Tri-Planar Geometric Dimensioning and Tolerancing Characteristics of SS 316L Laser Powder Bed Fusion Process Test Artifacts and Effect of Base Plate Removal

The precision of LPBF manufactured parts is quantified by characterizing the geometric tolerances based on the ISO 1101 standard. However, there are research gaps in the characterization of geometric tolerance of LPBF parts. A literature survey reveals three significant research gaps: (1) systematic design of benchmarks for geometric tolerance characterization with minimum experimentation; (2) holistic geometric tolerance characterization in different orientations and with varying feature sizes; and (3) a comparison of results, with and without the base plate. This research article focuses on addressing these issues by systematically designing a benchmark that can characterize geometric tolerances in three principal planar directions. The designed benchmark was simulated using the finite element method, manufactured using a commercial LPBF process using stainless steel (SS 316L) powder, and the geometric tolerances were characterized. The effect of base plate removal on the geometric tolerances was quantified. Simulation and experimental results were compared to understand tolerance variations using process variations such as base plate removal, orientation, and size. The tolerance zone variations not only validate the need for systematically designed benchmarks, but also for tri-planar characterization. Simulation and experimental result comparisons provide quantitative information about the applicability of numerical simulation for geometric tolerance prediction for the LPBF process.

Rigidity Regulation Approach for Geometric Tolerance Optimization in End Milling of Thin-walled Components

The paper presents a novel approach to improve geometric tolerances (flatness and cylindricity) by manipulating the rigidity among finishing and roughing cutting sequences during end milling of thin-walled components. The proposed approach considers the design configuration of the thin-walled component as an input and aims to determine semi-finished geometry such that the geometric tolerances are optimized while performing finish cutting sequence. The objective is accomplished by combining Mechanistic force model, Finite Element (FE) analysis based workpiece deflection model and Particle Swarm Optimization (PSO) technique to determine optimal disposition of material along the length of component thereby regulating rigidity. The algorithm has been validated by determining rigidity regulated semi-finished geometries for thin-walled components having straight, concave and convex configurations. The outcomes of the proposed algorithm are substantiated further by conducting a set of end milling experiments for each of these cases. The results of the proposed strategy are compared with a traditional approach considering no change in the rigidity of component along length of the cut. It is demonstrated that the proposed approach can effectively optimize geometric tolerances for thin-walled components during end milling operation.

Reliability-based tolerance redesign of mechanical assemblies using Jacobian-Torsor model

The purpose of this paper is to present a new method to redesign dimensional and geometric tolerances of mechanical assemblies at a lower cost and with higher reliability. A parametric Jacobian-Torsor model is proposed to conduct tolerance analysis of mechanical assembly. A reliability-based tolerance optimization model is established. Differing from previous studies of fixed process parameters, this research determines the optimal process variances of tolerances, which provide basis for the subsequent assembly tolerance redesign. By using the Lambert W function and the Lagrange multiplier method, the analytical solution of the parametric tolerance optimization model is obtained. A numerical example is presented to demonstrate the effectiveness of the model, while the results indicate that the total cost is reduced by 10.93% and assembly reliability improves by 2.12%. This study presents an efficient reliability-based tolerance optimization model. The proposed model of tolerance redesign can be used for mechanical assembly with a better economic effect and higher reliability.

The Influence of Automated Machining Strategy on Geometric Deviations of Machined Surfaces

This paper deals with various automated milling strategies and their influence on the accuracy of produced parts. Among the most important factors for surface quality is the automated milling strategy. Milling strategies were generated from two different programs, CAM system SolidCAM, with the help of workshop programming in the control system Heidenhain TNC 426. In the first step, simulations of different toolpaths were conducted. Using geometric tolerance is becoming increasingly important in robotized production, but its proper application requires a deeper understanding. This article presents the measurement of selected planes of robotized production to evaluate their flatness, parallelism and perpendicularity deviations after milling on the coordinate measuring machine Carl Zeiss Contura G2. Total average deviations, including all geometric tolerances, were 0.020 mm for SolidCAM and 0.016 mm for Heidenhain TNC 426. The result is significantly affected by the flatness of measured planes, where the overlap parameter of the tools has a significant impact on the flatness of the surface. With interchangeable cutter plate tools, it is better to use higher overlap to achieve better flatness. There is a significant difference in production time, with SolidCAM 25 min and 30 s, and Heidenhain 48 min and 19 s. In accordance with these findings, the SolidCAM system is more suitable for production.

Physics-Based Part Orientation and Sentencing: A Solution to Manufacturing Variability

Casting deviations introduce geometric variability that impacts the aerodynamic performance of turbomachinery. These effects are studied for a high-pressure turbine rotor blade from a modern aero-engine. A sample of 197 blades were measured using structured-light three-dimensional scanning, and the performance of each blade is quantified using Reynolds-averaged Navier–Stokes (RANS) simulations. Casting variation is typically managed by applying geometric tolerances to determine the suitability of a component for service. The analysis demonstrates that this approach may not be optimal since it does not necessarily align with performance, in particular the capacity and efficiency. Alternatively, functional acceptance based on the predicted performance of each blade removes the uncertainty associated with geometric tolerancing and gives better performance control. Building on these findings, the paper proposes a method to set the orientation of the fir-tree, which is machined after casting. By customizing the alignment of each blade, performance variability and scrap rates can be significantly reduced. The method uses predictions of performance to reorient the castings to compensate for manufacturing-induced errors, without changing the design-intent blade geometry and with minimal changes to the manufacturing facility.