Abstract
The realization of a higher business value in manufacturing requires optimized internal logistics systems in terms of operational performance, uptime and sustainability. This paper deals with the introduction of Internet of Things (IoT) to unlock new capabilities for enhancing the performance of intralogistics. Specifically, it introduces a design perspective for IoT-driven analytics in intralogistics, within a Cyber-Physical Systems (CPS) approach. Such an approach enables the creation of data process chains linked to performance measurement for intralogistics, a prerequisite for optimizing logistics operations within production environments. An overview of key performance indicators for this domain is offered, followed by an outline of recent research on IoT and CPS and the role of context information management for IoT-enabled data process chains. The conceptual model is illustrated through a representative use case of a CPS demonstrator for performance monitoring in intralogistics. The application implements a simple data process chain, starting from the acquisition and processing of data from a conveyor testbed, followed by the determination and visualization of appropriate performance monitoring information on a dashboard.
Highlights
Production management activities, ranging from sourcing raw materials all the way to delivering finished goods to customers, need to jointly optimize manufacturing and logistics operations
While Internet of Things (IoT)-enabled data value chains deal with the acquisition, transmission, and effective transformation of raw data into applied knowledge, it is their inclusion within Cyber-Physical Systems (CPS) that can deliver their outcomes in intralogistics practice and further work is needed to this end
The aim is to bring together some of the key elements of the conceptual approach on a physical intralogistics infrastructure to demonstrate a case of IoT-driven key performance indicators (KPIs) analytics for performance monitoring
Summary
Production management activities, ranging from sourcing raw materials all the way to delivering finished goods to customers, need to jointly optimize manufacturing and logistics operations. Such connectivity upgrades the capabilities for collecting data relevant to mapping the state of individual subsystems and of the internal logistics system as a whole This allows to monitor and analyze the operating performance of intralogistics, which is a prerequisite for making more informed choices regarding its management and optimization (Macaulay, Buckalew, & Chung, 2015). Leveraging upon such capabilities, the implementation of Cyber-Physical Systems (CPS) brings together the benefits of connectivity and interaction. The paper concludes with a discussion and summary of the main contributions, including pointers for further work
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