Development of Web Based Application for Supply Chain Management

As a firm staying competitive in the market is never easy. It faces a lot competition from each and every competitor. The firms have to always come up with a better strategy to satisfy their customers, incorporate latest technologies to provide better service to their customers. The web based application for the supply chain management is a solution that supports collaboration in Supply Chain as the foundation for gaining competitive advantage and maintain market share. There are some other ways to obtain the collaboration but this is a better solution. There are several technologies that are needed for the design and implementation of this web application, some of the include technologies like Java, HTML, CSS, Java Script, Angular JS, Angular Schema form. There is a high level integration needed to bring this on to a single track and make this work. This web application has used the up to date technologies so this way the application can be the most sophisticated one on the market. This application uses technologies that are completely open source and involves a lot less capital than other tools out there in the world. This way the firm whoever uses this technology will be able to see a growth in the productivity, higher profits and the most important thing would be to make the customers happier. With some minor changes to the application it shall be able to make it available to other companies as well. This report describes the technologies used and how are they integrated, if this application was really able to manage the supply chain management in the company. This section gives an overview about the design of the application, the forecasting of the demand. The results showed an improvement in the manufacturing process of the company, reduction in the transportation costs

An Inference-based Prognostic Framework for Health Management of Automotive Systems

This paper presents a unified data-driven prognostic framework that combines failure time data, static parameter data and dynamic time-series data. The framework employs proportional hazards model and a soft dynamic multiple fault diagnosis algorithm for inferring the degraded state trajectories of components and to estimate their remaining useful life times. The framework takes into account the cross-subsystem fault propagation, a case prevalent in any networked and embedded system. The key idea is to use Cox proportional hazards model to estimate the survival functions of error codes and symptoms (probabilistic test outcomes/prognostic indicators) from failure time data and static parameter data, and use them to infer the survival functions of components via soft dynamic multiple fault diagnosis algorithm. The average remaining useful life and its higher-order central moments (e.g., variance, skewness, kurtosis) can be estimated from these component survival functions. The framework is demonstrated on datasets derived from two automotive systems, namely hybrid electric vehicle regenerative braking system, and an electronic throttle control subsystem simulator. Although the proposed framework is validated on automotive systems, it has the potential to be applicable to a wide variety of systems, ranging from aerospace systems to buildings to power grids