Publication Abstract

Production Cost Sensitivity Analysis for Metal Powder Injection Molding

German, R., & Blaine, D. (2004). Production Cost Sensitivity Analysis for Metal Powder Injection Molding. Advances in Powder Metallurgy and Particulate Materials - 2004, Part 4. Princeton, NJ: Metal Powder Industries Federation. 1-10.

Abstract

An economic simulation is used to analyze the powder injection molding (PIM) process. The five layer analysis has been verified and provides a consistent means to determine the key drives on component cost, including consideration of tooling, material (powder), component features, economic batch size, and production steps. The model is accurate within 10%. Benchmark parts are used to assess the sensitivity to several factors ranging from complexity, size, tolerances, shape, feature combinations, materials, batch size, and various debinding and sintering technologies. Components from stainless steel at 1, 10 and 100 g mass are used to illustrate the interplay between the adjustable parameters with respect to production cost. The simulation helps the designer understand the sensitivity to various features and to anticipate design options to minimize PIM production costs. Each design differs, but these calculations some typical PIM components. Two approaches are used to show relative contributions to price via pie charts and to show price sensitivities. Analysis of price sensitivity derives from differentiation of the fabrication cost with respect to design criteria - material, mass, complexity, tolerances, and such. The sensitivity analysis ranks case-specific factors such as process yield, labor cost, and furnace loading. For a typical PIM case (8 g stainless steel component with maximum dimension of 25 mm produced at 1 million parts per year via thermal debinding and batch sintering), this analysis shows the lowest cost comes from self-mixing, coring to reduce mass, improved process yields, water atomized powder, and high furnace loading. Attention to these areas results in a 45% savings. Other examples are included in the analysis.