How can production data be collected and visualized in real time?

The Industrial Internet of Things offers numerous opportunities to collect, visualize and specifically evaluate production data in real time. The results can be used to gain valuable insights into production and manufacturing processes, machine running times, and any malfunctions. Production data forms the basis for suggestions for improvement, cost reductions and can result in far-reaching business decisions.

What is production data?

Production data define the framework conditions of industrial services. Both qualitative and quantitative components play a role. They are important for the planning and control of production and should ensure a smooth flow as well as the economic design of processes.

In detail, production data are:

• responsibilities

• material data

• scheduling

• control data

• sequence planning

• technical data and

• tolerances.

What is machine data?

Machine data can be divided into process data and product data. Process data provides information that is necessary for the operation of machines. This primarily involves control data obtained during operation. From the product data, conclusions can be drawn about the product quantity and the production process.

In detail, the machine data are:

• the number of parts

• the product quantity

• the utilization

• the runtime

• the availability

• the reliability

• the condition of the machines and

• the energy consumption.

Sensors and actuators for capturing production data

With special software solutions, it is possible to capture production data in real time exactly where it is generated. Either sensors or actuators are used for this purpose. These are intelligent devices that are connected to the Industrial Internet of Things network. The abbreviation for industrial Internet of Things is IIoT (Industrial Internet of Things). It is a subset of the Internet of Things that relates exclusively to the field of production and manufacturing. The Internet of Things (IoT or Internet of Things), on the other hand, is concerned with interactions between people and smart devices.

Connecting and transmitting production data on IIoT platforms

The Industrial Internet of Things (IIoT) consists of a network of smart devices connected into systems. They are capable of generating and collecting data in real time and transferring it to dedicated servers for further processing. In order to gain broad benefits from the data, it is very important that it is continuously monitored and analyzed. In this way, errors and deviations in the manufacturing process can be detected in good time. This happens long before a serious defect or failure of machines or machine parts occurs.

Furthermore, not only data, products and processes, but also employees can be networked with each other.

The Manufacturing Execution System - MES

With the Manufacturing Execution System, production and manufacturing processes can be monitored in real time and continuously optimized. It is a modern and powerful software that can collect, merge and prepare data. Several applications are integrated, which can place their focus not only on production, but also on quality or on personnel. The goal is to obtain a digital and timely image of the entire production or manufacturing process. All data can be visualized and evaluated in detail. The results form the basis for important decisions by the responsible persons in the production process.

Advantages of data visualization and data evaluation in real time

When production data is collected, visualized and evaluated in real time, this has a whole range of advantages. Plant managers or other decision-makers thus have the chance to intervene immediately in the production process if it becomes apparent that processes are not optimal or that errors are creeping in. This is possible at a very early stage. In the medium and long term, optimizations can be made on the basis of the production data obtained and strategic decisions can be made on the future of the production and manufacturing process as well as on the business orientation.