Numerical and experimental case study on simultaneous optimization of blank shape and variable blank holder force trajectory in deep drawing

Kitayama, Satoshi; Koyama, Hiroki; Kawamoto, Kiichiro; Noda, Takuya; Yamamichi, Ken; Miyasaka, Takuji

doi:10.1007/s00158-016-1484-4

Cited by 21 publications

(11 citation statements)

References 31 publications

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“…

\begin{matrix} left \\ {([], \sum_{i = 1}^{2} {(w_{i} {\overset{f}{true}}_{i} (boldx))}^{p})}^{1 / p} \to \min \\ \begin{array}{c} x_{i}^{L} \leq x_{i} \leq x_{i}^{U} & i goodbreak= 1, 2, \dots, n \end{array} \end{matrix}\}

where

w_{i}

represents the weight of the i th objective function and p is the parameter. According to references 25–29, p is set to 4. Various weights are assigned to find a set of pareto‐optimal solutions

{boldx}^{p}

under

w_{1} + w_{2} = 1

.…”

Section: Multiobjective Optimization Of Multistage Packing Pressure P...mentioning

confidence: 99%

“…Since the pareto-frontier between warpage and cycle time is unknown in advance, the SAO is used to identify the pareto-frontier. We have already resolved several engineering issues such as sheet metal forming using servo press, [25][26][27] process parameters optimization in cold forging 28 and energy management system for hybrid electric vehicle 29 using the SAO with the RBF network. Then, this system is used as the design optimization tool.…”

Section: Sequential Approximate Optimization To Identify Pareto-frontiermentioning

confidence: 99%

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Numerical optimization of multistage packing pressure profile in plastic injection molding and experimental validation

Kitayama

Matsubayashi

Takano

et al. 2022

Polymers for Advanced Techs

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Plastic injection molding (PIM) is a crucial processing technology for producing lightweight products. Process parameters such as melt temperature, packing pressure, and cooling time directly affect not only the product quality but also the productivity, and they are conventionally adjusted by the trial‐and‐error method. A constant packing pressure is conventionally used, but the multistage packing pressure profile recently attracts attention. However, the packing pressure profile is unknown in advance, and it is difficult to determine it through the trial‐and‐error method. In this paper, the multistage packing pressure profile as well as other process parameters so as to minimize the warpage and cycle time are determined by using computational intelligence and design optimization. It is found from the numerical result that 27% warpage and 50% cycle time reduction can be achieved, compared with ones using reference process parameters. In addition, it is clarified that clamping force can be reduced. This indicates that PIM using the optimal multi‐stage packing pressure profile can produce plastic product with small clamping force that makes the tool life long. Finally, the experiment using PIM machine equipped with servo controller (MS100, Sodick) is carried out to examine the effectiveness of the multistage packing pressure profile.

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“…

\begin{matrix} left \\ {([], \sum_{i = 1}^{2} {(w_{i} {\overset{f}{true}}_{i} (boldx))}^{p})}^{1 / p} \to \min \\ \begin{array}{c} x_{i}^{L} \leq x_{i} \leq x_{i}^{U} & i goodbreak= 1, 2, \dots, n \end{array} \end{matrix}\}

where

w_{i}

represents the weight of the i th objective function and p is the parameter. According to references 25–29, p is set to 4. Various weights are assigned to find a set of pareto‐optimal solutions

{boldx}^{p}

under

w_{1} + w_{2} = 1

.…”

Section: Multiobjective Optimization Of Multistage Packing Pressure P...mentioning

confidence: 99%

Section: Sequential Approximate Optimization To Identify Pareto-frontiermentioning

confidence: 99%

Numerical optimization of multistage packing pressure profile in plastic injection molding and experimental validation

Kitayama

Matsubayashi

Takano

et al. 2022

Polymers for Advanced Techs

Self Cite

View full text Add to dashboard Cite

show abstract

“…5(a). To determine the back-pressure profile, as we have already performed (Kitayama et al, 2017), the total stroke of 3.02 mm is divided into three sub-stroke steps. The backpressure of each sub-stroke step (P1, P2, and P3 in Fig.…”

Section: Design Variablesmentioning

confidence: 99%

Determination of back-pressure profile and slide motion of servo press in cold forging using sequential approximate optimization

Kitayama

Higuchi

Takano

et al. 2020

JAMDSM

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Forging is one of the important manufacturing technologies to produce various mechanical components with high productivity. Recently, servo press that can control the back-pressure and the slide motion during the forging has attracted attention for high product quality without losing productivity. However, the back-pressure or the slide motion that affects the product quality and the productivity is completely determined by a trial-and-error method, and the determination is a crucial issue in forging using servo press. In this paper, a small product is selected as the case study, and both the back-pressure profile and the slide motion in cold forging are optimized. Numerical simulation using DEFORM3D is so intensive that sequential approximate optimization using radial basis function network is adopted to determine them. Based on the numerical result, the experiment using servo press (H1F200-2, Komatsu Industries, Corp.) is conducted. Through the numerical and experimental result, the validity of the proposed approach is examined.

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“…ここで，式 ( 4・3 分割ブランクホルダー力の優位性著者らの研究グループでは，薄板成形における VBHF の最適軌道設計に関する研究を継続的に行ってきており，シミュレーションとサーボプレスによる実験を通じ，その有用性を検証してきている (Kitayama et al, 2010, Kitayama et al, 2012Kitayama et al, 2013, Kitayama et al, 2016 …”

Section: 自動車部品やシンクなど多くの工業製品は，深絞り加工によって成形される．深絞り加工では，薄板(ブランク)unclassified

Design optimization of initial blank shape and segmented variable blank holder force trajectories in deep drawing

Kawamoto

Miyasaka

Yamamichi

et al. 2017

Transactions of the JSME (In Japanese)

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Blank shape minimizing earing, which is trimmed off after forming, is an important issue in sheet metal forming. In addition, blank holder force (BHF) have an influence on the product quality. Recently, variable BHF (VBHF) that the BHF varies through punch stroke is recognized as one of the advanced forming technologies. Furthermore, segmented VBHF will be valid to complex shapes for successful sheet metal forming. However, the optimal segmented VBHF trajectories and the optimal blank shape minimizing the earing are unknown in advance, and consequently the trial and error method is widely used to determine them. To resolve above issues, in this paper, a simultaneous design optimization of the blank shape and the segmented VBHF trajectories is performed. Numerical simulation in sheet metal forming is so intensive that a sequential approximate optimization using a radial basis function network is adopted to determine them. Based on the numerical result, the experiment using AC servo press is carried out. It is confirmed from the numerical and experimental result that the proposed approach is valid.

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Numerical and experimental case study on simultaneous optimization of blank shape and variable blank holder force trajectory in deep drawing

Cited by 21 publications

References 31 publications

Numerical optimization of multistage packing pressure profile in plastic injection molding and experimental validation

Numerical optimization of multistage packing pressure profile in plastic injection molding and experimental validation

Determination of back-pressure profile and slide motion of servo press in cold forging using sequential approximate optimization

Design optimization of initial blank shape and segmented variable blank holder force trajectories in deep drawing

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