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A nut bolt joint is a primary device that connects mechanical components. The vibrations cause bolted joints to self-loosen. Created by motors and engines, leading to machine failure, and there may be severe safety issues. All the safety issues and self-loosen are directly and indirectly the functions of the accuracy and precision of the fabricated nut and bolt. Recent advancements in three-dimensional (3D) printing technologies now allow for the production of intricate components. These may be used technologies such as 3D printed bolts to create fasteners. This paper aims to investigate dimensional precision, surface properties, mechanical properties and scanning electron microscope (SEM) of the component fabricated using a multi-jet 3D printer.

Multi-jet-based 3D printed nut-bolt is evaluated in this paper. More specifically, liquid polymer-based nut-bolt is fabricated in sections 1, 2 and 3 of the base plate. Five nuts and bolts are fabricated in these three sections.

Dimensional inquiry (bolt dimension, general dimensions’ density and surface roughness) and mechanical testing (shear strength of nut and bolt) were carried out throughout the study. According to the ISO 2768 requirements for the General Tolerances Grade, the nut and bolt’s dimensional examination (variation in bolt dimension, general dimensions) is within the tolerance grades. As a result, the multi-jet 3D printing (MJP)-based 3D printer described above may be used for commercial production. In terms of mechanical qualities, when the component placement moves from Sections 1 to 3, the density of the manufactured part decreases by 0.292% (percent) and the shear strength of the nut and bolt decreases by 30%. According to the SEM examination, the density of the River markings, sharp edges, holes and sharp edges increased from Sections 1 to 3, which supports the findings mentioned above.

Hence, this work enlightens the aspects causing time lag during the 3D printing in MJP. It causes variation in the dimensional deviation, surface properties and mechanical properties of the fabricated part, which needs to be explored.

In recent years, additive manufacturing (AM) technology has been acknowledged as an efficient method for producing geometrical complex objects with a wide range of applications. However, dimensional inaccuracies and presence of defects hinder the broad adaption of AM procedures. These factors arouse concerns regarding the quality of the products produced with AM and the utilization of quality control (QC) techniques constitutes a must to further support this emerging technology. This paper aims to assist researchers to obtain a clear sight of what are the trends and what has been inspected so far concerning non-destructive testing (NDT) QC methods in AM.

In this paper, a survey on research advances on non-destructive QC procedures used in AM technology has been conducted. The paper is organized as follows: Section 2 discusses the existing NDT methods applied for the examination of the feedstock material, i.e. incoming quality control (IQC). Section 3 outlines the inspection methods for in situ QC, while Section 4 presents the methods of NDT applied after the manufacturing process i.e. outgoing QC methods. In Section 5, statistical QC methods used in AM technologies are documented. Future trends and challenges are included in Section 6 and conclusions are drawn in Section 7.

The primary scope of the study is to present the available and reliable NDT methods applied in every AM technology and all stages of the process. Most of the developed techniques so far are concentrated mainly in the inspection of the manufactured part during and post the AM process, compared to prior to the procedure. Moreover, material extrusion, direct energy deposition and powder bed processes are the focal points of the research in NDT methods applied in AM.

This literature review paper is the first to collect the latest and the most compatible techniques to evaluate the quality of parts produced by the main AM processes prior, during and after the manufacturing procedure.

There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were developed for other traditional manufacturing methods involving considerably different physics. Process optimization to determine processing recipes for newly developed materials is expensive and time-consuming. The purpose of the current work is to use a systematic printability assessment framework developed by the co-authors to determine windows of processing parameters to print defect-free parts from a binary nickel-niobium alloy (NiNb5) using laser powder bed fusion (LPBF) metal AM.

The printability assessment framework integrates analytical thermal modeling, uncertainty quantification and experimental characterization to determine processing windows for NiNb5 in an accelerated fashion. Test coupons and mechanical test samples were fabricated on a ProX 200 commercial LPBF system. A series of density, microstructure and mechanical property characterization was conducted to validate the proposed framework.

Near fully-dense parts with more than 99% density were successfully printed using the proposed framework. Furthermore, the mechanical properties of as-printed parts showed low variability, good tensile strength of up to 662 MPa and tensile ductility 51% higher than what has been reported in the literature.

Although many literature studies investigate process optimization for metal AM, there is a lack of a systematic printability assessment framework to determine manufacturing process parameters for newly designed AM materials in an accelerated fashion. Moreover, the majority of existing process optimization approaches involve either time- and cost-intensive experimental campaigns or require the use of proprietary computational materials codes. Through the use of a readily accessible analytical thermal model coupled with statistical calibration and uncertainty quantification techniques, the proposed framework achieves both efficiency and accessibility to the user. Furthermore, this study demonstrates that following this framework results in printed parts with low degrees of variability in their mechanical properties.

The aim of this research is to reach a deep understanding on the effect of the process parameters of Direct Metal Laser Sintering process (DMLS) on macroscopic properties (hardness and density) of AlSi10Mg parts and resulting microstructure.

A full factorial design of experiment (DOE) was applied to determine the most significant process parameter influencing macroscopic properties of AlSi10Mg parts manufactured by DMLS process. The analysis aims to define the optimum process parameters and deduce the process window that provides better macroscopic properties of AlSi10Mg parts. Optical microscopy observations are carried out to link the microstructure to macroscopic properties.

Macroscopic properties of DMLS parts are influenced by the change in process parameters. There is a close correlation between the geometry of scan tracks and macroscopic properties of AlSi10Mg parts manufactured by DMLS process.

The knowledge of utilizing optimized process parameters is important to fabricate DMLS parts with better mechanical properties. The present research based on applying experimental design is the first analysis for AlSi10Mg parts produced in DMLS process.

The purpose of this paper is to investigate self-competence—the ability to act responsibly on one's own—and likely nonlinear wage returns across different levels of self-competence as part of training curricula.

The authors identify the teaching of self-competence at the occupational level by applying machine-learning methods to the texts of occupational training curricula. Defining three levels of self-competence (high, medium, and low) and using individual labor market data, the authors examine nonlinearities in wage returns to different levels of self-competence.

The authors find nonlinear returns to teaching self-competence: a medium level of self-competence taught in an occupation has the largest wage returns compared to low or high levels. However, in occupations with a high cognitive requirement profile, a high level of self-competence generates positive wage returns.

This paper first adds to research on the importance of teaching noncognitive skills for economic outcomes, which recently—in addition to personality traits research—has primarily focused on social skills by introducing self-competence as another largely unexplored but important noncognitive skill. Second, the paper studies not only average but also nonlinear wage returns, showing that the right level of self-competence is crucial, i.e. neither teaching too little nor too much self-competence provides favorable returns because of trade-offs with other skills (e.g. technical or professional skills). Third, the paper also examines complementarities between cognitive skills and noncognitive skills, again pointing toward nonlinear returns, i.e. only in occupations with a high cognitive requirement profile, high levels of self-competence generate positive wage returns.

The purpose of this article is to explore the barriers to the implementation of city development strategy (CDS) to achieve the goals in Iranian cities which have experienced rapid uncontrolled growth in recent decades. As comprehensive planning method has failed to tackle the challenges facing the cities, various recommendations have been made to employ the CDS as a successful method based on strategic urban planning to develop Iranian cities.

This study is qualitatively conducted based on the primary and secondary data in which the primary data were obtained from 11 semi-structured interviews, while the secondary data were collected through a review of international theoretical studies, Iranian experimental research and reports.

The findings of this study indicate five major barriers to the implementation of the Iranian urban planning process based on the CDS. These comprise the centralization of urban planning structure, coordination and relationship of agencies, financial resources, related laws and regulations and public participation.

This study develops a compelling argument that what is missing from research on CDS is an examination of the potential barriers of CDS implementation, particularly in Iranian cities.

Mg-Al powder mixture was used to manufacture Mg-Al alloy by laser powder bed fusion (LPBF) process. This study aims to investigate the influence of initial Al content and processing parameters on the formability, microstructure and consequent mechanical properties of the laser powder bed fused (LPBFed) component.

In this study, Al powder with different weight ratio ranged from 3 to 9 per cent was mixed with pure Mg powder, and the powder mixture was processed using different LPBF parameters. Microstructure and compressive properties of the LPBFed components were examined.

It was found that the presence of Al significantly modified the microstructure and improved the mechanical properties of the LPBFed components. Higher volume of ß-Al12Mg17 precipitates was produced at higher initial Al content and higher laser energy density. For this reason, the a-Mg was significantly refined and the compressive strength was improved. The highest yield compressive strength achieved was 279 MPa when using Mg-9 Wt. % Al mixture.

This work demonstrates that LPBF of Mg-Al powder mixture was a viable way to additively manufacture Mg-Al alloy. Both Al content and processing parameters can be modified to control the microstructure and mechanical properties of the LPBFed components.

The purpose of this article is to analyze the historical significance of Donald J. Urquhart, who established the National Lending Library for Science and Technology (NLL) that later was merged into the British Library Lending Division (BLLD), now called the British Library Document Supply Centre (BLDSC).

The paper presents a short history of the probabilistic revolution, particularly as it developed in the UK in the form of biometric statistics due to Darwin's theory of evolution. It focuses on the overthrow of the normal paradigm, according to which frequency distributions in nature and society conform to the normal law of error. The paper discusses the importance of the Poisson distribution and its utilization in the construction of stochastic models that better describe reality. Here the focus is on the compound Poisson distribution in the form of the negative binomial distribution (NBD). The paper then shows how Urquhart extended the probabilistic revolution to librarianship by using the Poisson as the probabilistic model in his analyses of the 1956 external loans made by the Science Museum Library (SML) as well as in his management of the scientific and technical (sci/tech) journal collection of the NLL. Thanks to this, Urquhart can be considered as playing a pivotal role in the creation of bibliometrics or the statistical bases of modern library and information science. The paper relates how Urquhart's son and daughter‐in‐law, John A. and Norma C. Urquhart, completed Urquhart's probabilistic breakthrough by advancing for the first time the NBD as the model for library use in a study executed at the University of Newcastle upon Tyne, connecting bibliometrics with biometrics. It concludes with a discussion of Urquhart's Law and its probabilistic implications for the use of sci/tech journals in a library system.

By being the first librarian to apply probability to the analysis of sci/tech journal use, Urquhart was instrumental in the creation of modern library and information science. His findings force a probabilistic re‐conceptualization of sci/tech journal use in a library system that has great implications for the transition of sci/tech journals from locally held paper copies to shared electronic databases.

Urquhart's significance is considered from the perspective of the development of science as a whole as well as library and information science in particular.

Additive Manufacturing technology (AMT) is swiftly gaining prominence to induce automation and innovation in manufacturing systems. It holds immense potential to change supply chain dynamics by providing the possibility of printing objects on demand. This study thus formulates and analyzes the framework to incorporate AMT to handle the spare parts supply chain management (SPSCM) in capital-intensive industries by identifying and assessing the critical success factors (CSFs).

Assessment of the CSFs is performed using the novel Grey Causal Modeling method (GCM) with the objective of making SPSCM resilient and efficient. GCM conducts causal analysis by taking into consideration cause, effects, the objectives, and the situations.

Findings indicate that; Logistics Lead Time (SD4), Time to manufacture (SD3), Management Support (SD11), and Risk Management (SD20) are the most prominent causal factor having a maximum impact when incorporating AMT in SPSCM. The results also reveal that the performance of manufacturing organizations that adopt AMT is substantially influenced by internal and external factors such as Management Support (SD11) and Government Regulations (SD16).

This research provides valuable information for getting the global spare parts supply chain equipped for the post-COVID age, where digital technologies such as AMT will be fundamental for bolstering supply chain resilience and efficiency.

This research proposes a framework for performance assessment when incorporating AMT in SPSCM. Study also demonstrates methodological application of novel Grey Causal Modelling technique using a real case in a spare parts manufacturing industry in India.

In this paper, we consider a two color multi-drawing urn model. At each discrete time step, we draw uniformly at random a sample of m balls (m≥1) and note their color, they will be returned to the urn together with a random number of balls depending on the sample’s composition. The replacement rule is a 2 × 2 matrix depending on bounded discrete positive random variables. Using a stochastic approximation algorithm and martingales methods, we investigate the asymptotic behavior of the urn after many draws.