@article {
author = {Chiu, Samuel S. and Larson, Richard C.},
title = {Bertrand’s Paradox Revisited: More Lessons about that Ambiguous Word, Random},
journal = {Journal of Industrial and Systems Engineering},
volume = {3},
number = {1},
pages = {1-26},
year = {2009},
publisher = {Iranian Institute of Industrial Engineering},
issn = {1735-8272},
eissn = {},
doi = {},
abstract = {The Bertrand paradox question is: “Consider a unit-radius circle for which the length of a side of an inscribed equilateral triangle equals 3 . Determine the probability that the length of a ‘random’ chord of a unit-radius circle has length greater than 3 .” Bertrand derived three different ‘correct’ answers, the correctness depending on interpretation of the word, random. Here we employ geometric and probability arguments to extend Bertrand’s analysis in two ways: (1) for his three classic examples, we derive the probability distributions of the chord lengths; and (2) we also derive the distribution of chord lengths for five new plausible interpretations of randomness. This includes connecting (and extending) two random points within the circle to form a random chord, perhaps being a most natural interpretation of random.},
keywords = {Bertrand paradox,geometrical probability,Randomness,Mathematical Modeling},
url = {http://www.jise.ir/article_3997.html},
eprint = {http://www.jise.ir/article_3997_6a52197644296c9501c5be1f63955e8a.pdf}
}
@article {
author = {Chandna, Pankaj and Chandra, Arunesh},
title = {Quality Tools to Reduce Crankshaft Forging Defects: An Industrial Case Study},
journal = {Journal of Industrial and Systems Engineering},
volume = {3},
number = {1},
pages = {27-37},
year = {2009},
publisher = {Iranian Institute of Industrial Engineering},
issn = {1735-8272},
eissn = {},
doi = {},
abstract = {Crankshafts are the most important loaded components in the case of an automobile. In order to achieve required mechanical properties most of crankshafts for automobile are forged with micro alloyed steel. Usually, the shapes of crankshafts are complex, and many defects are induced during the process of crankshaft forging such as under-filling, laps and folds etc. In this work the forging analysis of six cylinder crankshaft produced by hot forging having engine bore of ninety-seven mm popularly known as 697 crankshaft manufactured by TATA Motors, Jamshedpur INDIA (previously known as TELCO) used in trucks and buses is being made. Forging analysis is being made to explain that how the defects appear and how to prevent them. This analysis can be easily done with the help of various quality tools used for quality improvement process. With the help of Pareto diagrams, which are mostly used to identify critical areas, the forging defects of the crankshaft have been prioritized by arranging them in decreasing order of importance. Then cause and effect diagram is being applied to explore possible causes of defects through brain storming session and to determine the causes which has the greatest effect. Corrective measures are being suggested to overcome the forging defects of the 697 integral counter weight crankshafts. Finally, few remedial measures and suggestions have been provided for the existing crankshaft production line in the forging shop. It is also concluded that the proper implementation of the proposed corrective plan may reduce the present rejection rate from 2.43% to 0.21% and rework from 6.63% to 2.15%.},
keywords = {Cause and effect diagram,Crankshafts,Forging defects,Pareto diagrams},
url = {http://www.jise.ir/article_3998.html},
eprint = {http://www.jise.ir/article_3998_619aa108bfe84aefbd9f2711596cde1d.pdf}
}
@article {
author = {Weckman, G.R. and Millie, D.F. and Ganduri, C. and Rangwala, M. and Young, W. and Rinder, M. and Fahnenstiel, G.L.},
title = {Knowledge Extraction from the Neural ‘Black Box’ in Ecological Monitoring},
journal = {Journal of Industrial and Systems Engineering},
volume = {3},
number = {1},
pages = {38-55},
year = {2009},
publisher = {Iranian Institute of Industrial Engineering},
issn = {1735-8272},
eissn = {},
doi = {},
abstract = {Phytoplankton biomass within the Saginaw Bay ecosystem (Lake Huron, Michigan, USA) was characterized as a function of select physical/chemical indicators. The complexity and variability of ecological systems typically make it difficult to model the influences of anthropogenic stressors and/or natural disturbances. Here, Artificial Neural Networks (ANNs) were developed to model chlorophyll a concentrations, a measure for water-column phytoplankton biomass and a proxy for system-level health. ANNs act like “black boxes” in the sense that relationships are encoded as weight vectors within the trained network and as such, cannot easily support the generation of scientific hypotheses unless these relationships can be explained in a comprehensible form. Accordingly, the ‘knowledge’ and/or rule-based information embedded within ANNs needs to be extracted and expressed as a set of comprehensible ‘rules’. Such extracted information would enhance the delineation and understanding of ecological complexity and aid in developing usable prediction tools. Comparisons of various computational approaches (including TREPAN, an algorithm for constructing decision trees from neural networks) used in extracting rule-based information from trained Saginaw Bay ANNs are discussed.},
keywords = {Ecological monitoring,Artificial Neural Networks,chlorophyll prediction,knowledge
extraction},
url = {http://www.jise.ir/article_3999.html},
eprint = {http://www.jise.ir/article_3999_ab9ebfa0ac17897cafc8666ab3994380.pdf}
}
@article {
author = {Eshragh, Ali and Modarres, Mohammad},
title = {A New Approach to Distribution Fitting: Decision on Beliefs},
journal = {Journal of Industrial and Systems Engineering},
volume = {3},
number = {1},
pages = {56-71},
year = {2009},
publisher = {Iranian Institute of Industrial Engineering},
issn = {1735-8272},
eissn = {},
doi = {},
abstract = {We introduce a new approach to distribution fitting, called Decision on Beliefs (DOB). The objective is to identify the probability distribution function (PDF) of a random variable X with the greatest possible confidence. It is known that f X is a member of = { , , }. 1 m S f L f To reach this goal and select X f from this set, we utilize stochastic dynamic programming and formulate this problem as a special case of Optimal Stopping Problem. The decision is made on the basis of the outcome of a limited number of experiments. A real number, namely, belief is assigned to each candidate by considering the outcome of observations. At each stage and after a random observation, beliefs are updated by applying Bayesian formula and then either one element of S is selected as the desired PDF or another observation is made. At each stage, a PDF from S with the greatest belief is accepted as the desired PDF provided the belief is higher than a least acceptable designated level. We assume the total number of possible observations can not exceed N and a cost is incurred for each observation. Dynamic and nonlinear programming are applied to calculate the least acceptable belief value for each stage. To reduce the search of the optimal solution, the concept of entropy is utilized.},
keywords = {Distribution fitting,Dynamic programming,Markovian decision process},
url = {http://www.jise.ir/article_4000.html},
eprint = {http://www.jise.ir/article_4000_0ebb501631041b248635fe2b800c0cd1.pdf}
}