JOURNAL ARTICLE
Evaluation of OEE at Lifelong India Using Lean Practices: A Case Study.
Published In: International Journal of Reliability, Quality & Safety Engineering, 2025, v. 32, n. 2. P. 1 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Surya, Amit; Kumar, Rakesh; Trehan, Rajeev 3 of 3
Abstract
Today, the industry is facing issues related to nonvalue-added activities (NVA). By integrating lean practices, industries can systematically evaluate and enhance their overall equipment effectiveness (OEE), leading to more efficient and effective production processes. This alignment not only boosts productivity by eliminating nonvalue activities but also contributes to higher quality outputs and reduced operational costs as well. Manufacturers are required to use value-added approaches in their manufacturing management due to the intense rivalry in real-world markets and growing client needs. Through continuous improvement, lean manufacturing (LM) has been demonstrated to be a significant technique for getting rid of nonvalue-added operations in manufacturing organizations. OEE at Lifelong India is assessed using lean tools and techniques, including Pareto analysis, Why–Why analysis, Kaizen concept and evaluation of Kaizen ideas, as well as before-and-after comparison, in order to assess the operational performance of the organization. A questionnaire was designed with data collection in mind, and business professionals in the field were surveyed and contacted personally. This study indicates that widespread implementation of lean principles leads to an increase in OEE of 95.89%, a level of OEE that is unmatched in the industry and ensures flawless output. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Reliability, Quality & Safety Engineering. 2025/04, Vol. 32, Issue 2, p1
- Document Type:Article
- Subject Area:Economics
- Publication Date:2025
- ISSN:0218-5393
- DOI:10.1142/S0218539324400035
- Accession Number:184324680
- Copyright Statement:Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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