108,388 research outputs found
Continuous maintenance and the future – Foundations and technological challenges
High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security
Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor
The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities
Using gaming paratexts in the literacy classroom
This paper illustrates how digital game paratexts may effectively be used in the high school English to meet a variety of traditional and multimodal literacy outcomes. Paratexts are texts that refer to digital gaming and game cultures, and using them in the classroom enables practitioners to focus on and valorise the considerable literacies and skills that young people develop and deploy in their engagement with digital gaming and game cultures. The effectiveness of valorizing paratexts in this manner is demonstrated through two examples of assessment by students in classes where teachers had designed curriculum and assessment activities using paratexts
Innovation Initiatives in Large Software Companies: A Systematic Mapping Study
To keep the competitive advantage and adapt to changes in the market and
technology, companies need to innovate in an organised, purposeful and
systematic manner. However, due to their size and complexity, large companies
tend to focus on maintaining their business, which can potentially lower their
agility to innovate. This study aims to provide an overview of the current
research on innovation initiatives and to identify the challenges of
implementing the initiatives in the context of large software companies. The
investigation was performed using a systematic mapping approach of published
literature on corporate innovation and entrepreneurship. Then it was
complemented with interviews with four experts with rich industry experience.
Our study results suggest that, there is a lack of high quality empirical
studies on innovation initiative in the context of large software companies. A
total of 7 studies are conducted in such context, which reported 5 types of
initiatives: intrapreneurship, bootlegging, internal venture, spin-off and
crowdsourcing. Our study offers three contributions. First, this paper
represents the map of existing literature on innovation initiatives inside
large companies. The second contribution is to provide an innovation initiative
tree. The third contribution is to identify key challenges faced by each
initiative in large software companies. At the strategic and tactical levels,
there is no difference between large software companies and other companies. At
the operational level, large software companies are highly influenced by the
advancement of Internet technology. Large software companies use open
innovation paradigm as part of their innovation initiatives. We envision a
future work is to further empirically evaluate the innovation initiative tree
in large software companies, which involves more practitioners from different
companies
An overview of disruptive technologies for aquaculture
The world wild fish stocks are being depleted in an ever-increasing speed. Aquaculture is the only way to ensure sufficient seafood for the world. Conventional aquaculture can be traced back to 4000 years in China and has been very successful in the past three decades. However, aquaculture has faced serious challenges, including only a few improved species, labour-intensiveness, environmental pollution, diseases and lack of traceability of products. Aquaculture needs disruptive technologies to increase fish production. Novel and disruptive technologies, including genome editing, artificial intelligence, offshore farming, recirculating aquaculture systems, alternative proteins and oils to replace fish meals and fish oils, oral vaccination, blockchain for marketing and internet of things, may provide solutions for sustainable and profitable aquaculture. This review briefly introduces these emerging and disruptive technologies to open up a forum for an in-depth discussion on how to integrate these technologies into aquaculture to improve its sustainability and profitability
Big data analytics:Computational intelligence techniques and application areas
Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment
A framework for smart production-logistics systems based on CPS and industrial IoT
Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems
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