Investigations for Mechanical Properties of Hybrid Investment Casting: A Case Study

2014 ◽  
Vol 808 ◽  
pp. 89-95 ◽  
Author(s):  
Parlad Kumar ◽  
Rupinder Singh ◽  
I.P.S. Ahuja
Keyword(s):  
Investment Casting ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Casting Process ◽  
Manufacturing Processes ◽  
Biomedical Implant ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Investment Casting Process

Conventional investment casting is one of the old manufacturing processes. It involves expensive tooling for making sacrificial wax patterns to make ceramic moulds. However, with the emergence of rapid prototyping technologies, now it is possible to make and use plastic patterns instead of wax patterns along with some advantages. In this paper, plastic patterns have been prepared by using fused deposition modeling and used for investment casting process. A case study has been discussed to make a biomedical implant by the hybridization of fused deposition modeling with investment casting. Dimensional accuracy, surface finish and hardness of the casted biomedical implants have been tested and reported.

Investigations for statistically controlled investment casting solution of FDM-based ABS replicas

2014 ◽  
Vol 20 (3) ◽  
pp. 215-220 ◽  
Author(s):  
Rupinder Singh ◽  
Gurwinder Singh
Keyword(s):  
Investment Casting ◽  
Fused Deposition Modeling ◽  
Plastic Material ◽  
Dimensional Accuracy ◽  
International Standard Organization ◽  
Content Type ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Standard Organization ◽  
Measuring Machine

Purpose – The purpose of the present study is to investigate statistically controlled investment casting (IC) solution of fused deposition modeling (FDM)-based ABS replicas. Design/methodology/approach – The work started with the identification of the benchmark/component. Prototypes (to be used as pattern) were built on FDM with ABS plastic material, followed by IC. The measurements on final casting prepared were made on the co-ordinate measuring machine (CMM) from which international tolerance (IT) grades were calculated to establish the dimensional accuracy of the components. Findings – This study further highlighted the cast component properties (like hardness and surface finish) for suitability of this process. Final castings produced are acceptable as per international standard organization (ISO) standard UNI EN 20286-I (1995). Originality/value – This process ensures development of statistically controlled IC solution as technological prototypes and proof of concept at less production cost and time.

scholarly journals Investigation of Investment Casting Pattern Using Fused Deposition Modeling

2021 ◽  
pp. 201-207
Author(s):  
Kamal Ukey ◽  
Santosh Hiremath ◽  
Himadri Majumder
Keyword(s):  
Investment Casting ◽  
Fused Deposition Modeling ◽  
Low Cost ◽  
Process Time ◽  
Medium Size ◽  
Fused Deposition ◽  
Economic Climate ◽  
Deposition Modeling ◽  
Metallic Parts

In today's economic climate, various organizations fight with decreasing sales and increasing costs. However, industries that have implemented the process of investment casting are one of the ways of manufacturing complex metallic parts at a low cost. High tooling costs and long manufacturing time are associated with the metal molds production for producing investment casting wax (sacrificial) patterns. It leads to a problem with cost justification for personalized single casting or production of small lots. The present study evaluates the suitability of the fused deposition modeling (FDM) fabricated pattern for investment casting. For this, a case study on a part was also conducted to collect experimental data regarding the process. A trial component was fabricated in an FDM machine and then cast by the investment method. This research resulted in reduced process time and cost for the small and medium size of the batch.

Probabilistic Modeling and Analysis of Fused Deposition Modeling Process Using Surrogate Models

2016 ◽  
Author(s):  
Yi Liu ◽  
Pingfeng Wang
Keyword(s):  
Manufacturing Process ◽  
Composite Structures ◽  
Fused Deposition Modeling ◽  
Probabilistic Modeling ◽  
Surrogate Models ◽  
Manufacturing Processes ◽  
Modeling And Analysis ◽  
Fused Deposition ◽  
Deposition Modeling

Various sources of uncertain parameters at multiple levels, from design steps to manufacturing processes, are often involved in composite structures. Probabilistic modeling and analysis of the composite structure and its manufacturing processes can provide underlying information to assess uncertainties and improve the quality of the developed composite structures. This paper presents a stochastic multi-level modeling framework considering material, structural, modeling parameters as well as the manufacturing process based on a surrogate model. An enhanced laminate theory is employed to determine the elastic constants of the composite materials considering imperfect bonding among filaments in the manufacturing process. To improve the computational efficiency in simulation-based reliability approach, the evaluation of the structure properties is approximated by employing surrogate models based upon the physics model. To apply the present framework, a case study with a composite laminate beam under three-point bending, which is made through fused deposition modeling, is conducted, and the case study results demonstrate the efficacy of the presented modeling scheme and analysis methodology.

Knowledge-Based Design of Artificial Neural Network Topology for Additive Manufacturing Process Modeling: A New Approach and Case Study for Fused Deposition Modeling

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Hari P. N. Nagarajan ◽  
Hossein Mokhtarian ◽  
Hesam Jafarian ◽  
Saoussen Dimassi ◽  
Shahriar Bakrani-Balani ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Expert Knowledge ◽  
Fused Deposition ◽  
Knowledge Based ◽  
Deposition Modeling ◽  
Artificial Neural

Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Toward that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge-based ANN (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modeled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, part height, and total part mass in a fused deposition modeling (FDM) process. The KB-ANN-based model for FDM has the same performance with better generalization capabilities using fewer weights trained, when compared to a classical ANN.

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