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To propose a method to manufacture a hybrid rapid tool (a multi component tool).

The part is decomposed into multi component prototype instead of a part made from a single piece. First, this method is based on a topological analysis of the tool. Features are regrouped starting from the numerical definition of the die. Second, the manufacturing possibilities of the high speed milling (HSM), direct metal laser sintering (DMLS) and electro discharge machining (EDM) process are analyzed. Finally this information is synthesized to obtain solutions. This method is validated by industrial example.

A method is proposed to choose the best manufacturing process in order to optimize the manufacture of a “hybrid rapid tooling” between three processes: HSM, DMLS and EDM. So, it is possible to obtain the different components of the hybrid rapid tooling according to the envisaged process.

The final goal is to propose a software assistant used in association with CAD system during the design of hybrid rapid tooling. An important work concerning the features recognition must be implemented. The assembly of the different parts of the hybrid rapid tooling must be considered and optimized.

This method allows the selection of the best process among EDM, HSM and DMLS technologies form manufacturing tools.

The analysis of manufacturing hybrid rapid tooling has not been studied yet.

The purpose of this paper is to propose a method to obtain hybrid rapid tools with elementary component assembly.

The authors' method proposes a functional representational model, starting with the product features, analyzed from three points of view: a feasibility analysis; a manufacturing analysis; and an assembly and synthesis analysis. This method, based on CAD STEP AP‐224 data, makes it possible to obtain an exhaustive list of solutions for the module. The work is illustrated with an industrial example. To construct the Assembly Identity Card (AIC) and test the various parameters that influence the quality of the injected parts, a hybrid injection mold has been produced. The methodology associated with the use of this AIC uses a “representation graph”, which makes it possible to propose a set of valid solutions for assembling the various tooling modules. This method is validated by industrial example.

The product part is decomposed into a multi‐component prototype (MCP), instead of being made as a single part, which optimizes the manufacturing process and enables greater reactivity during the development of the product.

The final goal is to propose a software assistant used in association with CAD system during the design of hybrid rapid tooling. An important work concerning the features recognition must be implemented. The assembly of the different parts of the hybrid rapid tooling must be considered and optimized.

This method allows the selection of the best process technologies from manufacturing tools.

The analysis of manufacturing hybrid rapid tooling has not been studied previously.

The purpose of this paper is to propose a methodology to estimate manufacturing complexity for both machining and layered manufacturing. The goal is to take into account manufacturing constraints at design stage in order to realize tools (dies and molds) by a combination of a subtractive process (high‐speed machining) and an additive process (selective laser sintering).

Manufacturability indexes are defined and calculated from the tool computer‐aided design (CAD) model, according to geometric, material and specification information. The indexes are divided into two categories: global and local. For local indexes, a decomposition of the tool CAD model is used, based on an octree decomposition algorithm and a map of manufacturing complexity is obtained.

The manufacturability indexes values provide a well‐detailed view of which areas of the tool may advantageously be machined or manufactured by an additive process.

Nowadays, layered manufacturing processes are coming to maturity, but there is still no way to compare these new processes with traditional ones (like machining) at the early design stage. In this paper, a new methodology is proposed to combine additive and subtractive processes, for tooling design and manufacturing. A manufacturability analysis is based on an octree decomposition, with calculation of manufacturing complexity indexes from the tool CAD model.

The application of rapid prototyping in fabricating a non‐assembly, multi‐articulated robotic hand with inserts is presented in this paper. The development of robotic systems that have all necessary components inserted, with no assembly required, and ready to function when the manufacturing process is complete is quite attractive. Layered manufacturing, in particular stereolithography, can provide a means to do this. Stereolithography produces a solid plastic prototype via a manufacturing procedure where three‐dimensional solid models are constructed layer upon layer by the fusion of material under computer control. An important aspect of the rapid prototype method used in this research is that multi‐jointed systems can be fabricated in one step, without requiring assembly, while maintaining the desired joint mobility. This document presents the design and techniques for part insertion into a non‐assembly, multi‐articulated, dexterous finger prototype built with stereolithography.

The aim of this paper is to present the main results of a research project finished in 2008 which concerned the selective laser melted (SLM) prototype of a new kind of minimally invasive resurfacing hip arthroplasty (RHA) endoprosthesis with the original multi‐spiked connecting scaffold (MSC‐Scaffold). Previous attempts performed in pre‐Direct Metal Manufacturing (DMM) era demonstrated that it was impossible to manufacture suitable prototypes of this RHA endoprosthesis (especially of the MSC‐Scaffold) using traditional machining technologies. Owing to an extensive development of DMM technologies observed in recent years the manufacturing of such prototypes has become possible.

Computer aided design models of pre‐prototypes and the prototype of the RHA endoprosthesis with MSC‐Scaffold were designed and initially optimized within the claims and the general assumptions of international patents by Rogala. Prototyping in SLM technology was subcontracted to SLM Tech Center (Paderborn, Germany). Macroscopic and SEM microscopic evaluation of the MSC‐Scaffold was performed using SLM manufactured prototypes and paying special attention to the quality and precision of manufacturing.

It was found that SLM can be successfully applied to manufacturing of prototypes of the original minimally invasive RHA endoprosthesis. The manufacturing quality of the 3D spikes system of the MSC‐Scaffold, which mimics the interdigitations of articular subchondral bone, has been proved to be geometrically corresponding to the biological original. Nevertheless, some pores and non‐melted zones were found in SLM prototyped RHA endoprosthesis cross‐sections which need to be eliminated to minimize the potential risk of clinical failure.

The presented case study was performed with a limited number of samples. More research needs to be performed on the rapid prototyped samples including microstructural and mechanical tests. The results may enable the optimization of the SLM manufacturing process of the prototypes of the minimally invasive RHA endoprosthesis with MSC‐Scaffold.

The SLM can be considered as potentially suitable for the fabrication of patient‐fitted minimally invasive RHA endoprostheses with MSC‐Scaffold.

For the first time, largely owing to SLM technology, it was possible to manufacture the prototype of the original minimally invasive RHA endoprosthesis with MSC‐Scaffold suitable for further research.

Three-dimensional printing (3DP) is an established process to print structural parts of metals, ceramic and polymers. Further, multi-material 3DP has the potentials to be a milestone in rapid manufacturing (RM), customized design and structural applications. Being compatible as functionally graded materials in a single structural form, multi-material-based 3D printed parts can be applied in structural applications to get the benefit of modified properties.

The fused deposition modelling (FDM) is one of the established low cost 3DP techniques which can be used for printing functional/ non-functional prototypes in civil engineering applications.

The present study is focused on multi-material printing of primary recycled acrylonitrile butadiene styrene (ABS), polylactic acid (PLA) and high impact polystyrene (HIPS) in composite form. Thermal (glass transition temperature and heat capacity) and mechanical properties (break load, break strength, break elongation, percentage elongation at break and Young’s modulus) have been analysed to observe the behaviour of multi-material composites prepared by 3DP. This study also highlights the process parameters optimization of FDM supported with photomicrographs.

The present study is focused on multi-material printing of primary recycled ABS, PLA and HIPS in composite form.

The purpose of this paper is to design and validate an electronic nose (E-nose) prototype using commercially available metal oxide gas sensors (MOX). This prototype has a sensor array board that integrates eight different MOX gas sensors to handle multi-purpose applications. The number of sensors can be adapted to match different requirements and classification cases. The paper presents the validation of this E-nose prototype when used to identify three gas samples, namely, alcohol, butane and cigarette smoke. At the same time, it discusses the discriminative abilities of the prototype for the identification of alcohol, acetone and a mixture of them. In this respect, the selection of the appropriate type and number of gas sensors, as well as obtaining excellent discriminative abilities with a miniaturized design and minimal computation time, are all drivers for such implementation.

The suggested prototype contains two main parts: hardware (low-cost components) and software (Machine Learning). An interconnection printed circuit board, a Raspberry Pi and a sensor chamber with the sensor array board make up the first part. Eight sensors were put to the test to see how effective and feasible they were for the classification task at hand, and then the bare minimum of sensors was chosen. The second part consists of machine learning algorithms designed to ensure data acquisition and processing. These algorithms include feature extraction, dimensionality reduction and classification. To perform the classification task, two features taken from the sensors’ transient response were used.

Results reveal that the system presents high discriminative ability. The K-nearest neighbor (KNN) and support vector machine radial basis function based (SVM-RBF) classifiers both achieved 97.81% and 98.44% mean accuracy, respectively. These results were obtained after data dimensionality reduction using linear discriminant analysis, which is more effective in terms of discrimination power than principal component analysis. A repeated stratified K-cross validation was used to train and test five different machine learning classifiers. The classifiers were each tested on sets of data to determine their accuracy. The SVM-RBF model had high, stable and consistent accuracy over many repeats and different data splits. The total execution time for detection and identification is about 10 s.

Using information extracted from transient response of the sensors, the system proved to be able to accurately classify the gas types only in three out of the eight MQ-X gas sensors. The training and validation results of the SVM-RBF classifier show a good bias-variance trade-off. This proves that the two transient features are sufficiently efficient for this classification purpose. Moreover, all data processing tasks are performed by the Raspberry Pi, which shows real-time data processing with miniaturized architecture and low prices.

Industry 4.0 emerged as the Fourth Industrial Revolution aiming at achieving higher levels of operational efficiency, productivity and automation. In this context, manual assembly systems are still characterized by high flexibility and low productivity, if compared to fully automated systems. Therefore, the purpose of this paper is to propose the design, engineering and testing of a prototypal adaptive automation assembly system, including greater levels of automation to complement the skills and capabilities of human workers.

A lab experimental field-test is presented comparing the assembly process of a full-scale industrial chiller with traditional and adaptive assembly system.

The analysis shows relevant benefits coming from the adoption of the adaptive automation assembly system. In particular, the main findings highlight improvements in the assembly cycle time and productivity, as well as reduction of the operator’s body movements.

The prototype is applied in an Italian mid-size industrial company, confirming its impact in terms of upgrades of the assembly system flexibility and productivity. Thus, the research study proposed in this paper provides valuable knowledge to support companies and industrial practitioners in the shift from traditional to advanced assembly systems matching current industrial and market features.

This paper expands the lacking research on adaptive automation assembly systems design proposing an innovative prototype able to real-time reconfigure its structure according to the product to work, e.g. work cycle, and the operator features.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

Mashups have been studied extensively in the literature; nevertheless, the large body of work in this area focuses on service/data level integration and leaves UI level integration, hence UI mashups, almost unexplored. The latter generates digital environments in which participating sources exist as individual entities; member applications and data sources share the same graphical space particularly in the form of widgets. However, the true integration can only be realized through enabling widgets to be responsive to the events happening in each other. The authors call such an integration “widget orchestration” and the resulting application “mashup by orchestration”. This article aims to explore and address challenges regarding the realization of widget‐based UI mashups and UI level integration, prominently in terms of widget orchestration, and to assess their suitability for building web‐based personal environments.

The authors provide a holistic view on mashups and a theoretical grounding for widget‐based personal environments. The authors identify the following challenges: widget interoperability, end‐user data mobility as a basis for manual widget orchestration, user behavior mining – for extracting behavioral patterns – as a basis for automated widget orchestration, and infrastructure. The authors introduce functional widget interfaces for application interoperability, exploit semantic web technologies for data interoperability, and realize end‐user data mobility on top of this interoperability framework. The authors employ semantically enhanced workflow/process mining techniques, along with Petri nets as a formal ground, for user behavior mining. The authors outline a reference platform and architecture that is compliant with the authors' strategies, and extend W3C widget specification respectively – prominently with a communication channel – to foster standardization. The authors evaluate their solution approaches regarding interoperability and infrastructure through a qualitative comparison with respect to existing literature, and provide a computational evaluation of the behavior mining approach. The authors realize a prototype for a widget‐based personal learning environment for foreign language learning to demonstrate the feasibility of their solution strategies. The prototype is also used as a basis for the end‐user assessment of widget‐based personal environments and widget orchestration.

The evaluation results suggest that the interoperability framework, platform, and architecture have certain advantages over existing approaches, and the proposed behavior mining techniques are adequate for the extraction of behavioral patterns. User assessments show that widget‐based UI mashups with orchestration (i.e. mashups by orchestration) are promising for the creation of personal environments as well as for an enhanced user experience.

This article provides an extensive exploration of mashups by orchestration and their role in the creation of personal environments. Key challenges are described, along with novel solution strategies to meet them.