Design and development of a cyber-physical system for adaptive scheduling and control of manufacturing systems

Traditional manufacturing, through the fourth industrial revolution, moves to each next phase that if digitalization. This revolution transforms the manufacturing systems into modern, digitalized ones. However, the digital transformation of manufacturing requires flexible and adaptive production...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Βλάχου, Αικατερίνη
Άλλοι συγγραφείς: Μούρτζης, Δημήτριος
Μορφή: Thesis
Γλώσσα:Greek
Έκδοση: 2019
Θέματα:
Διαθέσιμο Online:http://hdl.handle.net/10889/12338
Περιγραφή
Περίληψη:Traditional manufacturing, through the fourth industrial revolution, moves to each next phase that if digitalization. This revolution transforms the manufacturing systems into modern, digitalized ones. However, the digital transformation of manufacturing requires flexible and adaptive production systems which however lead to increased system’s complexity. Moreover, the lack of communication among the existing information and communications (ICT) tools in the production and the absence of infrastructure for the automated management and the re-use of knowledge can lead to difficulties to the communication and the transmission of information. Summarising the above, existing production systems utilize ICT tools which work in isolation without interfacing or communication among them. Consequently, often, the information but also the knowledge remains in the limits of concrete department of enterprise without communicating it to the rests functions of the company so as to be informed aiming to make accurate decisions based on the real-condition of the production. This thesis, considering the main challenges of the digitalized manufacturing enabled by the 4 th Industrial revolution, is focused on the design and development of a cyber-physical system capable of sensing and capturing data from shop-floor in near real-time and transmitting them using wireless sensor networks and industrial communication protocols to a cloud platform. Once the data is captured is analysed, and the meaningful information is delivered to a multi-criteria decision-making algorithm for adaptive scheduling as well as to a condition-based maintenance tool which is also supported by Augmented reality technology. The main contribution of the present thesis is summarized in the bullets below: 1. Investigation of the needs and challenges of manufacturing systems towards digitalized manufacturing enabled by the 4 th Industrial revolution and the Industrial Internet of Things. 8Increased need for interoperability, communication, and adaptability through the effective and efficient integration between the physical and the cyber systems. 2. Design and development of a low-cost, reliable and reconfigurable monitoring system capable of sensing the real shop-floor condition and transmitting the captured data though wireless sensor networks and industrial communication protocols and standards. Through the proposed system can be identified and calculated the machine tool status, the machine tool actual machining time, the energy consumption, as well as the condition of the running tasks. 3. Definition and calculation of meaningful performance indicators (KPIs monitoring) in near real- time, considering among others machine tool status, actual machining time, machine tool energy consumption, remaining operating time between failure, machine tool availability and utilization. 4. Design and development of an algorithm and tool for adaptive production scheduling based on the real information captured from shop-floor. Interface and data exchange between the monitoring system and the scheduling algorithm. A multi-criteria algorithm capable of recognizing and receiving meaningful information from shop-floor and generating feasible alternative schedules quickly and accurately. The monitoring system senses the shop-floor condition and in case it recognizes any disturbances, inform the scheduling algorithm and tool and also sends to it the current shop-floor condition aiming to use the provided information and reschedule based on that. 5. Design and development of an algorithm for condition-based maintenance of machine tools supported by Augmented reality technology. Remote maintenance of machine tools based on their real condition, recognizing their status and the remaining operating time between failures. The AR remote maintenance application is capable of receiving in near real-time the machine tools condition, capturing the problem using the AR mobile application and receiving thought AR the required instructions aiming to perform the maintenance of the machine tools efficiently, quickly and cost-effectively. 6. Development of the cyber-physical system in a cloud platform. The developed applications can be provided as service through the cloud platform and also it enables ubiquitous data access and interoperability among the different tools and methods. Through the developed cloud platform multi user can have access to the application increasing collaboration and efficient data exchange. 7. Implementation and validation of the developed cyber-physical system in real industrial environments with real industrial data. The different tools and methods of the CPS are implemented in different industrial cases considering a machine shop-floor, a mould-making industry and a white goods industry. The results of the implementation revealed the main benefits of the proposed system compared to the traditional way of manufacturing systems operation as well as compared to existing approaches.