Purpose 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. Design/methodology/approach 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. Findings Based on literature review, research gaps are identified and scope of future work in FDM along with roadmap is discussed. Research limitations/implications 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. Originality/value 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.

The present article focuses on mechanism of delamination and kerf geometry in abrasive water jet machining of carbon epoxy composite. In the present study, four process parameters of abrasive water jet machining namely hydraulic pressure, traverse rate, stand-off distance, and abrasive mass flow rate are considered. The experiments are performed on the basis of response surface methodology as a statistical design of experiment approach. Delamination in machined samples is observed by using scanning electron microscope. Analysis of variance is performed in order to investigate the influence of process parameters on delamination, kerf taper ratio, and kerf top width. It is found that delamination decreases with increase in pressure and abrasive mass flow rate and decrease in stand-off distance and traverse rate. Kerf taper ratio decreases with increase in pressure and decrease in traverse rate and stand-off distance. Kerf top width decreases with decrease in stand-off distance and increase in traverse rate. Based on analysis, mathematical models are developed to predict the maximum delamination length, kerf taper ratio, and kerf top width. Further, a multi-response optimization is performed on the basis of desirability function to minimize delamination, kerf taper ratio, and kerf top width.

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Purpose This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized. Design/methodology/approach Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts. Findings It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function. Research limitations/implications The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration. Originality/value From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.

The present article is focused on investigating the influence of process parameters under compressive loading in case of reentrant auxetic structures fabricated by fused deposition modeling (FDM). Auxetic structures of acrylonitrile butadiene styrene (ABS) and poly‐lactic acid (PLA) materials are fabricated. Three process parameters of FDM namely layer thickness, raster angle, and number of contours are considered to investigate their influence on compressive strength, stiffness, and specific energy absorption (SEA). Experiments are performed on the basis of central composite design and analysis is performed using ANOVA. It is found that compressive strength of auxetic structure improves with increase in layer thickness. But with increase in raster angle, it increases first and then decreases. Compressive stiffness of structures initially decreases and then increases with increase in raster angle, while it increases with increase in number of contours. SEA of structures increases with decrease in layer thickness. Based on the analysis of experimental results, regression models are developed to predict these responses. Also, multi‐response optimization is performed to optimize strength, stiffness, and SEA. Auxetic structures failed under compressive loading are also examined using scanning electron microscope.