Applying Industrial Internet of Things Analytics to Manufacturing

Author:

Wu Chun-Ho1ORCID,Ng Stephen Chi-Hung1ORCID,Kwok Keith Chun-Man2ORCID,Yung Kai-Leung3ORCID

Affiliation:

1. Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong

2. Ka Shui Enterprise Academy, Ka Shui International Holdings Limited, Kowloon Bay, Hong Kong

3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Abstract

The proliferation of Industry 4.0 (I4.0) technologies has created a new manufacturing landscape for manufacturing, requiring that companies follow I4.0 trends to stay competitive. However, in this novel digital automated environment, these companies must also ensure that lean manufacturing principles are upheld. This study proposes a data-driven framework for analysing raw data across machines in manufacturing systems that can provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework offers an alternative approach to improving manufacturing processes that involves utilising the power of I4.0 technologies in conjunction with lean manufacturing principles. This study’s examination of unprocessed data also provides guidance on improving legislation. The findings of this study provide direction for future research in the field of manufacturing and offer useful advice to businesses wishing to integrate I4.0 technologies into their operations.

Funder

University Grants Committee of the HKSAR, China

School Research Grant, HSUHK

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Optimization,Mechanical Engineering,Computer Science (miscellaneous),Control and Systems Engineering

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