Supply Chain Analytics And Modelling: Quantitative Tools And Applications

Your first steps in descriptive, predictive and prescriptive analytics to solve your toughest supply chain problems

Despite significant achievements, the discipline of supply chain management is still unable to satisfactorily handle many practical real-world challenges. The authors of Networks Against Time claim that a unified supply chain network analytics framework is needed which should be able to handle optimization and competitive behavior while also maintain relevance to many industrial sectors in which perishable products are prominent, from healthcare to food and from fashion apparel to technology.

by Ph.d. Islam, Sardar M. N. (Author), Faraz Bidar (Author)
The widespread adoption of information technologies (IT) characterising the recent competitive advantage scenario has been of great interest to researchers and practitioners

Build a strong and efficient IoT solution at industrial and enterprise level by mastering industrial IoT using Microsoft Azure. This book focuses on the development of the industrial Internet of Things (IIoT) paradigm, discussing various architectures, as well as providing nine case studies employing IoT in common industrial domains including medical, supply chain, finance, and smart homes.

Reverse logistics concerns the integration of used and obsolete products back into the supply chain as valuable resources. Economic, marketing, and legislative drivers increasingly are leading companies to take back and recover their products after use. The arising product flows pose novel challenges for supply chain management.

This book covers important issues related to managing supply chain risks from various perspectives. Supply chains today are vulnerable to disruptions with a significant impact on firms’ business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions.