5 research outputs found

    An Agent-Based Approach to Self-Organized Production

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    The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c

    Sustainability assessment of nations and related decision making using fuzzy logic

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    This paper refines and extends in fundamental ways an existing model for the numerical assessment of sustainability called sustainability assessment by fuzzy evaluation (SAFE). SAFE, in its basic form, uses fuzzy logic to combine a large suite of basic indicators and then computes numerical values of sustainability for a number of composite indicators such as air, land, economy, health, etc. At a higher hierarchy it computes the sustainability of an ecological and a human component, and finally, it computes overall sustainability of a country or region. As state-of-the-art in fuzzy analysis has advanced, we are prompted to modify SAFE accordingly. The refined model uses the so-called Takagi-Sugeno-Kang inference scheme (TSK) which together with a few technical requirements guarantees monotonicity, i.e., an improvement of a basic indicator leads to an improvement of sustainability. Another refinement concerns the data inputs. To include the effects of past environmental pressures and development policies on the present state of sustainability, we use exponential smoothing to take account of the past with exponentially decaying weights. Finally, the model is now applied to all countries of the world for which data could be obtained and their corresponding sustainabilities are computed. Also, through sensitivity analysis, the most important indicators that affect sustainability are identified

    Analysis of production networks of the finite queue type with breakdowns

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    Summarization: Production networks of any topology with finite buffers, random rates, and breakdowns are analyzed using a simple analytic/simulation model. Random rates are approximated by piecewise deterministic variables and parts of the network are collapsed into single servers between events. Occurrence of events represents the slow nonlinear system dynamics which is handled by simulation. The fast piecewise linear dynamics between events is handled algebraically. The model compared to a brute-force simulator is accurate and extremely fastPresented on: IEEE Transactions on Robotics and Automatio

    On the use of fuzzy inference systems for assessment and decision making problems

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    The Fuzzy Inference System (FIS) is a popular paradigm for undertaking assessment/measurement and decision problems. In practical applications, it is important to ensure the monotonicity property between the attributes (inputs) and the measuring index (output) of an FIS-based assessment/ measurement model. In this chapter, the sufficient conditions for an FIS-based model to satisfy the monotonicity property are first investigated. Then, an FIS-based Risk Priority Number (RPN) model for Failure Mode and Effect Analysis (FMEA) is examined. Specifically, an FMEA framework with a monotonicity-preserving FIS-based RPN model that fulfils the sufficient conditions is proposed. A case study pertaining to the use of the proposed FMEA framework in the semiconductor industry is presented. The results obtained are discussed and analyzed

    Sensitivity Reduction and Robustness

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