<p>Cracking in continuous casting has always been one of the main problems of steel mills. Many cracks that occur during solidification are difficult to observe from outside the industrial mold. In order to better understand the formation of this defect, compared with the large-scale simulation used in the entire industrial process, microsimulation is also essential. A comprehensive study of using phase field method to simulate microstructure evolution has been conducted. A variety of two-dimensional models based on phase-filed method has been developed in order to simulate dendrites growth in continuous casting process. The basic concepts of phase-field method are presented. Among those models, Kobayashi model was first introduced to describe the morphology of pure material solidification, in this article, which are pure water and pure iron. In order to get closer to the actual situation of continuous casting, a multi-component model was introduced to solve the problem. To go a step further, by introducing a series of temperature parameters and modifications to a series of terms, the binary alloy directional solidification model was used to simulate the process of dendrite growth in continuous casting. Furthermore, the detailed derivation of the binary alloy solidification model and how to apply the model in open source software will also be introduced in this article. The effects of physical parameters such as anisotropic strength, temperature gradient and cooling rate on the growth and evolution of the dendrite interface were quantitatively analyzed. Finally, potential improvement of this model, optimization to primary cooling section in continuous casting process and various applications of the simulation were discussed.</p>

The principle of Continuous Double Auctioning (CDA) is known to provide an efficient way of matching supply and demand among distributed selfish participants with limited information. However, the literature indicates that the classic CDA algorithms developed for grid-like applications are centralised and insensitive to the processing resources capacity, which poses a hindrance for their application on resource constrained, smart micro-grids (RCSMG). A RCSMG loosely describes a micro-grid with distributed generators and demand controlled by selfish participants with limited information, power storage capacity and low literacy, communicate over an unreliable infrastructure burdened by limited bandwidth and low computational power of devices. In this thesis, we design and evaluate a CDA algorithm for power allocation in a RCSMG. Specifically, we offer the following contributions towards power auctioning on RCSMGs. First, we extend the original CDA scheme to enable decentralised auctioning. We do this by integrating a token-based, mutual-exclusion (MUTEX) distributive primitive, that ensures the CDA operates at a reasonably efficient time and message complexity of O(N) and O(logN) respectively, per critical section invocation (auction market execution). Our CDA algorithm scales better and avoids the single point of failure problem associated with centralised CDAs (which could be used to adversarially provoke a break-down of the grid marketing mechanism). In addition, the decentralised approach in our algorithm can help eliminate privacy and security concerns associated with centralised CDAs. Second, to handle CDA performance issues due to malfunctioning devices on an unreliable network (such as a lossy network), we extend our proposed CDA scheme to ensure robustness to failure. Using node redundancy, we modify the MUTEX protocol supporting our CDA algorithm to handle fail-stop and some Byzantine type faults of sites. This yields a time complexity of O(N), where N is number of cluster-head nodes; and message complexity of O((logN)+W) time, where W is the number of check-pointing messages. These results indicate that it is possible to add fault tolerance to a decentralised CDA, which guarantees continued participation in the auction while retaining reasonable performance overheads. In addition, we propose a decentralised consumption scheduling scheme that complements the auctioning scheme in guaranteeing successful power allocation within the RCSMG. Third, since grid participants are self-interested we must consider the issue of power theft that is provoked when participants cheat. We propose threat models centred on cheating attacks aimed at foiling the extended CDA scheme. More specifically, we focus on the Victim Strategy Downgrade; Collusion by Dynamic Strategy Change, Profiling with Market Prediction; and Strategy Manipulation cheating attacks, which are carried out by internal adversaries (auction participants). Internal adversaries are participants who want to get more benefits but have no interest in provoking a breakdown of the grid. However, their behaviour is dangerous because it could result in a breakdown of the grid. Fourth, to mitigate these cheating attacks, we propose an exception handling (EH) scheme, where sentinel agents use allocative efficiency and message overheads to detect and mitigate cheating forms. Sentinel agents are tasked to monitor trading agents to detect cheating and reprimand the misbehaving participant. Overall, message complexity expected in light demand is O(nLogN). The detection and resolution algorithm is expected to run in linear time complexity O(M). Overall, the main aim of our study is achieved by designing a resilient and cheating-free CDA algorithm that is scalable and performs well on resource constrained micro-grids. With the growing popularity of the CDA and its resource allocation applications, specifically to low resourced micro-grids, this thesis highlights further avenues for future research. First, we intend to extend the decentralised CDA algorithm to allow for participants’ mobile phones to connect (reconnect) at different shared smart meters. Such mobility should guarantee the desired CDA properties, the reliability and adequate security. Secondly, we seek to develop a simulation of the decentralised CDA based on the formal proofs presented in this thesis. Such a simulation platform can be used for future studies that involve decentralised CDAs. Third, we seek to find an optimal and efficient way in which the decentralised CDA and the scheduling algorithm can be integrated and deployed in a low resourced, smart micro-grid. Such an integration is important for system developers interested in exploiting the benefits of the two schemes while maintaining system efficiency. Forth, we aim to improve on the cheating detection and mitigation mechanism by developing an intrusion tolerance protocol. Such a scheme will allow continued auctioning in the presence of cheating attacks while incurring low performance overheads for applicability in a RCSMG.

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Fluid flow accompanied by heat transfer, solidification and interrelated chemical reactions play a key role during Continuous Casting (CC) of steel. Generation of defects and production issues are a result of the interaction between mould flux, steel grade and casting conditions. These issues are detrimental to both productivity and quality. Thus, the development of reliable numerical models capable of simulating fluid flow coupled to heat transfer and solidification are in high demand to assure product quality and avoid defects. The present work investigates the influence of steel grade, mould powder and casting conditions on process stability by including heat and mass transfer through liquid steel, slag film layers and solidifying shell. The thesis addresses the application of a numerical model capable of coupling the fluid flow, heat transfer and solidification developed by Swerea MEFOS; based on the commercial CFD code FLUENT v12. The Volume of Fluid (VOF) method, which is an interface tracking technique, is coupled to the flow model for distinction of the interface between steel and slag. The current methodology not only allows the model to describe the behaviour of molten steel during solidification and casting but also makes the assessment of mould powders performance possible.  Direct prediction of lubrication efficiency, which is demonstrated by solid-liquid slag film thickness and powder consumption, is one of the most significant advantages of this model. This prediction is a direct result of the interaction between metal/slag flow, solidification and heat transfer under the influence of mould oscillation and transient conditions.  This study describes the implementation of the model to analyse several steel and mould powder combinations. This led to detection of a combination suffering from quality problems (High Carbon Steel + High Break Temperature Powder) and one, which provides the most stable casting conditions (Low Carbon Steel + Low Break Temperature Powder).  Results indicate the importance of steel pouring temperature, mould powder break temperature and also solidification range on the lubrication efficiency and shell formation. Simulations illustrate that Low Carbon Steel + Low Break Temperature Powder delivers the best lubrication efficiency and thickest formed shell. In contrast, High Carbon Steel + High Break Temperature Powder conveys the minimum lubrication efficiency. Therefore, it was concluded that due to absence of proper powder consumption and solidification rate the latter combination is susceptible to production defects such as stickers and breakouts during the casting sequence.

No description available.

Literature regarding faculty development in uniprofessional healthcare programs is prolific; however, little has been written about instructional programs designed for faculty delivering interprofessional education (IPE). In this paper, we describe the genesis, content, and improvement of a faculty development workshop which exemplifies a meta teaching model and was designed to serve faculty facilitators in a rapidly growing IPE program. Evaluations following initial delivery of the workshops in fall 2018 returned high faculty satisfaction ratings and feedback suggesting a need for even more pedagogical training with a stronger emphasis on meta techniques and less on a review of student content. In response, program developers incorporated additional teaching techniques in the spring 2019 training. Faculty evaluations in spring 2019 reflected even greater satisfaction with the increased focus on “meta skills”. The faculty development program described in this paper supports the need for a structured training process for faculty facilitating in IPE programs.

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Purpose - The purpose of this article is to present one example of how the strategies of total quality management (TQM) and continuous improvement are being used by US health care providers to meet the challenges of the future. Design/methodology/approach - This article presents an application utilizing the strategies of TQM and continual and rapid improvement in the area of assessing internal customer satisfaction in the health care arena. Satisfaction information concerning internal processes is critically important to the health care provider, and this article presents the development and application of an instrument designed to provide timely and relevant internal customer satisfaction information to individual health care providers. This provides information on problem identification and improvement opportunities for a world-class continuous improvement program. Findings - The article finds that customer satisfaction is increasingly being recognized as an appropriate measure for determining how well a particular organization is accomplishing its mission and, while customer satisfaction surveys provide valuable information and may be used to improve the entire operation, they provide limited insight into the details of the inner workings of each cost center. Each of the measures discussed in this article is potentially equally insightful and may provide more directly usable information when applied to internal customers. Originality/value - This article provides useful information on providing customer satisfaction in the health care arena.

The approach taken by the College of Business and Technology at East Tennessee State University uses multidisciplinary teams to develop an assessment process that unifies the organization's culture to focus on assurance of learning. The theoretical literatures in change management processes and organizational culture are the foundations for the design of the assessment process that spans seven diverse departments and satisfies the requirements of multiple disciplinary accreditors. Lessons learned and recommendations for others are shared.

Lean, with its origin in the Japanese automotive production and Toyota, is broadly seen as the most adopted manufacturing philosophy since several decades. One of the core values of Lean is Continuous Improvements (CI). CI is about the many small, simple and cheap improvements, which everyone is involved in, every day. As digitalization is making its way into the manufacturing environment, a hype around what is called Industry 4.0 (I4.0), also known as the fourth industrial revolution, has been created. In short, I4.0 refers to different technology-driven changes in an organization’s manufacturing systems. However, the true implications of those changes remain dimmed by the single-sided discussion of I4.0’s portrayed conceptual benefits. Moreover, despite the importance of CI for corporate success and the overall relevance of the I4.0 topic, no studies have been found to address their potential interaction. Thus, the purpose of this thesis has been to explore how the conditions for CI will be affected post I4.0 implementation. By focusing on the potential negative impacts on the overall rate of improvement, the purpose has also encompassed the identification of specific success factors to mitigate these negatives.   Due to the explorative nature of the research, a two-iteration Delphi survey containing open-ended questions has been chosen as a means of data collection; targeting experienced Lean and I4.0 personnel within the manufacturing industry. The first iteration survey encouraged participants to identify both positive and negative aspects of I4.0 impact on CI, while the second iteration survey encouraged participants to identify success factors. To make the concept of I4.0 more tangible, the technologies have been condensed into three I4.0 value drivers: Connectivity, Intelligence and Flexible automation. The data processing revealed that 64% of the answers provided for all value drivers were positive. This indicated an overall positive belief in the impacts of I4.0 on the conditions for CI both through enhanced problem-sensitivity, built by Lean values and principles, and through increased problem-solving capabilities. While the results reflected the current I4.0 hype, they also highlighted the difficulty in critically assessing the potential impact from technologies that are not yet widely implemented. Nevertheless, for each value driver the participants have also identified Challenges (18% of answers) and Risks (18% of answers) that can adversely affect CI. Based on the Challenges and Risks, a total of 74 success factors have been compiled and divided into four categories: Purpose, Involvement of people, Competence and Implementation strategy.   This research has contributed to the discussion about the Possibilities, Challenges and Risks of the I4.0 value drivers’ impact on the conditions for CI in the manufacturing environment. Furthermore, with emphasis on the identified Challenges and Risks, the authors have tried to cut through the noise of the ongoing I4.0 hype. As such, this research has introduced an alternative perspective that sets it apart from the overwhelmingly uncritical discussions surrounding I4.0. While the research’s theoretical contribution has been built by the insight into the I4.0’s potential impact on the conditions for CI, its practical contribution has been derived from the identified success factors; factors that can work as guiding principles for I4.0 adopters.