Powder Injection Molding (PIM) for Low Cost Manufacturing of Intricate Parts to Net-Shape
Abstract : Powder Injection Molding (PIM) is a low cost manufacturing process that produces very complex parts to net-shape in a wide variety of materials and unique alloys, including superalloys, stainless steels and carbides, resulting in minimal secondary and assembly operations. PIM offers significant cost savings, increased design and materials flexibility, increased possibility of miniaturization, high mechanical properties, good surface finish and high speed production. The activities and expertise in powder metallurgy as well as in process numerical modeling related to powder injection molding at the Industrial Materials Institute of the National Research Council of Canada (NRC-IMI) and at Maetta Sciences, a company that has research and development facilities at the NRC-IMI, will be presented. Selected solutions and examples realized by NRC-IMI and by Maetta Sciences using respectively their high pressure and their scalable PIM platforms will be presented and described. Potential applications for the military, transportation and aerospace sectors will be highlighted.
A dimensional analysis based model to predict completion of solvent debinding step for Metal Injection Moulded parts
ABSTRACT The objective of this study is to develop a mathematical model to predict, for instance, the time for complete debinding of a metal injection moulded (MIM) part, the extent of solvent debinding (%) at any point of time and the debinding rate (g/min). To this end, two feedstocks, one containing carbonyl iron powder and the other made from irregular-shaped metallic particles from the shopfloor grinding sludge (both mixed with an organic binder system) were used to make by MIM, parts of nine different geometries. Each geometry has its own modulus. The effects of powder material, solid loading (influencing the binder content) and debinding temperature on the debinding characteristics were studied for the moduli of the nine parts. Parts with smaller moduli (thin parts) were found to debind faster than those with higher moduli. Parts, made of carbonyl iron feedstock (CI90), debind faster than that made of irregular-shaped particulates. A generalised solvent debinding model based on dimensional analysis has been proposed and verified experimentally. The root mean square error was found to be approximately 4% between experimentally determined and predicted debinding characteristics. These predictions are used to effectively design and curtail the solvent debinding cycles in MIM process.
Robust solutions of inverse problems in electromagnetic non-destructive evaluation
Non-destructive testing (NDT) is the application of physical measurement technology based on energy interaction with the material and its nonconformities. The material's response is sensed by transducers and sensors which?in most cases?scan the component and document the results in inspection images. However, NDT measures a physically defined quantity or even an intrinsic property. The difference between non-destructive evaluation (NDE) and NDT is in the interpretation of the inspection data. NDE has to discuss the inspection results in terms of quality elements and characteristics which are relevant to describe the fitness of the material for use. In the case of macroscopic defects these are the kind of defect (cracklike, globular) and its size and orientation to the main stress directions; in the case of material property determination the parameters are mainly mechanical properties. Therefore, in NDE one has to solve inverse problems. The solution of inverse problems based on mathematical procedures such as integral equations is a strong developing discipline and most of the articles prepared for this special issue of the journal have the objective of discussing the latest state of the art in that field. However, practical NDE needs robust and quick solutions which are to be applied mainly online. Therefore, we present here inversion procedures based on multiple linear regression algorithms applied to inspection data. We describe the calibration procedure to fit the free parameters of the model functions and give examples of practical applications in industry.