64 research outputs found

    Altruistic behaviour in a two-echelon supply chain with unmatched proportional feedback controllers

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    We study a two-echelon supply chain with first order autoregressive demand and unit replenishment lead-times. Each echelon of the supply chain uses conditional expectation to generate Minimum Mean Squared Error forecasts. Both echelons use these forecasts inside the 'Order-Up-To' policy to generate replenishment orders. We investigate three different scenarios. The first is when each echelon aims to minimise their own local inventory holding and backlog costs. The second scenario is concerned with an altruistic retailer who is willing and able to sacrifice some of his own performance for the benefit of the total supply chain. The retailer does this by smoothing the demand placed on the manufacturer by using a matched proportional controller in the inventory and Work-In-Progress feedback loops. The third scenario is concerned with an altruistic retailer with two, unmatched controllers. The matched controller case outperforms the traditional case by 14.1%; the unmatched controller case outperforms the matched controller case by 4.9%

    Human-Autonomy Teaming - an Evolving Interaction Paradigm: Teaming and Automation

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    Intelligent and complex systems are becoming common in our workplace and our homes, providing direct assistance in transport, health and education domains. In many instances the nature of these systems are somewhat ubiquitous, and influence the manner in which we make decisions. Traditionally we understand the benefits of how humans work within teams, and the associated pitfalls and costs when this team fails to work. However, we can view the autonomous agent as a synthetic partner emerging in roles that have traditionally been the bastion of the human alone. Within these new Human-Autonomy Teams we can witness different levels of automation and decision support held within a clear hierarchy of tasks and goals. However, when we start examining the nature of more autonomous systems and software agents we see a partnership that can suggest different constructs of authority depending on the context of the task. This may vary in terms of whether the human or agent is leading the team in order to achieve a goal. This paper examines the nature of HAT composition whilst examining the application of this in aviation and how trust in such stystems can be assessed

    Sintonización de controlador PID utilizando Quorum Sensing (QS) bacterial

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    Objective: PID controllers are widely used to operate AC motors due to their simplicity and easy implementation. However, adjusting its parameters in search of an optimal scheme can be complex because it requires manual tuning by trial and error. This research aims to implement an optimized tuning scheme through a search based on the idealized behavior of a community of bacteria and its Quorum Sensing (QS). Methodology: A closed-loop system model with PID control considering disturbances is proposed in order to tune a disturbance-resistant controller. The response of the model is calculated using a search that mimics a simplified model of bacterial behavior. The scheme uses ITSE (Integral Time Squared Error) as the performance index. Results: The tuning resulting from the proposed scheme was evaluated by simulation and compared with tunings of the same model made by Root Locus and Genetic Algorithms (GA). The results showed a satisfactory response according the design criteria. Conclusions: Nowadays, PID controllers are still basic industrial control tools, particularly important in motor operation. The performance of these controls depends fundamentally on the design of their gain. In the case of complex plants, additional tools are required to facilitate PID tuning. We propose an intelligent and bio-inspired tuning scheme that demonstrates high performance in laboratory tests. Financing: University Francisco José de Caldas through the project 1-72-578-18.Objetivo: Los controladores PID son ampliamente utilizados para operar motores AC debido a su simplicidad y fácil implementación. Sin embargo, la sintonización de sus parámetros en busca de un esquema óptimo puede ser compleja debido a que requiere sintonización manual mediante prueba y error. El objetivo de esta investigación es implementar un esquema de ajuste optimizado mediante una búsqueda basada en el comportamiento idealizado de una comunidad de bacterias y su detección de quórum (Quorum Sensing, QS). Metodología: Se plantea el modelo del sistema en lazo cerrado con control PID considerando las perturbaciones con el objetivo de sintonizar un controlador resistente a ellas. La respuesta del modelo se calcula mediante una búsqueda que imita un modelo simplificado de comportamiento bacterial. El esquema utiliza el ITSE (Integral Time Squared Error) como indice de desempeño. Resultados: La sintonización mediante el esquema propuesto fue evaluada mediante simulación y comparada con sintonizaciones del mismo modelo realizadas mediante Root Locus y Algoritmos Genéticos (GA). Los resultados mostraron una respuesta satisfactoria frente a los criterios de diseño. Conclusiones: Los controladores PID siguen siendo hoy en día herramientas básicas de control industrial, particularmente importantes en el manejo de motores. El desempeño de estos controles depende fundamentalmente del diseño de su ganancia. En el caso de plantas complejas se requiere de herramientas adicionales que faciliten la sintonización del PID. Nosotros proponemos un esquema de sintonización inteligente y bio-inspirado que demuestra un alto desempeño en pruebas de laboratorio. Financiamiento: Universidad Distrital Francisco José de Caldas a través del proyecto 1-72-578-18

    Facilitating HRI by Mixed Reality Techniques

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    Renner P, Lier F, Friese F, Pfeiffer T, Wachsmuth S. Facilitating HRI by Mixed Reality Techniques. In: HRI '18 Companion: 2018 ACM/IEEE International Conference on Human-Robot Interaction Companion. ACM/IEEE; 2018.Mobile robots start to appear in our everyday life, e.g., in shopping malls, airports, nursing homes or warehouses. Often, these robots are operated by non-technical staff with no prior experience/education in robotics. Additionally, as with all new technology, there is certain reservedness when it comes to accepting robots in our personal space. In this work, we propose making use of state-of-the-art Mixed Reality (MR) technology to facilitate acceptance and interaction with mobile robots. By integrating a Microsoft HoloLens into the robot's operating space, the MR device can be used to a) visualize the robot's behavior-state and sensor data, b) visually notify the user about planned/future behavior and possible problems/obstacles of the robot, and c) to actively use the device as an additional external sensor source. Moreover, by using the HoloLens, users can operate and interact with the robot without being close to it, as the robot is able to \textit{sense with the users' eye

    Analysis of Characteristics of Non-Commercial Software Systems for Assessing Flatness Error by Means of Minimum Zone Method

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    As far as machine parts are concerned, accuracy can be defined in many aspects. In order for a workpiece to be functional, dimensional and surface roughness requirements are not enough. Accuracy of geometric elements and position tolerances is necessary information. The notation, definitions, interpretations and general values of geometric tolerances are defined by standards. Nevertheless, there are several mathematical methods of calculating values based on data measured by means of coordinate measuring machines. Standards demand the use of the minimum zone method in assessing form deviation without mentioning the way of obtaining it. In this paper, the minimum zone method, which is an iterative algorithm, was investigated. Thus, the result of flatness measurement was calculated by continuous approximation. There are various methods of defining the steps of iteration, affecting the length of time and accuracy of the flatness value. The aim of the research was to examine the characteristics of two non-commercial software solutions for assessing the minimum zone in comparison with the commercial CMM software. Based on the analysis, it can be concluded that the developed software solutions are efficient in assessing flatness error and that the differences between these and the commercial software are negligible

    Application of Learning Curves in Operations Management Decisions

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    In the time of industry 4.0 and big data, methods which are based on the collection and the processing of a large amount of data in order to support managerial decisions have outstanding significance. The learning curve theory pertains to these methods. The purpose of this paper is to explore some application possibilities of the classical learning curve in manufacturing and service operations. The learning effect assumes that as the quantity of units manufactured increases, the time needed to produce an individual unit decreases. The function describing this phenomenon is the learning curve. Various learning curves have been developed and applied in the area of production economics and much research studies the significance of the learning effect in management decisions. This study summarizes the main learning curve models and demonstrates how learning can be considered in three classical areas of operations management. First, the calculation of economic manufacturing quantity in the presence of learning is studied. Next, the effect of learning in break-even analysis and assembly line balancing is explored. The results show that with the consideration of the learning effect, calculations become more complex and require greater efforts, but the application of the learning curve concept can provide valuable insight both at operational and strategic levels

    Modeled Insulin Sensitivity and Interstitial Insulin Action from a Pilot Study of Dynamic Insulin Sensitivity Tests

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    An accurate test for insulin resistance can delay or prevent the development of Type 2 diabetes and its complications. The current gold standard test, CLAMP, is too labor intensive to be used in general practice. A recently developed dynamic insulin sensitivity test, DIST, uses a glucose-insulin-C-peptide model to calculate model-based insulin sensitivity, SI. Preliminary results show good correlation to CLAMP. However both CLAMP and DIST ignore saturation in insulin-mediated glucose removal. This study uses the data from 17 patients who underwent multiple DISTs to investigate interstitial insulin action and its influence on modeled insulin sensitivity. The critical parameters influencing interstitial insulin action are saturation in insulin receptor binding, αG, and plasma-interstitial difiusion rate, nI . Very low values of αG and very low values of nI produced the most intra-patient variability in SI. Repeatability in SI is enhanced with modeled insulin receptor saturation. Future parameter study on subjects with varying degree of insulin resistance may provide a better understanding of different contributing factors of insulin resistance
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