UPM Institutional Repository

Improvement of plastic manufacturing processes by six sigma and dmaic methods


Citation

Seham Ismail, Alhatem Satta and As'arry, Azizan and Sapuan, Salit Mohd and Tarique, Jamal (2023) Improvement of plastic manufacturing processes by six sigma and dmaic methods. Applied Science and Engineering Progress, 16 (spec.3). art. no. 6838. pp. 1-12. ISSN 2672-9156; ESSN: 2673-0421

Abstract

Improvements are required in any industry to maximize productivity by reducing faults in any method and removing overall waste produced within the manufacturing facility. This study examines the problems faced by some leading companies in the plastic manufacturing industry, such as Motorola, General Electric, and Zamil Plastic and how to solve them. In this study, the key difficulty in this plastic manufacturing industry was black dots, which can be seen in injection molding operations. When compared to other faults, the injection molding technique result shows that black dot defects are the main reason for rejects in May, making up almost 41% of all rejects. Because, Defectives Per Million Opportunities (DPMO) of products in Plastic Remote Controls (PRC) result in numerous wastes, statistical quality control (SQC) methods, such as the Pareto chart, cause-effect diagram, and control chart were utilized to examine the data. Also, this study shows that the time necessary for tool changeover was extremely long, resulting in a significant wait for manufacturing because multiple dies and molds were required for production (types of plastic fuel tanks). The novelty of this research is that it clarifies when the company uses six sigma and the DMAIC method to rapidly discover the problem in the products and find a suitable solution to save time, effort, and cost. Run charts and the layout of mold storage are used to solve the problem and ensure that the process is truly improved by reducing the time it takes to change over for tools and dies.


Download File

[img] Text
Improvement of Plastic.pdf - Published Version
Restricted to Repository staff only

Download (973kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.14416/j.asep.2023.04.003
Publisher: King Mongkut's University of Technology North Bangkok
Keywords: Black dot; DMAIC; DPMO; Six sigma; TQM; Industry; Innovation and infrastructure
Depositing User: Ms. Che Wa Zakaria
Date Deposited: 11 Oct 2024 07:42
Last Modified: 11 Oct 2024 07:42
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.14416/j.asep.2023.04.003
URI: http://psasir.upm.edu.my/id/eprint/108853
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item