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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.

The purpose of this paper is to improve the performance and quality of Ti-6Al-4V fabricated by laser powder bed fusion.

Single-track experiments were conducted during the fabrication process to obtain the single tracks with excellent wettability to narrow the process parameter window. The effects of process parameters on the build surface, cross-section, relative density, defects, surface roughness, microstructure and mechanical properties of the parts were analyzed through multilayer fabrication experiments and surface optimization experiments.

The point distance has the greatest influence on the build surface of the fabricated parts, and the unmelted defects can be eliminated when the point distance is 35 µm. The relative density of the fabricated parts decreased with the increase of the point distance, and the hatch spacing has different characteristics with respect to the relative density of the fabricated parts under different laser powers. It was observed that the most of experimental groups with higher relative densities than 99%, and the highest density could reach 99.99%. The surface roughness can be reduced to less than 10 µm through remelting optimization.

The research results can provide theoretical support for scientific researchers and data support for engineers.

The purpose of this study was to research how the reassembly (remanufacturing assembly) achieves a quality that is not lower than original production with different precision remanufactured parts based on the integration of mechanics, mathematics (measurement uncertainty) and management (optional classification). Remanufactured product quality is the soul of the remanufacturing project.

First, this paper studies the recycled parts features and reassembly features. Then, we build the mathematical sub-model with remanufactured parts and dimensional precision, which is proven that optional classification can effectively improve the reassembly accuracy mathematically. The optimization model of optional classification for reassembly is proposed under the constraint of a dimensional chain, and the solutions are studied based on particle swarm optimization. Finally, this method is applied in a remanufacturing enterprise and achieves good results.

The method can reduce the cost of quality loss and improve the quality of remanufactured products.

It provides a new solution and idea for reassembly with different precision remanufactured parts and promotes the healthy development of reverse logistics with a high level of customer satisfaction. This method can maximize the use of different levels of quality remanufactured parts and improve reassembly accuracy by mathematical proofs and examples.

The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.

Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.

This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.

While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.

Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.

This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.

Selective laser melting (SLM) is increasingly used for the manufacture of end‐use metal tools and parts, requiring the careful identification of a range of appropriate process parameters and conditions to achieve desirable properties and quality. Process conditions such as the relation between layout of parts and internal gas flow within the SLM platform can influence the consolidation of metal powers and therefore the quality and properties of the final parts. The purpose of this paper is to investigate the effect of part layout on quality and mechanical properties of cylindrical 316L stainless steel parts manufactured by SLM.

The cylindrical 316L stainless steel parts were manufactured in two directions, one perpendicular to the gas flow direction and one parallel to it. The investigation first focuses on visual inspection and porosity measurements to compare the quality factors such as delamination and porosity of the parts. A mechanical test procedure including tensile, compressive, and shear‐punch is used to assess the mechanical properties of the SLM specimens. Cross sectional analyses are carried out to better understand of material response under mechanical tests.

The results show that the part layout and gas flow condition have a negligible influence on porosity formation, however they notably affect the thermal stress and bonding strength between particles which consequently influences the mechanical properties of final parts. The manufacturing of parts perpendicular to gas flow seems to be more advantageous rather than parallel to gas flow.

This is the first work investigating the effects of the SLM layout on the quality and mechanical properties of stainless steel specimens. The results can be used in quality control purposes and for quality improvement of SLM parts.

Although additive manufacturing (AM) has been demonstrated to have significant potential in improving spare part delivery operations and has been adopted to a degree in the aviation and automotive industries, its use in spare part production is still limited in other fields due to a variety of implementation barriers. The purpose of this article is to assess the significance of previously reported barriers in the context of the machine-building industry.

Adoption barriers are identified from the literature and formulated as hypotheses, which are verified with a set of focus group interviews consisting of original equipment manufacturers (OEMs), AM service providers and quality inspection and insurance institutions. The results of the interviews are reported qualitatively, and the transcripts of the interviews are subjected to quantitative content analysis.

The article identifies distrust in quality, insufficient material and design knowledge among stakeholders and poor availability of design documentation on spare parts as the key barriers of adopting AM in the production of spare parts. The three key barriers are interconnected and training engineers to be proficient in design and material issues as well as producing high-quality design documentation will yield the highest increase in AM implementation in spare parts.

The article offers a unique approach as it investigates the subjective views of a cross-organizational group of industrial actors involved in the machine-building industry. The article contributes to the theory of digital spare parts by verifying and rejecting presented barriers of AM implementation and how they are interconnected.

Fused deposition modelling (FDM) is the most economical additive manufacturing technique. The purpose of this paper is to describe a detailed review of this technique. Total 211 research papers published during the past 26 years, that is, from the year 1994 to 2019 are critically reviewed. Based on the literature review, research gaps are identified and the scope for future work is discussed.

Literature review in the domain of FDM is categorized into five sections – (i) process parameter optimization, (ii) environmental factors affecting the quality of printed parts, (iii) post-production finishing techniques to improve quality of parts, (iv) numerical simulation of process and (iv) recent advances in FDM. Summary of major research work in FDM is presented in tabular form.

Based on literature review, research gaps are identified and scope of future work in FDM along with roadmap is discussed.

In the present paper, literature related to chemical, electric and magnetic properties of FDM parts made up of various filament feedstock materials is not reviewed.

This is a comprehensive literature review in the domain of FDM focused on identifying the direction for future work to enhance the acceptability of FDM printed parts in industries.

Inconsistencies in build quality part-to-part and build-to-build continue to be a problem in additive manufacturing (AM). The flexibility of AM often enables low-volume and custom production, making conventional methods of machine qualification and health monitoring challenging to implement. Machine health has been difficult to separate from the effects of design and process decisions, and therefore inferring machine health through part quality has been similarly complicated.

This conceptual paper proposes a framework for monitoring machine health by monitoring two types of witness parts, in the form of witness builds and witness artifacts, to provide sources of data for potential indicators of machine health.

The proposed conceptual framework with witness builds and witness artifacts permits the implementation into AM techniques to monitor machine health according to part quality. Subsequently, probabilistic models can be used to optimize machine costs and repairs, as opposed to statistical approaches that are less ideal for AM. Bayesian networks, hidden Markov models and Markov decision processes may be well-suited to accomplishing this task.

Though variations of witness builds have been created for use in AM to measure build quality and machine capabilities, the literature contains no previously proposed framework that permits the evaluation of machine health and its influence on quality through a combination of witness builds and witness artifacts, both of which can be easily added into AM production.

This work aims to evaluate the influence of rheological properties of building materials on the bonding quality and ultimate tensile strength in the fused deposition modeling (FDM) process, through the investigation of parts printed by semi-crystalline and amorphous resins. Little information is currently available about the influence of the crystalline nature on FDM-printed part quality.

Semi-crystalline polyamide 12 and amorphous acrylonitrile butadiene styrene (ABS) were used to assess the influence of rheological properties on bonding quality and the tensile strength, by varying three important process parameters: materials, liquefier temperature and raster orientation. A fractography of both tensile and freeze-fractured samples was also investigated.

The rheological properties, mainly the melt viscosity, were found to have a significant influence on the bonding quality of fused filaments. Better bonding quality and higher tensile strength of FDM parts printed with semi-crystalline PA12, as compared with amorphous ABS, are suggested to be a result of higher initial sintering rates owing to the lower melt viscosity of PA12 at low shear rates. Near-full dense PA12 parts were obtained by FDM.

This project provides a variety of data and insight regarding the effect of materials properties on the mechanical performance of FDM-printed parts. The results showed that FDM technique allows the production of PA12 parts with adequate mechanical performance, overcoming the greatest limitation of a dependence on amorphous thermoplastics as a feedstock for the production of prototypes.

The purpose of this paper is to identify the causal relationship between the independent variables such as process quality and product innovation in regard to the dependent variable of competitiveness, in the manufacturing sector of the automotive industry, specifically for Tier 1 auto parts manufacturing companies in the state of Nuevo León, México.

Based on a thorough review of the literature, an instrument was designed to measure the competitiveness of automotive industry manufacturing; it was applied to Tier 1 suppliers of automotive parts in the state of Nuevo León, México. Various statistical analysis tests were applied to the results; first, Cronbach's alpha to determine the reliability of the instrument, and next, a factor analysis to measure construct validity. In addition, a multiple linear regression analysis was carried out to identify the causal relationships between the variables analysed.

This study found that process quality as well as product innovation have independent and positive causal relationships with respect to competitiveness in automotive manufacturing.

The limitations of this paper are its focus on a single manufacturing sector, application in a single country and small sample size.

Companies that supply automotive parts will be able to invest in the key elements of quality and innovation while focusing their efforts on reinforcing their competitiveness.

Auto parts suppliers will be able to perform specific actions to improve their quality processes through lean manufacturing and quality assurance practices and by designing new and innovative products that will enhance their competitiveness.