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Two-sided assembly lines are heavily used in automotive industry for producing large-sized products such as buses, trucks and automobiles. Mixed-model lines help manufacturers satisfy customized demands at a reasonable cost with desired quality. This paper addresses to mixed-model two-sided lines incorporating incompatible task groups and proposes a new method for minimizing two conflicting objectives, namely cycle time and the number of workstations, to maximize line efficiency. While such an approach yields to a so-called type-E problem in the line balancing domain, the proposed nondominated sorting ant colony optimization (NSACO) approach provides a set of solutions dominating others in terms of both objectives (pareto front solutions). The solution which has the highest line efficiency among pareto front solutions is then determined as the best solution. An additional performance criterion is also applied when two different solutions have the same values for both objectives. The solution which has the smoother workload distribution is favoured when both criteria are the same. NSACO is described and a numerical example is provided to exhibit its running mechanism. The performance of the algorithm is tested through test problems in two conditions, i.e. incompatible task sets are considered and not considered, and computational results are presented for the first time. The results indicate that NSACO has a promising solution capacity., İki-taraflı montaj hatları otomotiv endüstrisinde otobüs, kamyon ve otomobil gibi geniş hacimli ürünlerin üretiminde yoğunlukla kullanılmaktadır. Karışık modelli hatlar ise üreticilere müşterilerin kişiselleştirilmiş talebini uygun maliyetle ve istenen kalitede ulaştırmak için yardımcı olmaktadır. Bu çalışma uyumsuz iş gruplarını içeren karışık-modelli iki taraflı montaj hatlarını konu almaktadır ve hat etkinliğini maksimize etmek için birbiriyle çelişen iki amacı (çevrim zamanı ve istasyon sayısı) minimize eden yeni bir yöntem önermektedir. Böyle bir yaklaşım montaj hattı alanında tip-E olarak adlandırılan probleme işaret etse de önerilen bastırılmamış sınıflandırmalı karınca koloni algoritması (NSACO) diğer çözümleri her iki amaç açısından da bastıran çözüm seti sunmaktadır (pareto yüzey çözümler). Çözümler arasından en yüksek hat etkinliğine sahip olanı en iyi çözüm olarak belirlenmektedir. İki farklı çözüm her iki amaç açısından da aynı değerlere sahip olduğu zaman, ilave bir performans kriteri uygulanmaktadır. Her iki amaç da aynı değerlere sahip olduğu zaman daha düzgün iş yükü dağılımına sahip olan çözüm tercih edilmektedir. NSACO tanımlanmıştır ve çalışma prensibi bir sayısal örnek üzerinden anlatılmıştır. Algoritmanın performansı, uyumsuz iş seti kısıtlarını dikkate alarak ve almayarak iki durum altında test edilmiştir ve araştırma sonuçları ilk defa sunulmuştur. Sonuçlar göstermektedir ki NSACO ümit verici çözüm kapasitesine sahiptir.

Thanks to their interesting optical and electrical properties, conductive polymers are one of the materials to have highest potential utility in technological applications. But theirs usage in practical applications are limited due to poor solubility, cannot be easily processed and lack of good mechanical strength and stability. In this work synthesis of conductive polymer was achieved in environmentally friendly aqueous dispersion of polystyrene sulfonic acid instead of harmful organic solvent (dichloromethane, acetonitrile, chloroform,). Thus, a water-insoluble monomer was polymerized in an aqueous medium instead of organic solvents which are harmful to environment and human health. Also, conductive polymer obtained in aqueous medium has superior optical and electrical properties than the conductive polymer obtained in the presence of organic solvents. This paper has been shown that other conductive polymers synthesized in hazardous organic solvents can be synthesized in aqueous media with superior optic and electrical properties which is important for the technological application.

This paper presents a computer aided detection (CAD) system which uses wiener filter based approach for detection of defects in poplin fabric. The defective fabric images are taken with the help of the digital camera. The developed system consists of three phases, including preprocessing, segmentation and detection of fabric defect In preprocessing phase, a RGB to gray level conversion and image enhancement operations were applied to digital camera images. In segmentation phase, background of the gray level image segmented using morphologic operations. Then, segmented image was converted to binary image to facilitate fabric defect detection process. Fabric defect detection was performed using wiener filter in the detection phase of the system. Wiener filter is applied to binary level image to eliminate structures which are not defect The developed detection system applied on defective poplin images for detection. The obtained results on different kinds of fabric defects show that the proposed algorithm gives promising results.

The effect of the unmodeled dynamics and unknown disturbances prevent the accurate control of the real-time systems. The designed controllers must undertake the effect of these undesired uncertainties. In this paper, adaptive uncertainty modeling based model predictive controller is proposed for the control of uncertain linear systems. The uncertainty modeling structure uses an artificial neural network with adaptive learning rate for fast approximation. The stability of the proposed adaptive uncertainty modeling based model predictive control (UMPC) is shown using Lyapunov candidate function. Conventional MPC and proposed UMPC are applied to the control of a real-time DC/DC buck power converter. The conventional MPC cannot accurately control the DC/DC converter due to the unknown parameters and unmodeled dynamics. However, the proposed UMPC controller can accurately control the system with modeling the uncertainties in controller dynamics. The proposed controller is promising to control uncertain systems in future applications.