M
Mohd Nizam Ab Rahman
Researcher at National University of Malaysia
Publications - 222
Citations - 2121
Mohd Nizam Ab Rahman is an academic researcher from National University of Malaysia. The author has contributed to research in topics: Supply chain & Lean manufacturing. The author has an hindex of 21, co-authored 211 publications receiving 1713 citations. Previous affiliations of Mohd Nizam Ab Rahman include Islamic University of Indonesia.
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A systematic literature review of internal capabilities for enhancing eco-innovation performance of manufacturing firms
TL;DR: In this article, the authors present the lack of current research regarding the internal capabilities of manufacturing firms in enhancing eco-innovation, and present a framework with recommendations for future research, including the most crucial capabilities, dynamic, and integration.
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A framework for organisational change management in lean manufacturing implementation
TL;DR: In this article, the authors present a thorough literature review for lean manufacturing approach in the context of organisational change management and propose an organizational change framework for Lean manufacturing implementation that would serve as the basis for further empirical research and validation.
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Implementation of 5S Practices in the Manufacturing Companies: A Case Study
Mohd Nizam Ab Rahman,Nor Kamaliana Khamis,Rosmaizura Mohd Zain,Baba Md Deros,Wan Hasrulnizzam Wan Mahmood +4 more
TL;DR: In this paper, two manufacturing companies were involved in a study to assess the implementation of 5S practice, and both companies agreed that 5S is seen as an effective technique that can improve housekeeping, environmental performance, health and safety standards in their workplace.
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Lean supply chain practices in the Halal food
TL;DR: In this paper, a survey was conducted to assess the possibility of implementing lean practices in the Halal food supply chain, and the barriers to their implementation, which revealed that more than 70 percent of the firms reported that lean supply chain has not yet been implemented in their firm.
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Lung Infection Segmentation for COVID-19 Pneumonia Based on a Cascade Convolutional Network from CT Images.
Ramin Ranjbarzadeh,Saeid Jafarzadeh Ghoushchi,Malika Bendechache,Amir Amirabadi,Mohd Nizam Ab Rahman,Soroush Baseri Saadi,Amirhossein Aghamohammadi,Mersedeh Kooshki Forooshani +7 more
TL;DR: In this article, a two-route convolutional neural network (CNN) was proposed by extracting global and local features for detecting and classifying COVID-19 infection from CT images, which achieved precision 96%, recall 97%, F score, average surface distance (ASD) of 2.8 ± 0.3 mm, and volume overlap error (VOE) of 5.6 ± 1.2%.