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.
In recent years, one of the main challenges in industry has been to obtain work parameters in real time for later analysis to understand the process better. The purpose is to obtain substantial information about the process for better decision-making and to find out what happens during manufacturing to know both the state of the equipment and the product, looking for savings in maintenance costs and quality controls among others. This has not been an exception for the automotive industry. These challenges have been associated with the concept of Industry 4.0, specifically with Big Data and IIoT (Industrial Internet of Things) techniques. Following this concept, many of the companies and research teams develop their algorithms and ideas based on the installation of new sensors without taking into account the implications that this proposal has in real factories. The cost of the sensor, the installation setup, maintenance, machine modifications and replication for hundreds of machines make many of the ideas fail when innovation is implemented in the companies. For that reason, in our previous work we have introduced a novel concept in Industry 4.0, the development of algorithms by using exclusively the information that is available in the equipment. Machines, as well as presses and general automated systems, include sensors for their automated normal production. These sensors are installed and the information they provide is almost free. Following this philosophy, the present paper proposes the Criterion-360 for real press shops. With this criterion, it is possible to measure a lot of variables with no cost, not only the tonnage, but also, many variables such as the press speed, Counterbalance and overload pressure, Cushion Pressure & Position, lubrication, etc., and therefore with this amount of information many possibilities arise. As the new developed system does not need new sensors and additional installation setup, it is easy and cheap to replicate it in other presses and plants.
This article presents two tools that have been developed from the information obtained with this criterion, these tools are currently in operation and have been used to modify work processes and get the press to work in optimal conditions.
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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