Cyber Physical System

The manufacturing industry represents a data rich environment, in which larger and larger volumes of data are constantly being generated by its processes. However, only a relatively small portion of it is actually taken advantage of by manufacturers. As such, the proposed Intelligent Data Analysis and Real-Time Supervision (IDARTS) framework presents a possible solution for the implementation of scalable, flexible and pluggable data analysis and real-time self-monitoring systems for manufacturing environments. IDARTS is aligned with the current Industry 4.0 trend, being aimed at allowing manufacturers to translate their data into a business advantage, combining distributed data acquisition, machine learning and run-time decision making support to assist in fields such as predictive maintenance and quality control, reducing the impact of disruptive events in production.

The war to technology and economic power have been the driver for industrialization in most developed countries. The first industrial revolution (industry 1.0) earned millions for textile mill owners while the second industrial revolution (industry 2.0) opened the way for tycoons and captains of industry like John D. Rockefeller, J.P. Morgan and Henry Ford. The third industrial revolution (industry 3.0) engendered technology giants like Apple and Microsoft, and made magnates of men like Steve Jobs and Bill Gates. Now, the race for the fourth industrial revolution (industry 4.0) is on and there is no option, every country whether developed or developing must participate. Many countries have positively responded to industry 4.0 by developing strategic initiatives to strengthen industry 4.0 implementation. Unlocking the country's potential to industry 4.0 has been of interest to researchers in the recent past. However, the extent to which industry 4.0 initiatives being launched globally has never been revealed. Therefore, the present study aimed at exploring industry 4.0 initiatives through comprehensive electronic survey of literature to estimate the extend of its launching in different regions. Inferences were drawn from industry 4.0 initiatives in developed nations to be used as the recommendations for East Africa Community. Results of the survey revealed that 117 industry 4.0 initiatives have been launched in 56 countries worldwide consisting of five regions. The country's percent of industry 4.0 initiatives as per region were: Latin America and the Caribbean (15%), North America (40%), Europe (53%), Asia and Oceania (25%), Middle East and Africa (11%). While the worldwide percent was estimated as 25%. This revealed that the big gap is existing between countries towards the race for industry 4.0.

We would like to invite you to join this exciting new project as a chapter contributor on one of the topics listed below. Since this is a textbook, a great deal of this chapter entails a survey on the topic under the paradigm of cyber-physical systems, what can be done onboard and remotely, the distributed nature of the system and some exercises on futurology (anticipating trends can shed some light on upcoming designs). IET will bring great visibility to your work. Each chapter should be around 20-25 pages each and can be submitted as a Word or Latex File. The IET will send you additional info (formatting, permission form, etc.) with the contributor's agreement once you have decided to contribute to the book. Visit http://www.theiet.org/resources/author-hub/books/index.cfm to get all contributor's information to an IET research-level book. Each book is expected to have a total number of 500 printed pages (with approximately 550 words per page and a 20% allowance for figures and tables). We have included a tentative schedule and list of topics below. If this is something you would consider, please send us the title of your chapter, a short description/abstract of the chapter content, and your full contact details. We will expect original content and new insights for this book. You can, of course, reuse published material but the percentage of material reuse for the chapter should be less than 40%. The IET will run a piracy software on the full manuscript to control that you are including original material and will reject chapters who contain a large amount of already-published material so please do take this into consideration. We would appreciate your feedback by December 31, 2017. Please do not hesitate to contact us if you have any queries. We look forward to working with you towards the successful publication.

An Emergency Response (ER) Cyber-Physical System (CPS) to avoid landslides and survey areas located on or near slopes is introduced that handles two problems: electronic waste disposal, and environmental disasters. Uncomplicated detection circuits using salvaged components can pinpoint floods in impoverished regions. CPSs simplify hazard prediction and mitigation in disaster supervision. Nonetheless, few green practices and efforts have been accomplished in this regard. Recent technical advances help landslides studies and the evaluation of suitable risk alleviation measures. This work addresses in situ meters, and cameras to observe ground movements more accurately. The ER-CPS identifies and can help mitigate landslides using techniques based on motion detection that can productively predict and monitor the zone conditions to classify it, and the landslide-related data can be transmitted to inspecting stations to lessen the erosion/sedimentation likelihood while increasing security.

This paper proposes a novel method for the structuring of the knowledge of a service process in order to be processed by lightweight declarative computing infrastructures. Through the identification of self-similarities in the process, the flow of the structured information and the sequence of activities performed in the process are easily implemented by means of cyber-physical systems technologies, in order to timely meet the customer/stakeholder’s requirements. The study was performed in a telecommunication service providing organization. Service teams create a collaborative network. With the use of the CPS proposed in this work they can communicate problems and disseminate solutions. This methodology uses the information of a set of performance indicators of the service organization to achieve a better control of the effectiveness and the bottlenecks in the supply network. The methodology is borrowed from the mechatronics field and it is prone to a natural extension and reuse for the similar information structures in manufacturing processes.

Industrial 4.0 technology of cyber-physical system enables real-time monitoring, sensing and actuating of physical machinery for predictive maintenance that replaces the conventional labor-intensive approach. This paper presents the design and development of a universal, cost-effective and internet of thing (IoT)-based proof-of-concept prototype universal cyberphysical system (UniCPS) with a cloud platform with an open and modularbased design of three-tier system architecture. The prototype demonstrates promising precision and accuracy for predictive maintenance on a pilot use case with MAPE of 3.77%, and average RMSE of 0.50. Besides, real-time visualization and detection of anomaly were also demonstrated with a cloudbased solution. The maintenance alert sent out by the actuator serves to notify the authorized personnel immediately for corrective action. As an extension to this work, a wireless sensor network can be incorporated in future work to acquire various data from diverse locations to overcome the limitations of sensor data.