TOWARDS FOURTH-PARTY LOGISTICS PROVIDERS A Business Model for Cloud-Based Autonomous Logistics

Abstract: Cloud computing denotes a paradigm shift in computing that enables a flexible allocation of hardware and software resources on demand. Therewith, it is particularly appealing for applications with a high degree of computational complexity and dynamics. This paper identifies logistics planning and control as a promising application for clouds. However, two prerequisites must be met for cloud-based logistics control. Firstly, the platform-as-a-service layer must provide a synchronisation of the physically distributed real-world material flows and the data flows in the cloud. Secondly, appropriate and scalable control software must be implemented on the software-as-a-service layer. Apart from outlining the technical foundations, this paper describes how both steps enable a business model that is usually referred to as fourth-party logistics

Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE

Industry 4.0 has shifted the manufacturing related processes from conventional processes within one organization to collaborative processes across different organizations. For example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. This complex and competitive collaboration requires the underlying system architecture and platform to be flexible and extensible to support the demands of dynamic collaborations as well as advanced functionalities such as big data analytics. Both operation and condition of the production equipment are critical to the whole manufacturing process. Failures of any machine tools can easily have impact on the subsequent value-added processes of the collaboration. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machineries using various analyses. In this context, this paper explores how the FIWARE framework supports predictive maintenance. Specifically, it looks at applying a data driven approach to the Long Short-Term Memory Network (LSTM) model for machine condition and remaining useful life to support predictive maintenance using FIWARE framework in a modular fashion

A Semantic Mediator for Data Integration in Autonomous Logistics Processes

Autonomous control in logistic systems is characterized by the ability of logistic objects to process information, to render and to execute decisions on their own. This paper investigates whether the concept of the semantic mediator is applicable to the data integration problems arising from an application scenario of autonomous control in the transport logistics sector. Initially, characteristics of autonomous logistics processes are presented, highlighting the need for decentral data storage in such a paradigma. Subsequently, approaches towards data integration are examined. An application scenario exemplifying autonomous control in the field of transport logistics is presented and analysed, on the basis of which a concept, technical architecture and prototypical implementation of a semantic mediator is developed and described. A critical appraisal of the semantic mediator in the context of autonomous logistics processes concludes the paper, along with an outlook towards ongoing and future work