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Application of sensor data based predictive maintenance and artificial neural networks to enable Industry 4.0
Get PDFPossessing an efficient production line relies heavily on the availability of the production equipment. Thus, to ensure that the required function for critical equipment is in compliance, and unplanned downtime is minimized, succeeding with the field of maintenance is essential for industrialists. With the emergence of advanced manufacturing processes, incorporating predictive maintenance capabilities is seen as a necessity. Another field of interest is how modern value chains can support the maintenance function in a company. Accessibility to data from processes, equipment and products have increased significantly with the introduction of sensors and Industry 4.0 technologies. However, how to gather and utilize these data for enabling improved decision making within maintenance and value chain is still a challenge. Thus, the aim of this paper is to investigate on how maintenance and value chain data can collectively be used to improve value chain performance through prediction. The research approach includes both theoretical testing and industrial testing. The paper presents a novel concept for a predictive maintenance platform, and an artificial neural network (ANN) model with sensor data input. Further, a case of a company that has chosen to apply the platform, with the implications and determinants of this decision, is also provided. Results show that the platform can be used as an entry-level solution to enable Industry 4.0 and sensor data based predictive maintenance
The Premier League: breaking the cycle of gang violence
No full textIn this chapter, The Premier League: Breaking the Cycle of Gang Violence, Christine Barter, Paul Hargreaves, Kelly Bracewell and John Pitts report on the findings of the BBC Children in Need and the Premier League Charitable Fund programme Breaking the Cycle of Youth Violence. The programme, was based on eight Premier League football clubs in England (Arsenal, Burnley, Crystal Palace, Everton, Newcastle United, Southampton, Stoke City and Tottenham Hotspur). It aimed to reduce youth violence in the communities in which Premier League football clubs operated. Each of the eight participating clubs had Club Community Organisations funded through the BCYV programme that undertook work with young people in their catchment area. This chapter is based on those elements of the programme which investigated the clubs responses to gang-involved young people in their area
Production control method and DEMO study of mass personalization production in Industry 4.0
No full textWith the development of information technology, it is more and more convenient to obtain personalized customer demand information. After obtaining personalized demand information, how to transform the customer's personalized demand information into the products to meet the customer needs becomes the difficulty of manufacturing industry. Aiming at this production difficulty, this paper carries out research on the control method of personalized product assembly in workshop equipment layer. A personalized product assembly control model was proposed, which can assemble different products according to different order information to meet the needs of different customers. In the assembly control model, in order to solve the problem that the same assembly task needs to trigger the robot action many times, the concept of false assembly location is proposed. Finally, Personalized product assembly line based on industry 4.0 was developed in the Robot Laboratory of Shanghai Polytechnic University, and the effectiveness of the proposed assembly control method was verified
Critical discourse analysis
No full textCritical Discourse Analysis is a text-focused approach to the study of social institutions which examines language as a power distribution mechanism. How do people use language as a means of influencing their audience? With case studies and examples, this chapter will equip students to understand the relationship between language, discourse and social practices
Supporting young women affected by gang association and county lines
No full textIn this chapter, Supporting Young Women Affected by Gang Association and County Lines, Fiona Factor & Abi Billinghurst outline the political and practice context of supporting young women affected by gang association and County Lines drug dealing. It presents the model of practice developed by Abianda, a social enterprise in London working with young women. The authors consider the key practice challenges faced by Abianda when delivering gender specific services, and how the learning gleaned from their combined experience in research and professional practice, could be helpful to policy makers and practitioners working with girls and young women
“So what if ChatGPT wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
Get PDFTransformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts
A knowledge empowered explainable gene ontology fingerprint approach to improve gene functional explication and prediction.
Get PDFFunctional explication of genes is of great scientific value. However, conventional methods have challenges for those genes thatmay affect biological processes but are not annotated in public databases. Here, we developed a novel explainable gene ontology fingerprint (XGOF) method to automatically produce knowledge networks on biomedical literature in a given field which quantitatively characterizes the association between genes and ontologies. XGOF provides systematic knowledge for the potential function of genes and ontologically compares similarities and discrepancies in different disease-XGOFs integrating omics data. More importantly, XGOF can not only help to infer major cellular components in a disease microenvironment but also reveal novel gene panels or functions for in-depth experimental research where few explicit connections to diseases have previously been described in the literature. The reliability of XGOF is validated in four application scenarios, indicating a unique perspective of integrating text and data mining, with the potential to accelerate scientific discovery
Can travel advisors influence physical activity in personal travel planning projects using the theory of planned behaviour? A longitudinal study
Get PDFThe objective was to examine the effect of travel advisors (TAs) used in personal travel planning interventions (PTP) on physical activity (PA) in an urban, ethnically diverse residential settings. The study assessed the utility of the Theory of Planned Behaviour (TPB) to predict both intention and PA associated with “TAs”. A quasi-experimental longitudinal study was conducted with two groups to examine changes in physical activity levels. The methods involved a survey targeted at residents in a PTP targeted area who spoke to a TA (intervention group) and residents who did not (control group). Participants in the intervention group (n = 147) and control group (n = 95) self-reported their PA levels and constructs of the TPB at three time points. The results show that residents who had spoken to a TA reported significantly higher levels of physical activity at each of the three time points. ANOVA”s revealed significant interaction effects for the TPB constructs. The overall conclusion was that those who had spoken to a TA reported more PA at each of the three time points
Do research incentives promote researchers’ mental health?
Get PDFResearchers have a higher risk of anxiety and depression than the general population, so it is important to promote researchers’ mental health. Method: Based on the data from 3210 global researchers surveyed by the journal Nature in 2021, confirmatory factor analysis, OLS regression and other regressions were used to explore the research incentive dimensions and their effects on researchers’ mental health. Results: (1) Material incentive factors, work-family life balance factors, good organizational environment and spiritual motivation had significant positive effects on researchers’ mental health. (2) The spiritual motivation could better promote researchers’ mental health than the other factors. (3) Heterogeneity analysis showed that material incentive factors and spiritual motivation created more significant stimulating effects on the mental health of humanities and social sciences researchers. Work-family life balance factors were more effective in promoting the mental health of the mid-career group and the overtime group. Conclusion: Application of the four research incentives resulted in lower likelihood of anxiety or depression among researchers, and special attention should be paid to the role of the spiritual motivation. In order to promote researchers’ mental health, different incentives should be applied to different researcher groups to better improve researchers’ mental health
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