Constant-Volume Deformation Manufacturing for Material-Efficient Shaping

TL;DR

This work introduces a volume-preserving, digital-mold shaping framework that enables continuous, controllable deformation of plastic materials by integrating real-time volume modeling, geometry-aware deformation prediction, and error compensation. A dedicated intelligent kneading system converts 3D models into layer-wise kneading instructions and uses adaptive strategies (Envelope Shaping First and Similar Gradient) to maintain volume and surface continuity while reproducing complex geometries. Experimental validation across five shapes demonstrates high fidelity and material utilization above 98%, with compensation and geometry-specific kneading selections crucial for accuracy. The approach bridges digital models, real-time sensing, and adaptive forming to support sustainable, zero-waste, user-customized manufacturing at scale.

Abstract

Additive and subtractive manufacturing enable complex geometries but rely on discrete stacking or local removal, limiting continuous and controllable deformation and causing volume loss and shape deviations. We present a volumepreserving digital-mold paradigm that integrates real-time volume-consistency modeling with geometry-informed deformation prediction and an error-compensation strategy to achieve highly predictable shaping of plastic materials. By analyzing deformation patterns and error trends from post-formed point clouds, our method corrects elastic rebound and accumulation errors, maintaining volume consistency and surface continuity. Experiments on five representative geometries demonstrate that the system reproduces target shapes with high fidelity while achieving over 98% material utilization. This approach establishes a digitally driven, reproducible pathway for sustainable, zero-waste shaping of user-defined designs, bridging digital modeling, real-time sensing, and adaptive forming, and advancing next-generation sustainable and customizable manufacturing.

Figures (27)

• Figure 1: Overview of the intelligent kneading workflow. (A) The complete processing pipeline from extracting PCL from the input STL geometry, generating kneading commands, to the corresponding intermediate workpiece states after each kneading stage. (B) The detailed kneading and forming process of the geometric object, where B-V-A illustrates the effective region applied during each incremental kneading layer.
• Figure 2: Analysis of kneading accuracy for Geometries A and B. (A1, B1) Ideal machining PCL generated from kneading commands for Geometry A and B. (A2, B2) Actual kneaded PCL obtained from the platform. (A3, B3) Line plots showing the registration of ideal PCL, actual kneaded PCL, compensated PCL, and 3D-printed PCL against the target PCL. (A4, B4) Statistical significance analysis of differences between actual kneaded PCL and 3D-printed PCL with respect to the target PCL. $K_A$ — actual kneaded PCL; $I_A$ — ideal kneading PCL; $K_{\text{Scale-A}}$ — compensated actual kneaded PCL; $AM_A$ — 3D-printed scanned PCL
• Figure 3: Analysis of kneading accuracy for Geometries C, D, and E. (C1, D1, E1) Ideal machining PCL generated from kneading commands for Geometries C, D, and E. (C2, D2, E2) Actual kneaded PCL obtained from the platform using two different kneading methods. (C3, D3, E3) Line plots showing the registration of ideal PCL, actual kneaded PCL from both methods, compensated PCL corresponding to each method, and 3D-printed PCL against the target PCL. (C4, D4, E4) Statistical significance analysis of differences between actual kneaded PCL from both methods and 3D-printed PCL with respect to the target PCL. $K_{C1}$ — actual kneaded PCL using Similar Gradient method $K_{C2}$ — actual kneaded PCL using Envelope Shaping First method $I_C$ — ideal kneading PCL $K_{\text{Scale-C1}}$ — compensated actual kneaded PCL using Similar Gradient method $K_{\text{Scale-C2}}$ — compensated actual kneaded PCL using Envelope Shaping First method $AM_C$ — 3D-printed scanned PCL
• Figure 4: Analysis of kneading process and material utilization. (I) Material quality and utilization for Geometries A, B, C, D, and E, including material lost after kneading. (II) Kneading time and number of processing cycles for each geometry. (III) Visualization of the kneading formation process for each geometry. (IV-A, IV-B, IV-C, IV-D, IV-E) Surface area evolution during the kneading process for Geometries A, B, C, D, and E; red lines indicate the surface area of the target geometry. (K_C1) Demonstrates the geometry kneaded using the Similar Gradient method.
• Figure S1: Hardware structure diagram