Towards Real Time Predictive System for Mechanical Stamping Presses to Assure Correct Slide Parallelism

Peinado-Asensi, Ivan; Montés, Nicolás; García, Eduardo

doi:10.5220/0010547203960402

Cited by 3 publications

(3 citation statements)

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“…In SA presses there is one slide for the tool and a cushion system as blank holder that make the Deep Drawing operation more effective, and one can reach faster cycle time per produced part. As explained in [12] during the thesis, an application has been developed that allows us to monitor the work parameters in real time by taking data from the PLC that governs the press. Variables such as Tonnage load, Counterbalance Pressure, Overload Pressure, among others are being monitored.…”

Section: Stamping Processmentioning

confidence: 99%

Towards a Hybrid Twin Model to Obtain the Formability of a Car Body Part in Real Time

Peinado-Asensi

Montés

García

et al. 2022

KEM

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In recent days there are many possibilities in develop solutions for industrial manufacturing process thanks to the emerging technology based in Industry 4.0, where one can measure and manage data from an industrial process in real time been able to know more information than ever before from the process. But still having challenges in complex process where monitoring data and give a solution is less intuitive, mostly due to a complex physical definition of the process and manufacturing car body parts in automotive is a clear example. In deep drawing process is common to have variations in the process parameters and they can carry out bad manufactured parts. The cycle time, the robust process and the complex physics in the process are the main problems to obtain feasible information from the process. In the following it is proposed a new methodology to have full knowledge of the process applying the so-called method Hybrid Twin.

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Section: Stamping Processmentioning

confidence: 99%

Towards a Hybrid Twin Model to Obtain the Formability of a Car Body Part in Real Time

Peinado-Asensi

Montés

García

et al. 2022

KEM

Self Cite

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“…In this case, not only are technologies required for the real-time handling of a very big amount of data [23], but smart methods are needed for the filtering and compression of process signals [24]. Modern presses are equipped with four force sensors, one for each of the press columns [25], but four signals might not be enough to achieve effective decomposition and feature recognition. For this reason, multiple sensors are used to achieve a richer supply of data, such as acoustic sensors embedded in the tool holders [26][27][28], thin film local load sensors [29] or sensors to measure in-process the geometry [30], the quality [31] or the temperature [32] of the stamped parts.…”

Section: Introductionmentioning

confidence: 99%

A Data-Based Tool Failure Prevention Approach in Progressive Die Stamping

Farioli

Kaya

Fumagalli³

et al. 2023

JMMP

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The research on methods for monitoring sheet metal stamping is benefiting from the increased availability of enabling technologies such as sensors, data mining software, cloud computing, and artificial intelligence. The predictive maintenance policies of tools (punches and dies) can be targeted at monitoring progressive wear or at the detection of sudden failures or anomalies. Early detection of tool failure is the method preferred by the recent literature on data management in sheet metal stamping. However, the stamping of small parts poses challenges due to multiple tools and signals and limited visibility of die wear, requiring management of multiple sensors and data sources. This paper proposes a failure prevention approach for progressive die stamping using global and local force sensors with upper bounds for maximum values to indicate unhealthy conditions. The methodology was tested on millions of small washers made of carbon steel. The stamping process was implemented using a servo-press with a high rate. The press was equipped with eight in-process sensors, including strain gauges, thin foil force sensors, and acoustic sensors. The data of material properties, maintenance reports, statistical process control data, and in-process sensors were collected and stored in a data lake. By combining the in-process sensor acquisition with the corresponding log events and maintenance data in the same time span, it is possible to look for correlations among the variables and build an effective tool health prevention policy.

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“…The objective of our research is, through the data available in the press, to optimize the process from the point of view of machine health, part quality and energy saving. This paper focuses on optimizing the process from the machine health point of view and shows the experimental validation of the tool developed to monitor the center of gravity of the slide [5] in order to relate it to the press imbalance when it moves within previously defined working limits.…”

Section: Introductionmentioning

confidence: 99%

In Process Measurement Techniques Based on Available Sensors in the Stamping Machines for the Automotive Industry

Peinado-Asensi

Montés

García

2022

KEM

Self Cite

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We are currently going through an industrial period in which connectivity, data collection of the process and its understanding to optimize it is becoming more and more common. The automotive industry is no exception as we are on the way towards connected factories where the digitization of the stamping process is a trend followed by manufacturers. A common problem often encountered is the high cost required to develop solutions by using this technology. Obtaining parameters of the manufacturing process is a challenge on many occasions. New solutions have been proposed from an opposite point of view, i.e., we evaluate what information can be extracted from the equipment and from the data obtained we can bring forward the possible tools to be developed without the need for extra investment. This article shows the verification of an experimental process, previously developed, with which we intend to find out the status of the press during the drawing process for each cycle that is carried out during production and also the status of the equipment at all times, up to the point of detecting if there is any problem both in the die and in the mechanical components of the press and verifying it with the developed tool, showing that we can know the status of the equipment by monitoring the data in real time.

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Towards Real Time Predictive System for Mechanical Stamping Presses to Assure Correct Slide Parallelism

Cited by 3 publications

References 0 publications

Towards a Hybrid Twin Model to Obtain the Formability of a Car Body Part in Real Time

Towards a Hybrid Twin Model to Obtain the Formability of a Car Body Part in Real Time

A Data-Based Tool Failure Prevention Approach in Progressive Die Stamping

In Process Measurement Techniques Based on Available Sensors in the Stamping Machines for the Automotive Industry

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