Effective allocation of customers to distribution centres: A multiple ant colony optimization approach

The global and competitive business environment has identified the importance of a quick and efficient service towards the customers in the past few decades. Distribution centre (DC) plays an important role in maintaining the uninterrupted flow of goods and materials between the manufacturer and customers. The performance of the supply chain network can be easily improved by an effective or balanced allocation of customers to DCs. Improper or unbalanced allocation of customers can lead to the under- or overutilization of facilities and can further deteriorate the customer service. Performance of the DC can be judged on the basis of its ability to provide the right goods, at the right time and at the right place. The lead time or transit time to deliver the goods to the customers is an important parameter for the measuring the efficiency and effectiveness of a particular DC in a supply chain. In this paper, a multiple ant colony optimization (MACO) approach is discussed in an effort to design a balanced and efficient supply chain network that maintains the best balance of transit time and customers service. The focus of this paper is on the effective allocation of the customers to the DCs with the two-fold objective of minimization of the transit time and degree of imbalance of the DCs. MACO technique is a modified form of the traditional ant colony system, where multiple ant colonies cooperate with each other to find the best possible customer allocation pattern for the DC. The proposed technique shows better performance because of its nature of considering both positive and negative feedback in search of optimum or near-optimum results. The developed algorithm based on the proposed approach is tested on a real practical problem and the results are discussed in this paper.     

Synthesis and Characterization of Spark Plasma Sintered FeAl and In situ FeAl–Al2O3 Composite

In the present work, nanocrystalline FeAl and FeAl–Al₂O₃ composite were synthesized by high energy ball milling and subsequent compaction by spark plasma sintering. Microstructural changes during all stages of processing are studied using X-ray analysis. After 20 h of milling, the disordered FeAl and some amount of Fe rich solid solution was obtained in both of these compositions. Subsequent heat treatment results in formation of ordered FeAl. However, disordering of FeAl was observed in both compositions after spark plasma sintering. Nanocrystallinity is retained in both the compositions even after sintering at high temperature of 1,000 °C. Very high hardness of ~575 HV₁ and ~600 HV₁ was exhibited by FeAl and FeAl–Al₂O₃ composite.     

The role of interface structure in spallation of a layered nanocomposite

Interfaces in nanostructured materials play a central role in endowing some extraordinary properties to certain nanolayered composites. Here, we examine how interfaces influence spallation under extreme strain-rate loading using atomistic simulations, and illustrate how even at the picosecond-scale the interface structure, or lack thereof, governs dynamic fracture.     

Surface runoff estimation over heterogeneous foothills of Aravalli mountain using medium resolution remote sensing rainfall data with soil conservation system‐curve number method: A case of semi‐arid ungauged Manesar Nala watershed

Manesar Nala watershed, having an aerial extent of 71.53 km², was subjected to modelling of its hydrological behaviour for assessing its water resource potential. Modern tools and techniques of Remote Sensing (RS) and Geographic Information System (GIS) were used for assessment of runoff generating potential using the Hydrologic Soil Cover Complex (HSCC) Method [U.S. Department of Agriculture (USDA)‐Soil Conservation System‐Curve Number (SCS‐CN) approach]. RS and GIS were used in generation and integration of thematic maps [such as Land use/Land cover (using LISS‐III data) and Hydrologic Soil Group (HSG), (using soil map of study area) to derive the Curve Number (CN) for simulating Runoff (R_o)]. The daily rainfall (P) data for the study period 2002–2015 were acquired from NOAA Climate Prediction Center (NCPC). Corresponding R_o from the watershed for intense storm events for 14 years were calculated through RS and GIS. GIS and SCS‐CN model was employed for modelling the runoff production to study its hydrological behaviour. The study showed that the Manesar Nala watershed was having a composite Curve Number – II (CN_II) value of 82.5 for normal conditions. For dry and wet conditions these values were estimated at 66.44 (CN_I) and 91.56 (CN_III), respectively. This investigation showed that Manesar Nala watershed exhibited an annual average (of 14 years, 2002–2015) R_o volume of 4 542 514.37 m³ based on the average annual rainfall (P) of 0.72 m (720 mm). The average annual surface runoff (R_o) was predicted to be approximately 0.21 m with annual runoff coefficient (C_R) of 0.29. During the study, we also found a strong correlation ‘r’ between satellite driven P and R_o from NRCS‐CN method of the order of 0.94. The methodology so developed has the potential to be used in other similar ungauged watersheds in the same agro‐climatic conditions for the purpose of planning of watershed conservation measures and other developmental activities.     

Imprinting localized plasmons for enhanced solar cells

Imprinted silver nanovoid arrays are investigated via angle-resolved reflectometry to demonstrate their suitability for plasmonic light trapping. Both wavelength-?and subwavelength-scale nanovoids are imprinted into standard solar cell architectures to achieve nanostructured metallic electrodes which provide enhanced absorption for improving solar cell performance. The technique is versatile, low-cost and scalable and can be applied to a wide range of organic semiconductors. Absorption features which are independent of incident polarization and weakly dependent on incident angle reveal localized plasmonic modes at the structured interface. Metallic nanostructure-PCPDTBT:PCBM samples demonstrate absorption enhancements of up to 40%. The structured interface provides light trapping, which boosts absorption at wavelengths where the semiconductors absorb poorly.     

LSI implementation of a low-power 4×4-bit array two-phase clocked adiabatic static CMOS logic multiplier

As the density and operating speed of complementary metal oxide semiconductor (CMOS) circuits increases, dynamic power dissipation has become a critical concern in the design and development—of personal information systems and large computers. The reduction of supply voltage, node capacitance, and switching activity are common approaches used in conventional CMOS. In adiabatic switching circuits, the current flow through transistors can be significantly reduced by ensuring uniform charge transfer over the entire available time. This paper presents the simulation of this current in two-phase clocked adiabatic static CMOS logic (2PASCL) and conventional CMOS. From the SPICE simulations, at transition frequencies from 1 to 12 MHz, a 4×4-bit array 2PASCL multiplier shows a maximum reduction in power dissipation of 77% relative to that of a static CMOS. The measurement results of a 4×4-bit array 2PASCL multiplier demonstrate a 57% reduction compared to a 4×4-bit array two-phase clocked adiabatic dynamic CMOS logic (2PADCL). These results indicate that 2PASCL technology can be advantageous when applied to low-power digital devices operated at low frequencies, such as radio-frequency identification (RFID) tags, smart cards, and sensors.     

Recovery of pyridine from water by pervaporation using filled and crosslinked EPDM membranes

Organoselective membrane was prepared from ethylene propylene diene monomer (EPDM) rubber. Crosslinked EPDM rubber was filled with 2, 4 and 6 wt% N330 carbon black filler to produce three different filled membranes designated as EPDMCV2, EPDMCV4 and EPDMCV6, respectively. These filled rubber membranes were used for pervaporative recovery of low concentration of pyridine from water. These filled membranes were characterized by crosslink density, SEM, XRD and mechanical properties. Sorption thermodynamics were discussed. Partial permeability, intrinsic membrane selectivity and diffusion coefficients of solvents were also determined. The filled membranes showed much higher pyridine selectivity than most of the membranes reported for similar system.     

High Temperature Corrosion Behavior of Cold Spray Ni-20Cr Coating on Boiler Steel in Molten Salt Environment at 900 °C

Cold spray is an emerging technology that produces high density metallic coatings with low oxide contents and high thermal conductivity, which makes them ideal for high temperature corrosion resistance. In the current investigation, Ni-20Cr alloy powder was deposited on SA 516 boiler steel (0.19C-1.07Mn-0.020S-0.25P-0.010Si-balance Fe) by cold spray process. Oxidation kinetics was established for the uncoated and cold spray Ni-20Cr coated boiler steel in an aggressive environment of Na₂SO₄-60%V₂O₅ at 900 °C for 50 cycles by the weight change technique. X-ray diffraction, FE-SEM/EDAX, and x-ray mapping techniques were used to analyze the oxidation products. Uncoated steel suffered corrosion in the form of intense spalling and peeling of its oxide scale, which may be due to the formation of unprotective Fe₂O₃ oxides. The Ni-20Cr coating was successful in reducing the weight gain of the steel by 87.2% which may be due to the formation of oxides of nickel and chromium.     

Automatic recognition of machining features from a solid model using the 2D feature pattern

Feature recognition systems are now widely identified as a cornerstone for conceiving an automated process planning system. Various techniques have been reported in the literature, but a few of them acquired a status of generic methodology. A flexible and robust approach is demanded for recognising a wide variety of features, e.g., non-interacting, interacting circular and slanting features. This research aims to exploit the concept of the ray - firing technique, in which a 2D surface pattern for each feature is generated and information is extracted from these patterns to correlate it with the corresponding machining features. The system first defines a virtual surface and then probing rays are dropped from each point of this surface to the 2.5D features of the B-rep solid model. According to the length of rays between the bottom face of the 2.5D machining features and the virtual surface, 2D feature patterns are formed for each machining feature. Finally, features are recognised using an algorithm described in this article. Different types of examples have been considered to demonstrate the effectiveness of the proposed approach.