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All Journal International Journal of Supply Chain Management
Narayanan, Shankar Bhaskaran
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Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Optimizing Liquified Natural Gas (LNG) Transportation & Logistics - Application of Compressors and Al-Driven Analytics Narayanan, Shankar Bhaskaran
International Journal of Supply Chain Management Vol 14, No 2 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i2.6299

Abstract

Liquefied Natural Gas (LNG) transportation is not just a fascinating process but also a crucial activity in the international energy market. Countries across the world are switching over from coal and crude oil to natural gas to lower carbon footprint. But natural gas has to be transported, generally over long distances, from source to place of consumption and that to in the form of liquid. Conversion of natural gas into LNG facilitates its comparatively easy and safe transport, particularly where distances are large. The entire process of transformation and transportation is very complex, but demands study due to the growing importance of LNG as an alternative fuel – a crucial element in energy transition and sustainability. This article explores the role played by compressors in the transportation of LNG. The article while adding to the pool of literature on LNG transport optimization, establishes that compressors are vital to optimizing LNG transportation and logistics. This article also establishes the utility of Artificial Intelligence (AI) in improving profitability of the players. It shows how predictive analytics be useful in enhancing the efficiency and economy of LNG transportation through the churning of huge volume of data generated at every step of the transportation process and then use it effectively to improve performance.
Optimizing Spare Parts Inventory and Logistics for Maximum Plant Uptime in the Energy Sector Narayanan, Shankar Bhaskaran
International Journal of Supply Chain Management Vol 14, No 2 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i2.6305

Abstract

Equipments play a critical role in Oil Gas (ONG) operations. Failure of their proper and efficient functioning has direct and significant bearing on plant uptime, energy output and supply chain (SC) stability. This article delves into the mechanical failure modes and predictive maintenance techniques, to enhance spare part forecasting. It establishes the usefulness of predictive analytics in deciding optimum spare parts inventory levels necessary for ensuring cost rationalization for balancing operational cost and efficiency. The article focuses on the application of sophisticated technology for achieving maximum plant uptime.
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