TY - JOUR
T1 - Extended material requirement planning (MRP) within a hybrid energy-enabled smart production system
AU - Guchhait, Rekha
AU - Sarkar, Mitali
AU - Sarkar, Biswajit
AU - Yang, Liu
AU - AlArjani, Ali
AU - Mandal, Buddhadev
N1 - Publisher Copyright:
© 2024 Elsevier Inc.
PY - 2024/11
Y1 - 2024/11
N2 - A smart production system can be made energy-efficient using renewable energy and is considered to maintain the extended material requirement planning under a logistics system by using radio frequency identification. The tracking technology provides information about products with real-time notification. This study investigates renewable energy usage within a smart production system as renewable energy can contribute to Net Zero Emissions. The logistics framework involves an autonomation technology-based production system, optimum cash flow, logistics, and carbon emissions. Time is an essential influencer for material requirement planning. The model is solved with a Laplace integral transformation, where an associated matrix method is utilized by the input–output analysis. The theoretical concept is elaborated through an illustrative numerical example, where the energy consumption and corresponding net present values are evaluated. Numerical and graphical studies prove the effectiveness of the model for the use of renewable energy within for material planning under a reverse logistics system. The result reveals that efficient renewable energy consumption can save considerable costs and reduce the negative net present value of the system. It is found that skilled workers are worthy of a smart production system, not only in a qualitative aspect but also in an economic aspect.
AB - A smart production system can be made energy-efficient using renewable energy and is considered to maintain the extended material requirement planning under a logistics system by using radio frequency identification. The tracking technology provides information about products with real-time notification. This study investigates renewable energy usage within a smart production system as renewable energy can contribute to Net Zero Emissions. The logistics framework involves an autonomation technology-based production system, optimum cash flow, logistics, and carbon emissions. Time is an essential influencer for material requirement planning. The model is solved with a Laplace integral transformation, where an associated matrix method is utilized by the input–output analysis. The theoretical concept is elaborated through an illustrative numerical example, where the energy consumption and corresponding net present values are evaluated. Numerical and graphical studies prove the effectiveness of the model for the use of renewable energy within for material planning under a reverse logistics system. The result reveals that efficient renewable energy consumption can save considerable costs and reduce the negative net present value of the system. It is found that skilled workers are worthy of a smart production system, not only in a qualitative aspect but also in an economic aspect.
KW - Industry 4.0
KW - Laplace transformation
KW - Radio frequency identification
KW - Reverse logistics
KW - Smart extended material requirement planning
KW - Smart production system
UR - http://www.scopus.com/inward/record.url?scp=85208283604&partnerID=8YFLogxK
U2 - 10.1016/j.jii.2024.100717
DO - 10.1016/j.jii.2024.100717
M3 - Article
AN - SCOPUS:85208283604
SN - 2452-414X
VL - 42
JO - Journal of Industrial Information Integration
JF - Journal of Industrial Information Integration
M1 - 100717
ER -