Maria Drakaki

An Intelligent Multi-Agent System Framework for Fault Diagnosis of Squirrel-Cage Induction Motor Broken Bars

Decision making in fault diagnosis is a critical factor in industrial production maintenance. Artificial intelligence (AI) techniques are widely used to accurately identify faults in induction motors. Multi-agent systems (MAS) as a distributed AI method are efficient in representing intelligent manufacturing systems to achieve decision robustness. In this paper, an intelligent MAS is developed for the decision making in fault diagnosis of three-phase squirrel cage induction motor rotor bars. Agents in the proposed MAS represent induction motor in different health conditions, i.e. healthy motor and motor with 1, 2 and 3 broken bars and also a supervisor agent. Each agent is embedded with an artificial neural network and trained with measurement data taken from a motor in the corresponding health condition. Measurement data are obtained with the classical motor current signature analysis (MSCA) method. Each agent makes local decision making and communicates its output to the supervisor agent that makes the final fault diagnosis based on a threshold value.

Modeling and performance evaluation of an agent-based warehouse dynamic resource allocation using Colored Petri Nets

High accuracy modeling plays an important role for the optimization of planning and control in the supply chain members. Agent-based planning and control systems are efficient in representing intelligent manufacturing systems to achieve decision robustness. The purpose of this paper is to combine Colored Petri Nets (CPNs) with an agent-based warehouse control system in order to model the system, evaluate petri net related system properties, and evaluate system performance. A dynamic resource allocation of an order-picking process is presented as a case study to illustrate the applicability of the method. A hierarchical timed CPN (CTPN) model has been implemented. Simulation and state space results are used to identify system properties and evaluate performance.

De-embedding method for on-wafer RF CMOS inductor measurements

In this work, an accurate de-embedding method for on-wafer RF measurements of CMOS large area devices like the inductors is presented. The method uses distributed and lumped-element models to represent the parasitic elements. The interconnect parasitics are calculated using the transmission line theory. The proposed method is compared to existing de-embedding methods. The validity of the method is checked with the DC resistance value of the interconnects as calculated from the layout and as extracted from measurements, as well as with inductance results of the fabricated inductor, extracted from measurements and from electromagnetic simulations. On-wafer S-parameter measurements have been taken from a test chip up to 20GHz.

An Intelligent Multi-agent System Using Fuzzy Analytic Hierarchy Process and Axiomatic Design as a Decision Support Method for Refugee Settlement Siting

Crises and disasters of recent years are complex and occasionally interrelated phenomena, which require complex decision making for effective humanitarian relief operations provision. Moreover, coordination is needed between different humanitarian actors as decision makers. Massive refugee and migrant arrivals in Greece since 2014, mainly a result of a refugee crisis, require complex humanitarian supply chain management and logistics operations. In this paper, refugee settlement site planning decision making process is addressed with an intelligent multi-agent system (MAS) modeling approach. The MAS uses two multi-criteria decision making (MCDM) methods: fuzzy analytic hierarchy process (FAHP) to determine the weights of criteria and fuzzy axiomatic design approach extended with risk factors (RFAD) to rank alternative sites for refugee settlement. The proposed method will be applied to evaluate currently operating temporary accommodation sites in Greece.

Community-based social partnerships in crisis resilience: a case example in Greece

Purpose The purpose of this paper is to describe in-depth a community-based social partnership, emerged in response to the financial crisis in Greece, with members from the private, public and civic sectors, using a case example of a grass-root self-organised national network. Design/methodology/approach Formal and informal interviews as well as written communication with members of the partnership mainly formed the basis for the analysis. Topics covered formation and implementation activities, outcomes, relationship issues, such as trust and links to social capital. Findings A shared community risk and a national media campaign to increase public awareness of the issue were catalysts for individuals’ sensitisation and participation in the partnership. The shared risk was the loss of community’s social cohesion, through poverty aggravated by the financial crisis. Self-organisation led to innovative relationships, whereas trust, collective action and collaboration show social capital attributes in the partnership enabling resilience development. Research limitations/implications The research contributes in the fields of community-based partnerships and engagement in building community and crisis resilience. The findings are based on a case example. More evidence is needed in order to derive generalised statements about the partnership’s contribution to crisis resilience. Practical implications The partnership has shown impact on community engagement, health and well-being. Originality/value This paper presents a partnership type for building community and crisis resilience with the case example of one such partnership in Greece, formed to alleviate community distress caused by the crisis.

Comparison of Fuzzy Multi Criteria Decision Making Approaches in an Intelligent Multi-agent System for Refugee Siting

Refugee crisis has escalated into a leading crisis in recent years, including Europe since 2015 after the massive refugee and migrant sea arrivals in the Mediterranean. Therefore, its socio-economic and environmental impact requires complex decision making for the delivery of effective humanitarian aid operations. Refugee settlement and shelter is an operations sector where the application of multi-criteria decision making (MCDM) methods seems appropriate. Additionally, the range of involved decision makers as well as their relationships can be addressed using a multi-agent system (MAS). Different decision making fuzzy methods have been proposed in the literature which can be used by the agents in order to address refugee siting. The purpose of this paper is to perform a comparative analysis of two such methods, namely, hierarchical fuzzy TOPSIS and fuzzy axiomatic design approach used in a MAS for refugee siting. The comparative study has been done by evaluating operating temporary sites in Greece and the obtained results reflect the current situation.

An educational purpose built three dimensional printer

A three dimensional printer using step motors from 3.5-inch disk drives was built for our undergraduate research thesis project. An Arduino microcontroller was in charge of controlling the steppers through the DC drivers and a 3D pen was used as the printing unit. The program was created with the Arduino suite and the design of the drawing with the open source Grbl using g code. For the axes, three disk drives were reassembled to form the X, Y and Z levels. Moreover, this structure can be operated as a Computerized Numerical Control machine by replacing the 3D pen with other components, such as a drill. The 3D printer will be used for educational purposes, as a teaching tool in laboratory projects. It provides an opportunity for students to learn more about robotic machines and create one from scratch.

Improving the quality factor estimation for differentially driven RF CMOS inductor

The quality factor of on-chip differentially driven RF CMOS inductors is derived using energy based formulas from an equivalent differential one-port model for the inductor, taking into account the influence of signal leakage to ground at high frequencies. The quality factor is calculated for various load conditions and compared to published results based on existing definitions of the quality factor. Results suggest that both differential and common mode signals have to be taken into account for an accurate estimation of the quality factor.