Metal-free syn-dioxygenation of alkenes

Reactions employing inexpensive reagents from sustainable sources and with low toxicity are becoming increasingly desirable from an academic and industrial perspective. A fascinating example of a synthetic transformation that requires development of alternative procedures is the osmium catalysed dihydroxylation. Recently there has been considerable interest in achieving this reaction through metal-free procedures. This review describes the methods available for metal-free syn-dioxygenation of alkenes

Industrial Megaprojects: Concepts, strategies and practices for success

This is a review of a recent book on Megaprojects written by an experienced practitioner and researcher of megaprojects who has been writing about them over the last three decades. It focuses on industrial megaprojects covering mainly megaprojects in the Oil & Gas Production, Petroleum Processing and Refining, Minerals and Metals, Chemical, LNG, Power Generation and Pipelines. The book is written mainly from the perspective of project owners but contains some good advice to project managers as well.

Methodological advances in the analysis, assessment and intervention of industrial landscapes

We are currently witnessing a gradual extension of the concept of heritage. This idea has evolved to encompass landscapes and is even reaching into an area which, until recently, had not received sufficient attention: industrial heritage. This new notion of what constitutes heritage is particularly interesting from a cultural perspective, with the appearance of the term “cultural landscape” which covers landscapes produced by industrial decay, among other things. This extended concept of heritage, which is gradually growing both quantitatively and qualitatively, has not only added extra complexity to the limits of what is considered heritage, but is also bringing an evolution in the methodological parameters used for analysis, protection and action, from a 19th-Century modern scientific perspective towards a more epistemological, ideological, political, cultural and technical approach. The object of this paper is to study and analyze the theoretical principles and developments made at international level in relation to environmental research, from the second half of the 20th century to the present day. More specifically, we will focus on the methodologies which seek to overcome the obsolescent tools and methods used in landscape analysis. For this purpose, we will pay particular attention to the methodologies that go beyond considering landscapes as mere visual phenomena, to treat them as an intimate and complex relationship between people and a place. The British methodology Landscape Character Assessment will have a special place in this study. However, this interest in LCA does not mean that we will be ignoring other major methodological contributions. This method review will ultimately enable us to define the basic supporting pillars for the development of a specific methodology to be used in the analysis and intervention of industrial landscapes produced by industrial decay.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

How to Do Machine Learning with Small Data? -- A Review from an Industrial Perspective

Artificial intelligence experienced a technological breakthrough in science, industry, and everyday life in the recent few decades. The advancements can be credited to the ever-increasing availability and miniaturization of computational resources that resulted in exponential data growth. However, because of the insufficient amount of data in some cases, employing machine learning in solving complex tasks is not straightforward or even possible. As a result, machine learning with small data experiences rising importance in data science and application in several fields. The authors focus on interpreting the general term of "small data" and their engineering and industrial application role. They give a brief overview of the most important industrial applications of machine learning and small data. Small data is defined in terms of various characteristics compared to big data, and a machine learning formalism was introduced. Five critical challenges of machine learning with small data in industrial applications are presented: unlabeled data, imbalanced data, missing data, insufficient data, and rare events. Based on those definitions, an overview of the considerations in domain representation and data acquisition is given along with a taxonomy of machine learning approaches in the context of small data

Black phosphorus: narrow gap, wide applications

The recent isolation of atomically thin black phosphorus by mechanical exfoliation of bulk layered crystals has triggered an unprecedented interest, even higher than that raised by the first works on graphene and other two-dimensional, in the nanoscience and nanotechnology community. In this Perspective we critically analyze the reasons behind the surge of experimental and theoretical works on this novel two-dimensional material. We believe that the fact that black phosphorus band gap value spans over a wide range of the electromagnetic spectrum that was not covered by any other two-dimensional material isolated to date (with remarkable industrial interest such as thermal imaging, thermoelectrics, fiber optics communication, photovoltaics, etc), its high carrier mobility, its ambipolar field-effect and its rather unusual in-plane anisotropy drew the attention of the scientific community towards this two-dimensional material. Here we also review the current advances, the future directions and the challenges in this young research field.Comment: Updated version of the perspective article about black phosphorus, including all the feedback received from arXiv users + reviewer

Designer as integrator: reality or rhetoric?

This research was developed from Bohemia’s doctoral study: Lean Manufacturing and its impact on the role of Industrial Designers in Australia (University of New South Wales, Sydney, 2002). The broader research aim was to investigate the impact of lean manufacturing on the role of the industrial designer in Australian manufacturing organisations. Thomas Walton, a former editor of the Design Management Review stated that: ‘Leadership is significant, especially as design becomes a more prominent component of management. It is perhaps for this reason that Borja de Mozota and her colleagues chose to include an analysis by Erik Bohemia that probes ‘the emergence of design as a source of new product ideas and as a potential partner for managing a product development group’, Professor Cooper, editorial chair for The Design Journal, summed up the significance of Bohemia’s research in this area, by stating ‘This study found that, contrary to existing thought, manufacturers reported that designers are not perceived as playing integrative roles. Lean manufacturers view designers as providing competitive advantage in areas such as perceived product value, increased market share and reduced product cost, more when they are employed rather than acting as consultants to an organisation. This is counter to current theory, especially in the US and UK, where most research indicates that designers add intangible value through their interactive and interpretive skills’. Additional research findings related to the research have been presented at several international conferences: Bohemia, E., ‘The difference between in-house and contracted industrial designers: an Australian perspective’, the Futureground, Melbourne, November 2004. Bohemia, E., ‘Designer as integrator’, and ‘Performance of Industrial Designers’, (two papers) at the 11th International Forum on Design Management Research & Education, Massachusetts, USA, June 2002

Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective

Data-driven decision making is becoming an integral part of manufacturing companies. Data is collected and commonly used to improve efficiency and produce high quality items for the customers. IoT-based and other forms of object tracking are an emerging tool for collecting movement data of objects/entities (e.g. human workers, moving vehicles, trolleys etc.) over space and time. Movement data can provide valuable insights like process bottlenecks, resource utilization, effective working time etc. that can be used for decision making and improving efficiency. Turning movement data into valuable information for industrial management and decision making requires analysis methods. We refer to this process as movement analytics. The purpose of this document is to review the current state of work for movement analytics both in manufacturing and more broadly. We survey relevant work from both a theoretical perspective and an application perspective. From the theoretical perspective, we put an emphasis on useful methods from two research areas: machine learning, and logic-based knowledge representation. We also review their combinations in view of movement analytics, and we discuss promising areas for future development and application. Furthermore, we touch on constraint optimization. From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries. We also describe currently available commercial off-the-shelf products for tracking in manufacturing, and we overview main concepts of digital twins and their applications

The EPICS Software Framework Moves from Controls to Physics

The Experimental Physics and Industrial Control System (EPICS), is an open-source software framework for high-performance distributed control, and is at the heart of many of the world’s large accelerators and telescopes. Recently, EPICS has undergone a major revision, with the aim of better computing supporting for the next generation of machines and analytical tools. Many new data types, such as matrices, tables, images, and statistical descriptions, plus users’ own data types, now supplement the simple scalar and waveform types of the former EPICS. New computational architectures for scientific computing have been added for high-performance data processing services and pipelining. Python and Java bindings have enabled powerful new user interfaces. The result has been that controls are now being integrated with modelling and simulation, machine learning, enterprise databases, and experiment DAQs. We introduce this new EPICS (version 7) from the perspective of accelerator physics and review early adoption cases in accelerators around the world