T. J. Nye

Real-Time Process Characterization of Open Die Forging for Adaptive Control

Open die forging is a process in which products are made through repeated, incremental plastic deformations of a workpiece, Typically, the workpiece is held by a manipulator. which can position the workpiece through program control between the dies of a press. The part programs are generated with an empirically derived parameter, called the spread coefficient, whose value is subject to some contention. In this work, we demonstrate how process information can be used in real time to derive the actual spread coefficient for a given workpiece as it is being formed. These measurements and calculations occur in real time, and can be used to regenerate part programs to optimize the forming process, or can be used to adaptively control each incremental deformation of the workpiece.

Optimal investment in setup reduction in manufacturing systems with WIP inventories

Abstract A number of models have been proposed to predict optimal setup times, or optimal investment in setup reduction, in manufacturing cells. These have been based on the economic order quantity (EOQ) or economic production quantity (EPQ) model formulation, and have a common limitation in that they neglect work-in-process (WIP) inventories, which can be substantial in manufacturing systems. In this paper a new model is developed that predicts optimal production batch sizes and investments in setup reduction. This model is based on queuing theory, which permits it to estimate WIP levels as a function of the decisions variables, batch size and setup time. Optimal values for batch size and setup time are found analytically, even though the total cost model was shown to be strictly non-convex.

Reliability Analysis of the Tube Hydroforming Process Based on Forming Limit Diagram

Tube hydroforming is an attractive manufacturing process in the automotive industry because it has several advantages over alternative methods. In order to determine the reliability of the process, a new method to assess the probability of failure is proposed in this paper. The method is based on the reliability theory and the forming limit diagram, which has been extensively used in metal forming as the criteria of formability. From the forming limit band in the forming limit diagram, the reliability of the forming process can be evaluated. A tube hydroforming process of free bulging is then introduced as an example to illustrate the approach. The results show this technique to be an innovative approach to avoid failure during tube hydroforming.

Improving the Reliability of the Tube-Hydroforming Process by the Taguchi Method

The tube-hydroforming process has undergone extremely rapid development. To ensure a reliable hydroforming process at the design stage, applying robust design methodologies becomes crucial to the success of the resulting process. The reliability of the tube-hydroforming process based on the tube wall thickness thinning ratio is studied in this paper. In order to improve the reliability of the process, the Taguchi method, which is capable of evaluating the effects of process variables on both the mean and variance of process output, is used to determine the optimal forming parameters for minimizing the variation and average value of the thinning ratio. Finite element simulation is used to analyze the virtual experiments according to the experimental arrays. A cross-extrusion hydroformed tube is employed as an example to illustrate the effectiveness of this approach.

Stamping Die Strip Optimization for Paired Parts

In stamping, operating costs are dominated by raw material costs, which can typically reach 75% of total costs in a stamping facility. In this paper, a new algorithm is described that determines stamping strip layouts for pairs of parts such that the layout optimizes material utilization efficiency to any desired accuracy. This algorithm predicts the jointly-optimal blank orientation on the strip, relative positions of the paired blanks and the optimum width for the strip. Examples are given for nesting pairs of the same parts together, and for pairs of different parts nested together. This algorithm is ideally suited for incorporation into die design CAE systems.© 2002 ASME

Automated Optimal Design for Manufacturability of Sheet/Plate Assemblies

A wide variety of products are manufactured from raw materials that are in the form of sheets or plates. Once the product is designed, parts are unfolded or flattened into flat blanks, which are nested onto the raw material for cutting. Optimization of nesting and packing problems has been an active research field for many years, and many good algorithms have been created. These algorithms have a fundamental limitation, however, in that they assume the set of blanks to be nested is fixed. In this work we relax this assumption, and by linking a parametric CAD system, a part-unfolding module and a sheet-nesting module that all intercommunicate, nests are created which maintain the parametric dimensions of the assembled product. Given a nest of the set of required blanks, dimensions of the blanks are optimized for a particular objective, such as maximizing raw material utilization or minimizing total use of raw material, subject to assembly, part dimension, part and blank dimension constraints. Once optimized, these blank dimensions are returned to the CAD system to update the product model. Through the use of this system, a designer can simultaneously optimize all the dimensions within a product to minimize manufacturing costs early in the design phase while maintaining acceptable product performance. This paper will demonstrate a prototype of this DFM system, discuss issues such as performance improvement through randomized trials, and suggest how additional design objectives (e.g., strength to weight ratio, stiffness, etc.) can be integrated with the reduced manufacturing cost objective.Copyright

Reliability Analysis of the Tube Hydroforming Process Using Fuzzy Sets Theory

Tube hydroforming currently enjoys increasingly widespread application in industry, especially in the automotive industries, because of several advantages over traditional methods. Reliability analysis as a probabilistic method to deal with the probability of the failure of the structure or the system has been widely used in industry. A new reliability analysis approach for the tube hydroforming process using the fuzzy sets theory is presented in this paper. The stress of the hydroformed tube is related to several parameters, such as geometry, material properties, and process parameters. In most cases, it is difficult to express in a mathematical formula, and its relative parameters are not random variables, but the uncertain variables that have not only randomness but also fuzziness. In this paper, the finite element method is applied as a numerical experiment tool to find the statistical property of the stress directly by a fuzzy linear regression method. Based on the fuzzy stress-random strength interference model, the fuzzy reliability of the tube hydroforming process can be evaluated. A tube hydroforming process for cross-extrusion is then introduced as an example to illustrate the approach. The result shows that this approach can be extended to a wide range of practical tube hydroforming process.© 2004 ASME

Adaptive Control for Intelligent Open Die Forging

Open die forging is a manufacturing process with a number of advantages; in particular it is an inherently flexible manufacturing process that makes efficient use of raw material. A fundamental drawback of this process, however, is the difficulty found in creating forging programs to control part manipulation and forming steps. A-priori approaches to creating these programs, such as by using FEM simulations or using modeling materials, are slow and have a strong tendency for errors to accumulate when predicting the results of consecutive forming steps. In this paper we present a new approach in which process feedback is used between forming steps to update a part geometry model that allows the forming sequence to be adjusted adaptively. This approach has been implemented in a simulated forging cell that uses non-linear FEM analyses to predict the effects of each forming step. A fully adaptive control scheme has been implemented that efficiently forges bars of one cross sectional shape into another shape, such as square to round or hexagonal. Programming the forging system with this scheme has proved particularly simple; the shape of the raw material is measured, and a desired shape is specified. Physical experiments have confirmed the simulation results.Copyright

Product Development via Industry-University Joint R&D Ventures: What Makes a “Win-Win” Partnership?

There are substantial benefits for both industry and universities from performing joint R&D projects. Given the significant potential benefits, both tangible and intangible, the level of such activity, however, seems surprisingly low. One reason hypothesized for this discrepancy is that the potential partners are motivated towards opposite goals: industry wishes to limit publication of research results due to fears of loss of competitive advantage in their markets as competitors obtain the benefits of the research at no cost, while academia is motivated to maximize publication. Intuitively, this would seem to be a fundamental difference between the potential partners. This paper studies this issue through the use of insights gained by a new analytic model of the profitability of such collaborations. First amongst these is that given the typical speed of product innovation and the typical publishing delay found in archival journals, little or no competitive advantage is expected to be lost by the industrial partner by allowing unrestricted publication freedom to the university partner. A second interesting insight occurs in the situation where a firm’s competitor forms the collaboration with the university partner. In general, if it is profitable for one industry partner to join the collaboration, the most beneficial decision for other firms in that market is to also join the collaboration.Copyright

Collaborative Agent Based Optimization of Draw Die Design

In this paper we consider the problem of automatically determining optimal drawbead sizes and blankholder forces when designing draw dies for stamped parts. A network of software agents, each implementing a different numerical optimization technique, was used in combination with metal forming simulation software to optimize process variables. Three test cases were used of varying complexity from a rectangular cup to the NUMISHEET’99 automobile front door panel simulation benchmark. It was found that the performance of each agent (and optimization technique) depended strongly on the complexity of the problem. More interestingly, for a given amount of computational effort, a network of collaborating agents using different optimization techniques always outperformed agents using a single technique in terms of both the best solution found and in the variance of the collection of best solutions.Copyright