An exploration of supply chain management practices in the aerospace industry and in Rolls-Royce

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.Includes bibliographical references (leaves 95-96).This thesis is a part of the Supply Chain 2020 research project which seeks to study best practices in supply chain management in multiple industries in order to develop a deeper understanding of key principles and practices characterizing the creation of excellent supply chains through a long-term research agenda. This thesis addresses the first phase of the research by concentrating on the aerospace industry and by focusing on Rolls-Royce through a case study. The objective of the thesis is to conduct an exploratory study of the best practices in supply chain management in the aircraft engine manufacturing industry, and how these practices impact the competitive positioning of an engine manufacturer within the industry. The analysis involves a broad review of the current state and future directions of the aerospace industry by tracing the key factors shaping its evolution and by identifying the major strategic forces that would influence its future. Within this general industry context, the thesis analyzes Rolls-Royce's position in the industry as a leading aircraft engine manufacturer and presents a focused study of Rolls-Royce's supply chain management practices.(cont.) In particular, the thesis involves a deeper exploration of the aircraft engine manufacturing business segment of Rolls-Royce and strives to understand the company's supply chain management practices, by examining the role of major factors that have proven crucial to effective supply chain management within the company. The thesis also presents more specific case study examples that track the implementation and results of major supply chain management initiatives. Finally, the supply chain design and management practices are analyzed from the perspective of their role in the company's business strategy. This is accomplished by employing a number of business strategy frameworks to understand the key factors that determine the competitiveness of a tier one supplier in the aerospace industry, such as Rolls- Royce, and by examining how those factors have affected Rolls-Royce's supply chain management strategies and practices.by Mohit Tiwari.M.Eng.in Logistic

Language Without Words: A Pointillist Model for Natural Language Processing

This paper explores two separate questions: Can we perform natural language processing tasks without a lexicon?; and, Should we? Existing natural language processing techniques are either based on words as units or use units such as grams only for basic classification tasks. How close can a machine come to reasoning about the meanings of words and phrases in a corpus without using any lexicon, based only on grams? Our own motivation for posing this question is based on our efforts to find popular trends in words and phrases from online Chinese social media. This form of written Chinese uses so many neologisms, creative character placements, and combinations of writing systems that it has been dubbed the "Martian Language." Readers must often use visual queues, audible queues from reading out loud, and their knowledge and understanding of current events to understand a post. For analysis of popular trends, the specific problem is that it is difficult to build a lexicon when the invention of new ways to refer to a word or concept is easy and common. For natural language processing in general, we argue in this paper that new uses of language in social media will challenge machines' abilities to operate with words as the basic unit of understanding, not only in Chinese but potentially in other languages.Comment: 5 pages, 2 figure

Inferno: Side-channel Attacks for Mobile Web Browsers

We demonstrate power consumption as a side-channel on mobile devices. While web pages may look aesthetically similar, the web browser exercises different behaviors while rendering the underlying code. The variance between the browser’s behavior and power consumption implies that different webpages consume different amounts of power. Thus, webpages can be uniquely identified from one another by analyzing power traces collected during a page load. While power channel attacks and defenses have been analyzed for fixed function units such as secure cryptoprocessors, this side- channel has not been studied for general-purpose systems such as mobile devices. In our evaluation, we use this side-channel to reveal a mobile user’s browsing activity from the hardware level with 80% accuracy. In addition, we attempt to develop countermeasures to combat this type of attack. We use two approaches to decrease information leakage: normalizing the computational workload to make a signal indistinguishable or increasing the amount of computational noise to make a signal incomparable. To do this, we altered DVFS (Dynamic Voltage and Frequency Scaling) to alter CPU frequency. We noticed that holding CPU frequency constant improved the accuracy of our machine learning classification. Thus, we developed a CPU governor that would change the frequency randomly. This defense managed to reduce the accuracy of the attack to 26%.Electrical and Computer Engineerin

NeuroComb: Improving SAT Solving with Graph Neural Networks

Propositional satisfiability (SAT) is an NP-complete problem that impacts many research fields, such as planning, verification, and security. Mainstream modern SAT solvers are based on the Conflict-Driven Clause Learning (CDCL) algorithm. Recent work aimed to enhance CDCL SAT solvers by improving their variable branching heuristics through predictions generated by Graph Neural Networks(GNNs). However, so far this approach either has not made solving more effective, or has required online access to substantial GPU resources. Aiming to make GNN improvements practical, this paper proposes an approach called NeuroComb, which builds on two insights: (1) predictions of important variables and clauses can be combined with dynamic branching into a more effective hybrid branching strategy, and (2) it is sufficient to query the neural model only once for the predictions before the SAT solving starts. NeuroComb is implemented as an enhancement to a classic CDCL solver called MiniSat and a more recent CDCL solver called Glucose. As a result, it allowed MiniSat to solve 11% and Glucose 5% more problems on the recent SATCOMP-2021 competition problem set, with the computational resource requirement of only one GPU. NeuroComb is therefore a both effective and practical approach to improving SAT solving through machine learning

Exploring Machine Learning Methods for IoT Network Intrusion Detection Systems

An ad hoc network is a transient network that is self-organizing and does not require any infrastructure. Therefore, the majority of its applications are in the field of military work and disaster assistance. Because of wireless connectivity and the ability to organize itself, ad hoc networks are becoming more common. Susceptible to a greater number of breaches or assaults than the conventional system. Blackhole assault is a significant routing disruption attack that a rogue node promotes itself as being capable of. as a step along the way to the final destination. In this research, we simulated a black hole using computer models. Assault in a setting with ad hoc networking, as well as data collection of important features for the purpose of classifying aggressive behaviour. Then, several different approaches to machine learning have been developed. utilized for the classification of information regarding benign and harmful packets. It seems to imply. a novel method for the selection of certain features, the gathering of crucial information, and the intrusion detection in an ad hoc network with the application of machine learning algorithms

Data Security Using Stegnography and Quantum Cryptography

Stegnography is the technique of hiding confidential information within any media. In recent years variousstegnography methods have been proposed to make data more secure. At the same time differentsteganalysis methods have also evolved. The number of attacks used by the steganalyst has only multipliedover the years. Various tools for detecting hidden informations are easily available over the internet, sosecuring data from steganalyst is still considered a major challenge. While various work have been done toimprove the existing algorithms and also new algorithms have been proposed to make data behind theimage more secure. We have still been using the same public key cryptography like Deffie-Hellman andRSA for key negotiation which is vulnerable to both technological progress of computing power andevolution in mathematics, so in this paper we have proposed use of quantum cryptography along withstegnography. The use of this combination will create key distribution schemes that are uninterceptable thusproviding our data a perfect security.Keywords: Stegnography, Steganalysis, Steganalyst, Quantum Cryptography