A Digital Platform for Heterogeneous Fleet Management in Manufacturing Intralogistics

In: Handbook on Digital Business Ecosystems in Manufacturing

Nitish Singh, Alp Akcay, Quang-Vinh Dang, Ivo Adan, and E.A. Thijssen, 1 Jan 2024

Brainport Industries Campus (BIC) is a unique initiative taken by the high-tech suppliers of the Eindhoven region to come together and work towards collaborative consumption of shared resources such as production machines, automated guided vehicles, clean rooms, and storage spaces in order to jointly meet their customers’ demands, reduce cost of ownership, and better manage risks during uncertain demand and supply cycles. However, the matching-demand-with-supply process in a sharing economy requires novel perspectives and tools. In this chapter, we propose a digital platform for serving multiple tenants of BIC, sharing a fleet of heterogeneous automated guided vehicles (AGVs). The proposed platform includes a user interface as an order input system, an order database, and a central cloud server that houses the necessary intelligence for communicating with all the aforementioned modules. This platform that serves multiple tenants sharing a heterogeneous AGV fleet is the first of its kind.


Dispatching AGVs with Battery Constraints using Deep Reinforcement Learning

In: Computers & Industrial Engineering

Nitish Singh, Alp Akcay, Quang-Vinh Dang,Tugce Martagan, Ivo Adan, 1 Nov 2023

This paper considers the problem of real-time dispatching of a fleet of automated guided vehicles (AGVs) with battery constraints. AGVs must be immediately assigned to transport requests, which arrive randomly. We formulate this online decision-making problem as a Markov decision process and propose a solution approach based on deep reinforcement learning.


A Matheuristic for AGV Scheduling with Battery Constraints

In: European Journal of Operational Research

Nitish Singh, Quang-Vinh Dang, Alp Akcay, Ivo Adan, Tugce Martagan, 1 May 2022

This paper considers the problem of scheduling automated guided vehicles (AGVs) with battery constraints. Each transport request involves a soft time window, and the AGV fleet used to service those requests is heterogeneous with a diverse set of capabilities and travel costs.


Simulation-based AGV management with a linear dispatching rule

In: WSC 2023 - Winter Simulation Conference

Nitish Singh, Jeroen B.H.C. Didden, Alp Akcay, Tugce G. Martagan, Ivo J.B.F. Adan, 12 Dec 2023

This paper considers the problem of real-time dispatching of a fleet of heterogeneous automated guided vehicles (AGVs) with battery constraints. The AGV fleet is heterogeneous in terms of material handling capabilities; some can tow loads, some can lift loads while others manipulate loads with the assistance of a robotic arm. Transport requests arrive in real-time and include a soft time window, with late delivery incurring tardiness costs. Transport requests need to be assigned to a capable AGV based on required material handling capabilities with the objective to minimize a weighted sum of tardiness costs of transport requests and travel costs of AGVs. In this paper, an AGV-specific linear dispatching rule (LDR) learning approach is proposed to assign AGVs to randomly arriving transport requests in real time over a finite horizon. The proposed approach is compared with a heuristic policy from practice by using real-world data provided by our industry partner.


Simulation-based performance evaluation of a manufacturing facility with vertical as/rs

In: WSC 2019 - Winter Simulation Conference

Nitish Singh, Koen Herps, Tugce G. Martagan, Ivo J.B.F. Adan, 12 Dec 2019

Klein Mechanisch Werkplaats Eindhoven (KMWE) is a precision manufacturing company situated in the Netherlands and recently relocated to a new location known as the ‘Brainport Industries Campus’ (BIC). This move allowed KMWE to improve the performance of its manufacturing facility known as the ‘Tool Service Center’ (TSC) by investing in vertical automated storage and retrieval systems (AS/RSs). However, these decisions needed to be made under input uncertainties since the move to BIC and modernization of existing equipment would cause changes in operating parameters inside the facility, over which little information was known in advance. In this study, we show how hybrid simulation modelling was used to assess the impact of input uncertainties (such as operator productivity, vertical storage height) on the throughput performance of TSC. Ultimately, the outcomes of this research project were used by KMWE to make an investment decision on new equipment acquisition quantity.


Scheduling heterogeneous multi-load AGVs with battery constraints

In: Computers & Operations Research

Quang-Vinh Dang, Nitish Singh, Ivo Adan, Tugce Martagan, Dirk van de Sande, 12 Dec 2021

Recent trends towards larger and more complex systems necessitate the use of heterogeneous and flexible automated guided vehicles (AGVs) to fulfill the transport demand within a factory. To operate the fleet of AGVs efficiently, it is also important to consider their limited battery capacity. In this context, we tackle the problem of scheduling transport requests on multi-load and multi-ability AGVs with battery management.