Non-dominated ranked genetic algorithm for a multi-objective mixed-model assembly line sequencing problem

The increasing market demand for product variety forces manufacturers to design mixed-model assembly lines (MMAL) on which a variety of product models similar to product characteristics are assembled. This paper presents a method combining the new ranked based roulette wheel selection algorithm with Pareto-based population ranking algorithm, named non-dominated ranking genetic algorithm (NRGA) to a just-in-time (JIT) sequencing problem when two objectives are considered simultaneously. The two objectives are minimisation the number of setups and variation of production rates. This type of problem is NP-hard. Various operators and parameters of the proposed algorithm are reviewed to calibrate the algorithm by means of the Taguchi method. The solutions obtained via NRGA are compared against solutions obtained via total enumeration (TE) scheme in small problems and also against four other search heuristics in small, medium and large problems. Experimental results show that the proposed algorithm is competitive with these other algorithms in terms of quality and diversity of solutions.     

Graph-neural network approach in cellular manufacturing on the basis of a binary system

In the past several years, many studies have been carried out on cellular manufacturing. Group technology is a manufacturing philosophy in which similar parts are identified and grouped together to take advantage of their similarities in manufacturing and design. The main problem in the development of cellular manufacturing is that of cell formation. In this paper, a graph-neural network approach is given for cell formation problems in group technology. Effort has been made to develop an algorithm that is more reliable than conventional methods. A graph-neural network has the advantages of fast computation and the ability to handle large scale industrial problems without the assumption of any parameter and the least exceptional elements in the presence of bottleneck machines and/or bottleneck parts. Two examples from the literature have been solved to demonstrate the advantages of the algorithm.     

A DEA approach for comparing solution efficiency in U-line balancing problem using goal programming

Line balancing problem plays an important role in the decision making process to increase efficiency and productivity. Recently, U-shaped layout in many production lines has replaced the traditional straight line layout using just-in-time concept. Here, we propose a model, using multi-objective decision making approach to the U-shaped line balancing problem, to offer enhanced decision maker flexibility, by allowing for conflicting goals. The assembly line operation efficiency is the most significant aim in our study, and this efficiency relates to management of resources and the solution of line balancing problem. First, the U-shaped line balancing problem is solved considering the model's goals. Then, the index function of assembly line balancing is determined and the efficiencies of the optimal solution outputs are evaluated using data envelopment analysis (DEA). Finally, the discrimination weakness and distribution of illogical weight in simple DEA models are resolved using a mixed method.     

Thermal behavior and entropy generation rate analysis of a viscous flow in MHD micropumps

Studying the effects of various parameters on the behavior of velocity, temperature and thus the entropy generation rate in the microfluidic systems to reduce loss power is very important. Minimization of entropy generation in the flow system enables us for the parametric optimization of the MHD micropumps operation. In the present study, a transient, laminar and fully developed electrically conductive fluid flow in MHD micropumps has been investigated and the temperature distribution and effects of dimensionless influencing parameters on the entropy generation rate has been presented. Pumping operator in MHD micropumps are the Lorentz forces, which is produced as a result of the interaction between magnetic and electric fields. Governing equations have been solved numerically using finite-difference (ADI) method. The results of simulation have shown good agreement with analytical results by ei-genfunction expansion method. In addition, the results are compared with experimental data from literature which confirms the accuracy of the model. The obtained results showed that aspect ratio, Hartman, Prandtl, Eckert numbers and Joule heating parameter have significant influences on the flow and temperature distribution as well as entropy generation rate in MHD micropumps that controlling them can lead us for optimized operation of MHD micropumps.

     

On the dispersion of CNTs in polyamide 6 matrix via solution methods: assessment through electrical, rheological, thermal and morphological analyses

In this study, polyamide 6 (PA 6)/multi-walled carbon nanotube (MWCNT) nanocomposites were prepared by different solution methods based on phase inversion, drop-casting and simple evaporation processes. Optical microscopy and field emission scanning electron microscopy techniques were used to investigate the dispersion states of the nanotubes in PA 6 matrix. The results indicated that the dispersion state of MWCNTs in the nanocomposites prepared by the phase inversion-based method was better than those in the nanocomposites prepared by the other two methods. Electrical, rheological, differential scanning calorimetry and thermo-gravimetric analysis measurements showed that the PA 6/MWCNTs nanocomposites prepared by the phase inversion-based method had higher electrical conductivity, storage modulus, crystallization temperature and thermal stability in comparison with those prepared by the other two methods, attributed to the better dispersion state of MWCNTs. These results confirmed achievement of a good dispersion state of MWCNTs within PA 6 matrix by the phase inversion-based efficient approach.     

Lipase-catalyzed synthesis and characterization of flaxseed oil-based structured lipids

The biosynthesis of structured lipids (SLs) was carried out by the interesterification of flaxseed oil (FO) and tricaprylin (TC) in an organic solvent medium (OSM), using selected commercial lipases, including Amano DF, Novozym 435, Lipozyme TL-IM and Lipozyme RM-IM. The fatty acyl chains of the synthesized triacylglycerols (TAGs) were identified by atmospheric pressure chemical ionization/mass spectrometric (APCI/MS) analysis, while the fatty acid positional distribution of the MLM- and MML-SLs (M-medium and L-long chain fatty acids) was determined by silver-ion high-performance liquid chromatographic (Ag⁺/HPLC) analysis. The effects of reaction temperature (T_r, 30–50 °C), enzyme concentration (E_c, 0.5–4%, w/v), initial water activity (a_w, 0.05–0.43) and reaction time (R_t, 0–72 h) on the efficiency of the enzymes, were studied. The bioconversion yield (%) of the synthesized MLM- and MML-SLs was monitored under the established reaction parameters for each lipase. The maximum yield of MLM-SLs was obtained in the order, of Novozym 435 > Lipozyme TL-IM > Lipozyme RM-IM > Amano DF. Moreover, considering the ratio of the MLM- to MML-SLs produced by each enzyme, Novozym 435 and Lipozyme TL-IM were selected as the most effective enzymes for interesterification of FO and TC.     

Influence of Growth Conditions on Magnetite Nanoparticles Electro-Crystallized in the Presence of Organic Molecules

Magnetite nanoparticles were synthesized by electrocrystallization in the presence of thiourea or sodium butanoate as an organic stabilizer. The synthesis was performed in a thermostatic electrochemical cell containing two iron electrodes with an aqueous solution of sodium sulfate as electrolyte. The effects of organic concentration, applied potential and growth temperature on particle size, morphology, structure and magnetic properties were investigated. The magnetite nanoparticles were characterized by X-ray diffraction, electron microscopy, magnetometry and Mössbauer spectrometry. When the synthesis is performed in the presence of sodium butanoate at 60 °C, a paramagnetic ferric salt is obtained as a second phase; it is possible to avoid formation of this phase, increase the specific magnetization and improve the structure of the oxide particles by tuning the growth conditions. Room-temperature magnetization values range from 45 to 90 Am²kg⁻¹, depending on the particle size, type of surfactant and synthesis conditions. Mössbauer spectra, which were recorded at 290 K for all the samples, are typical of nonstoichiometric Fe_3−δO₄, with a small excess of Fe³⁺, 0.05 ≤ δ ≤ 0.15.     

Effect of Fiber Acid Treatment on the Dynamic Mechanical Properties of Unsaturated Polyester/Carbon Fiber Unidirectional Composites

In this study, the surface modification of carbon fiber by sulfuric acid is investigated. Atomic Force Microscopy was employed to capture the corresponding changes in the surface roughness of the carbon fiber. Moreover, using treated and untreated fibers, unsaturated polyester unidirectional composite rods were prepared and their flexural properties were determined by three-point bending and dynamic mechanical thermal analysis.

The results indicated that the carbon fiber surface roughness increases in all samples. It is also found that treating the fiber decreases the magnitude of loss modulus. Besides, the flexural strength of composites made of the treated carbon fiber significantly increased.     

A genetic algorithm for the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties

In this paper, we consider the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties, with no machine idle time. The problem is strongly NP-hard. We proposed a new mathematical model, with non-linear terms and integer variables. We develop a genetic algorithm for solving the problem in medium and large size. The proposed procedure is compared with optimal solutions for the smaller instance sizes. The genetic procedure is also quite close to the optimum and provided an optimal solution for most of the test problems. Numerical examples show that the proposed algorithm is efficient and effective. Scheduling with early and tardy penalties has received extensive attention from the scheduling community because of its practical significance. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides outcomes that prove functional for more complex scheduling areas.