Resource management in decentralized industrial Automated Guided Vehicle systems

Abstract

This paper proposes an advanced decentralized method where an Automated Guided Vehicle (AGV) can optimally insert charging stations into an already assigned optimal tour of task locations. In today's industrial AGV systems, advanced algorithms and techniques are used to control the whole fleet of AGVs robustly and efficiently. While in academia, much research is conducted towards every aspect of AGV control. However, resource management or battery management is still one aspect which is usually omitted in research. In current industrial AGV systems, AGVs operate until their resource level drops below a certain threshold. Subsequently, they head to a charging station to charge fully. This programmed behaviour may have a negative impact on the manufacturing systems performance. AGVs lose time charging at inconvenient moments while this time loss could be avoided. Using the approach, an AGV can choose independently when it will visit a charging station and how long it will charge there. A general constrained optimization algorithm will be used to solve the problem and the current industrial resource management will be used as a benchmark. We use a simple extension of the Traveling Salesman Problem (TSP) representation to model our approach. The paper follows a decentral approach which is in the interest of the authors. The result of the proposal is a compact and practical method which can be used in today's operative central or decentral controlled AGV systems.

Decentral task allocation for industrial AGV-systems with resource constraints

“…In earlier work [10], we presented an intelligent resource management approach for decentral industrial AGV-systems. In this approach, an AGV has a local list of tasks it needs to execute.…”

“…Besides the task allocation, we have also considered resource constraints by introducing our previous work that focused on the resource management problem within an AGVsystem. In this previous work [10], we have proposed an intelligent resource management approach in which an AGV chooses an optimal insertion of a charging station in its initial sequence of tasks as well as an optimal charging time needed to finish its task sequence with zero (or a predefined minimum of) resources (zero battery level).…”

Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review

“…Particularly different manufacturing, as well as automotive industries, are advancing towards utilization of resources to improve proficiency and profitability without trading off the current manufacturing capacity. De Ryck et al [41] proposed a methodology that makes resource management in automated guided vehicle systems more effective. The resource management aims at providing robust strategies in manufacturing systems to accomplish the resource allocation and to solve related issues, for example, resource levelling, and production layout adjustment in production planning.…”

Anarchic manufacturing: Distributed control for product transition

“…Distributed structures offer a completely different approach to transition and ramp up, given the volatile and unpredictable nature the proposed self-organising, flexible and adaptable characteristics of distributed systems (Ma et al, 2019a;Ouelhadj & Petrovic, 2009;Shen & Norrie, 1999) would be highly desirable. Distributed systems have been investigated for a variety of production scenarios and applications, for example the resource management of automated guided vehicles (De Ryck, Versteyhe, & Shariatmadar, 2020) and to integrate multiple planning functions for manufacturing (Kumar, Manjrekar, Singh, & Kumar Lad, 2020).…”