Classification of cyber-physical production systems applications: Proposition of an analysis framework
Introduction
First definition that can be found about cyber-physical systems (CPS) dates from 2006 [1], during a workshop with the American National Science Foundation1 (NSF). The extension of cybernetic systems towards CPS is therefore explicitly dealt with in literature since 2006–2007 and is constantly growing in popularity. Fig. 1 shows a short analysis of the evolution of the number of journal article mentioning explicitly the term “cyber-physical” in the 5 major scientific publishers. This term was chosen as it encompasses various aspects and applications of the CPS. In the past decades, many research articles were dealing about notions and concepts that have been at the origin of current CPS. These works are not listed here as they do not mention the cyber-physical keyword even though the scientific content is compatible. The objective of this figure is to exhibit the trend of acceptance of the notion in literature, whatever the field of research and the publisher. Over the last six years, i.e. since the total number of publications reached 1000, a 40% increase in average per year can be noticed, which demonstrates the high level of acceptance of the notion. Looking at the publisher proportions, it can be noticed that IEEE was very present in the early years, whereas the publication rate is more shared nowadays. This is an effect of the dissemination of the notion to a large number of new fields of application that were not present in the first years.
All along their development, more synthetic definitions were suggested, such as those of [2] or [3]. For example, CPS are defined by [4] as cooperating systems, having a decentralized control, resulting from the fusion between the real world and the virtual world, having autonomous behaviors and dependent on the context in which they are, being able to constitute in systems of systems with other CPS and leading a deep collaboration with the human. For this, embedded software in CPS uses sensors and actuators, connect to each other and to human operators by communicating via interfaces, and have storage and data processing capabilities from the sensors or the network [5]. The recent one, suggested by [6], allows a clear synthesis of the various aspects of this large concept, coupling in addition the notion of services with CPS : “Cyber-Physical Systems (CPS) are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the internet”. To do so, embedded software in CPS uses sensors and actuators, connect with each other and with humans communicating via standard interfaces, and have abilities of storage and processing of data coming from sensors or from the network [5]. This interconnection of systems, as stated by [7], derives from the fact that a CPS encompasses together control, computation but also communication devices [8]. What can be spotted in the evolution of the definition is the notion of system of systems that was not considered in the early definition of 2006 [1].
The notion of CPS is very wide and encompasses an extremely large class of systems. As a matter of fact, numerous fields of research are relevant of this keyword. This is probably a huge opportunity as it gives the possibility to create a consistent ecosystem in numerous fields of applications: from autonomous vehicles [9] to health devices [10], from electrical grid management [11] to HVAC building control [12].
The industrial domain is of course interested in this field, and the development of major evolutions such as Industrie4.0 in Germany [13] is based on CPS. The application of CPS in the field of production management was formalized in the past few years [6], under the term of Cyber-Physical Production Systems (CPPS). According to [14], the main benefits that can be expected from the generalization of CPPS are: (i) Optimization of production processes; (ii) Optimized product customization; (iii) Resource-efficient production; (iv) Human-centered production processes.
Many fundamental research questions emerge from the development of the concept of CPPS. Among these, the modelling and forecasting of their emergent behavior, the optimization of the control laws at each level of the system and the establishment of a convenient environment for developing autonomy, cooperation, optimization and responsiveness can be cited [6,15]. In parallel, a credible answer to this last element was given thanks to the development of Holonic Manufacturing Systems [[16], [17], [18], [19], [20]], but still needs to be developed in order to fit the requirements of industrial implementation at a large scale. On the other hand, a special interest is being given nowadays to cloud technologies, which are becoming a more and more credible actor of future industrial systems [[21], [22], [23]]. Projects such as IMC-AESOP [24] for example studied the benefits that can be expected from the coupling between cloud and CPPS, and technologies such as Service-oriented Architectures (SoA) are given a certain credit in order to foster interoperability, agility and self-* abilities of systems [25]. The human-machine interaction [26,27], the social aspect [28] and the cyber-security issues [[29], [30], [31]] applied to industry and manufacturing are also major questions that are under study and directly connected to CPPS.
Considering this extremely large field of research and the large perimeter of the definition of CPPS, there is a risk of scattering of research efforts inside this wide notion. The main challenge of the next few years is to provide proofs of concepts, industrial applications and laboratory developments able to prove the advantages given by the CPPS paradigm in terms of flexibility and performance. This article intends to introduce an analysis framework aiming at classifying the various developments and applications of literature. This framework is intended for future researchers or engineers willing to establish rapidly an overview of the main trends of literature developments.
First, an analysis of the research context from the international roadmaps perspective is presented. Then, the framework will be presented and the items defining the axes of the framework are described. Finally, the application of the framework to various examples of developments found in literature in order to illustrate the use of the framework is introduced, and a preliminary analysis of the state of the art based on the use of the framework is proposed in the agility domain.
Section snippets
Definition and fundamentals
CPPS classical definition [6] is widely accepted in the last few years as it exhibits well the notion of the necessary cooperation between CPS in a CPPS. However, the notion of knowledge management and decision making, which constitute still nowadays a large field of research, are missing. Notions such as digital twins used for dynamic simulation and forecasting are not present for example. Furthermore, notions of learning and auto-adaptation are not clearly mentioned. Finally, the adaptability
Framework items description
The core of the framework is to design a set of characteristics that are of interest for classifying the applications and implementations of CPPS in literature. To do so, one possibility was to analyze the main characteristics and objectives of global CPPS and deduce the criteria of the framework. Exploring this possibility resulted in various criteria that were not directly related to the developments of the CPPS, but rather on the methodology and objectives.
In this work, the different points
Example of application of the framework to a subset of current literature
The objective of this article is to introduce an innovative framework enabling the classification of cyber-physical production systems developments in literature in order to identify either the convergence between the different authors or the leads that were not explored for example. In this section, a short example of use of the framework and a preliminary analysis is performed in order to illustrate the benefit of such a framework for future potential users.
The focus of this analysis was
Conclusion
This article introduces a new analysis framework for classifying Cyber-Physical Production Systems applications relatively to various items, including their cognitive abilities, their application extent, the interaction with human operators, the distribution of intelligence and the network technologies that are used.
This framework was described and applied to several examples retrieved from literature. From the grid extracted from this analysis, several conclusions are drawn for each
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