Liqueur Plant case study

myLiqueur production system

[Note: The following description of the case study is from [1]].

The liqueur plant system used as case study in [2] and [3] was adopted as base for the definition of the myLiqueur production system, which exploits IoT to allow end users to produce custom types of liqueur. Production parameters that define the specific type of liqueur could be defined by the end user through the myLiqueur App. The myLiqueur production system is composed of the following cyber-physical components, as shown in Fig. 1 below: smartSilo1, smartSilo2, smartSilo3, smartSilo4 and smartPipe. Each one of these has a well defined interface through which it exposes its behavior to be used by the liqueur production process. The smartSilo i has an input valve INi and an output valve OUTi through which it is cyclically filled and emptied with liquid. It also has a sensor Ei for the lower level and a sensor Fi for the upper level. Smart silos 2 and 4 have a resistance Ri to heat the liquid and a sensor Ti to monitor the temperature. Smart silos 3 and 4 have a mixer Mi to mix their content. Low level details as the above are encapsulated by the smartSilo to offer services of higher layer such as fill, empty, heat and mix. Silos are reserved in couples for the production of specific types of liqueur; silos 1 and 4 form one couple, silos 2 and 3 form the other couple. Raw liquid undergoes a basic process in smartSilo1 and then it is poured into smartSilo4 where it is further processed, i.e., it is heated and then mixed. Raw liquid is heated in smartSilo2 until a given temperature is reached and then it is transferred to smartSilo3 where it is mixed for a given time. The two liqueurs may be generated independently and in parallel with the constraint to use the smartPipe in an exclusive manner. Moreover, mixing the liquid in smartSilo3 and smartSilo4 at the same time is not permitted due to a constraint in power consumption.

A software simulator of the LPS case study, developed for educational purposes to demonstrate a modular system development, can be downloaded from here.

The video shows a prototype implementation of the Liqueur Plant production system using two software Silo simulators (Silos 1 and 2) and two hardware ones (silos 3 and 4) integrated using IoT protocols stacks.

The hardware Silo Simulator

The prototype implementation of the myLiqueur production system is based on the hardware silo simulator shown in Fig.2, which has been implemented by Foivos Christoulakis. For a detailed description of the Silo Simulator see SiloSimulator

Silo Industrial Automation Thing

We have currently implemented IoT enabled smart Silos (Silo Industrial Automation Things) using

a) Raspberry [4] and [6],

b) Contiki [5], and

c) Bosch XDK.

A. Raspberry-based Silo Industrial Automation Thing

Fig. 3a presents two Raspberry-based IoT-enabled Smart Silos used in the liqueur plant prototype implementation. The Raspberry-based Silo IAT was developed by Foivos Christoulakis in the context of his Thesis.

OSGi Based Implementation

Fig. 3b presents the liqueur plant prototype implementation based on OSGi and Raspberries. This LPS was developed by Panos Bochalis and John Bouloumpasis in the context of their Theses.

Youtube video: https://www.youtube.com/watch?v=WC71Tvv9jCY&feature=youtu.be

B. Contiki-based Silo Industrial Automation Thing

Fig. 4 presents the Contiki-based IoT-enabled Smart Silo. The Contiki-based Silo IAT was developed by Theodoros Foradis in the context of his Thesis.

C. XDK-based Silo Industrial Automation Thing

1st prize at XDK Ideation Jam

Fig. 5 presents the XDK-based IoT-enabled Smart Silo. The XDK-based Silo IAT was developed by Jason Athanasoglou and Alexandros Solanos.

Youtube video: https://www.youtube.com/watch?v=kPfR4irPERg

References

[1] K. Thramboulidis, F. Christoulakis, “UML4IoT—A UML-based approach to exploit IoT in cyber-physical manufacturing systems”, Computers In Industry, Online publication: 22-JUN-2016, DOI: 10.1016/j.compind.2016.05.010F.

[2] Basile, P. Chiacchio, and D. Gerbasio, “On the Implementation of Industrial Automation Systems Based on PLC”, IEEE Trans. on automation science and engineering, vol. 10, no. 4, pp.990-1003, Oct 2013.

[3] K. Thramboulidis, “A Cyber-Physical System-based Approach for Industrial Automation Systems”, Computers in Industry, Volume 72, September 2015, Pages 92–102.

[4] F. Christoulakis, K. Thramboulidis, “IoT-based Integration of IEC 61131 Industrial Automation Systems”, IEEE Inter. Symposium on Industrial Electronics, Santa Clara, CA, June 2016.

[5] Foradis, T. and Thramboulidis, K. (2017) From Mechatronic Components to Industrial Automation Things: An IoT Model for Cyber-Physical Manufacturing Systems. Journal of Software Engineering and Applications, 10, 734-753.

[6] K. Thramboulidis, P. Bochalis, J. Bouloumpasis, “A framework for MDE of IoT-BasedManufacturing Cyber-Physical Systems”, The 7th International Conference on the Internet of Things (IoT 2017), October 22–25, 2017, Linz, Austria.