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DATA ANALYTICS SUPPORTING LEAN MANUFACTURING TOWARDS INDUSTRY 4.0 THROUGH SIMULATION: A REVIEW
Author(s) -
Soufhwee Abdul Rahman,
Effendi Mohamad,
Azrul Abdul Rahman,
Ihwan Hamdala,
Aisyah Larasati,
Supawi Pawenang,
Teruaki Ito
Publication year - 2020
Publication title -
journal of engineering and management in industrial system
Language(s) - English
Resource type - Journals
eISSN - 2477-6025
pISSN - 2338-3925
DOI - 10.21776/ub.jemis.2020.008.01.6
Subject(s) - lean manufacturing , analytics , computer science , industry 4.0 , data science , production (economics) , manufacturing , manufacturing engineering , risk analysis (engineering) , industrial engineering , business , engineering , marketing , data mining , economics , macroeconomics
The Lean Manufacturing (LM) system has been increasingly used in many industrial applications, worldwide, in the last 3 decades. The LM system is based on sound philosophy and includes several tools and principles, which permit its usage in eliminating wastes and decreasing the production costs. Though the conventional LM is helpful, the new paradigm, i.e., Industry 4.0, has started challenging the system. The traditional LM system cannot analyse the complex issues present in the existing competitive market on its own. This is because the Industry 4.0 is based on data which is more diverse, complex and fast. In this review, the researchers have attempted to identify the solution for the current scenario. Literature survey showed that simulation was a relevant tool that could be used for addressing the complexity-based issues related to the new concept. Though the combination of the simulation and LM system helped in understanding the problems, there still existed a gap in the LM system with regards to the merging of the 2 technologies of Industry 4.0.

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