Reconfiguring process plans: A mathematical programming approach

Increased global competition and frequent unpredictable market changes are current challenges facing manufacturing enterprises. Unpredictable changes of part design and engineering specifications trigger frequent and costly changes in process plans, which often require changes in the functionality and design of the manufacturing system. Process planning is a key logical enabler that should be further developed to cope with the changes encountered at the system level as well as to support the new manufacturing paradigms and continuously evolving products. Retrieval-based process planning predicated on rigid pre-defined boundaries of part families, does not satisfactorily support this changeable manufacturing environment. Since purely generative process planning systems are not yet a reality, a sequential hybrid approach at the macro-level has been proposed. Initially the master plan information of the part family\u27s composite part is retrieved, then modeling tools and algorithms are applied to arrive at the process plan of the new part, the definition of which does not necessarily lie entirely within the boundary of its original part family. Two distinct generative methods, namely Reconfigurable Process Planning (RPP) and Process Re-Planning were developed and compared. For RPP, a genuine reconfiguration of process plans to optimize the scope, extent and cost of reconfiguration is achieved using a novel 0-1 integer-programming model. Mathematical programming and formulation is proposed, for the first time, to reconfigure process plans to account for changes in parts\u27 features beyond the scope of the original product family. The computational time complexity of RPP is advantageously polynomial compared with the exponentially growing time complexity of its classical counterparts. As for Process Re-Planning, a novel adaptation of the Quadratic Assignment Problem (QAP) formulation has been developed, where machining features are assigned positions in one-dimensional space. A linearization of the quadratic model was performed. The proposed model cures the conceptual flaws in the classical Traveling Salesperson Problem; it also overcomes the complexity of the sub-tour elimination constraints and, for the first time, mathematically formulates the precedence constraints, which are a comer stone of the process planning problem. The developed methods, their limitations and merits are conceptually and computationally, analyzed, compared and validated using detailed industrial case studies. A reconfiguration metric on the part design level is suggested to capture the logical extent and implications of design changes on the product level; equally, on the process planning level a new criterion is introduced to evaluate and quantify impact of process plans reconfiguration on downstream shop floor activities. GAMS algebraic modeling language, its SBB mixed integer nonlinear programming solver, CPLEX solvers and Matlab are used. The presented innovative new concepts and novel formulations represent significant contributions to knowledge in the field of process planning. Their effectiveness and applicability were validated in different domains

Weighted transfer learning for improving motor imagery-based brain-computer interface

One of the major limitations of motor imagery (MI)-based brain-computer interface (BCI) is its long calibration time. Due to between sessions/subjects variations in the properties of brain signals, typically a large amount of training data needs to be collected at the beginning of each session to calibrate the parameters of the BCI system for the target user. In this paper, we propose a novel transfer learning approach on the classification domain to reduce the calibration time without sacrificing the classification accuracy of MI-BCI. Thus, when only few subject-specific trials are available for training, the estimation of the classification parameters is improved by incorporating previously recorded data from other users. For this purpose, a regularization parameter is added to the objective function of the classifier to make the classification parameters as close as possible to the classification parameters of the previous users who have feature spaces similar to that of the target subject. In this study, a new similarity measure based on the kullback leibler divergence (KL) is used to measure similarity between two feature spaces obtained using subject-specific common spatial patterns (CSP). The proposed transfer learning approach is applied on the logistic regression classifier and evaluated using three datasets. The results showed that compared to the subject-specific classifier, the proposed weighted transfer learning classifier improved the classification results particularly when few subject-specific trials were available for training (p<0.05). Importantly, this improvement was more pronounced for users with medium and poor accuracy. Moreover, the statistical results showed that the proposed weighted transfer learning classifier performed significantly better than the considered comparable baseline algorithms

Robust common spatial pattern estimation using dynamic time warping to improve BCI systems

Common spatial patterns (CSP) is one of the most popular feature extraction algorithms for brain-computer interfaces (BCI). However, CSP is known to be very sensitive to artifacts and prone to overfitting. This paper proposes a novel dynamic time warping (DTW)-based approach to improve CSP covariance matrix estimation and hence improve feature extraction. Dynamic time warping is widely used for finding an optimal alignment between two time-dependent signals under predefined conditions. The proposed approach reduces within class temporal variations and non-stationarity by aligning the training trials to the average of the trials from the same class. The proposed DTW-based CSP approach is applied to the support vector machines (SVM) classifier and evaluated using one of the publicly available motor imagery datasets. The results showed that the proposed approach, when compared to the classical CSP, improved the classification accuracy from 78% to 83% on average. Importantly, for some subjects, the improvement was around 10%

Zooplankton stresnih područja uzduž obale Damietta (Egipat) u Sredozemnom moru

The spatial pattern of zooplankton communities at Damietta coast, southeastern Mediterranean was studied to assess the impact of human activities on the abundance and community structure. Twenty-five stations from five different stressed sites were sampled in June-July 2014. Thirty-four zooplankton taxa were recorded, in addition to the larvae of copepods and meroplankton. Copepoda was the most abundant group among which, Oithona nana, Euterpina acutifrons, and Parvocalanus cirrostratus were the most frequent. The calanoid copepod Pseudodiaptomus trihamatus is a new record for the Mediterranean Sea that may have been introduced via ballast water. Multivariate/Univariate analyses demonstrated that 1) the environmental variables and zooplankton communities represented significant differences among five sites; 2) the spatial variations of community structure were undoubtedly due to land-based effluents; and 3) among all environmental variables, salinity and phytoplankton biomass had the major determining effects on the spatial patterns of zooplankton categories. The results indicates that not only the discharged water makes the Damietta coast at risk, but also the ballast water is not less dangerous. Hence, we emphasize the need for activation of the ballast water management to reduce the risk of future species invasions.Istraživana je prostorna struktura zooplanktonskih zajednica na obali Damietta (Egipat, jugoistočni Mediteran) kako bi se procijenio utjecaj ljudskih aktivnosti na obilje i strukturu zajednice. U lipnju i srpnju 2014. uzorkovano je na dvadeset pet postaja s pet različitih mjesta izloženih zagađenju. Uz larve veslonožaca i meroplanktona zabilježene su 34 zooplanktonske vrste.Veslonošci se bili najbrojnija skupina među kojima su najčešći Oithona nana, Euterpina acutifrons i Parvocalanus cirrostratus. Kalanoidni veslonožac Pseudodiaptomus trihamatus je novi nalaz za Sredozemno more, a vjerojatno je da je možda unesen putem balastnih voda. Multivarijatne / jednosmjerne analize pokazale su da 1) varijable okoliša i zooplanktonske zajednice predstavljaju značajne razlike između pet mjesta; 2) prostorne varijacije strukture zajednice nedvojbeno su posljedica tehnoloških otpadnih voda (pročišćenih i nepročišćenih) sa kopna; i 3) između svih varijablia okoliša, saliniteta i biomase fitoplanktona imali su glavne utjecaje na prostorne obrasce kategorija zooplanktona. Rezultati pokazuju da je samo ne ispuštena voda rizična za obalu Damiette, već i balastna voda, koja nije nimalo manje opasna. Stoga se naglašava potreba za aktivacijom upravljanja balastnim vodama kako bi se smanjio rizik unosa invazivnih vrsta

Evidence for the speed-value trade-off: human and monkey decision making is magnitude sensitive

Complex natural systems from brains to bee swarms have evolved to make adaptive multifactorial decisions. Recent theoretical and empirical work suggests that many evolved systems may take advantage of common motifs across multiple domains. We are particularly interested in value sen- sitivity (i.e., sensitivity to the magnitude or intensity of the stimuli or re- ward under consideration) as a mechanism to resolve deadlocks adaptively. This mechanism favours long-term reward maximization over accuracy in a simple manner, because it avoids costly delays associated with ambivalence between similar options; speed-value trade-offs have been proposed to be evolutionarily advantageous for many kinds of decision. A key prediction of the value-sensitivity hypothesis is that choices between equally-valued options will proceed faster when the options have a high value than when they have a low value. However, value-sensitivity is not part of idealised choice models such as diffusion to bound. Here we examine two different choice behaviours in two different species, perceptual decisions in humans and economic choices in rhesus monkeys, to test this hypothesis. We observe the same value sensitivity in both human perceptual decisions and monkey value-based decisions. These results endorse the idea that neural decision systems make use of the same basic principle of value-sensitivity in order to resolve costly deadlocks and thus improve long-term reward intake

A robust uniform B-spline collocation method for solving the generalized PHI-four equation

In this paper, we develop a numerical solution based on cubic B-spline collocation method. By applying Von-Neumann stability analysis, the proposed technique is shown to be unconditionally stable. The accuracy of the presented method is demonstrated by a test problem. The numerical results are found to be in good agreement with the exact solution

A probabilistic multi-objective approach for FACTS devices allocation with different levels of wind penetration under uncertainties and load correlation

This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the Multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller