Necessity of new label: Cyber Physical System (CPS) – A network of Mechatronics Systems

By Dr Madhavan Shanmugavel, Prof. and Research in Mechatronics at Monash University Malaysia

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Cyber Physical Systems, MEchatronics, Industrila Iot

Mechatronics System (MS) encompasses one or more physical system with with closed loop (CL) feedback control. By nature, a CL feedback system immune to external disturbances. Thanks to advances in Micro Electro Mechanical Systems (MEMS) which paved the way for miniaturization in turn lead to affordable sensors. Since the date of introduction, the major contribution of MS can be found within the realm automation and manufacturing.

A typical manufacturing industry has several work sites such as production, assembly, development, prototype section etc. with hundreds of MS. The material flow, quality control, products, processes, and operations at one site depend on what’s going on other site. The Quality and Performance (Q&P) of final product would be the summation of Q&P of individual systems from the work sites.

Mechatronics SystemsFor example, consider two work sites: WA, and WB, each produces component CA, and CB, and their Q&P are evaluated by their corresponding MSA, and MSB. A Final Product (FP) is produced by assembly of these components: FP @ CAÅ CB. The Q&P of the FP would be assessed after the assembly. The quality of the FP will be attributed from that of CA, and CB, while the performance of the FP is partially attributed from the components. The better quality can be achieved by making interaction between MSA, and MSB at the critical stages during the production of components.

Also, better performance can be achieved by the user feedback, or the live field data. Until recently, no such practice is not available in a large scale. Such a Network of Mechatronic Systems(NMS): MSAB{i,j}@ MSA{i,j}Å MSB{i,j}.form a network of their own. This network is formed within the realm of the industry. This definitely needs a seamless communication and higher computations.

The recent influx of massive data from distributed mobile sensor platforms through the cyber world increases the complexity of the network not only in terms of computation and also with communication, and decision making. The collection of these sensor platforms talk to one another through internet called Internet of Things (IOT). They exchange knowledge {K1, K2,…,Ki, Kn} with the Mechatronics Systems. This knowledge may be customer feedback, field data, services, and service-requests. They may be required to take a wise decision which will enhance time to market, high productivity, reduced latency, delay and so on.

Fundamentally, the whole system is formed by network of Mechatronic Systems (NMS) which are interacting with the cyber world through knowledge, information, or services & requests. It is the necessity of time to inform the new generation about these changes through new buzz word called Cyber Physical System (CPS).

In addition to higher computation loads and communications, the CPS also carries one of the most challenges persists with the Mechatronic system design, that is Unified Modelling platform which would provide a seamless communication and exchange of ideas and thoughts across different domains and stakeholders is still not available for designing a Mechatronics product. There are various software tools: Model Driven Development (MDD), Unified Modelling Language (UML) and Object Constraint Language (OCL), etc. However, they have limitations in providing a common design platform. Recently, Bond Graph based Unified Modelling Framework was proposed which could handle this design issue through both signal, and energy level interactions between system entities.


Author Bio:

Cyber Physical SystemDr Madhavan Shanmugavel is involved in teaching and research of Mechatronics at Monash University Malaysia campus for the past five years. His area of research includes Unmanned Autonomous Vehicle & vehicle systems, Path & trajectory planning and control, Navigation, Lateral dynamics and uncertainty propagation, Dynamical systems – Design, Modelling, Control, and experimentations.

He has extensive research and industrial experience in Mechatronics, Automotive and Aerospace domains. He holds PhD for the thesis work on Cooperative path planning of Unmanned Autonomous Vehicles from Cranfield University, UK. He acquired industrial experience in automotive testing and development from TATA Motors, India for four years. He got his Masters degree from Indian Institute of Technology Madras, India for the research on active suspension control. He holds professional memberships in Society of Automotive Engineers (SAE), International Federation of Automatic Control (IFAC) – Aerospace section. His main teaching duties are Dynamical systems, Mechatronics project, Engineering Mechanics, and Mechanics of Materials.

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