A fuzzy grey goal programming approach for aggregate production planning

Aggregate planning is a medium-range capacity planning that suggests the production strategies in order to meet the forecasted demand considering the capacity constraints. As the period of planning length increases, the uncertainty of information will grow. Regarding this point, in this paper, a multi-objective model is proposed for aggregate planning problem in which the parameters of the model are expressed in the form of grey numbers. The suggested grey multi-objective model is solved based on a goal programming problem with fuzzy aspiration levels. The model is applied in a real-world problem, and its results are illustrated. The obtained results give a range for decision variables, and decision makers can handle the inevitable uncertainty of information by using these ranges.     

Synthesis of nano-crystalline (Ni/NiO)–YSZ by microwave-assisted combustion synthesis method: The influence of pH of precursor solution

Microwave-assisted combustion synthesis can be used to synthesize the nano-crystalline (Ni/NiO)–YSZ composites. In this study nano-crystalline powders were prepared by combustion synthesis process in a microwave oven. The influence of pH value of the precursor solution on the combustion behavior and phase formation of synthesized powders were investigated by X-ray diffraction technique (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), thermal analysis (DTA/TGA), infrared (IR) spectroscopy, and BET surface area analysis. The results show that by increasing pH value, the combustion rate decreases. The as-burnt powder prepared with pH 0.5 has a higher crystallite size (32 nm). Furthermore, FTIR studies show that the glycine monodentate complex convert to bidentate complex with increasing pH.     

Effects of dielectric substrate thickness on plasma immersion ion implantation

A one-dimensional plasma fluid model is developed for investigating the effects of dielectric substrate thickness on plasma immersion ion implantation. By considering the effects of secondary electron emission from the dielectric substrate and using finite difference schemes, evolution of plasma sheath, ion fluence and dielectric surface potential versus time and substrate thickness are evaluated. It was demonstrated that with the increasing dielectric thickness, sheath width and ion fluence over the dielectric surface decrease and surface potential reduces. These effects can be attributed to the accumulation of positive ions and ejection of secondary electrons from the dielectric surface and thereby lessening the strength of the electric field over the dielectric substrate. It is also shown that the secondary electrons have a profound effect on implantation results and must be considered in plasma immersion ion implantation of dielectric materials.     

Effects of strong magnetic field on plasma immersion ion implantation of dielectric substrates

In this paper the effects of a strong magnetic field on plasma immersion ion implantation (PHI) of dielectric substrates were investigated. A plasma fluid model and finite difference schemes were used to simulate a one-dimensional system of plasma immersion ion implantation. The effect of secondary electron emission from the electrode on PHI was also taken into consideration. It was found that the magnitude and direction of the magnetic field have slight effects on sheath thickness but have considerable effects on current densities in the y and z directions which are perpendicular to the direction of the electric field (the x direction). The simulations showed that the current densities in the y and z directions increased significantly with increasing magnitude of the magnetic field at a given fixed angle, the reason being attributed to the rotational force exerted on the ions by the magnetic field. With a fixed magnetic field, increasing the angle of the magnetic field, θ, with respect to the electric field produced a continuous increase in current density in the y direction from zero to its maximum at θ = 90° but the current density in the z direction could be described as saddle-shaped being zero at both ends.     

Combined role of SiC whiskers and graphene nano-platelets on the microstructure of spark plasma sintered ZrB2 ceramics

This research explores the sintering behavior and microstructure of ZrB₂-based materials containing graphene nano-platelets (GNPs) and SiC whiskers (SiC_w). Spark plasma sintering (SPS) process at 1900 °C was implemented to sinter the specimen, leading to a composite with 100% relative density. High-resolution transmission electron microscopy (HRTEM), field emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), field emission-electron probe microanalyzer (FE-EPMA), and high-resolution X-ray diffractometry (HRXRD) were employed to study the SPSed sample, along with the thermodynamics predictions. According to the HRXRD result and microstructural observations, the sintering process was non-reactive, which was endorsed with the XPS analysis. Furthermore, graphene presented a beneficial role for eradicating the oxide impurities in the sample during the sintering. Such oxide impurities were reduced to the original phases of SiC and ZrB₂, contributing to porosity removal. Nanostructural investigations revealed the formation of ultrathin amorphous interfaces (~10 nm) between ZrB₂/graphene phases, disordered atomic planes in graphene platelets, and dislocations in ZrB₂ grains. One reason for generating crystalline defects in the microstructure was found out to be the mismatches amongst the elastic properties of the available compounds in the system.     

Modeling of Free Chlorine Consumption and Escherichia coli O157:H7 Cross‐Contamination During Fresh‐Cut Produce Wash Cycles

Controlling the free chlorine (FC) availability in wash water during sanitization of fresh produce enhances our ability to reduce microbial levels and prevent cross‐contamination. However, maintaining an ideal concentration of FC that could prevent the risk of contamination within the wash system is still a technical challenge in the industry, indicating the need to better understand wash water chemistry dynamics. Using bench‐scale experiments and modeling approaches, we developed a comprehensive mathematical model to predict the FC concentration during fresh‐cut produce wash processes for different lettuce types (romaine, iceberg, green leaf, and red leaf), carrots, and green cabbage as well as Escherichia coli O157:H7 cross‐contamination during fresh‐cut iceberg lettuce washing. Fresh‐cut produce exudates, as measured by chemical oxygen demand (COD) levels, appear to be the primary source of consumption of FC in wash water, with an apparent reaction rate ranging from L/mg·min for all produce types tested, at stable pH levels (6.5 to 7.0) in the wash water. COD levels increased over time as more produce was washed and the lettuce type impacted the rate of increase in organic load. The model parameters from our experimental data were compared to those obtained from a pilot‐plant scale study for lettuce, and similar reaction rate constant (5.38 × 10^-4 L/mg·min) was noted, supporting our hypothesis that rise in COD is the main cause of consumption of FC levels in the wash water. We also identified that the bacterial transfer mechanism described by our model is robust relative to experimental scale and pathogen levels in the wash water. Finally, we proposed functions that quantify an upper bound on pathogen levels in the water and on cross‐contaminated lettuce, indicating the maximum potential of water‐mediated cross‐contamination. Our model results could help indicate the limits of FC control to prevent cross‐contamination during lettuce washing.     

Distributed system of autonomous buoys for scalable deployment and monitoring of large waterbodies

The design, construction, and testing of a large distributed system of novel, small, low-cost, autonomous surface vehicles in the form of self-propelled buoys capable of operating in open waters is reported. We detail the successful testing of collective behaviors of systems with up to 50 buoys, achieving scalable deployment and dynamic monitoring in unstructured environments. This constitutes the largest distributed multi-robot system of its kind reported to date. We confirm the robustness of the system to the loss of multiple units for different collective behaviors such as flocking, navigation, and area coverage. For dynamic area monitoring, we introduce a new metric to quantify coverage effectiveness. Our system exhibits near optimal scalability for fixed target areas and a high degree of flexibility when the shape of the target changes with time. This system demonstrates the potential of distributed multi-robot systems for the pervasive and persistent monitoring of coastal and inland water environments.     

A Rapid Photopatterning Method for Selective Plating of 2D and 3D Microcircuitry on Polyetherimide

In this work, a method for the rapid synthesis of metallic microtracks on polyetherimide is presented. The method relies on the photosynthesis of silver nanoparticles on the surface of the polymer substrates from photosensitive silver chloride (AgCl), which is synthesized directly on the polyetherimide surface. The study reveals that the use of AgCl as a photosensitive intermediate accelerates the reactions leading to the formation of silver nanoparticles by up to two orders of magnitude faster than other photodecomposition schemes. The patterning can be conducted under blue light, with notable advantages over UV exposure. Polymers of significant interest to the microelectronics and 3D printing industries can be directly patterned by light using this photography‐inspired technique at throughputs high enough to be commercially advantageous. Light exposures as short as a few seconds are sufficient to allow the direct metallization of the illuminated polyetherimide surface. The results show that the silver required for the seed layer is minimal, and the later copper electroless plating results in the selective growth of conductive tracks for circuitry on the light‐patterned areas, both on flexible films and 3D printed surfaces.     

Trade‐offs in integer data envelopment analysis

If production trade‐offs—which represent simultaneously feasible exchanges in the inputs and outputs of decision‐making units (DMUs)—are added to an integer production possibility set (IPPS), a new IPPS is produced; conventional axioms of production do not generate a new IPPS, however. This paper develops the axiomatic foundation for data envelopment analysis (DEA) for integer‐value inputs and outputs in the presence of production trade‐offs by introducing a new axiom of “natural trade‐offs.” First, a mixed‐integer linear programming formula called an integer DEA trade‐off (IDEA‐TO) is presented for computing efficiency scores and reference points. The numeration algorithm (NA) method presented in this concept is improved, and an improved numeration algorithm (INA) method for solving integer DEA (IDEA) models is developed. Finally, comparison between the two methods and a generalized INA method for solving the IDEA‐TO model are presented.