Analysis of asset location data to support decisions in production management and control

Abstract

In the era of cyber-physical environments, indoor asset tracking systems enable to monitor and control production in a smarter way than ever before, as they are capable of providing data about the location of various equipment on the shop-floor in near real time. The right use of this data contributes to the improvement of production control and management processes, however, utilization of the related information often requires novel methods. In the paper, decision-making approaches are presented that rely on advanced data analytics for asset location systems. The efficiency of the results are presented through an industry related use-case.