Photo of Dr Jelena Milisavljevic Syed

Dr Jelena Milisavljevic Syed PhD MS MEng MIET FHEA

Honorary PGR Supervisor Civil Engineering and Industrial Design

Research

Architecting Cyber-Physical-Product-Service Systems

Architecture for Design of Cyber-Physical-Product-Service (CPPS) Systems
Architecture for Design of Cyber-Physical-Product-Service (CPPS) Systems

In today’s global market, dynamic market changes due to variations in customer preferences or disruptions in supply chains or during production require global adjustments in manufacturing to accommodate these changes and meet the demands in a timely manner. Further, global competition requires enterprises to provide cost-effective manufacturing processes while improving product quality and shortening time to market. Traditional manufacturing is designed to fit the need for mass production at a low cost and cannot respond adequately in a timely manner to today’s market demands.
Integration of smart sensors and networked manufacturing systems has given rise to Cyber-Physical Manufacturing Systems that are capable of addressing the requirements of individual customers on a global scale. In the Industry 4.0, we bring together technologies such as the Internet of Things (IoT), Big Data Analysis, Machine Intelligence, with traditional technologies such as Smart Automation, Supply Chain, Logistics, and Cloud Computing making a new wave of advances in Manufacturing Technology. Factories conforming to Industry 4.0 will integrate services across the entire manufacturing process and will be able to adapt to disruptions in real-time and thereby improving the quality of products and services. The vertical integration of IoTs and analytics will enable these factories to optimize supply and logistic networks, implement policies based on predictive instead of reactive behavior, improve end-to-end throughput, and provide services and products at a lower cost.To understand Industry 4.0 it is essential to realize the full value chain which includes the supply chain, customer and markets, see figure. The digitization of the production process is supposed to enable the creation of digitized models of the manufacturing process, interactions with customers help address inefficiencies in production while improving customer satisfaction through the introduction of value-added services. Further, data and optimization across the value chain enable new capabilities in areas such as product design, prototyping and development, remote control, services and diagnosis, condition monitoring, pro-active and predictive maintenance, track and trace, structural health and systems health monitoring, planning, innovation capability, agility, real-time applications and more.
There are two fundamental ways in which these technologies are integrated into Industry 4.0. The first is vertical integration, see figure vertically, where low-level components such as IoT sensors and machine controllers across the manufacturing enterprise are networked with big data analytics in order to monitor the manufacturing process and improve system performance and product quality in real-time. Vertical integration also allows for the creation of interoperable ‘systems of systems’ that can integrate a seemingly diverse set of machines, sensors, and controllers to produce a resilient manufacturing process that is capable of withstanding disruptions in the supply chain, environment and in the market. The second is the horizontal integration, see figure horizontally, which is not about the hierarchical view of several systems as in vertical integration but about the end-to-end value chain: from a supplier and the processes, information flows and IT systems in the product development and production stage to logistics, distribution and ultimately the customer. In addition to the challenges in integration, implementation of Industry 4.0 also has to address cloud computing, big data analytics, and cybersecurity.

Prospective students should send their CV and cover letter for consideration at the
dropbox link.

Knowledge-based Design of Cyber-Physical-Product-Service (CPPS) Systems

In today’s global market, dynamic market changes due to variations in customer preferences or disruptions in supply chains or during production require global adjustments in production to accommodate these changes and meet the demands in a timely manner. Further, global competition requires enterprises to provide cost-effective processes while improving process-product-service quality and shortening time to market.
Designing systems that can address the needs of the modern (digitized) industry has to start by selecting an architecture that can accommodate the demands of the marketplace and the influence of disruptive technologies in the design of the Cyber-Physical-Product-Service (CPPS) systems. However, this is not a trivial task and there are challenges such as inefficient knowledge exchange between different domains, extract and save useful information in the mass of data for effective decision making, and reuse this knowledge to improve the design of CPPS systems while meeting the dynamic market requirements in a timely manner.
Our aim is to investigate how to exchange knowledge efficiently between domains in concurrent design of CPPS systems, achieve decision support, and (re)use the knowledge for feedforward dynamic management of the CPPS systems.
Prospective students should apply at the following link

Framework for Supply Chain 4.0

Conventional manufacturing is centered around the need to mass produce goods with consistent quality and at a low cost. One of the objectives of conventional manufacturing was to reduce the effect of variations in components, sensor/actuator faults, or local disruptions in the supply chain on the quality of the product and productivity of the process. However, such implementations are not capable of addressing globally distributed manufacturing processes or dynamic changes in the market and in customer preferences.
Design of manufacturing systems in the age of Industry 4.0 requires a new paradigm that considers the distributed and networked aspect of the manufacturing process and provides a mechanism for the seamless exchange of data between the physical and cyber components. While this implementation of such paradigm facilitates efficient data flows between different machines in the manufacturing process until now it did not deliver on the promise of Industry 4.0 as the integration with supply chain, big data analytics or enterprise-level planning modules is a challenging task.
Our aim is to investigate a scientifically grounded computational framework for decision-based adaptable concurrent design, operability and reconfiguration of cyber-physical supply chain activities in cloud manufacturing networks.
Prospective students should apply at the following link

Research Collaborations

Janet K. Allen

Project: Cloud-Based Design and Manufacturing
External: System Realization Laboratory (SRL), the University of Oklahoma

International System Realization Partnership (ISRP) is a partnership between the Systems Realization Laboratory (OU), USA, the Design Engineering Laboratory (Purdue), USA, the Institute for Industrial Engineering (Beijing Institute of Technology), China, the Division of Industrial Design, University of Liverpool, UK, and the Department of Electrical and Biomedical Engineering, University of Nevada, USA.

Farrokh Mistree

Project: Cloud-Based Design and Manufacturing
External: System Realization Laboratory, the University of Oklahoma

International System Realization Partnership (ISRP)

Guoxin Wang

Project: Cloud-Based Design and Manufacturing
External: Beijing Institute of Technology

International System Realization Partnership (ISRP)

Dirk Schaefer

Project: Cloud-Based Design and Manufacturing
Internal

International System Realization Partnership (ISRP)

Sesh Commuri

Project: Cloud-Based Design and Manufacturing
External: Department of Electrical and Biomedical Engineering, the University of Nevada, Reno

International System Realization Partnership (ISRP)

Zhenjun Ming

Project: Cloud-Based Design and Manufacturing
External: Beijing Institute of Technology

International System Realization Partnership (ISRP)

Anand Balu Nellippallil

Project: Cloud-Based Design and Manufacturing
External: Mississippi State University

International System Realization Partnership (ISRP)

Xiwen Shang

Project: Cloud-Based Design and Manufacturing
External: China North Vehicle Research Institute

International System Realization Partnership (ISRP)

Ru Wang

Project: Cloud-Based Design and Manufacturing
External: Beijing Institute of Technology

International System Realization Partnership (ISRP)