To Implement “Lean Six Sigma” Concept in Automobile Manufacturing – A Case Study | Cloud Computing

Paper Title To Implement “Lean Six Sigma” Concept in Automobile Manufacturing – A Case Study Authors Dr. Narendra Mohan Mishra, Dr. S. M. Karim Abstract With the ever increasing demand of the customer in a highly competitive environment quality perfection is a desirable objective. The purpose of this paper is to bring the focus on problem solving techniques using Lean Six Sigma methodology and to change the mind set of peoples within the organization that root cause cannot be established just by thinking and engineering guesses. Six Sigma methodologies help to pin root causes using simple data collection and analysis technique. This case study will explain the application of various graphical and statistical tools of problem solving in real life like Pareto, Box Plot, Main effect plot, Interval plot and Binary logistic regression. The study was conducted at M/S Asahi India Glass an auto glass manufacturer a Tier 1 supplier of Maruti Suzuki India Limited (Largest Car Manufacturer of India). The major pain area was high rejection in Tempering process i.e. 62158 PPM against the target of 45000 PPM in FY 2013-14. With the scoping tools like tree diagram and Pareto, Product Backlite glass of Swift Dzire (MPG-BCK) was found the major contributor and characteristics identified for analysis were Curvature NG, Blast Head Breakage, and Roller Imprint. This rejection was being reported since inception. As a result by this case study after analysis and countermeasures the overall rejection reduced by 40%. Keywords Automotive Industry Case study on Quality improvement, Manufacturing Process–Tempered Glass, Customer Satisfaction, Major management Pain Area and Application of Various Statistical tools. Citation/Export MLA Dr. Narendra Mohan Mishra, Dr. S. M. Karim, “To Implement “Lean Six Sigma” Concept in Automobile Manufacturing – A Case Study”, April 16 Volume 4 Issue 6 , International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 370 - 408 APA Dr. Narendra Mohan Mishra, Dr. S. M. Karim, April 16 Volume 4 Issue 6, “To Implement “Lean Six Sigma” Concept in Automobile Manufacturing – A Case Study”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 370 - 408

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  International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 4 Issue: 6 355 - 359  ________________________________________________________________________________________________________    355 IJRITCC | June 2016, Available @     ________________________________________________________________________________________________________    Secure   Auditing   and   Maintaining   Block Le v el   Integrity   with Reliability   of Data   in   Cloud   Ms. Aishwarya R. Kumthekar, Dept. of computer, RMDSSOE , Pune Prof. Jyoti Raghatwan   Dept. of computer,   RMDSSOE, Pune   Abstract   —  Cloud storage systems are  becoming increasingly  popular and popular and the cloud computing is get ting enhance day by day it needs to provide more security with secure auditing. For storing large and large amount of data in cloud, requires more space and data can be replicated which will increase the space and cost too unnecessar  ily .  T o avoid this deduplication needs to be done. So , in this  paper, pondering the main issue of honesty and secure deduplication on cloud information. Specifically, going for achieving  both information uprightness as well as deduplication in cloud. And in this  paper, proposing the algorithm which will audit securely and provide block le v el deduplication as well as it will maintain reliability of data in cloud   Index T   erms   —  Secure  auditing,  Deduplication,  Reliability, Cloud computing, Third Party Auditor .    __________________________________________________*****_________________________________________________ I.   I  NTRODUCTION   Despite  the fact that cloud stockpiling framework has been generally embraced,   it neglects to oblige some critical emerging needs, for example, the capacities of auditing the integrity of cloud by cloud customers and then detecting copied by cloud servers. Shows the   issues underneath. The more issue is known as integrity auditing. Cloud server has the capacity alleviate customers from the substantial weight of capacity administration and maintenance. The distinction of the cloud stockpiling from the customers in-house stock-  piling is that the data is exchanged by means of the Internet and put away into some uncertain domain, and not under the control of the customers by any kind of stretch of the imagination, which inevitably raises the customers worries on the integrity of their data. These worries srcinate from the way that cloud stockpiling is defenseless to the security dangers from both the sides i.e. from outside and from in- side of the cloud, and also the uncontrolled cloud servers might inactively conceal the some amount of data misfortune the incidents from the customers to maintain their notoriety. In addition to this is that for saving money and the space, the cloud servers may effectively and purposely dispose of once in a while got to data less belonging to an ordinary customer.  Fig.1.Flow model. In the figure, user will upload file in the cloud, then third party auditor(TPA) will generate tag and encrypt the file. Blocks will be verified , deduplication of block will be taken place. If the tag exists then it wont generate the tag again. For each file it will generate secret key while when user will register into system, that time also secret key will  be generated with some random number. Clients of the cloud have vast information files to put away and it is de  pends on the cloud for information support and calculation. They can be the singular buyers or  business associations. The rest of the  paper is organized as follows:  - Section 2 discusses Literature Survey. Section 3  provides an overview of Proposed Work and implementation details Section 4 is consists of  proposed algorithm section 5 consists of r  esults and discussion and section 6 discusses about conclusion.  II.   LITERATURE SURVEY  1) Enabling Public Verifiability and Data Dynamics for Storage Security in Cloud Computing:  Cloud Computing is considered as the next generation architecture of IT Enterprise. It moves the database and the application software to the centralized large data centers, where the management of all the data and the services may not be fully tr  ustworthy[5]. This factor is unique and which brings about many security challenges, which have not  been well understood yet. In this  paper, it studies the  problem of ensuring the data integrity of all the storage in the Cloud Computing. In  particular, it can be consider the task of allowing a TPA, on the behalf of the cloud client and which verifies the integrity of all the data stored in the total cloud storage but only the dynamic data. Here introduction of TPA eliminates the total involvement of client through auditing, whether its data is stored in the cloud is indeed intact[5]. The support for data dynamics of data operation, such as  block modification,  International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 4 Issue: 6 355 - 359  ________________________________________________________________________________________________________    356 IJRITCC | June 2016, Available @     ________________________________________________________________________________________________________    updation,deletion , insertion is also a significant step towards  practicality .[5]. 2) Proofs of Ownership in Remote Storage   Systems:  Cloud storage systems are  becoming very  popular and  popular. It is the  pr  omising technology which keeps their cost down and is removing duplication of file , which stor  es only single copy of the data repeating[4]. In the Client side deduplication , it tries to attempts to identify the deduplication opportunities which are already present at the client and it saves the  bandwidth of uploading the copies of existing files to the server which is harmful. In this  paper trying to identify the attacks that exploit client-side deduplication, which is allowing an attacker to gain the access to arbitrary size files of other users based on a very small hash signature of these files[4]. An attacker , if he knows the hash signature of a file then he can convince the storage service that it owns that file, hence that server lets the attacker download the entire file. 3) DupLESS: Server-Aided Encryption for    Deduplicated Storage : The cloud storage service  providers such as Dropbox and others  performs the deduplication to save the space by only storing one copy of each file uploaded on it. Should clients conventionally encrypt their files, however their savings are lost. Message locked encryption (the  prominent manifestation of which is convergent encryption) r  esolves this all the tension[2]. However it is inher  ently subject to the  brute force attack that can r  ecover files falling into some known set. It enables the client for storing encrypted data with an existing service that have the service  perform deduplication on their behalf, and yet achieves strong confidentiality guarantees[2]. Showing that encryption for the de-duplicated storage can achieve the  performance and the space savings close to that of using all the storage service with  plaintext data.  4) Provable Data Possession at Untrusted   Stores : It Introduce a model for  provable data p ossession that is PDP , which allows a client that has stored data at an untrusted server for the verification of the server  possesses the srcinal data without retrieving[3]. This model generates the  probabilistic  proofs of the  possession  by sampling some random sets of blocks from the server, which drastically reduces the I/O costs[7]. III.   I MPLEMENTATION D ETAILS   3.1 SOFTWARE SPECIFICATIONS  For implementation we have used : 1. Coding Platform: Java  2. IDE : Eclipse  3. Database : MySQL   3.2 MATHEMATICAL MODEL    Fig. 2.  Mathematical Model Set Theory:  Let S be the system object It consist of following  Where S={ U, F,T P A,CSP } S denoted the System which consists of the following , That is U denotes Users , where F for Files , TPA denotes Third Party Auditor and CSP denotes Cloud Service Provider. Where input  1. I= {U,F} U={u1,u2,u3,..un} that is users can be infinite  F={f1,f2,f3,..fn} and files can be infinite. P that is  process consists of   2. P={TG,C,PF,V,POW, DD,BD,PF,F} CSP = {DD,BD,PF,F} DD= Deduplication  BD=Block level Deduplication   PF=proof if duplicate tag exist. F= store files if tag not exist T PA= { TG,C,P F,V ,POW } TG= tag Generation   C=challenge  PF =Proof by CSP V= Verification  by T PA POW= Proof of ownership  O is for the output  3. O= { Result } Save Tag and encrypted file if not exist.   3.3 PROPOSED SYSTEM ARCHITECTURE    Fig. 3 Architecture Cloud Clients:  Cloud Clients have large data to be stored and it depends on the cloud for the maintenance and computation of the data. They can be either the  International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 4 Issue: 6 355 - 359  ________________________________________________________________________________________________________    357 IJRITCC | June 2016, Available @     ________________________________________________________________________________________________________    =   individual consumers or may be the commer  cial organizations. Cloud Servers:  Cloud Servers are virtualize the resources ac- cording to the requirements of the clients and then it expose them as the storage  pools. Cloud clients may buy or lease storage capacity fr  om cloud servers, and then it stores their individual data in these  bought or the rented spaces for future utilization.   Auditor : Auditor helps the clients to upload and au- dit their outsourced data which maintains a MapReduce cloud and acts like a certificate authority. This assumption presumes that the auditor is associated with a pair of public and  private keys. Public key is made available to other entities in the system. IV.   P ROPOSED A LGORITHM   4.1 PHASES :   1. Setup Phase :  The challenger which first runs the setup algorithm with all the required security  parameter and the other  public  parameter as input. Then, it generates the public and secret key pair as (pk; sk). Then the public key pk is forwarded to the adversary A.   2. Query Phase :  The adversary A , is allowed to query the file upload as file F. Then, the file with the correct tags are generated and uploaded to the cloud storage server. These all the tags can  be  publicly verified with respect to the public key  pk[1].   3. Challenge Phase.:  Here A can adaptively send file F to the file tag then tag comes, C runs the integrity verification protocol known as IntegrityVerifyA C(pk; tag) with A.   4.Forgery:  Here A outputs a file tag and then the description of a  prover Pt.And can be said that a  prover Pt on tag is -admissible, if the following two conditions are hold:  (1) tag is a file tag output  by a  previous upload quer  y . (2) Pr[IntegrityVerifyPt C(pk; tag) = 1] . 4.2 Protocols Using   1.File Uploading Protocol: This  protocol used to allow the clients to upload files via the auditor.   Algorithm  1 Convergent   encryption  1: KeyGen: Input = file content F Output = the convergent ke y . 2: Encrypt: Input = convergent key, and file content Output = Ciphertext.  3: Decrypt: Input = convergent key, and ci-  phertext Output = Plain text  4: TagGen: Input= Takes a file content F Out-  put = Generate the tag. Algorithm 2 AES: AES use for encryption and decryption (for block level it uses 16 byte  block  ) 1: At the start derive the set of round keys from the cipher ke y . 2: Initialize the state array with the block data   (plaintext data).  3: Add the initial rounds key to the starting state of the arra y . 4: Perform nine rounds of state manipulation.  5: Perform the tenth and final round of state manipulation.  6: Copy the final state array out as the en-   crypted   data   (ciphertext).  plays the role of  prover, while the auditor or client works as the verifier of the data. 3.Proof of Ownership Protocol: This  protocol is typically comes with the file uploading protocol to  prevent the leakage of side channel information. On the contrast to integrity auditing protocol, in PoW the cloud server works as verifier, while the client  plays the role of the  pr  over  . Algorithm 3 SHA1- Block level deduplication (it is not encryption it is used for hash compu- tation)  1: Append Padding Bits  2: Append the Length to it  3: Prepare the  processing functions  4: Prepare processing constants  5: Initialize the  buf  fers  6: Processing   message in 512-bit blocks Parameter AES DES Key Size 128, 192 and 256 bits 64 (8:parity, effective key length:56 bits) Block Size 128 bits 64 bits Rounds 10,12,14 16 Flexible Flexible Not flexible Features Replacement for DES. Not enough structure. Table : Difference between AES and DES. 2.Integrity   Auditing  Protocol: The   cloud   server    Algorithm 4 Block level deduplication  1.   User will register to the system with his information  2.   Random secret key generation using Random( ) function. 3.   When user will login to the system , secret key must be verified.  4.   User will successfully login to the system , user will upload any file to cloud . 5.   File will have unique secret ke y . 6.   Setup Phase : The auditor initializes the  public key and  private key  Pk = ( g  , { u i  } t ) Sk ←   α  7.   KeyGen(F) : This key generation algorithm   takes a file content F as input and outputs the convergent key ckF of F;   K eyGen(F ) → ckF.    International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 4 Issue: 6 355 - 359  ________________________________________________________________________________________________________    358 IJRITCC | June 2016, Available @     ________________________________________________________________________________________________________    =   i =   8.   Encrypt(ckF; F) : Here the encryption algorithm takes the convergent key ckF and file content F as input and outputs the cipher- text ctF; 9.   Decrypt(ckF; ctF) : Here the decryption algorithm takes the convergent key ckF and ciphertext ctF as input and outputs the plain file F; 10.   TagGen(F) : Then the tag generation algo rithm takes a file content F as input and outputs the tag tagF of F.  Fig. 4. This  screen is used  for checking the role of user whether he is admin or user or T   P   A α ij = [ H   ash( I  DF || B i   )Π t u B ik    ]  j  11: Dividing the file into no of blocks First divide F ile into no of blocks and generate separate  block id for each block by using  12: File store on   server in the form of    ( I  D, F, α s )   4.3 Why to use these algorithms?  1. Why Convergent  encryption ? - If using file and users key then it will not  be able to detect the duplicate files since cipher texts of two files will be dif  fer  ent.  2. Why AES  Fig. 5. Here  secret key needs to enter using this  screen.  Fig. 6. User needs to upload file using this  screen.   V.   C ONCLUSION   Aiming to achieve both that is data integrity as well as  block level deduplication in cloud,  proposed in the above algorithm.  This helps the clients to generate the  block tags  before uploading as well as it helps to audit the integrity of data having  been stor  ed in cloud.   Additionly, this will enable secure  block level deduplication through intr  oducing a Proof of Ownership protocol and  preventing all the leakage of side channel information in data deduplication. Thus secur  e auditing,maintaining  block level integrity and will  provide reliability of data. R  EFERENCES   [1]   Secure Auditing and Deduplicating data in cloud, Jingwei Li , Jin Li, Dongqing Xie and Zhang cai ,IEEE T ransactions on computer vol . PP no 99 YEAR 2015”  [2]   S. Keelveedhi, M. Bellare, and T. Ristenpart, Dupless: Server- aided encryption for deduplicated storage, in Pro- ceedings of the 22Nd USENIX Conference on Security, ser. SEC13. Washington, D.C.: USENIX Association, 2013, pp. 179194. [3]   G. Ateniese, R. Burns, R. Curtmola, J. Herring, O. Khan, L. Kissner, Z. Peterson, and D. Song, Remote data checking using provable data possession, ACM Trans. Inf. Syst. Secur., vol. 14, no. 1, pp. 12:112:34, 2011. [4]   S. Halevi, D. Harnik, B. Pinkas, and A. Shulman-Peleg, Proofs of ownership in remote storage systems, in Pro- ceedings of the 18th ACM Conference on Computer and Communications Security. ACM, 2011, pp. 491500. [5]   Q. Wang, C. Wang, J. Li, K. Ren, and W. Lou, Enabling  public verifiability and data dynamics for storage security in cloud computing, in Computer Security ESORICS 2009, M. Backes and P. Ning, Eds., vol. 5789. Springer Berlin Heidelberg, 2009,  pp. 355370. [6]   G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner  , Z. Peterson, and D. Song, Provable data  possession at un- trusted stores, in Proceed- ings of the 14th ACM Conference on Computer and Communications Security, ser. CCS 07. New York,  NY, USA: ACM, 2007, pp. 598 609. [7]   G. Ateniese, R. Di Pietro, L. V. Mancini, and G. Tsudik, Scal- able and efficient  provable data  possession, in Proceedings of the 4th International Conference on Security and Privacy in
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