IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-981-10-5577-5_22.html
   My bibliography  Save this book chapter

Six Sigma Implementation in Cutting Process of Apparel Industry

In: Quality, IT and Business Operations

Author

Listed:
  • Reena Nupur

    (Gautam Buddha University)

  • Kanika Gandhi

    (Bhavan’s Usha & Lakshmi Mittal Institute of Management)

  • Anjana Solanki

    (Gautam Buddha University)

  • P. C. Jha

    (University of Delhi)

Abstract

The present competitive market is focusing on industrial efforts in producing high-quality products with the lowest possible cost. In every real-life system, there are a number of factors that cause disturbance in the process performance and their output. Process improvements through minimizing or removing such factors provide advantages such as reduced wastage or re-machining and improved market share. To help in accomplishing these objectives, various quality improvement philosophies have been put forward in recent years that can maximize the quality characteristics to ensure the enhancement of product and process. Six Sigma is an emerging data-driven approach that uses methodologies and tools that lead to improved quality levels and fact-based decision-making. This paper presents the application of the Six Sigma methodology to reduce defects in a cutting process of a garment manufacturing company in India, which is concluded through an action plan for improving product quality level. The define–measure–analyze–improve–control (DMAIC) approach has been followed here to solve the underlying problem of reducing defects and improving sigma level through continuous improvement process. The process helps in establishing specific inspection methods adapted for defect type which causes maximum rejection and to prevent their appearance in product.

Suggested Citation

  • Reena Nupur & Kanika Gandhi & Anjana Solanki & P. C. Jha, 2018. "Six Sigma Implementation in Cutting Process of Apparel Industry," Springer Proceedings in Business and Economics, in: P.K. Kapur & Uday Kumar & Ajit Kumar Verma (ed.), Quality, IT and Business Operations, pages 279-295, Springer.
  • Handle: RePEc:spr:prbchp:978-981-10-5577-5_22
    DOI: 10.1007/978-981-10-5577-5_22
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:prbchp:978-981-10-5577-5_22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.