Effectiveness improvement in manufacturing industry : trilogy study and open innovation dynamics
Tayal, Ashwani and Kalsi, Nirmal Singh and Gupta, Munish Kumar and Pimenov, Danil Yurievich and Sarikaya, Murat and Pruncu, Catalin I. (2020) Effectiveness improvement in manufacturing industry : trilogy study and open innovation dynamics. Journal of Open Innovation: Technology, Market and Complexity, 7 (1). 7. ISSN 2199-8531 (https://doi.org/10.3390/joitmc7010007)
Preview |
Text.
Filename: Tayal_etal_JOITMC_2020_Effectiveness_improvement_in_manufacturing_industry.pdf
Final Published Version License: Download (5MB)| Preview |
Abstract
The purpose of this investigation is to compute overall equipment effectiveness (OEE) in the small-scale industry. The novel approach is introduced to detect bottlenecks by which OEE can be improved. This study attempts to help small-medium enterprises in analyzing performance in a better way. The automotive industry was chosen for conducting the research. The present study is comprised of three phases. In the first phase, OEE was computed and compared with world-class manufacturing. The second phase includes three-level of Pareto analysis followed by making fishbone diagram to mitigate the losses. The third phase conducts improved OEE in the industry. There are seven major losses present in the industry which adversely affects the effectiveness of machine in any industry. This approach can reduce these losses and improve the quality, asset utilization (AU), OEE, total effective equipment performance (TEEP) and productivity of the machine. The study exposes that Pareto analysis uncovers all the losses and works on the principle of 80/20 rule. The major losses were thoroughly explored with the help of the fishbone diagram and solutions were implemented at the shop floor. As a result, availability, performance, quality, OEE, AU and TEPP show increment of 4.6%,8.06%, 6.66%, 16.23%, 4.16% and 14.58% respectively. The approach offers a good opportunity for both researchers and small-medium enterprises around the world to analyze the indicators of production losses, performance, and productivity in the manufacturing industry.
ORCID iDs
Tayal, Ashwani, Kalsi, Nirmal Singh, Gupta, Munish Kumar, Pimenov, Danil Yurievich, Sarikaya, Murat and Pruncu, Catalin I. ORCID: https://orcid.org/0000-0002-4926-2189;-
-
Item type: Article ID code: 74965 Dates: DateEvent30 December 2020Published25 December 2020AcceptedSubjects: Technology > Manufactures Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 05 Jan 2021 11:32 Last modified: 11 Nov 2024 12:56 URI: https://strathprints.strath.ac.uk/id/eprint/74965