Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence Manufacturing

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 an...

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Main Authors: Lekan, Amusan (Author), Aigbavboa, Clinton (Author), Emetere, Moses (Author), Owolabi, James (Author)
Format: Ebooks
Published: IntechOpen, 2021-03-24.
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042 |a dc 
100 1 0 |a Lekan, Amusan  |e author 
700 1 0 |a Aigbavboa, Clinton  |e author 
700 1 0 |a Emetere, Moses  |e author 
700 1 0 |a Owolabi, James  |e author 
245 0 0 |a Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence Manufacturing 
260 |b IntechOpen,   |c 2021-03-24. 
500 |a https://mts.intechopen.com/articles/show/title/adapting-disruptive-applications-in-managing-quality-control-systems-in-intelligence-manufacturing 
520 |a 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. 
540 |a https://creativecommons.org/licenses/by/3.0/ 
546 |a en 
690 |a Quality Control - Intelligent Manufacturing, Robust Design and Charts 
655 7 |a Chapter, Part Of Book  |2 local 
786 0 |n https://www.intechopen.com/books/9925 
787 0 |n ISBN:978-1-83962-497-1 
856 \ \ |u https://mts.intechopen.com/articles/show/title/adapting-disruptive-applications-in-managing-quality-control-systems-in-intelligence-manufacturing  |z Get Online