Y. Ravi Kumar

A robust process optimisation for fused deposition modelling

Rapid Prototyping (RP) technology is being widely used in diverse areas including mould manufacturing. However, the quality of RP parts is significantly affected by the process parameters of the RP machine. This work presents an experimental design technique for determining the optimal quality of a part build by the Fused Deposition Modelling (FDM) process with ABS plastic material. The design investigates (L9 Taguchi array) the effect of the parameters, contour width, raster width, raster angle and air gap on the dimensional accuracy, form features and surface finish. The experimental results are analysed by using the Analysis of Variance (ANOVA) method.

An application of Taguchi’s technique to improve the accuracy of rapid prototyped FDM parts

Rapid prototyping (RP) is finding applications in diverse fields in the industry today, with prototypes used for form, fit and function. Fused deposition modelling (FDM) is one of the rapid prototyping techniques and widely used for design verification. A step ahead, FDM prototypes are to be used as end products or for soft tooling applications, the accuracy of the prototypes has to be improved. This work presents an experimental design technique for determining the optimal accuracy of a part built by the FDM process. The design investigates the effect of the parameters, layer thickness, road width, air gap and speed on the accuracy. Experiments were conducted using Taguchi technique with three levels for each factor. This paper discusses the results of the study and the conclusions arrived from it.

Optimization of Computer Tomography Reconstruction Parameters using Additive Manufacturing

Additive Manufacturing (AM) is one of the advanced engineering manufacturing process and the application of this process is entered into each and every industry. This process best suits for production of each part uniquely. This technology best fits for medical and dental industry, where each patient has unique anatomy. Cone Beam Computed Tomography (CBCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are the major input data source for the AM medical softwares. The medical data is usually stored in Digital Imaging and Communication in Medicine (DICOM) file format. In the current days the most of the CT scanners are of multi slice scanners, which help to acquire maximum data of patient anatomy with in minimum time. Once CT data acquisition is done the reconstruction of data will start. In reconstruction of CT data slice thickness, slice increment and field of view parameters plays major role. The current work is to obtain best quality of data with minimal errors by optimizing the reconstruction parameters. Considered three reconstruction parameters with three levels to conduct the experiments. The reconstruction data is analyzed using L9 orthogonal array and S/N (Signal to Noise) ratio. The paper also explains the importance of reconstruction parameters theoretically and validated by experimental analysis, also applied on few case studies. The experimental results prove that slice thickness is majorly responsible for the quality of reconstructed data. The dimensional error is reduced from 0.78 mm to 0.65 mm. The same optimal parameters are implemented in the two case studies.

Parametric modelling and simulation of rapid prototyping

This work proposes a virtual system for parametric modelling and simulation of rapid prototyping (RP) process. The system aims to reduce the manufacturing risks of prototypes early in a product development cycle and, hence, reduce the number of costly design-build-test cycles. It involves modelling and simulation of RP system, which facilitates visualisation and testing the effects of process parameters on the part quality. Modelling of RP is based on qualifying the measures of part quality, which includes accuracy, build-time and efficiency of the selective laser sintering (SLS) process. The model incorporates various process parameters like layer thickness, hatch space, bed temperature, laser power and sinter factor, etc. It has been integrated with the simulation system to provide a testbed to optimise the process parameters.

Benefits of Additive Manufacturing Medical Model in Orbital Floor Reconstruction Surgery: A Case Study

Additive Manufacturing (AM) is one of the latest manufacturing processes. AM technology provides patient specific customized physical model, which is almost not achievable by any other technique. AM medical models are best suitable for pre-planning of complex medical surgeries such as reconstruction of the orbital floor which has fractured due to severe craniofacial trauma. Orbital floor is formed by a very thin bone which is often fractured during trauma. Among all the injuries of the craniofacial region, orbital fractures account for about 40 percent. The restoration of the orbit to its pre-traumatic volume and anatomy is one of the most delicate and difficult procedure. However this method which involves multiple try-ins, poses a risk of injury to the important structures within the orbit. AM provides the flexibility to bend, adapt/modify the plate prior to the surgery, which saves the intra-operative surgery time. This also avoids the revision of surgery in some cases. For the current study a patient specific preplanning medical model was made at a low cost using Fused Deposition Modeling (FDM). Placing a reconstruction plate/mesh which was pre-adapted on a model reduces operating time, risk of soft tissue trauma, and allows precise plate positioning and restoration of orbital volume. Using the FDM medical model overall surgery time is reduced by 40 minutes.

Dental surgical planning using CT scan and rapid prototyping

This work deals with the making of bio-models of jaws of patients using rapid prototyping from the data obtained from CT scan images. The bio-model was made with an intention of increasing the safety of dental surgeries and implant placement and aiding diagnosis and treatment planning. The bio-model made was used for planning an implant placement surgery on the patient whose CT scan data had been taken. A mock surgery was performed by making holes using drills and after that the implants were placed and screwed into the bio-model to secure their positions, as is done in an actual surgery.

Bio-Modelling Using Rapid Prototyping by Fused Deposition

This work deals with planning the dental surgery by making bio-model of the jaw of the patient using rapid prototyping (RP) technique called fused deposition modelling (FDM). The bio-model is not only increasing the safety of dental surgery but also aiding diagnosis and treatment planning. Having an exact model of the patient’s jaw in hand would enable a surgeon to plan the surgery more precisely, as compared to one which is planned using 2D images obtained from CT scan, magnetic resonance imaging (MRI) or X-ray. A mock surgery has been performed on the bio-model by making holes using drill bits of the same size and material as the ones used in an actual surgery and after that the implants were placed and screwed into the holes drilled to secure their positions. This drill has been given the surgeon an exact idea of size of the implant and the orientation in which the implant has to be placed and also depth up to which the hole has to be drilled in order to avoid the damage of the Inferior Alveolar Canal.

Modelling and simulation of bio-medical components by selective laser sintering

This work proposes a system for modelling and simulation of rapid prototyping (RP) process called selective laser sintering (SLS). The system aims to reduce the manufacturing risks in fabricating bio-medical components by SLS process. The system takes the computed tomography or magnetic resonance imaging data of the patient and it is processed into stereolithography (STL) format by using medical image processing software. It involves modelling and simulation of SLS system, which facilitates visualisation and testing the effects of process parameters on the part quality. Modelling of RP is based on qualifying the measures of part quality, which includes accuracy, build-time and efficiency of the SLS process. The model incorporates various process parameters such as layer thickness, hatch space, bed temperature, laser power, sinter factor, etc. It has been integrated with the simulation system to provide a test-bed to optimise the process parameters.