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Journal PROCEEDINGS IN MANUFACTURING SYSTEMS |
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ISSN 2343–7472 ISSN-L 2067-9238 |
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Journal PROCEEDINGS IN MANUFACTURING SYSTEMS □
Volume 19, Issue 1, 2024 · Gabriel LEITNER, Dominik
STADLTHANNER, Alexander ORTNER-PICHLER, Christian LANDSCHÜTZER,
Modeling
and parameterization of flexible consignments using multi flexible body
dynamics · Konstantinos PETROPOULOS, George-Christopher VOSNIAKOS, Emmanuel STATHATOS
On flexible
manufacturing system controller design and prototyping using Petri Nets and
multiple micro-controllers
Study on
the optimisation of material flows within an
automated warehouse equipped with AMRs
Selecting a
device solution for assessing the circularity deviation of a disc-type part · Ramy OBEIDAT, Mihaela Mădălina PUIUL,
The
influence of Artificial Intelligence on Warehouse Management Systems
Modeling and parameterization of flexible consignments using multi flexible body dynamics
Gabriel LEITNER1,*, Dominik STADLTHANNER2, Alexander
ORTNER-PICHLER3, Christian LANDSCHÜTZER4
1)
Dipl.-Ing., Research Assistant, Graz University of Technology, Institute of
Logistics Engineering, Graz, Austria 2)
Dipl.-Ing., Research Assistant, Graz University of Technology, Institute of
Logistics Engineering, Graz, Austria 3)
Dipl.-Ing. Dr.techn., Project-Senior Scientist, Graz University of
Technology, Institute of Logistics Engineering, Graz, Austria 4)
Assoc. Prof. Dipl.-Ing. Dr.techn. Prof.h.c., Deputy
Head / Prof. for Materials Handling, Graz University of Technology,
Institute of Logistics Engineering, Graz, Austria Abstract:
The
courier, express, and parcel (CEP) industry is undergoing a shift in the
type of shipments towards dimensionally unstable consignments, presenting
novel challenges for sorting and conveying systems operators. Previous
simulation approaches are limited in their ability to model all relevant
operating principles. To address this gap, this paper presents a structured
approach to develop a simulation model that comprehensively represents the
motion behavior of dimensionally unstable consignments. The proposed
approach comprises four main steps, with this paper focusing on steps 3 and
4. In step 3, four different types of small consignments with flexible
packaging are modeled using Multi Flexible Body Dynamics (MFBD), which
involves a bottom-up approach to modeling packaging and contents into
consignment models. Step 4 involves parameterization, where real-world tests
are leveraged to determine target values, alongside the utilization of
Design of Experiments (DoE) to explore the effects of model parameters in
corresponding simulations. Surrogate models are subsequently employed for
parameter optimization to determine parameter values. Finally, to evaluate
the practical feasibility of these models, the bulk behavior of multiple
consignments on a conveyor belt is simulated. The resulting simulation is
capable of modeling the shape instability of consignments with a high level
of detail and reasonable computing times. This work makes a significant
contribution to the advancement of the simulation of the motion behavior of
dimensionally unstable consignments in the sorting process and thus supports
the development of innovative sorting and conveying technologies. Key words:
CEP, Polybag, MFBD, FMBD, Multi Flexible Body Dynamics, DoE,
Parameterization.
On flexible manufacturing system controller design and
prototyping using Petri nets and multiple micro-controllers Konstantinos PETROPOULOS1, George-Christopher VOSNIAKOS2,*, Emmanuel STATHATOS3 1)
MSc graduate student, School of Mechanical Engineering, National Technical
University of Athens, Athens, Greece 2)
Prof., Manufacturing Technology Laboratory, School of Mechanical
Engineering, National Technical University of Athens, Athens, Greece. 3)
Dr, Senior postgraduate researcher, School of Mechanical Engineering,
National Technical University of Athens, Athens, Greece. Abstract: This work aims to design the central controller of a Flexible Manufacturing System and test it beyond simulation. The FMS controller is modelled through standard PN formalism tested by simulation before subsequent controller prototyping. Then, prototypes are implemented in two alternative schemes. First, by a central controller and local micro-controllers of ArduinoTM-type, in a master-slave configuration, communication of micro-controllers with each other materializing through asynchronous data transmission over the I2C bus. Second, by replacing local controllers by light emitting diodes (leds) and switches for ‘receive’ and ‘send’ signals respectively. The central controller was implemented in microcontroller language by direct conversion from the respective simulated and analyzed Petri Net. Execution of the developed control programs was performed and evaluation proved that the developed prototyping method is efficient, low cost and scalable in a system-commissioning context. Study on the optimisation of material flows within an automated warehouse equipped with AMRs Daniela-Mariana ILIE1,*,
Constantin-Adrian POPESCU2,
Cicerone Laurentiu POPA3, Catalin-Ionut
SILVESTRU4, Costel Emil COTET5 1)
PhD, Robots and Production Systems Department, University “Politehnica”
of Bucharest, Romania 2)
Lecturer, PhD, Robots and Production Systems Department, University “Politehnica” of Bucharest,
Romania 3)
Assoc. Prof., PhD, Robots and Production Systems Department, University “Politehnica” of Bucharest,
Romania
4)
Assoc. Prof., PhD, Robots and Production Systems Department, University “Politehnica” of Bucharest,
Romania
5)
Prof., PhD, Robots and Production Systems Department, University “Politehnica” of Bucharest,
Romania Abstract:
The article presents the method of optimising flow within the
distribution warehouse as well as the equipment needed to carry out this
process. It is also intended to optimise the picking process through the
optimal functioning of the existing AMRs in the warehouse as well as the
packaging flow of the final order so that the entire activity has time,
cost, flexibility and, finally, integration. The
article consists of a presentation of the entire warehouse management, ways
of optimising flows and last but not least, a presentation of the simulation
of optimised equipment. On the other hand, it also aims to improve the
process of packing the final order after the items arrive from picking. For
this process, calculations are made involving the productivity of the entire
process and the entire flow. Selecting a device solution for assessing the circularity deviation of a disc-type part Andreea Mădălina PANĂ1, Bruno RĂDULESCU2, Mara Cristina RĂDULESCU3, Adriana MUNTEANU4, Andrei Marius MIHALACHE5, Adelina HRIȚUC6,*, Laurențiu SLĂTINEANU7 1)
Student, Department
of Digital Production System, "Gheorghe Asachi" Technical University of Iași,
Rumania 2)
Lecturer, Ph.D.,
Department of Digital Production System, "Gheorghe Asachi" Technical
University of Iași, Romania 3)
Lecturer, Ph.D.,
Department of Digital Production System, "Gheorghe Asachi" Technical
University of Iași, Romania 4)
Assoc. prof.,
Department of Digital Production System, "Gheorghe Asachi" Technical
University of Iași, Romania 5)
Lecturer, Ph.D.,
Department of Machine Manufacturing Technology, "Gheorghe Asachi" Technical
University of Iași, Rumania 6)
Ph.D. Student,
Department of Machine Manufacturing Technology, "Gheorghe Asachi" Technical
University of Iași, Rumania 7)
Prof., Ph.D., Department of Machine Manufacturing Technology, "Gheorghe
Asachi" Technical University of Iași, Romania Abstract: In the case of some categories of disc-type parts, there may be a requirement that the circularity deviation of the of the outer cylindrical surface does not exceed certain values. On the other hand, in certain situations, it is of interest to study the influence that different factors can exert on the measured values of circularity deviations. The consultation of specialized literature showed that the problem of measuring circularity deviations was a subject of interest for researchers in the field of manufacturing engineering. For such situations, the need to design and build a device was taken into account to allow experimental research to be carried out aimed at highlighting the influence exerted by some factors on the measured values of the circularity deviation. For this purpose, three variants of devices likely to meet the mentioned requirements have been designed. To select a solution when several alternatives are available, researchers have proposed and developed optimal selection methods by using appropriate selection criteria. In the investigated case, the selection of the most convenient solution was carried out using the analytic hierarchy process. Evaluation criteria of the three device variants were proposed, and the two-by-two solutions were compared. The use of a composite evaluation index led to the selection of a device that could be mounted on a universal lathe and that would allow for experimental research on the influence of different factors on the measured values of the deviation from the circular shape in the case of disc-type parts.
The influence of Artificial Intelligence on Warehouse
Management Systems Ramy OBEIDAT1,*, Mihaela Mădălina PUIUL2
1)
Ph.D Student, National University of Science and Technology Politehnica
Bucharest, Romania 2)
Ph.D Student, National University of Science and Technology Politehnica
Bucharest, Romania
Abstract: This article explores the integration of Artificial Intelligence (AI) algorithms with Warehouse Management Systems (WMS) to address the limitations of traditional warehouse operations. Modern supply chains demand real-time adaptability, predictive analytics, and dynamic optimization, areas where traditional WMS fall short. The research focuses on enhancing WMS by employing Genetic Algorithms (GA), Ant Colony Optimization (ACO), and Machine Learning (ML) techniques. These AI-driven models optimize key warehouse functions such as inventory management, order picking, routing, and resource allocation. Genetic Algorithms are utilized to minimize travel time during order picking by generating efficient routes, while Ant Colony Optimization dynamically adjusts picking paths based on real-time data. Machine Learning models, particularly regression techniques, are applied to predict demand and optimize stock levels, reducing stockouts and overstocking. Predictive maintenance models are also explored, forecasting equipment failures to reduce downtime. Simulations show significant improvements in operational efficiency, with travel time reduced by 25%, stockouts minimized by 30%, and a 15% reduction in overall operational costs. This paper also discusses the technological infrastructure required to implement AI-enhanced WMS, including high-performance computing, IoT sensors, and solid data integration systems. Future research will focus on scaling these AI models for multi-location warehouses and investigating hybrid AI models for further optimization. This study demonstrates that AI offers a transformative solution for modern warehouse operations, addressing the growing complexity and dynamic needs of today’s supply chains.
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