The performance of a magnetic-field-assisted finishing (MAF) process, an advanced surface finishing process, is severely affected by the rheological properties of an MAF brush. The yield stress and viscosity of the MAF brush, comprising iron particles and abrasives mixed in a liquid carrier medium, change depending on the brush’s constituents and the applied magnetic field, which in turn affect the material removal mechanism and the corresponding final surface roughness after the MAF. A series of experiments was conducted to delineate the effect of MAF processing conditions on the yield stress of the MAF brush. The experimental data were fitted into commonly used rheology models. The Herschel–Bulkley (HB) model was found to be the most suitable fit (lowest sum of square errors (SSE)) for the shear stress–shear rate data obtained from the rheology tests and used to calculate the yield stress of the MAF brush. Processing parameters, such as magnetic flux density, weight ratio of iron and abrasives, and abrasive (black ceramic in this study) size, with p-values of 0.031, 0.001 and 0.037, respectively, (each of them lower than the significance level of 0.05), were all found to be statistically significant parameters that affected the yield stress of the MAF brush. Yield stress increased with magnetic flux density and the weight ratio of iron to abrasives in MAF brush and decreased with abrasive size. A new process model, a rheology-integrated model (RM), was formulated using the yield stress data from HB model to determine the indentation depth of individual abrasives in the workpiece during the MAF process. The calculated indentation depth enabled us to predict the material removal rate (MRR) and the instantaneous surface roughness. The predicted MRR and surface roughness from the RM model were found to be a better fit with the experimental data than the pre-existing contact mechanics model (CMM) and wear model (WM) with a R² of 0.91 for RM as compared to 0.76 and 0.78 for CMM and WM. Finally, the RM, under parametric variations, showed that MRR increases and roughness decreases as magnetic flux density, rotational speed, weight ratio of iron to abrasive particles in MAF brush, and initial roughness increase, and abrasive size decreases.

As the metal additive manufacturing (AM) field evolves with an increasing demand for highly complex and customizable products, there is a critical need to close the gap in productivity between metal AM and traditional manufacturing (TM) processes such as continuous casting, machining, etc., designed for mass production. This paper presents the development of the scalable and expeditious additive manufacturing (SEAM) process, which hybridizes binder jet printing and stereolithography principles, and capitalizes on their advantages to improve productivity. The proposed SEAM process was applied to stainless steel 420 (SS420) and the processing conditions (green part printing, debinding, and sintering) were optimized. Finally, an SS420 turbine fabricated using these conditions successfully reached a relative density of 99.7%. The SEAM process is not only suitable for a high-volume production environment but is also capable of fabricating components with excellent accuracy and resolution. Once fully developed, the process is well-suited to bridge the productivity gap between metal AM and TM processes, making it an attractive candidate for further development and future commercialization as a feasible solution to high-volume production AM.

Magnetic field-assisted finishing (MAF) is a surface quality enhancing process that utilizes a flexible brush composed of ferrous metal and abrasive particles. This paper experimentally and statistically investigates the characteristics of a MAF process with nano-scale solid lubricant. A new MAF tool was developed by integrating iron and abrasive particles, and nano-scale solid lubricant. In this experiment, the optical microscopic images of the surface are obtained to measure the surface roughness resulting from MAF processes with varying the content of abrasive particles and the presence of nano-scale solid lubricant. Furthermore, spatial statistics techniques are used to quantitatively evaluate the quality of the surface resulting from each combination of MAF parameters. It is demonstrated that the size and type of abrasive particles mainly affect MAF process and the newly developed MAF tool with nano-scale solid lubricant can improve the final surface quality.