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In seaport industries, vessel arrival delay is inevitable because of numerous factors, e.g. weather, delay due to the previous stop, etc. The period of delay can be as short at 15 min of as long as a few days. This causes disruption to the planned sea operation operations, and more importantly, to the resources utilization. In traditional berth allocation and quay crane assignment problems (BA-QCA), the risk of vessel arrival delay has not been considered. Accordingly, the purpose of this paper is to employ a proactive planning approach by taking into consideration the vessel arrival delay into the optimization of BA-QCA problems.

In the existing BA-QCA problems, vessel arrival time is usually deterministic. In order to capture the uncertainties of arrival delay, this paper models the arrival time as a probability distribution function. Moreover, this paper proposes to model the delay risk by using the period between the expected arrival time and the expected waiting time of a vessel. Lastly, the authors propose a new modified genetic algorithm and a new quay crane assignment heuristic to maximize the schedule reliability of BA-QCA.

A number of numerical experiments are conducted. First of all, the optimization quality of the proposed algorithm is compared with the traditional genetic algorithm for verifying the correctness of the optimization approach. Then, the impact of vessel arrival delay is tested in different scenarios. The results demonstrate that the impact of vessel arrival delay can be minimized, especially in the situations of high vessel to potential berth ratio.

The proposed vessel arrival modeling approach and the BA and QCA approach can increase the operations efficiency of seaports. These approaches can increase the resource utilization by reducing the effect of vessel arrival delay. In other words, this can improve the throughput of seaport terminals.

This paper proposes to minimize the delay risk based on the conditional probability of the vessel completion time based on the previous vessel at the assigned berth. This modeling approach is new in literature.

Powder bed density is a key parameter in powder bed additive manufacturing (AM) processes but is not easily monitored. This research evaluates the possibility of non-invasively estimating the density of an AM powder bed via its thermal properties measured using flash thermography (FT).

The thermal diffusivity and conductivity of the samples were found by fitting an analytical model to the measured surface temperature after flash of the powder on a polymer substrate, enabling the estimation of the powder bed density.

FT estimated powder bed was within 8% of weight-based density measurements and the inferred thermal properties are consistent with literature findings. However, multiple flashes were necessary to ensure precise measurements due to noise in the experimental data and the similarity of thermal properties between the powder and substrate.

This paper emphasizes the capability of Flash Thermography (FT) for non-contact measurement of SS 316 L powder bed density, offering a pathway to in-situ monitoring for powder bed AM methods including binder jetting (BJ) and powder bed fusion. Despite the limitations of the current approach, the density knowledge and thermal properties measurements have the potential to enhance process development and thermal modeling powder bed AM processes, aiding in understanding the powder packing and thermal behavior.

Additive manufacturing (AM) offers substantial flexibility in shape, but much less flexibility in materials and functionality – particularly at small size scales. A system for automatically incorporating microscale components would enable the fabrication of objects with more functionality. The purpose of this paper is to consider the potential of self‐assembly to serve as an automated programmable integration method. In particular, it addresses the ability of random self‐assembly processes to successfully assemble objects with high performance despite the possibility of assembly errors.

A self‐assembled thermoelectric system is taken as a sample system. The performance expectations for these systems are then predicted using modified one‐dimensional models that incorporate the effects of random errors. Monte‐Carlo simulation is used to predict the likely performance of self‐assembled thermoelectric systems and evaluate the impact of key process and system design parameters.

While assembly yield can drop quickly with increasing numbers of assembled parts, large functional assemblies can be constructed by arranging components in parallel to provide redundancy. In some cases, the performance losses are minimal. Alternatively, sensing can be incorporated to identify perfect assemblies. For small assemblies, the probability of perfection may be high enough to achieve an acceptable assembly rate. Small assemblies could then be combined into larger functional systems.

The paper identifies two strategies that can guide the development of AM processes that incorporate miniature components to increase the system functionality. The analysis shows that this may be possible despite significant errors in the self‐assembly process because systems may be tolerant of significant assembly errors.

dding dopants to a powder bed could be a cost-effective method for spatially varying the material properties in laser powder bed fusion (LPBF) or for evaluating new materials and processing relationships. However, these additions may impact the selection of processing parameters. Furthermore, these impacts may be different when depositing nanoparticles into the powder bed than when the same composition is incorporated into the powder particles as by ball milling of powders or mixing similarly sized powders. This study aims to measure the changes in the single bead characteristics with laser power, laser scan speed, laser spot size and quantity of zirconia nanoparticle dopant added to SS 316 L powder.

A zirconia slurry was inkjet-printed into a single layer of 316 SS powder and dried. Single bead experiments were conducted on the composite powder. The line type (continuous vs balling) and the melt pool geometry were compared at various levels of zirconia doping.

The balling regime expands dramatically with the zirconia dopant to both higher and lower energy density values indicating the presence of multiple physical mechanisms that influence the resulting melt track morphology. However, the energy density required for continuous tracks was not impacted as significantly by zirconia addition. These results suggest that the addition of dopants may alter the process parameter ranges suitable for the fabrication of high-quality parts.

This work provides new insight into the potential impact of material doping on the ranges of energy density values that form continuous lines in single bead tests. It also illustrates a potential method for spatially varying material composition for process development or even part optimization in powder bed fusion without producing a mixed powder that cannot be recycled.

In binder jetting, the interaction between the liquid binder droplets and the powder particles defines the shape of the printed primitives. The purpose of this study is to explore the interaction of the relative size of powder particles and binder droplets and the subsequent effects on macro-scale part properties.

The effects of different particle size distribution (5–25 µm and 15–45 µm) of stainless steel 316 L powders and droplet sizes (10 and 30 pL) on part density, shrinkage, mechanical strength, pore morphology and distribution are investigated. Experimental samples were fabricated in two different layer thicknesses (50 and 100 µm).

While 15–45 µm samples demonstrated higher green density (53.10 ± 0.25%) than 5–25 µm samples (50.31 ± 1.06%), higher sintered densities were achieved in 5–25 µm samples (70.60 ± 6.18%) compared to 15–45 µm samples (65.23 ± 3.24%). Samples of 5–25 µm also demonstrated superior ultimate tensile strength (94.66 ± 25.92 MPa) compared to 15–45 µm samples (39.34 ± 7.33 MPa). Droplet size effects were found to be negligible on both green and sintered densities; however, specimens printed with 10-pL droplets had higher ultimate tensile strength (79.70 ± 42.31 MPa) compared to those made from 30-pL droplets (54.29 ± 23.35 MPa).

To the best of the authors’ knowledge, this paper details the first report of the combined effects of different particle size distribution with different binder droplet sizes on the part macro-scale properties. The results can inform appropriate process parameters to achieve desired final part properties.

Solid freeform fabrication processes such as three‐dimensional printing (3DP) and selective laser sintering (SLS) produce porous parts. Metal parts produced by these processes must be densified by sintering or infiltration to achieve maximum material performance. New steel infiltration methods can produce parts of standard alloy compositions with properties comparable to wrought materials. However, the infiltration process introduces dimensional errors due to both shrinkage and creep — particularly at the high temperatures required for steel infiltration. Aims to develop post‐processing method to reduce creep and shrinkage of porous metal skeletons.

The proposed process treats porous metal parts with a nanoparticle suspension that strengthens the bonds between particles to reduce creep and sintering shrinkage during infiltration. The process is tested by comparing the deflection and shrinkage of treated and untreated cantilevers heated to infiltration temperatures. The method is demonstrated with an iron nanoparticles suspension applied to parts made of 410 SS powder.

This process reduced creep by up to 95 percent and shrinkage by 50 percent. The best results were obtained using multiple applications of the nanoparticles dried under a magnetic field. Carbon deposited with the iron is shown to provide substantial benefit, but the iron is critical to establish strong bonds at low temperatures for minimal creep.

This work shows that dimensional stability of porous metal skeletons during infiltration processes can be significantly improved by treatment with nanoparticles. The increased dimensional stability afforded by this technique can combine the excellent properties of homogenous infiltration with substantially improved part accuracy and open up new applications for this manufacturing technology.

The work shows how solid freeform fabrication processes can be improved.

Staff at Boumemouth University Library & Information Services had been receiving requests from students for guidance on how to cite sources of information found on the Internet. No standards yet exist, although there are many suggestions to be found on the Web itself. We decided to put together a set of recommendations based on those suggestions that seemed most likely to be adopted by the UK information community. The article describes the chosen style, gives advice for finding the information required for producing a reference and discusses some of the issues involved, both for those wishing to cite online sources and those responsible for producing them.

Additive manufacturing (AM) is readily capable of producing models and prototypes of complex geometry and is advancing in creating functional parts. However, AM processes typically underperform traditional manufacturing methods in mechanical properties, surface roughness and hermeticity. Solvent vapor treatments (vapor polishing) are commonly used to improve surface quality in thermoplastic parts, but the results are poorly characterized.

This work quantifies the surface roughness change and also evaluates the effect on hermeticity and mechanical property impacts for “as-printed” and acetone vapor-polished ABS tensile specimens of 1-, 2- and 4-mm thicknesses produced by material extrusion (FDM).

Vapor polishing proves to decrease the power spectral density for surface roughness features larger than 20 µm by a factor of 10× and shows significant improvement in hermeticity based on both perfluorocarbon gross leak and pressure leak tests. However, there is minimal impact on mechanical properties with the thin specimens showing a slight increase in elongation at break but decreased elastic modulus. A bi-exponential diffusion decay model for solvent evaporation suggest a thickness-independent and thickness-dependent time constant with the latter supporting a plasticizing effect on mechanical properties.

The contributions of this work show vapor polishing can have a substantial impact on the performance for end-use application of ABS FDM components.

The purpose of this paper is to study the functionality of additively manufactured (AM) parts, mainly depending on their dimensional accuracy and surface finish. However, the products manufactured using AM usually suffer from defects like roughness or uneven surfaces. This paper discusses the various surface quality improvement techniques, including how to reduce surface defects, surface roughness and dimensional accuracy of AM parts.

There are many different types of popular AM methods. Unfortunately, these AM methods are susceptible to different kinds of surface defects in the product. As a result, pre- and postprocessing efforts and control of various AM process parameters are needed to improve the surface quality and reduce surface roughness.

In this paper, the various surface quality improvement methods are categorized based on the type of materials, working principles of AM and types of finishing processes. They have been divided into chemical, thermal, mechanical and hybrid-based categories.

The review has evaluated the possibility of various surface finishing methods for enhancing the surface quality of AM parts. It has also discussed the research perspective of these methods for surface finishing of AM parts at micro- to nanolevel surface roughness and better dimensional accuracy.

This paper represents a comprehensive review of surface quality improvement methods for both metals and polymer-based AM parts.

This study aims at compensating for sintering deformation of components manufactured by metal binder jetting (MBJ) technology.

In the present research, numerical simulations are used to predict sintering deformation. Subsequently, an algorithm is developed to counteract the deformations, and the compensated deformations are morphed into a CAD model for printing. Several test cases are designed, compensated and manufactured to evaluate the accuracy of the compensation calculations. A consistent accuracy measurement method is developed for both green and sintered parts. The final sintered parts are compared with the desired final shape, and the accuracy of the model is discussed. Furthermore, the effect of initial assumptions in the calculations, including green part densities, and green part dimensions on the final dimensional accuracy are studied.

The proposed computational framework can compensate for the sintering deformations with acceptable accuracy, especially in the directions, for which the used material model has been calibrated. The precise assumption of green part density values is important for the accuracy of compensation calculations. For achieving tighter dimensional accuracy, green part dimensions should be incorporated into the computational framework.

Several studies have already predicted sintering deformations using numerical methods for MBJ parts. However, very little research has been dedicated to the compensation of sintering deformations with numerical simulations, and to the best of the best of the authors' knowledge, no previous work has studied the effect of green part properties on dimensional accuracy of compensation calculations. This paper introduces a method to omit or minimize the trial-and-error experiments and leads to the manufacturing of dimensionally accurate geometries.