is color observed as a thought. By engaging in study, from this methodological approach, color can be modeled as a simple computational system of inter‐related abstract elements. This makes the complexity of the perceptual environment understandable and translatable to abstract data, but also makes the transition from the abstract back to actual possible.

The conceptual model approach has yielded a number of features for future study, not least of which is color, as a true mathematical system. This is very different from a simple color‐coding system.

With more development, the new system may prove to be of significance to future digital design applications. Given that music is also a spatial pattern system, revisiting the age‐old belief that there must be a correlation between color and music may now be productive.

This paper presents a puzzle with thought‐provoking questions, designed to solicit the information needed, in order to determine if a spatial correlation between color and sound is identifiable.

The purpose of this study was to develop and apply new physical heart defect models (PHDMs) that are patient-specific and color-coded with an optimized map.

Heart defect anatomies were segmented from medical images and reconstructed to form virtual models, which were then color-coded and rapid prototyped. The resulting PHDMs were used in a medical educational study to evaluate their pedagogical efficacy and in clinical case studies to investigate their utility in surgical planning.

A growing library of 36 PHDMs (including the most common defects) was generated. Results from the educational study showed that the PHDMs enabled uniquely effective learning, and the clinical case studies indicated that the models added value as surgical planning aids.

The education study involved a limited number of students, so future work should consider a larger sample size. The clinical case studies favored use of the PHDMs in surgical planning, but provided only qualitative support.

Workflow optimization is critical for PHDMs to be used effectively in surgical planning because some operations must be performed in emergently.

Because PHDMs have potential to influence surgeons’ actions as surgical planning aids, their use in that context must be thoroughly vetted.

The proposed models represent the first PHDMs that are patient-specific and fully color-coded with a standardized map optimized for the human visual system. The models enhanced medical education and facilitated effective surgical planning in this study.

The colors of change is an overview of change paradigms, created about two decades ago, that has been intensively used, tested, refined, shared, and elaborated by practitioners and academics alike. Here, the “color theory” is presented as it is now, and is situated within the literature. Its four main applications are described as well as rules of thumb that have been derived from reflective practice. This chapter illustrates that the color theory is clearly not one thing to all people, as it is understood in very different ways, both in terms of its theoretical foundations as well as the complexity of its applications. This probably adds to the versatility of the theory. Bringing together key insights about the color theory for academics and practitioners, this chapter strives both to give a concise overview and to explore its richness.

Here the authors investigate the effects of a visual color cue (brown color) on saltiness expectations, emotional responses and purchase intention of commercial soy sauce products.

The study enrolled 100 participates, and three sauce colors (light brown, medium brown and dark brown) were used as treatments in this experimental design research. The data analysis was done by a structural equation modeling (SEM) approach with repeated measures.

The findings indicated that, for the medium and dark brown sauces, the final model revealed a positive effect of sauce color intensity on saltiness expectation, a positive impact of saltiness expectation on emotion and a positive impact of emotion on purchase intention with statistically indifferent factor loadings. Hence, both the medium and dark brown colors soy sauces were the preferred choices for consumers. However, for the light brown color, the test result was unsatisfactory.

Several empirical studies have identified visual cues as useful for sodium reduction. However, from a marketing perspective, a causal relationship between the color intensity and a customer's purchase intention has not been explored in soy sauce products using an experimental design concept and SEM.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.

This paper aims to present a method of color three-dimensional (3D) printing based on color adherence.

First, experiments of the color effects of 3D printings using different carriers and different printing methods were performed. Second, the color of a specific point could be calculated through a theory of dimension-reducing, and the color distribution of 3D model was transformed from 3D to 1D color line corresponding with 3D print sequence. At last, the color lines, which were printed on a PE film by silk-screen printing, was carried by a filament and then printed through a fused deposition modeling 3D printer.

The printing ink and PE film are suitable as the pigment and carrier under this investigation, respectively. Based on an idea of reducing dimension, the method of 3D color printing through adhering color to a filament is realized. The color saturation of the sample was relatively high through the method.

It is hard to avoid that there may be some residual color in the nozzle through this method, and the purity of following color will be affected. As a result, continuous improvements should be made to perfect the method.

An approach of 3D color printing is described in detail, and what kind of model is more applicable is discussed particularly.

This approach is implemented to print color 3D objects with just one nozzle by means of color adherence. That is, printing the 3D objects using the filament is carried out with 1D color line, which is printed by a traditional printing method.

The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs.

The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size.

Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system.

The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered.

The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies.

The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.