Alexandros Nizamis

TL;DR: In this paper, a case study from a scrap metal producer that operates in the lift industry and a waste management company is presented, in order to illustrate how the deployment of a state-of-the-art industry 4.0 solution has the potential to improve sustainability both in the firm level and in the supply chain level.

TL;DR: In this article, an industry 40 waste-to-energy solution is developed and applied in a pilot case study comprised by a real-world supply chain to evaluate the sustainability performance of circular supply chain management (CSCM).

TL;DR: This paper describes how BC technology was applied in two real-life supply chain scenarios, showing how it can use SCs to identify the ingredients of food products and how to uniquely identify the food product throughout its shipment from the factory to the customer who purchase it.

TL;DR: In this article , a review article explores and locates the current state-of-the-art related to application areas from freight transportation, supply chain and logistics that focuses on arrival time, demand forecasting, industrial processes optimization, traffic flow and location prediction, the vehicle routing problem and anomaly detection on transportation data.

TL;DR: A cognitive analytics, self- and autonomous-learned system bearing predictive maintenance solutions for Industry 4.0 and a complete methodology for real-time anomaly detection on industrial data and its application on injection molding machines are presented.