Towards a general application programming interface (API) for injection molding machines
| Autor: | Kristian Martinsen, Mats Larsen, Olga Ogorodnyk, Ole Vidar Lyngstad |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Data acquisition system
0209 industrial biotechnology General Computer Science Computer science 02 engineering and technology Process variable lcsh:QA75.5-76.95 020901 industrial engineering & automation Data acquisition Scientific Computing and Simulation EMI 0202 electrical engineering electronic engineering information engineering Application programming interface (API) Protocol (object-oriented programming) Injection molding Application programming interface business.industry Cyber-physical systems 020208 electrical & electronic engineering Process (computing) Real-Time and Embedded Systems Open source Industry 4.0 Data exchange lcsh:Electronic computers. Computer science business Injection molding machine Computer hardware |
| Zdroj: | PeerJ Computer Science PeerJ Computer Science, Vol 6, p e302 (2020) |
| Popis: | Injection molding is a complicated process, and the final part quality depends on many machine and process parameters settings. To increase controllability of the injection molding process, acquisition of the process data is necessary. This paper describes the architecture and development of a prototype of an open application programming interface (API) for injection molding machines (IMMs), which has the potential to be used with different IMMs to log and set the necessary process parameter values. At the moment, the API includes an implementation of EMI data exchange protocol and can be used with ENGEL IMMs with CC300 and RC300 controllers. Data collection of up to 97 machine and process parameters (the number might vary depending on the type of machine at hand), obtained from sensors installed in the machine by the manufacturer is allowed. The API also includes a module for the acquisition of data from additional 3d party sensors. Industrial Raspberry Pi (RevPi) was used to perform analog-to-digital signal conversion and make sensors data accessible via the API prototype. The logging of parameters from the machine and from sensors is synchronized and the sampling frequency can be adjusted if necessary. The system can provide soft real-time communication. DOI 10.7717/peerj-cs.302 Copyright 2020 Ogorodnyk et al. Distributed under Creative Commons CC-BY 4.0 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|