Development and testing of a combined machine and process health monitoring system

Process monitoring has been shown to be capable of observing the quality of a machining operation through sensor signals and analysis in both the literature and in commercially available systems. Some of these systems provide an additional benefit of monitoring the health of a machine tool. However, the commercially available systems tend to utilise relatively simple analysis techniques for both the process and machine health, limiting their application and robustness. Industrial interest in systems that can profit from the current advances in machine tool digitalisation and data analytics has grown considerably. This is especially true for the capability of early-detection of quality issues in components, whilst also ensuring machine tools are in a condition that can achieve high quality production. The present research includes the development and testing of a fingerprint routine which can be run at regular intervals to detect potential failure modes or machine tool degradation through signal analysis. Machining trials were carried out with the objective of detecting known defects in a workpiece through signal analysis. For both cases, a combined monitoring system was developed for data capture during testing, and a number of failure modes and defects were physically simulated to test the possibility of detection in the acquired signals. Time domain, frequency domain, and time-frequency domain signal processing techniques were applied to the sensor data with various levels of success. Continuous wavelet transforms (CWT) were of particular interest, as they successfully captured signal changes between tests for the physically simulated failure modes of the machine tool and the component. Therefore, a comparative CWT analysis was developed which successfully emphasised some of the machine tool failure modes and part defects when compared to baseline signals. The output of the comparative analysis may be well-suited to automation through machine learning techniques

The application of machine learning to sensor signals for machine tool and process health assessment

Due to the latest advancements in monitoring technologies, interest in the possibility of early-detection of quality issues in components has grown considerably in the manufacturing industry. However, implementation of such techniques has been limited outside of the research environment due to the more demanding scenarios posed by production environments. This paper proposes a method of assessing the health of a machining process and the machine tool itself by applying a range of machine learning (ML) techniques to sensor data. The aim of this work is not to provide complete diagnosis of a condition, but to provide a rapid indication that the machine tool or process has changed beyond acceptable limits; making for a more realistic solution for production environments. Prior research by the authors found good visibility of simulated failure modes in a number of machining operations and machine tool fingerprint routines, through the defined sensor suite. The current research set out to utilise this system, and streamline the test procedure to obtain a large dataset to test ML techniques upon. Various supervised and unsupervised ML techniques were implemented using a range of features extracted from the raw sensor signals, principal component analysis and continuous wavelet transform. The latter were classified using convolutional neural networks (CNN); both custom-made networks, and pre-trained networks through transfer learning. The detection and classification accuracies of the simulated failure modes across all classical ML and CNN techniques tested were promising, with all approaching 100% under certain conditions

Review of Engaging Education: Developing Emotional Literacy, Equity and Co-education. Brian Matthews. (Book Review)

The book is only about a fraction of its title Engaging Education. His section on ‘engaging the emotions’ sums this up: whereas the book is largely about engaging the emotions positively, the definition of ‘Engaging’ is more far reaching: “that pupils should be involved in their learning; be active and absorbed and not just passive recipients of a set curriculum. Additionally, they should feel engaged in the processes of education and have some input into creating their own agendas for learning” (p.2). Exploring the full impact of this statement across the curriculum really needs a different book

Holocene LSA archaeology from Equus Cave, Buxton-Norlim Limeworks, South Africa : an analysis of the bone tool assemblage

Abstract: Equus Cave, Buxton-Norlim Limeworks, near Taung, North West Province, South Africa, was first excavated between 1978 and 1982. While the site dates to the terminal Pleistocene and Holocene the precise age of the different layers is debated, as is the technological assignment of the deepest deposits, which are said to contain both Later or Middle Stone Age elements. While the faunal assemblage and some of the human remains have been published, the archaeology has never been fully analysed or reported. New excavations in 2012 revealed numerous artefacts including ochre, something not previously noted for this site. Comparison of total lithic artefact counts versus faunal NISPs and MNIs shows that the height of human occupation occurred during the Holocene, with preliminary analysis of the >6000 lithic assemblage indicating a dominance of notched artefacts, which, coupled with the presence of 16 bone points, is characteristic of other HoloceneWilton (Later Stone Age) sites in the region. The focus of this paper is the 16 bone points, which include projectile points and link-shafts, and how these items were manufactured and used. The results provide one of the first detailed descriptions of Later Stone Age bone tools, including rare specimens that are mostly complete or still preserve the tips, making an important contribution to our limited understanding of Later Stone Age bone tool technology

Virtuality in human supervisory control: Assessing the effects of psychological and social remoteness

Virtuality would seem to offer certain advantages for human supervisory control. First, it could provide a physical analogue of the 'real world' environment. Second, it does not require control room engineers to be in the same place as each other. In order to investigate these issues, a low-fidelity simulation of an energy distribution network was developed. The main aims of the research were to assess some of the psychological concerns associated with virtual environments. First, it may result in the social isolation of the people, and it may have dramatic effects upon the nature of the work. Second, a direct physical correspondence with the 'real world' may not best support human supervisory control activities. Experimental teams were asked to control an energy distribution network. Measures of team performance, group identity and core job characteristics were taken. In general terms, the results showed that teams working in the same location performed better than team who were remote from one another

Does lateral lift-off occur in static and dynamic activity in a medially spherical total knee arthroplasty? A pulsed-fluoroscopic investigation.

Objectives: The medially spherical GMK Sphere (Medacta International AG, Castel San Pietro, Switzerland) total knee arthroplasty (TKA) was previously shown to accommodate lateral rollback while pivoting around a stable medial compartment, aiming to replicate native knee kinematics in which some coronal laxity, especially laterally, is also present. We assess coronal plane kinematics of the GMK Sphere and explore the occurrence and pattern of articular separation during static and dynamic activities. Methods: Using pulsed fluoroscopy and image matching, the coronal kinematics and articular surface separation of 16 well-functioning TKAs were studied during weight-bearing and non-weight-bearing, static, and dynamic activities. The closest distances between the modelled articular surfaces were examined with respect to knee position, and proportions of joint poses exhibiting separation were computed. Results: Overall, 1717 joint poses were analyzed. At a 1.0 mm detection threshold, 37 instances of surface separation were observed in the lateral compartment and four medially (p < 0.001). Separation was activity-dependent, both laterally and medially (p < 0.001), occurring more commonly during static deep flexion in the lateral compartment, and during static rotation in the medial compartment. Lateral separation occurred more frequently than medial during kneeling (7/14 lateral vs 1/14 medial; p = 0.031) and stepping (20/1022 lateral vs 0/1022 medial; p < 0.001). Separation varied significantly between individuals during dynamic activities. Conclusion: No consistent association between closest distances of the articular surfaces and knee position was found during any activity. Lift-off was infrequent and depended on the activity performed and the individual knee. Lateral separation was consistent with the design rationale. Medial lift-off was rare and mostly in non-weight-bearing activities.Cite this article: S. Key, G. Scott, J.G. Stammers, M. A. R. Freeman†, V. Pinskerova, R. E. Field, J. Skinner, S. A. Banks. Does lateral lift-off occur in static and dynamic activity in a medially spherical total knee arthroplasty? A pulsed-fluoroscopic investigation. Bone Joint Res 2019;8:207-215. DOI: 10.1302/2046-3758.85.BJR-2018-0237.R1

Structure of the PII signal transduction protein of Neisseria meningitidis at 1.85 Å resolution

The structure of the PII signal transduction protein of N. meningitidis at 1.85 Å resolution is described

Understanding Schools and Schooling. (Book Review)

A review of a book written by Clive Chitty (2002 with a useful focus on issues of equity and social justice, including prejudice, discrimination and bullying in secondary schools. Education policy makers need to explore the extent to which it is important to produce interested, motivated and socially balanced young adults. It is well researched and documented

The structure of NMB1585, a MarR-family regulator from Neisseria meningitidis

The structure of the MarR-family regulator NMB1585 from N. meningitidis has been solved using data extending to 2.1 Å resolution