Movement Analytics: Current Status, Application to Manufacturing, and
Future Prospects from an AI Perspective
- URL: http://arxiv.org/abs/2210.01344v1
- Date: Tue, 4 Oct 2022 03:27:17 GMT
- Title: Movement Analytics: Current Status, Application to Manufacturing, and
Future Prospects from an AI Perspective
- Authors: Peter Baumgartner, Daniel Smith, Mashud Rana, Reena Kapoor, Elena
Tartaglia, Andreas Schutt, Ashfaqur Rahman, John Taylor, Simon Dunstall
- Abstract summary: IoT-based and other forms of object tracking are an emerging tool for collecting movement data of objects/entities over space and time.
Movement data can provide valuable insights like process bottlenecks, resource utilization, effective working time etc.
- Score: 1.2908803492980705
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Data-driven decision making is becoming an integral part of manufacturing
companies. Data is collected and commonly used to improve efficiency and
produce high quality items for the customers. IoT-based and other forms of
object tracking are an emerging tool for collecting movement data of
objects/entities (e.g. human workers, moving vehicles, trolleys etc.) over
space and time. Movement data can provide valuable insights like process
bottlenecks, resource utilization, effective working time etc. that can be used
for decision making and improving efficiency.
Turning movement data into valuable information for industrial management and
decision making requires analysis methods. We refer to this process as movement
analytics. The purpose of this document is to review the current state of work
for movement analytics both in manufacturing and more broadly.
We survey relevant work from both a theoretical perspective and an
application perspective. From the theoretical perspective, we put an emphasis
on useful methods from two research areas: machine learning, and logic-based
knowledge representation. We also review their combinations in view of movement
analytics, and we discuss promising areas for future development and
application. Furthermore, we touch on constraint optimization.
From an application perspective, we review applications of these methods to
movement analytics in a general sense and across various industries. We also
describe currently available commercial off-the-shelf products for tracking in
manufacturing, and we overview main concepts of digital twins and their
applications.
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