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The study aims to analyze the intellectual structure in sustainable procurement (SP) research to identify the knowledge research clusters and provide potential avenues for future research.

The study conducted a bibliometric analysis to analyze the intellectual structure in the area of SP. Overall, 1,294 articles were selected from the Scopus database published between 2000 and 2022. The analysis was conducted using bibliometric R package, Biblioshiny and VOSviewer software. Further, content analysis of research clusters was carried out to set the future research agenda.

The study identifies four major knowledge research clusters of SP, namely, (1) green supply chain practices, (2) socially responsible purchasing, (3) environmental purchasing and (4) public procurement and policy. The study suggests a few research directions in the SP field. Moreover, the future research directions are aligned with specific organizational theories applicable in the area of SP research.

The study is dependent on the Scopus database for the source of research publications on SP. Future studies may consider other research database sources.

Identifying knowledge research clusters of SP research is of paramount importance for developing policies in the near future. These policy initiatives pave the way for the adoption of SP practices in the business. The findings indicate the issues managers encounter while implementing SP in organizations.

The study offers valuable insights concerning parameters such as significant publication outlets, influential countries concerning the number of publications, impactful authors, title keywords and identifying major knowledge research clusters of SP to suggest future research directions. Further, the present study highlights emerging areas that require further research, including process governance, supplier diversity, innovation, the role of emerging technologies and the application of organizational theories in SP.

Particles bed binding by selective cement activation (SCA) method is a computer-aided manufacturing (CAM) technique used to produce cementitious elements. A computer-aided design file is sliced to generate G-codes before printing. This paper aims to study the effect of key input parameters for slicer software on the final properties of printed products.

The one factor at a time (OFAT) methodology is used to investigate the impact of selected parameters on the final properties of printed specimens, and the causes for the variations in outcomes of each variable are discussed.

Finer aggregates can generate a more compact layer, resulting in a denser product with higher strength. Fluid pressure is directly determined by voxel rate (r_V); however, high pressures enable better fluid penetration control for fortified products; for extreme r_Vs, residual voids in the interfaces between successive layers and single-line primitives impair mechanical strength. It was understood that printhead movement along the orientation of the parts in the powder bed improved the mechanical properties.

The design of experiment (DOE) method assesses the influence of process parameters on various input printing variables at the same time. As the resources are limited, a fractional factorial plan is carried out on a subset of a full factorial design; hence, providing physical interpretation behind changes in each factor is difficult. OFAT aids in analyzing the effect of a change in one factor on output while all other parameters are kept constant. The results assist engineers in properly considering the influence of variable variations for future DOE designs.