Smart Analytics for Cold Chains in Building Sustainable and Resilient Supply Chains

Cold chain logistics has been found to be instrumental in the safe and effective movement of perishable items that are subject to changes in temperature, e.g., pharmaceuticals, food products, chemicals, etc. As the pressure increases on sustainable operations and sustainable supply chains, incorporating smart analytics into cold chain operations has become mandatory. The chapter examines the metamorphic effect of smart analytics on cold chains as guided by the development of plans that facilitate the provision of sustainable and robust supply chains. It discusses how data-driven management, predictive analytics, and real-time monitoring could be used to increase the efficiency of operations, reduce wastage, and improve the performance of the environment. Cold chains can attain major progress in terms of resource optimization, risk control, and legal compliance by relying on IoT, machine learning, AI, and blockchain. The data security, the integration with the legacy systems, and the initial cost of implementation are also regarded as the challenges discussed in the chapter. Examples of businesses that have effectively made use of smart analytics in a number of fields could prove beneficial in navigating innovation, lowering expenses, and making supply chains more resilient. Going into the future, the further development of technologies is going to open even more possibilities for optimizing cold chains in regard to sustainability and operational resilience. In this chapter, the MATLAB tool is applied for the demonstration of a graphical view of statistical data.