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Optimization of sheet metal forming processes
Linköping University, Department of Mechanical Engineering, Solid Mechanics. Linköping University, The Institute of Technology.
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The potential of using simulation and optimization techniques in the design of sheet metal forming processes has been investigated. Optimization has been used in a variety of sheet metal forming applications. This usage has given ideas and guidelines on how to formulate an optimization problems, how to ensure its rapid convergence and how to reach a feasible process design. Furthermore one method to include the uncertainty and variation in the governing parameters has been evaluated.

For each forming process many formability problems exist which usually are associated with fracture, wrinkling and springback. The aim of a good process design is to avoid these problems. By the use of simulation based design the physical trial- and error iterations can to a large extent be replaced by virtual iterations. When optimization techniques are used in the design process the number of iterations can be very large. In this work effort has been made to develop an optimization method, Space Mapping (SM), which is less computing intensive. It has been shown that SM can drastically reduce the required computing time and that its optimal solution is close to the optimal solution obtained by the more computing intensive Response Surface Methodology (RSM). The drawback of SM is that the method is less robust compared to RSM, and that it requires a better initial design for convergence.

Each industrial sheet metal forming process exhibits a certain degree of stochastic behavior due to uncertainties and variations in material properties, geometry and other process parameters. The forming process must be designed such that it is insensitive to these uncertainties and variations, i.e. the process must be robust. One possibility to consider uncer tainties and variations in a simulation and optimization based design process is to use the Monte Carlo method, in particular in combination with response surfaces as metamodels. It has been shown in this work that a linear response surface can successfully be used to identify the important design variables and to give an estimate of the probabilistic response. It has also been found that quadratic surfaces are required for a more accurate evaluation of the response.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2005. , 34 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 936
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-31401Local ID: 17172ISBN: 91-85297-74-7 (print)OAI: oai:DiVA.org:liu-31401DiVA: diva2:252224
Public defence
2005-05-13, C3, Hus C, Campus Valla, Linköpings Universitet, Linköping, 10:00 (Swedish)
Opponent
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2012-12-03Bibliographically approved
List of papers
1. Using surrogate models and response surfaces in structural optimization: with application to crashworthiness design and sheet metal forming
Open this publication in new window or tab >>Using surrogate models and response surfaces in structural optimization: with application to crashworthiness design and sheet metal forming
2003 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 25, no 2, 129-140 p.Article in journal (Refereed) Published
Abstract [en]

The aim of this paper is to determine if the Space Mapping technique using surrogate models together with response surfaces is useful in the optimization of crashworthiness and sheet metal forming. In addition, the efficiency of optimization using Space Mapping will be compared to traditional structural optimization using the Response Surface Methodology (RSM). Five examples are used to study the algorithm: one optimization of an analytic function and four structural optimization problems. All examples are constrained optimization problems. In all examples, the algorithm converged to an improved design with all constraints fulfilled, even when a conventional RSM optimization failed to converge. For the crashworthiness design problems, the total computing time for convergence was reduced by 53% using Space Mapping compared to conventional RSM. For the sheet metal forming problems the total computing time was reduced by 63%. The conclusions are that optimization using Space Mapping and surrogate models can be used for optimization in crashworthiness design and sheet metal forming applications with a significant reduction in computing time.

Keyword
Crashworthiness, Finite element, Optimization, Response surface, Sheet metal forming, Space mapping
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-46579 (URN)10.1007/s00158-002-0279-y (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-13
2. Optimization of draw-in for an automotive sheet metal part: an evaluation using surrogate models and response surfaces
Open this publication in new window or tab >>Optimization of draw-in for an automotive sheet metal part: an evaluation using surrogate models and response surfaces
2005 (English)In: Journal of Materials Processing Technology, ISSN 0924-0136, E-ISSN 1873-4774, Vol. 159, no 3, 426-434 p.Article in journal (Refereed) Published
Abstract [en]

In the present paper, an optimization of the draw-in of an automotive sheet metal part has been carried out using response surface methodology (RSM) and space mapping technique. The optimization adjusts the draw bead restraining force in the model such that the draw-in in the FE-model corresponds to the draw-in in the physical process. The conclusion of this study is that space mapping is a very effective and accurate method to use when calibrating the draw-in of a sheet metal process. In order to establish draw bead geometry from the draw bead restraining force a 2D-model was utilized. The draw bead geometry found showed good agreement with the physical draw bead geometry.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-31418 (URN)10.1016/j.jmatprotec.2004.06.011 (DOI)17196 (Local ID)17196 (Archive number)17196 (OAI)
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2017-12-13
3. Minimizing the risk of failure in a sheet metal forming process: optimization using space mapping with one-step and incremental solvers
Open this publication in new window or tab >>Minimizing the risk of failure in a sheet metal forming process: optimization using space mapping with one-step and incremental solvers
2006 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 31, no 4, 320-332 p.Article in journal (Refereed) Published
Abstract [en]

In the present paper, an optimization technique has been used to minimize the risk of failure in a sheet metal forming process. Two different types of finite element solvers, one using total plasticity and the other using incremental plasticity, have been used. A comparison between response surface methodology and space mapping (SM) with the one-step solver as surrogate model has been done. The conclusion of this study is that the use of the total plasticity theory drastically reduces the required computing time. Furthermore, the solution from the SM optimization algorithm is close to the solution obtained by the incremental plasticity solver.

Keyword
Incremental solver, One-step solver, Response surface methodology, Sheet metal forming, Space mapping
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-50249 (URN)10.1007/s00158-005-0604-3 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12
4. Optimizing sheet metal forming processes: using a design hierarchy and response surface methodology
Open this publication in new window or tab >>Optimizing sheet metal forming processes: using a design hierarchy and response surface methodology
2006 (English)In: Journal of Materials Processing Technology, ISSN 0924-0136, E-ISSN 1873-4774, Vol. 178, no 1-3, 218-233 p.Article in journal (Refereed) Published
Abstract [en]

In the present paper optimization has been used to evaluate alternative sheet metal forming processes. Six process set-ups were first defined in a hierarchy of designs and optimization was then used to evaluate each forming process of these designs. The challenge in designing the forming process was to avoid failure in the material and at the same time reach an acceptable through thickness strain. The conclusions of this study is that there may exist a different process that can give an improved product for the desired geometry. This process might be impossible for the optimization algorithm to reach due to either a poor starting point or a not so wise process set-up.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-41602 (URN)10.1016/j.jmatprotec.2005.03.040 (DOI)58201 (Local ID)58201 (Archive number)58201 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13
5. Reliability analysis of a sheet metal forming process using Monte Carlo analysis and metamodels
Open this publication in new window or tab >>Reliability analysis of a sheet metal forming process using Monte Carlo analysis and metamodels
2008 (English)In: Journal of Materials Processing Technology, ISSN 0924-0136, E-ISSN 1873-4774, Vol. 202, no 1-3, 255-268 p.Article in journal (Refereed) Published
Abstract [en]

The aim of the present paper is to evaluate the use of linear and quadratic approximating response surfaces as metamodels in a reliability assessment of a sheet metal forming process using the Monte Carlo simulation technique. Monte Carlo simulation was used to determine the probability for springback and thickness variation in a sheet metal part. The conclusions of this study is that Monte Carlo analysis can be used to identify the most important variables and to estimate the range of the studied responses. Linear metamodels can be used to identify the important variables and to give an estimate of the probabilistic response. But quadratic surfaces are required for a more accurate analysis.

Keyword
Monte carlo analysis, Reliability, Sheet metal forming, Springback, Thickness variation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-45955 (URN)10.1016/j.jmatprotec.2007.09.005 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-13

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