Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

American Society for Testing and Materials

One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet. Cyber-physical production systems (CPPS), relying on the latest, and the foreseeable further developments of computer science, information and communication technologies on one hand, and of manufacturing science and technology, on the other, may lead to the 4th industrial revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots in general – and in particular to the CIRP community – which point towards CPPS. Expectations towards research in and implementation of CPS and CPPS are outlined and some case studies are introduced. Related new R&D challenges are highlighted.

Cyber-physical systems in manufacturing

https://escholarship.org/content/qt4h56k1ch/qt4h56k1ch.pdf

Advanced monitoring of machining operations

Deep learning for smart manufacturing: Methods and applications

Selective Laser Melting (SLM) is an additive manufacturing (AM) technique which has been heavily investigated for the processing of Ti-6Al-4V (Ti64) which is used in the biomedical, aerospace and other industries. To date the SLM processing of this material has been inhibited by the requirement of post processes due to three primary challenges of martensitic microstructures, undesired porosity and residual stresses which are present in the as-built state. This work identifies the state of the art in process optimisation which is being used to confront these challenges in the as-built state with a view to removing the reliance on post processing. Regarding process optimisation, maximising part density is the primary goal due to the negative influence of pores on fracture and fatigue properties. To accomplish this, a high energy input is required which results in high cooling rates during processing. It is these cooling rates which are instrumental in the microstructural evolution and residual stress production. Accordingly novel methods have been proposed which aim to maintain the necessary high level of energy input but control the cooling rates to tailor the microstructure and reduce residual stresses. Research gaps have been identified pertaining to all three of these challenges when considering mechanical properties of as-built components. Thus in its current state post processes remain critical, however promising techniques in early stage development provide encouragement going forward.

Garret E. O’Donnell

Papers

Advanced monitoring of machining operations

Optimisation of process parameters to address fundamental challenges during selective laser melting of Ti-6Al-4V: A review

Industrial power and energy metering – a state-of-the-art review

Force generation during friction stir welding of AA2024-T3

Characterisation of tool shape and rotational speed for increased speed during friction stir welding of AA2024-T3