Solving machine loading problems in a flexible manufacturing system using a genetic algorithm based heuristic approach

The machine-loading problem of a flexible manufacturing system (FMS) has been recognized as one of the most important planning problems. In this research, a Genetic Algorithm (GA) based heuristic is proposed to solve the machine loading problem of a random type FMS. The objective of the loading problems is to minimize the system unbalance and maximize the throughput, satisfying the technological constraints such as availability of machining time, and tool slots. The proposed GA-based heuristic determines the part type sequence and the operation-machine allocation that guarantee the optimal solution to the problem, rather than using fixed predetermined part sequencing rules. The efficiency of the proposed heuristic has been tested on ten sample problems and the results obtained have been compared with those of existing methods.     

Manganese–Schiff base complex immobilized silica materials for electrocatalytic oxygen reduction

Curtailment of platinum catalysts loading in fuel cell is a recent central issue. As substitutes, these days several organic metal chelate compounds having featured moieties of M–N₄ or M–N₂O₂ (M = transition metal ion) are being used as cathode catalysts in fuel cells. Here, in this study, we report in detail the electrocatalytic activity of manganese–Schiff base complexes for oxygen reduction reaction in 0·05 M HClO₄ at room temperature. Actually, [Mn(salen)]⁺: [N,N′-bis(salicylaldehyde) ethylenediimino manganese(III)]⁺ and [Mn(salophen)]⁺: [N,N′-bis(salicylaldehyde)-1,2-phenylenediimino manganese(III)]⁺ were introduced into/onto the MCM-41 type silica spheres and used for the electrocatalytic reduction of oxygen. Synthesized materials were characterized by UV–Vis, FT–IR and electrochemical techniques. Significant low overpotential for oxygen reduction in 0·05 M HClO₄ on [Mn(salen)]⁺- and [Mn(salophen)]⁺-incorporated silica-modified glassy carbon electrodes was observed.     

Optimization of fermentation condition for co-production of ethanol and 2,3-butanediol (2,3-BD) from hemicellolosic hydrolysates by Klebsiella oxytoca XF7

Microbial production of ethanol and 2,3-butanediol (2,3-BD) from agro-residues has been attracting interest because of their applications in various industries, including generation of biofuel molecules. In the present investigation, the hemicellulosic fraction of corncob was hydrolyzed by indigenous holocellulase from novel psychrotolerant Aspergillus niger SH3 resulting in high xylose release (34.61?g?L^?1), followed by the bioconversion of xylose to ethanol and 2,3-BD. Taguchi design was adopted to optimize the process which resulted in 5.25- and 3.31-fold increase in 2,3-BD (12.18?±?0.53?g?L^?1) and ethanol (4.08?±?0.03?g?L^?1), as compared with un-optimized condition. For the first time, co-production of ethanol and 2,3-BD from the corncob hemicellulosic hydrolysate was performed using a newly isolated Klebsiella oxytoca XF7 strain, under the optimized fermentation conditions. These results suggest that K. oxytoca XF7 is a promising candidate for co-production of ethanol and 2,3-BD, with high xylose conversion efficiency (96.65%), facilitating the economical production of biofuel molecules.     

Inactivation efficacy of plasma-activated water: influence of plasma treatment time,exposure time and bacterial species

This study aimed to evaluate the influence of plasma treatment time, bacterial exposure time to PAW and bacterial species on the inactivation efficacy of plasma-activated water (PAW), with additional investigation of the inactivation mechanisms of PAW. Six bacterial species, including Listeria innocua, Staphyloccus aureus, Escherichia coli, Pseudomonas fluorescens, Shewanella putrefaciens and Aeromonas hydrophila were selected as the representative bacteria. The initial bacterial concentration was around 7 log CFU ml⁻¹ after mixing with PAW, and the inactivation efficacy was measured after different exposure times during the 4 °C storage. Scanning electron microscopy (SEM) images of the bacteria after PAW treatment were carried out to inspect the cell structure damage, and physicochemical properties of PAW, including pH, conductivity and long-living reactive species of H₂O₂, , and , were examined. The results showed that the inactivation efficacy of PAW was positively correlated with plasma treatment time and bacterial exposure time, and for the species examined in this study, the Gram-negative species were more sensitive to PAW than the Gram-positive species. Cell structure damage, including shrinkage, distortion, or holes, was observed after PAW treatment. The pH of PAW was acidified to 2.5–2.9, and conductivity was significantly increased to 518.0 μs cm⁻¹. and H₂O₂ were reduced during the 48 h storage, while an increased concentration was observed for . This study demonstrated that the processing parameters of plasma treatment time, exposure time and characteristics of bacteria can significantly affect the inactivation efficacy of PAW.     

A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

Real-time sensing plays an important role in ensuring the reliability of industrial wireless sensor networks (IWSNs). Sensor nodes in IWSNs have inherent limitations that give rise to different anomalies in the network. These anomalies can lead to disastrous and harmful situations or even serious system failures. This article presents a formulation to the design of an anomaly detection scheme for detecting the anomalous node along with the type of anomaly. The proposed scheme is divided into two major parts. First, spatiotemporal correlation within a cluster is obtained for the normal and anomalous behavior of sensor nodes. Second, the multilevel hybrid classifier is used by combining the sequential minimal optimization support vector machine (SMO-SVM) as a binary classifier with optimally pruned extreme learning machine (OP-ELM) as a multiclass classifier for detection of an anomalous node and type of anomalies, respectively. Mahalanobis distance-based lightweight K-Medoid clustering is used to build a new set of training datasets that represents the original training dataset, by significantly reducing the training time of a multilevel hybrid classifier. Results are analyzed using standard WSN datasets. The proposed model shows high accuracy, i.e., 94.79% and detection rate, i.e., 94.6% with a reduced false positive rate as compared to existing hybrid methods.     

Dietary exposure assessment of β-glucan in a barley and oat based bread

The objective of this study was to develop a β-glucan human exposure assessment model for a barley and a oat based bread and to compare the resulting exposure to the current FDA recommendation for a health promoting effect (3 g β-glucan/day, 0.75 g/portion of β-glucan). Three formulated barley and oat based breads with 30% (S1), 50% (S2) and 70% (S3) substitution of wheat flour were used in the Monte Carlo simulation model to predict human consumption levels. The level of soluble β-glucan was found to reach 0.77 g/portion for some barley and oat based breads with a substitution level of S3. Under normal consumption patterns, consumption of barley based bread can meet up to 50% of the FDA recommended intake with S1, 70% with S2, and 100% with S3, whereas by consuming an oat based bread the FDA recommended intake is met 30% with S1, 50% with S2 and 70% with S3. The model predicted that total cholesterol (TC) lowered with an increase intake of β-glucan content from ?0.27 to ?0.30 mmol/l and ?0.18 to ?0.29 mmol/l from S1 to S3 for barley and oats based bread, respectively. No significant change was noted for the blood glucose level.     

On electromagneto-thermoelastic plane waves under Green–Naghdi theory of thermoelasticity-II

The present work attempts to investigate the propagation of one-dimensional electromagneto-thermoelastic plane waves in an isotropic unbounded thermally and electrically conducting media with finite conductivity in the context of the theory of thermoelasticity of Green and Naghdi type-II. The heat conduction equation is affected with the Thomson coe?cient. Basic governing equations are modified by using Green–Naghdi theory of type-II. Our problem formulation derives two different systems. The first system is found to be coupled with the thermal field and represents the longitudinal wave. However, the second system represents transverse wave that is uncoupled with the thermal field. In both the cases, we identify waves that are affected with the magnetic field. Asymptotic expansions of dispersion relation solutions and various components of plane waves such as phase velocity, specific loss, and penetration depth are derived analytically for high- and low-frequency values in all cases. Analytical results predicting the limiting behavior of longitudinal and transverse waves are verified with the numerical results. The results of the present study are compared with the results of the thermoelastic case, and a detailed analysis of the effects of presence of the magnetic field under this theory has been presented.     

Thermal performance and embodied energy analysis of a passive house – Case study of vault roof mud-house in India

This paper investigates thermal performance of an existing eco-friendly and low embodied energy vault roof passive house (or mud-house) located at Solar Energy Park of IIT Delhi, New Delhi (India). Based on embodied energy analysis, the energy payback time for the mud-house was determined as 18 years. The embodied energy per unit floor area of R.C.C. building (3702.3 MJ/m²) is quiet high as compared to the mud-house (2298.8 MJ/m²). The mud-house has three rooms with inverted U-shape roof and remaining three rooms with dome shape roof. A thermal model of the house consisting of six interconnected rooms was developed based on energy balance equations which were solved by using fourth order Runge Kutta numerical method. The predicted six room air temperatures were found in good agreement with the experimental observed data on hourly basis in each month for one year. The annual heating and cooling energy saving potential of the mud-house was determined as 1481 kW h/year and 1813 kW h/year respectively for New Delhi composite climate. The total mitigation of CO₂ emissions due to both heating and cooling energy saving potential was determined as 5.2 metric tons/year. The annual carbon credit potential of mud-house was determined as € 52/year. Similar results were obtained for the different climatic locations in India.