James C. Malas

Examination on the use of acoustic emission for monitoring metal forging process: A study using simulation technique

The aim of this study is to determine the feasibility of using acoustic emission as a monitoring technique for metal forging operations. From the sensor development paradigm proposed by McClean et al. the most likely approach to determining feasibility for application is through signal recognition. For this reason, signature prediction and analysis was chosen to determine the suitability for forging applications.

Optimization of microstructure during deformation processing using control theory principles

Abstract A two stage approach based on modem control theory has been proposed to control the microstructure development during hot working. This method was utilized for optimal design of hot extrusion process. In the first stage, equations for dynamic recrystallization of plain carbon steel were utilized to obtain an optimal deformation path such that the grain size of the product would be 26 μm. In the second stage, the geometric mapping was utilized to develop an extrusion die profile such that the strain rate profile during extrusion matches with the optimal trajectory computed in the first stage. An extrusion experiment was performed to validate the proposed methodology, by utilizing the extrusion die geometry obtained in the second stage. The as-extruded grain size was observed to be in close agreement with the optimal design performed in the first stage. The results of the present investigation revealed that the principles of control theory can be reliably applied for the optimization and control of microstructure during deformation processing.

An innovative strategy for open loop control of hot deformation processes

A new strategy for systematically calculating near optimal control parameters for hot deformation processes is presented in this article. This approach is based on modern control theory and involves deriving state-space models directly from available material behavior and hot deformation process models. Two basic stages of analysis and optimization are established in this strategy for nonlinear, open loop control system design for producing required microstructural characteristics, uniformity of deformation and temperature distribution, and other important physical requirements of hot worked products.

Process Model Development for Optimization of Forged Disk Manufacturing Processes

This paper addresses the development of a system which will enable the optimization of an entire processing sequence for a forged part. Typically such a sequence may involve several stages and alternative routes of manufacturing a given part. It is important that such a system be optimized globally, (rather than locally, as is the current practice) in order to achieve improvements in affordability, producibility, and performance. This paper demonstrates the development of a simplified forging model, discussion techniques for searching and reducing a very large design space, and an objective function to evaluate the cost of a design sequence.

Nonlinear optimization-based design of ram velocity profiles for isothermal forging

The development of good material models, accurate nonlinear finite element codes, and computer-controlled presses make practical the application of control techniques to metal forging. This paper considers the open-loop problem of selecting a nominal ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and forging temperature. Two approaches for doing so are applied to a simple, but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks and offers potential savings in critical computations. Simulation studies for the two methods show good results. >

Optimization of Microstructure Development: Application to Hot Metal Extrusion

A new process design method for controlling microstructure development during hot metal deformation processes is presented. This approach is based on modern control theory and involves state- space models for describing the material behavior and the mechanics of the process. The challenge of effectively controlling the values and distribution of important microstructural features can now be systematically formulated and solved in terms of an optimal control problem. This method has been applied to the optimization of grain size and certain process parameters such as die geometry profile and ram velocity during extrusion of plain carbon steel. Various case studies have been investigated, and experimental results show good agreement with those predicted in the design stage.

Conceptual Design of Control Strategies for Hot Rolling

Summary This paper deals with the application of ‘axiomatic’ approach to the conceptual design of a hot rolling process. Functional requirements {FRs} of the rolling process are governed by the metallurgical and shape requirements of the product. Design parameters {DPs} which are capable of controlling the process in order to achieve the desired {FRs} are identified. A design matrix which relates {FRs} and {DPs} is then derived and re-arranged to maintain independency of the parameters and “decouple” the design. Results obtained using this approach will form a basis for subsequent, detailed design of the process.

Optimal Die Shape and Ram Velocity Design for Metal Forging

A primary objective in metal forming is designing the geometry of the workpiece and dies in order to achieve a part with a given shape and microstructure. This problem is usually handled by extensive trial and error—using simulations, or test forgings, or both—until an acceptable final result is obtained. The goal of this work is to apply optimization techniques to this problem. Expensive function evaluations make computational efficiency of prime importance. As a practical matter, off-the-shelf software is used for both process modeling and optimization. While this approach makes it possible to put together a working package relatively quickly, it brings several problems of its own. The algorithm is applied to a example of real current interest—the forging of an automobile engine valve from a high performance material—with some success.

Optimal Control of Metal Forging

The development of good material models, accurate nonlinear finite element codes, and computer- controlled presses makes practical the application of control techniques to metal forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and forging temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the forging temperature is also presented.