Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

TEXTILE TECHNOLOGIES IN CONCRETE ENVIRONMENTS."

Girli Concrete is a cross disciplinary funded research project based in the University of Ulster involving a textile designer/ researcher, an architect/ academic and a concrete manufacturing firm.
Girli Concrete brings together concrete and textile technologies, testing ideas of
concrete as textile and textile as structure. It challenges the perception of textiles as only the ‘dressing’ to structure and instead integrates textile technologies into the products of building products. Girli Concrete uses ‘low tech’ methods of wet and dry concrete casting in combination with ‘high tech’ textile methods using laser cutting, etching, flocking and digital printing. Whilst we have been inspired by recent print and imprint techniques in architectural cladding, Girli Concrete is generated within the depth of the concrete’s cement paste “skin”, bringing the trades and crafts of both industries together with innovative results.
Architecture and Textiles have an odd, somewhat unresolved relationship. Confined to a subservient role in architecture, textiles exist chiefly within the categories of soft furnishings and interior design. Girli Concrete aims to mainstream tactility in the production of built environment products, raising the human and environmental interface to the same specification level as the technical. This paper will chart:
The background and wider theoretical concerns to the project.
The development of Girli Concrete, highlighting the areas where craft becomes
art and art becomes science in the combination of textile and concrete
technologies.
The challenges of identifying funding to support such combination technologies,
working methods and philosophies.
The challenges of generating and sustaining practice within an academic
research environment
The outcomes to date

The Development of an Immersive Virtual Reality Environment for Manufacturing and Improving Organizational Learning

This paper examines the applicability of an immersive virtual reality (VR) system to the process of organizational learning in a manufacturing context. The work focuses on the extent to which realism has to be represented in a simulated product build scenario in order to give the user an effective learning experience for an assembly task. Current technologies allow the visualization and manipulation of objects in VR systems but physical behaviors such as contact between objects and the effects of gravity are not commonly represented in off the shelf simulation solutions and the computational power required to facilitate these functions remains a challenge. This work demonstrates how physical behaviors can be coded and represented through the development of more effective mechanisms for the computer aided design (CAD) and VR interface.

Prediction of integral type failures in semiconductor manufacturing through classification methods

Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Suitability, efficiency and microbiological safety of novel physical technologies for the processing of ready-to-eat meals, meats and pumpable products

Consumer studies and market reports show an increase in consumption of ready-to-eat (RTE) foods. Although conventional processing technologies can in most cases produce safe products, they can also lead to the degradation of nutritional compounds and negatively affect quality characteristics. Consumers strongly prefer food that is minimally processed with the maximum amount of health-promoting substances. Novel processing technologies as pre- or post-treatment decontamination methods or as substitutes of conventional technologies have the potential to produce foods that are safe, rich in nutrient content and with superior organoleptic properties. Combining novel with conventional processes can eliminate potential drawbacks of novel technologies. This review examines available scientific information and critically evaluates the suitability and efficiency of various novel thermal and nonthermal technologies in terms of microbial safety, quality as well as nutrient content on the production of RTE meals, meats and pumpable products.

Manufacturing System Simulation & Human Robot Interaction in VR:Manufacturing system simulation: Methodologies, software tools, case study in transportation design

Virtual Reality techniques are relatively new, having experienced significant development only during the last few years, in accordance with the progress achieved by computer science and hardware and software technologies. The study of such advanced design systems has led to the realization of an immersive environment in which new procedures for the evaluation of product prototypes, ergonomics and manufacturing operations have been simulated. The application of the environment realized to robotics, ergonomics, plant simulations and maintainability verifications has allowed us to highlight the advantages offered by a design methodology: the possibility of working on the industrial product in the first phase of conception; of placing the designer in front of the virtual reproduction of the product in a realistic way; and of interacting with the same concept. The aim of this book is to present an updated vision of VM through different aspects. We will describe the trends and results achieved in the automotive, aerospace and railway fields, in terms of the Digital Product Creation Process to design the product and the manufacturing process.