Transforming the steel industry supply chain: strategies for optimization, sustainability and resilience

Abstract

The steel supply chain, a critical component of the global economy, ‎is increasingly facing inefficiencies. The challenges reduce efficiency-‎cy and present an opportunity to enhance sustainability. This study ‎will deal with three main aspects: First, it will forecast steel prices ‎based on global GDP trends so that demand volatility can be miti-‎gated by linear regression model; second, it will reduce land trans-‎portation costs by a linear programming approach which means ‎minimizing the number of trips needed for delivery; and third, it will ‎make regulatory compliance better by studying sector feedback on ‎environmental policies for suggesting ways of better collaborating ‎with the regulators. This study results in a strong, data-backed ‎structure intended for addressing the major ineffectiveness in the ‎steel industry supply chain. The price forecasting model created ‎using linear regression with GDP growth shows a good correlation ‎between macroeconomic indicators and steel price trends. It enables ‎downstream steel producers to mitigate risks of overproduction or ‎understocking. In logistics optimization, the linear programming ‎model minimizes transportation costs by reducing the delivery trips. ‎The study demonstrates that even minor improvements in route ‎planning and truck load distribution can save a lot of money and ‎carbon emissions as well. Regarding regulatory issues, the survey ‎results bring out the key issues that are being faced by the players in ‎the industry. This lays down an understanding path on how to align ‎industrial practices with sustainability goals while keeping operational efficiency intact‎.