International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 02 | Feb-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 832 Asset Management in Manufacturing Industries Using Big Data Analytical Architecture Dr.T.R.Saravanan 1 , R.S.Vaibhave 2 1 Assistant Professor, Department of Computer Science and Engineering, JEPPIAAR SRR Engineering College, Padur, Chennai -603103. ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The asset management is for managing company's details by storing and sorting them. The company which wants to have a good place in market can make use of these ideas of storing data and further analyzing them. The storage is about details of the workers, machine and their functionalities, stock market details which require huge storage and therefore big data concept is employed. Handling with the data includes Hadoop, data mining technologies which are essential for this architecture. The structured, semi-structured and unstructured data has to be managed. The major purpose is to make use of the unused data of the company. The unused data are just the ones which have low necessity for the company but maybe of some use to the employee such as the machine details and the instructions of operating them. The employee can also get access to their own salary details by having authentication. By giving more features for the user the company can be more organized and easy for the employee at the same time. Here the data scientist plays an important role for visualizing the data which are to be given to the employee. The clustering and classification algorithms are used for sorted storage. The prediction process is carried after the report of all the data has been collected. Resultant graph is being generated so that it is easy for the authorities to analyze the growth and their position in market. Key Words: authentication, big data, classification, clustering, Hadoop, market 1. INTRODUCTION A huge amount of data for operating and maintaining is required and the asset of the company serves this purpose. Nowadays, every industry uses asset management functions for storing large amount of data. But they arenǯt using the best of it. Some companies donǯt even process the stored or existing data. This results in the degradation of the companyǯs performance and its efficiency. The Information and Communication Technologies have become dynamic and the industries should develop their standards by using these technologies efficiently [1]. Many applications and systems which are governed by these ICTǯs are implemented in some industrial areas. Though they make use of them, these technologies do not yield a complete overview about the system. Here the users and the data scientists are the major part of the system, primarily when it comes under the tree of big data. The big data objective is to process and handle data which is of high velocity, volume, variety and veracity [2]. In the view of Information and Communication Technology, Big Data is the best technology to be used in industries [3]. The data scientist must be an expert in solving the problems which arises during the understanding of data, preparing the data, modelling the data, evaluating the data and deploying it efficiently. Managing the assets in an efficient way with many facilities is the major goal. This includes maintaining the company's standards and also making the company more organized. The asset management system provides an easy way for storing the company's data and managing it. The architecture paves way for more accurate grouping of data and storing them in ordered way. The Hadoop distributed file system is used so that any type of data regarding the company can be handled. The data may be text, images and other formats also. The system overall generates a prediction report for the growth of the company. The upcoming part of the paper is arranged in the following manner. In section 2, this paper reviews about how the uploading of data and pre-processing is carried out. In section 3, the classification and clustering of the data is discussed. In section 4, the analysis and the prediction of the growth is explained. In section 5, the aspects of the user interface is presented. Section 6 depicts the overall structure of the system by explaining the architectural design. The section 7, describes the tools involved to achieve the successive environment. The following section consists of the future work to be carried out. Finally the section 8 summarizes the outcomes. These all operates in a single system and provides efficient management through big data technology. 2. FILE UPLOAD AND PREPROCESSING File uploading is the chief process which is carried out in every big data projects in order to work with it. Here in this system, the data stored up to date is to be considered for processing. Data gathering is the major step taken to perform stock market analysis. In the Manufacturing industrial sector, monitoring of various assets usually the sensors are used to keep the machineries in an optimal state and to reduce the maintenance downtime. This converts the physical machinery property into an electrical signal. Then the manipulation is performed using the filters to reduce the noise generated. And these are sent to a database where liable information can be obtained. This is also a part of asset of the company.