Integrated Computational Materials
Engineering (ICME) for
Steel Industry
Dr G Balachandran
Head ( R&D)
Kalyani Carpenter Special Steels Ltd.,
Pune – 411 036.
Indo-US Workshop on ICME for Integrated Realization of Engineered Materials and Products
Part of KALYANI GROUP Companies
Bharat Forge Ltd is the Flag Ship Company Kalyani Steels, Hospet
Kalyani Carpenter Special Steels Ltd., Pune
Joint Venture with Carpenter Technology Corporation
– Manufacturing facilities at Pune and Ranjangaon – Total Employees 800 – Current capacity 240,000 t/ annum
– Production in the year 2012-13 : Sales 174,587 ton
Production Facilities at KCSSL
Macro Models : Stoichiometry; Thermodynamics
The Steel Industry has to cater to wide variety of market segments - General Engineering industry
- Automotive industry - Oil & Gas Industry
- Chemical and Petro chemical industry - Mining industry
- Tool & Die steel industry
- Power generation industry [ Thermal, Wind, Hydro ] - Defence industry
- Nuclear Industry - Aerospace industry - Biomedical industry - Construction
Grades required are widely varying
Same grade with different properties for different industries may be required Sometimes customer specific alloy modifications are implemented
Industry needs to grasp and react to customer requirement quickly, confidently and with minimum development time
Needs of Steel for Industry
Belief in Virtual Tools : Simulation of Ingot Casting at KCSSL
Simulation predicts fluid flow, temperature profile, solid front movement, central porosity
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KCSSL is able to optimise mould, hot & casting condition using virtual experimentation
Micro-structure after 8th Pass
Predominant Compressive Stress
With deformation degree
- temperature. strain, stress, grain size, rolling load & torque could be predicted & matched with experiments
Belief in Virtual Tools: Hot Rolling Deformation Model at KCSSL
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Percentage of phases & Grain size
21% Ferrite 16% Ferrite 16% Ferrite
20% Ferrite 18% Ferrite
Load and Torque match at most point
Phase fraction and grain size match with experimental results
Belief in Virtual Tools: Microstructure Prediction in Hot Rolling
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Belief in Virtual Tools: Hot Rolling of 316 SS Compared with HSLA
316 SS results in,
- more passes for same strain penetration - high load/pass [>60%]
- higher adiabatic rise in temp - higher surface temp loss
Rolling Temp= 1235oC Cross section (mm)
Start Finish HSLA 320x400 204 x 270 316SS 325x325 210x225
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Is the Virtual Tools always successful?
• Simulations are used only as a guidance in many instance • Industry is guided more by
not attempting a prediction that gave poor results,
although, accuracy may be lacking in a successful model • Predictions can have differences as high as 20 to 30% due to
- configuring of problem inaccurately
- quality of input data [ data to be refined with experimentation correct data ] - basic validity of the generalized physical models in the in-built software
- limitations in computational techniques or software - experimental errors
- lack of skill [ Mechanical Vs Metallurgical Engineers ]
Role of ICME in Existing Steel Grades
Raw Material Cost saving Optimization of processing for a given raw material mix Process Route optimization Eliminate unwanted processing, saves raw material,
energy, & labour
Bench Marks Performance of each unit process assessed.
Enable effective capacity utilisation, optimum productivity Fixes targets on energy, labour & productivity
Yield Improvement Process optimization improves yield
(e.g.) Mold designs, deformation scheduling, fish tail reduction, loose structure elimination
Structure property correlations Enhances accuracy in getting desired properties Inventory Reduction Locates alternate application for aging material
Rejection Management Faster solution to solving internal & customer rejections Clean Environment and
Minimising Effluents
Choice of process conditions that minimizes pollution and effluents
Product Development in Industry
Role of ICME in New Development Grades
Choice of composition to meet customer property requirements
Faster and accurate choice of composition based on robust alloy design principles to meet properties.
Decision on processing route Choice of process route & parameters [melting, casting, forging/rolling, heat treatment ] within available
infrastructure
Equipment Choice Enables choice of equipment for processes Ex. AOD/VAD - ESR/ VAR.
Cost effectiveness Enables cost effectiveness of products by optimizing raw material and energy in unit processes
Yield Enables yield improvement in the unit processes
Delivery Fewer & faster development trials ensure faster delivery
Product Development in Industry
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Product Development in Industry
• Industries face internal failures & customer rejections [ especially in new products ]
- Quick solutions are needed
- Industries combat failures on every day basis
• Robust modeling or virtual tools are not available to foresee failures.
• Although theoretical information is available, • they are not predictive
. Non-metallic Inclusions type, shape, distribution as a function of processing - influence on properties [ undesirable & desirable nature]
- Statistical nature of inclusion & fatigue [ Murakami Extreme Value Statistics]
• Robust damage mechanism based on rules & theories
- Porosity formation in casting: Niyama or Yamanaka Criteria - Cracks in deformation : Latham Cockcroft criteria, C-Z Criteria
Other Failure modes not yet in the realm of simulation
- gas porosity, inter-dendritic shrinkage, porosity distribution - Hydrogen flaking, void crushing in deformation
- extent of banding, fracture prediction, FATT
• Industries will welcome in a big way for such virtual tools on failure
Customer is the Focal Point
ICME for Customer Needs
Quality Product Choice of alloy design & optimal processing route enables meeting Customer desired properties.
Customer expectation & draft of correct specification possible.
Cost effective product Every unit processes is optmized - cost effective product
- alternate cost effective material assessment.. Timely delivery Hasten process route selection
ICME for Customer Delights
Enhanced performance & Alerts
Additional desirable properties foreseen Customer can cash that in his components
Warning against detrimental properties can be an alert. Ease of subsequent fabrication
[Closed die forging,
machinability, weldablity etc]
Foreseeing performance of the material at customer end Component life in service conditions.
This reduces failure of product at all stages
Yield & Quality improvement Optimizes yield & quality improvement at customer end . Reduced rejection Reduced rejections & reliability at customer end , retains
customer and enhanced business
Conclusion
ICME can play a great role for industry. ICME needs to be
- universal based on robust and experimentally verified physical models and empirical formulations
- at every stage failure modes & effect analysis are to be evaluated - constantly upgraded in every unit at various levels
Institutions: Academic, Research & Industry
- data mining in industrial data can give excellent models for prediction - user friendly
- cost effective
- A body to validate & standardize
