Amusan, Lekan M and Aigbavboa, Clinton and Emetere, Moses and Owolabi, J. D (2023) Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence Manufacturing. In: Quality Control - Intelligent Manufacturing, Robust Design and Charts. Licensee IntechOpen, pp. 1-23.
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Abstract
Controlling quality has become a major trend in the circle of manufacturers and production managers that engage in intelligent manufacturing all over the world, on account of industry 4.0, in recent times. Intelligent manufacturing therefore is the use of advanced applications, analytics, sensors and Internet of Things (IoT) to improve manufacturing. The aim of the study is to carry out a study on application of disruptive application in managing quality system in intelligent manufacturing with a view to improving manufacturing process in organizations. Survey methods was used in collating responses from production managers of manufacturing companies at selected locations censoring production managers and supervisors on some parameters such as areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, Man-Whitney U Test, T-test, Pearson’s Test were used to analyze the collated data. Also, this study presents advanced analytical tools and applications to improve quality in manufacturing process. The study finally presents areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, emerging areas of application and recommendation for improvement.
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | quality, system, intelligence, adaptation, disruption, manufacturing, process |
| Subjects: | H Social Sciences > H Social Sciences (General) |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Civil Engineering and the Environment |
| Depositing User: | nwokealisi |
| Date Deposited: | 08 Jun 2023 11:22 |
| Last Modified: | 12 Jun 2023 12:22 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/16990 |
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