The ability to manufacture products according to variable lot size without substantially increasing production costs is a key indicator of the Smart Factory. The future success of production facilities will largely be determined by their capacity for production changeability and the ability to connect points along the entire value chain. In production operations, existing conditions at each location are important factors. That’s why the Smart Factory should not be viewed as a bolt-on solution, but as a smart version of an existing production line, with the added benefits of being unique as the processes of the company itself.
Smart Factory ideas, methods, and approaches must also be considered to improve existing individual production processes. These improvements may lie in more efficient use of resources during production, preventing duplication of applications along the value-added chain, or significantly shortening system engineering times.
No matter which method is applied for transitioning to the Smart Factory, networking existing processes and operations remains a prerequisite. This networking should include connections from the control system to the field level, as well as to the various steps in the value-added chain. Manufacturers should be aware that diverse media and system discontinuities can make correlating data logically and sensibly difficult across unique processes. As a rule, each IIoT (Industrial Internet of Things) approach consists of recording, digitizing, and linking data to one another such that a sustainable added value is generated for the corporation.
Data transparency for the Smart Factory
The first step along this path requires transparency across all production and system data. Only when data is brought into context, suitably processed, and consolidated into information can measures be introduced to improve the production process. This means that sensors must record product and production-relevant data at the field level. Therefore, these sensors must be considered in the system architecture or incorporated into the product itself. Regarding production-relevant data—which is recorded via sensors on the machines and systems—the challenge consists less in the mere collection of data, but in bringing information securely and error-free from the field level into a higher system, such as a manufacturing execution system or the cloud. A major factor impeding this is the relatively high expense of transferring and storing data in the cloud.
This is where edge controllers can provide a decisive contribution. Modular edge systems offer a suitable solution for practically any sensor interface by enabling signals to be reliably collected from the field level and managed locally on the plant floor. Edge controllers with different communication interfaces and fieldbuses can be used to collect this data from devices independent of the manufacturer via CANopen, Profibus DP, EtherNet/IP, or Modbus-TCP and can also manage the vertical information via MQTT and OPC UA protocols.
Some advanced edge controllers can be incorporated into existing automation systems as scalable nodes and gateways, which can be retrofitted without having to interfere with the actual automation process. The data can then be aggregated into abridged information for transmission to a higher-level system or the cloud. The advantages connected with a cloud link offer numerous benefits, as cloud solutions are flexible, scalable, highly available, and provide the opportunity for centralized access.