Research Progress on Continuous Rolling Technology for Seamless Steel Tubes

Literature Overview

This paper, published in the Journal of Anhui University of Technology (Natural Science) (Vol. 22, Issue 3, 2005) by Yin Yuande and Li Shengzhi from Anhui University of Technology, provides a comprehensive review of continuous rolling technology for seamless steel tubes. The paper focuses on the plug mill extension process as the primary deformation operation, discussing theoretical analysis, experimental research, and finite element simulation approaches for understanding metal flow and defect formation.

Technical Background and Process Description

Continuous Rolling Process Overview

The continuous rolling process for seamless steel tubes involves multiple rolling mills arranged in series, where the tube坯 (billet) is progressively reduced in cross-section through successive deformation passes. The process typically comprises:

Process Stage	Function	Typical Equipment
Homogenization	Uniform temperature and microstructure	Ring furnace or induction heater
Piercing	Initial hole formation	Mannesmann or plug piercing mill
Plug mill extension	Primary dimensional reduction	Plug rolling mill
Reducing mill	Final dimensioning	Two-high or three-high reducing mill
Coiling	Tube coil formation	Coiler
Straightening	Straight tube production	Straightener

The plug mill extension process is identified as the critical deformation stage that determines both production capacity and product quality. In this stage, the tube is simultaneously reduced in wall thickness and expanded in diameter through the interaction of plug rolls and outer rolls.

Key Deformation Characteristics

The metal flow during plug mill rolling is complex and involves:

Radial deformation: Wall thickness reduction due to plug roll penetration
Circumferential deformation: Diameter expansion due to material flow
Axial elongation: Length increase due to volume constancy
Non-uniform strain distribution: Higher strain at plug contact zone, lower strain at roll exit

Theoretical Analysis of Deformation Zone

Classical Analytical Models

The paper reviews several theoretical approaches to plug mill deformation:

Slab method: Divides the deformation zone into thin vertical slices and analyzes force equilibrium in each slice. This approach provides approximate stress distributions but assumes plane strain conditions that do not fully capture the three-dimensional metal flow.
Upper bound method: Applies variational principles to establish upper bounds for the rolling force. This method is useful for process parameter estimation but may overestimate forces by 15–25%.
Semi-analytical methods: Combine analytical solutions for specific regions with numerical integration for the overall deformation zone. These methods offer better accuracy but require significant computational effort.

Limitations of Traditional Approaches

The authors emphasize that traditional analytical methods face fundamental limitations:

Inability to model the complex three-dimensional contact between plug rolls, outer rolls, and tube
Difficulty in predicting localized defects such as fold formation, wall thickness variation, and surface cracks
Inability to account for material flow instabilities at high reduction rates
Assumption of rigid-plastic material behavior that ignores strain rate sensitivity and temperature effects

Finite Element Simulation Applications

Simulation Methodology

The paper highlights the growing application of finite element analysis (FEA) to continuous rolling processes:

FEA Aspect	Description
Mesh type	3D tetrahedral elements with adaptive refinement
Material model	Elastic-plastic with temperature-dependent flow stress
Contact modeling	Coulomb friction with temperature-dependent coefficient
Deformation control	Lagrangian formulation with remeshing
Thermal coupling	Coupled thermo-mechanical analysis
Software platforms	DEFORM-3D, DIANA, ABAQUS

Process Parameter Optimization

FEA has been applied to optimize several critical process parameters:

Roll gap settings: Determining optimal plug and outer roll positions to achieve target dimensions while minimizing residual stress
Reduction distribution: Allocating total reduction across multiple passes to avoid excessive strain in any single pass (recommended single-pass reduction: 15–25% for wall thickness)
Rolling speed: Balancing productivity against temperature drop and material workability
Pass schedule: Sequencing reductions to prevent fold formation and ensure uniform wall thickness

Roll Profile Design Optimization

The FEA-based roll profile optimization involves:

Identifying the optimal plug roll profile (flat, concave, or convex) for different tube specifications
Determining the outer roll contact arc length to minimize surface defects
Evaluating the effect of roll radius on strain distribution and dimensional accuracy
Designing roll profiles that promote uniform circumferential strain to prevent ovality

Engineering Practice Integration

Common Defects and FEA-Based Countermeasures

Defect Type	Root Cause	FEA-Identified Countermeasure
Wall thickness variation	Non-uniform strain distribution	Optimize plug roll profile and rolling speed
Fold formation	Material instability at high reduction	Reduce single-pass reduction below 25%
Surface cracks	Excessive surface strain and low temperature	Increase rolling temperature by 50–100°C
Ovality	Asymmetric roll contact	Adjust outer roll alignment and gap
Dimensional inaccuracy	Inadequate springback compensation	Incorporate elastic recovery in roll settings

Production Capacity Enhancement

The FEA-guided optimization of plug mill processes has demonstrated:

10–20% improvement in rolling speed through optimized pass schedules
5–15% reduction in rolling force through improved roll profiles
Significant reduction in dimensional tolerances (from ±0.5 mm to ±0.2 mm for wall thickness)
Decreased reject rates from 3–5% to below 1% through defect prevention

Key Questions and Reflections

The 2005 publication date of this paper places it at an important transitional point in the field—when FEA was moving from research laboratories to industrial applications. The paper raises questions about the scalability of simulation results to industrial conditions: laboratory-scale simulations often simplify boundary conditions, neglect oxide scale effects, and use idealized material models. The gap between simulation accuracy and production reality remains a challenge, particularly for high-alloy steels where flow stress behavior is complex and temperature-sensitive. Furthermore, the paper does not address the integration of FEA with real-time process monitoring systems, which has since become an important development in smart manufacturing.

Study Insights and Implications

This review paper captures a pivotal moment in the evolution of seamless tube continuous rolling technology, where computational methods began to supplement traditional empirical approaches. The key takeaway for practicing engineers is that FEA provides an indispensable tool for process optimization, particularly for novel product specifications or when process changes are contemplated. The systematic approach of using FEA to understand metal flow, identify defect mechanisms, and optimize process parameters represents a paradigm shift from trial-and-error development to physics-based process design. For engineers involved in seamless tube production, this paper emphasizes the importance of understanding the fundamental deformation mechanics and leveraging computational tools to predict process outcomes before committing to expensive production trials.