Smart products are products and components equipped with integrated systems which are able to collect data, to communicate and to connect with other systems to inter-exchange the received data for either data analysis or immediate data pro-cessing (Jasperneite). Every smart product carries information about the current situ-ation and is capable of sending this informsitu-ation to nearby connected smart products and machines. Future Industry 4.0 scenarios even predict that these smart products know how they are produced and what is needed for the production so everything will be steered by smart products completely autonomously. Moreover, these smart products can carry a digital product memory, which tracks and stores every single task operation and stage of the product lifecycle and allows it to be accessible at any time (Kagermann, Wahlster, & Helbig, Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0, 2013, p. 39; Nunes, Pereira, & Alves, 2017, p. 1220).
The focus of this paper will be particularly on Cyber-Physical-Systems (CPS), which will play a crucial role for production in the future since, the CPS will make it possi-ble to fully connect the production process. The literature gives numerous explana-tions of the term CPS. There is not, however, one approved consistent scientific defi-nition of CPS. This circumstance suggests that there will not be one settled defidefi-nition of the term, since it can be interpreted in various ways and the development of this topic area is still in progress (Bettenhausen & Kowalewski, 2013, p. 2).
Nevertheless, to get a general understanding of the term CPS, the following list of attributes will serve as a description of the specific characteristics of CPS. CPS are embedded systems which (Vogel-Heuser, Bayrak, & Frank, 2012, p. 15):
• collect physical data with the help of onboard sensors and react with the help of actuators on physical processes.
• analyze and save data and on this basis interact with the physical and virtual world in form of actions or reactions.
• connect to one other through digital networks locally and globally with wire-less as well as non-wirewire-less links.
• use globally available data and services for their purposes.
• include a number of multimodal human-machine-interfaces to enable a dif-ferentiated communication and steering of the CPS, for example, through voice-control or gesture-control.
Until a Cyber-Physical-Product fulfills these requirements, it needs to go through four development stages from passive Radio-Frequency-Identification (RFID)-Chips to System of Systems (Bauernhansel, Hompel, & Vogel-Heuser, 2014, p. 16f).
1. The 1st stage of development includes the implementation of RFID-Chips, which allows the exact identification of the equipped objects. However, this knowledge is only available through central information systems and does not enable an evaluation or storage of information and thus cannot be an intelli-gent CPS.
2. The 2nd stage of development requires an elementary set of sensors and actua-tors, which have a rather small range of functions.
3. The 3rd stage of development involves a more extensive set of sensors and ac-tuators with the capabilities of already having intelligence by receiving data and interfaces as well as the communication with different systems. This ena-bles machine-to-machine (M2M) communication.
4. In the last and 4th stage of development, the CPS evolves to Systems of Sys-tems. Now the CPS can use its own skills individually and intelligently to combine the features to reach a more efficient and effective output. Further-more, the CPS learns new skills and possibilities by itself and supplies this knowledge to other systems. Complex functionalities are constructed which were not possible before.
Due to a high degree of connection and the omnipresent accessibility of data and services, the vision of an adaptive, self-configuring, self-organizing and flexible pro-duction plant arises. This should enable a more economical and efficient propro-duction than today to be possible. The German Federal Government denotes this Industry 4.0 Vision as Cyber-Physical-Production-Systems (CPPS). In a CPPS, the automation hierarchy changes with the provision and usage of decentral services for the different hubs to a more functional based organization like shown in the figure below (Bettenhausen & Kowalewski, 2013, p. 4).
Figure 7: Break down of the automation hierarchy by CPS with distributed services (Bettenhausen & Kowalewski, 2013, p. 49)
In the following part, the automation structure of CPPS will be observed in a more detailed way. On the lowest level a CPPS consists of four basic elements (Bettenhausen & Kowalewski, 2013, p. 6; Givehchi, Trsek, & Jasperneite, 2013, S.
51):
1. Physical process for conversion of substances and energy which is a part of the production process.
2. Sensors for the permanent tracking of the current condition of the physical process, for example, temperature or position of the object.
3. Actuators for the influencing of the physical process through motors, outlets, etc.
4. Information processing for the execution of the automation logic behind the CPPS.
The above described basic elements of the lowest level of the automation structure of CPPS form on the upper levels the actual process. The measuring of the condition and the physical influence of the processes happen not only through the integrated sensors and actuators but especially through the help of information processing sys-tem from the virtual world. Different technological syssys-tems come into use for this purpose, for example, web-services and their orchestration, agent systems or
cloud-based systems (Vyatkin, 2013, p. 14; Dengel, 2012, S. 4; Bauernhansel, Hompel, &
Vogel-Heuser, 2014, p. 495; Göhner, 2013, S. 22)
With the use of Smart Products through CPS and in the future also CPPS, a large set of potential can be released with the increase in connectivity of production systems and the analysis of big data. This potential includes (Bettenhausen & Kowalewski, 2013, p. 5):
• Extraction and processing of all necessary data on each subsystem of the au-tomation hierarchy (including availability and quality data).
• Deployment of new algorithms and services which use the received data in an innovative way for a multilateral connection and derive action recommenda-tions on that basis.
• Constant information exchange across all disciplines and along the whole value chain of an organization about product status, process status, produc-tion status, etc.
• Adaptive configuration and partially self-organizing production processes and automation processes (plug & produce concept) for the immediate response on changing market situations.
• Assistance, explanation and transparency about product-lifecycle and plant-lifecycle for the human user.
• The product itself evolves to an automation component and communicates with the production plant which allows a more flexible and efficient produc-tion.
• Self-diagnosis of specific components of the production plant with the aim of reducing maintenance charges, attrition and downtime.
• Functional module consisting of hardware and software components, which serve as a functional unit for a better structure and documentation of an au-tomation system.