Industry 4.0 and Cybersecurity at Automobile Manufacturing in Smart Factories

The automotive industry in smart factories is constantly developing depending on technology. Depending on the developing technology, security problems come to the fore. Industry 4.0 and cyber security are widely used in automotive sector applications as well as in all areas of our lives. These applications pose security threats to automotive users and drivers. Attacks on vehicle software, especially by autonomous vehicle users, endanger passengers and vehicle safety. It should take the necessary precautions to be protected against cyber-attacks and be equipped to solve the problem. The rapid change of technology in smart factories and with industry 4.0 brings new security vulnerabilities and new cyber attacks. The hostility arising from inter-sectoral competition has lost its value compared to previous periods and has left its authority to cyberattacks, threats, and damaging moves against system security. Industry 4.0 is also known as the Industrial Revolution Industry, which covers a specific production technology and the interests of many groups, and exchanges data without human use and innovative system. With this industrial revolution, which also plays an active role in the establishment of a smart factory, more useful work examples are obtained as it ensures that each data is collected and analyzed in the best way in the production area. In this study, cyber attacks in the automotive industry and cyber threats in automobile factories are examined. In addition, layered protection has been proposed by investigating how to take precautions against these attacks and threats

Multi-objective resource allocation for Edge Cloud based robotic workflow in smart factory

Multi-robotic services are widely used to enhance the efficiency of Industry 4.0 applications including emergency management in smart factory. The workflow of these robotic services consists of data hungry, delay sensitive and compute intensive tasks. Generally, robots are not enriched in computational power and storage capabilities. It is thus beneficial to leverage the available Cloud resources to complement robots for executing robotic workflows. When multiple robots and Cloud instances work in a collaborative manner, optimal resource allocation for the tasks of a robotic workflow becomes a challenging problem. The diverse energy consumption rate of both robot and Cloud instances, and the cost of executing robotic workflow in such a distributed manner further intensify the resource allocation problem. Since the tasks are inter-dependent, inconvenience in data exchange between local robots and remote Cloud also degrade the service quality. Therefore, in this paper, we address simultaneous optimization of makespan, energy consumption and cost while allocating resources for the tasks of a robotic workflow. As a use case, we consider resource allocation for the robotic workflow of emergency management service in smart factory. We design an Edge Cloud based multi-robot system to overcome the limitations of remote Cloud based system in exchanging delay sensitive data. The resource allocation for robotic workflow is modelled as a constrained multi-objective optimization problem and it is solved through a multi-objective evolutionary approach, namely, NSGA-II algorithm. We have redesigned the NSGA-II algorithm by defining a new chromosome structure, pre-sorted initial population and mutation operator. It is further augmented by selecting the minimum distant solution from the non-dominated front to the origin while crossing over the chromosomes. The experimental results based on synthetic workload demonstrate that our augmented NSGA-II algorithm outperforms the state-of-the-art works by at least 18% in optimizing makespan, energy and cost attributes on various scenarios

Application of Industry 4.0 in the Procurement Processes of Supply Chains: A Systematic Literature Review

The fourth industrial revolution has significantly changed the traditional way of managing supply chains. The applications of Industry 4.0 (I4.0) technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) in different processes of supply chains have assisted companies to improve their performance. Procurement can be considered a critical process in supply chain management since it can provide novel opportunities for supply chains to improve their efficiency and effectiveness. However, I4.0 applications can be costly and may not be reasonably affordable. Therefore, the benefits of implementing these technologies should be clarified for procurement managers before investing in the digitalization of the procurement process. Despite the importance of this issue, few papers have attempted to address the effects of I4.0 technologies and smart systems in procurement. To fill this gap, a Systematic Literature Review (SLR) on the applications of I4.0 technologies in procurement has been used in this study. By reviewing 70 papers through appropriate keywords, a conceptual framework is developed to classify different value propositions provided by the different applications of I4.0 technologies in procurement processes. Results reveal nine value propositions that can provide a better understanding for the procurement department to analyze the benefits of implementing the related I4.0 technologies in different activities. Finally, findings and future study opportunities are concluded