Calculating production costs based on material consumption

Complex production processes, in which automation is intertwined with human work, often lead to situations in which it is difficult to precisely calculate the cost of producing a product. Many companies are still struggling with this problem, which makes it difficult to optimize production and attract new customers.

This is one of the problems that our customer was facing, and thanks to the cooperation he established with us, we were able to successfully measure the required machines and then prepare reports with ready calculations. Thanks to our solutions, the client received precise data on production costs, which allowed him to:

• Reduce production costs
• Know the consumption of materials
• Predict the consumption of materials based on the production plan

Description of the problem

A preliminary remark to better illustrate the situation: The client is a large foundry employing several hundred workers. It deals with casting parts with a total weight of several dozen tons.

The problem in this case had several levels. First, the human factor - no matter how hard we try to record every detail of the production process along with a log of materials used, there is a high probability that sooner or later such a log will depart from reality. Second - the complicated production process, including manual replenishment of materials during machine operation. Third - the lack of external access to data read by sensors installed in machines.

Solution

After a preliminary analysis of the problem, we proposed the solution architecture visible in the photo below.

The solution uses sensors installed in machines that are connected to the VermoBoard module from where they are sent via a secure TLS channel (secured by certificates provided by VermoPKI ) to the cloud infrastructure. There, the data is pre-processed and then saved in the secure VermoHub storage and in BigQuery to prepare reports. Based on the provided data, the computing service calculates the consumption of individual materials and saves the results in the VermoHub and BigQuery storage. The data used for the calculations comes from several sensors connected to the casting machine itself, i.e.:

• Pumps - voltage readings allow us to determine when the pump is working
• Valves - even if the pump is working, the material is not physically fed to the casting machine, valve readings allow us to determine when the material is being fed
• Actuators - reed switch readings allow us to calculate the consumption of bulk materials

While this data is very important in the calculation process, to make it possible we also need information on how much material can be supplied in a given time period. For this purpose, we have provided an interface integrated with the ERP system, which allows the customer to provide consumption in kg/s or kg/V.

In order to optimize implementation costs to the maximum extent, the solution makes extensive use of ready-made VermoHub components. The only cost for the customer in this case was the purchase of the VermoBoard device, implementation of the custom computing service and its deployment.

Based on the data collected in BigQuery, we are able to prepare a prediction of material consumption for a given casting.