Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Advanced Digital Technology in Logistics Engineering
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advanced Digital Technology in Logistics Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 34778

Special Issue Editor

Prof. Dr. Tone Lerher

E-Mail Website
Guest Editor
Laboratory for Cognitive Systems in Logistics, Faculty of Logistics, University of Maribor, Maribor, Slovenia
Interests: Intralogistics and Warehousing 4.0; automated warehouses; warehouse design and control; material handling systems; mobile collaborative robots in intralogistics; analytical and numerical modeling

Special Issue Information

Dear Colleagues,

The development trend in logistics engineering is based on the development of new technologies, the introduction of information and communications technology (ICT), the concept of the Internet of Things (IoT) and the concept of Industry 4.0 with its high degree of automation and robotization. Together with an interdisciplinary scientific approach, they create the conditions for new possibilities and dimensions using advanced and environmentally friendly technologies.

This Special Issue welcomes articles from transportation and logistics engineering with advanced digital technologies, covering a wide range of aspects such as intelligent transportation systems, autonomous vehicle storage and retrieval systems, robotized warehouse systems, human–machine interaction in warehousing, and artificial intelligence in logistics.

Contributions on both methodology and applied research related to transport and logistics engineering are equally welcomed, including analytical methods and numerical models for decision-making problems, and their application.

Prof. Dr. Tone Lerher
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Intralogistics
  • Warehouses (AS/RS, AVS/RS, SBS/RS, VLM)
  • Material handling systems in intralogistics
  • Automated (intelligent) material and part handling systems
  • Automated material and part identification
  • Warehouse layout
  • Warehouse design, routing, and product allocation
  • Single, double- and multi-deep storage systems
  • Design, control, and optimization of warehouse systems
  • Robotized warehouse systems
  • Robotic mobile fulfillment systems
  • Collaborative robots in intralogistics
  • Exoskeletons in intralogistics
  • Integrated warehouse systems
  • Human–machine interaction in warehousing
  • Warehouse sustainability
  • Order picking systems
  • Automated order picking systems
  • Human factors in order picking
  • Automated guided vehicles (AGV's)
  • Pick support AGVs
  • Artificial intelligence in logistics
  • Computer vision in logistics
  • Machine learning in logistics
  • Sensors, actuators and robots in logistics
  • Collaborative robots in logistics
  • Mobile collaborative robots in logistics
  • Multiagent systems in logistics
  • Digital twin models in logistics
  • Intelligent transportation systems
  • Internet of Things (IoT)
  • Industry 4.0
  • Physical internet
  • Sustainability of logistic operations

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

27 pages, 3706 KiB  
Article
Towards Productive and Ergonomic Order Picking: Multi-Objective Modeling Approach
by Brigita Gajšek, Simona Šinko, Tomaž Kramberger, Marcin Butlewski, Eren Özceylan and Goran Đukić
Appl. Sci. 2021, 11(9), 4179; https://doi.org/10.3390/app11094179 - 4 May 2021
Cited by 20 | Viewed by 4484
Abstract
The logistics sector should strive for sustainability alongside productivity by protecting its order pickers’ health and welfare. Existing storage assignment models are mainly based on the criterion of order picking time and, to a lesser extent, the human factor. In the paper, a [...] Read more.
The logistics sector should strive for sustainability alongside productivity by protecting its order pickers’ health and welfare. Existing storage assignment models are mainly based on the criterion of order picking time and, to a lesser extent, the human factor. In the paper, a solution to a storage assignment problem using a multi-objective model based on binary integer linear programing is presented by developing a solution that considers order picking time, energy expenditure and health risk. The Ovako Working Posture Assessment System (OWAS) method was used for health risk assessment. The downside of solely health risk-optimization is that the average order picking time increases by approximately 33% compared to solely time-optimization. Contrary to this, the developed multi-objective function emphasizing time has proven to be promising in finding a compromise between the optimal order picking time and eliminating work situations with a very-high risk for injuries. Its use increases the time by only 3.8% compared to solely time-optimization while significantly reducing health risk. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

14 pages, 35717 KiB  
Article
Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts
by Boris Jerman, Banu Yetkin Ekren, Melis Küçükyaşar and Tone Lerher
Appl. Sci. 2021, 11(5), 2283; https://doi.org/10.3390/app11052283 - 4 Mar 2021
Cited by 23 | Viewed by 4629
Abstract
This paper studies a novel autonomous vehicle-based storage and retrieval system (AVS/RS) design with movable lifts (AVS/RS/ML). In the proposed system, there are aisle-captive lifts that are able to travel along the warehouse aisle to position themselves at the target column location. Those [...] Read more.
This paper studies a novel autonomous vehicle-based storage and retrieval system (AVS/RS) design with movable lifts (AVS/RS/ML). In the proposed system, there are aisle-captive lifts that are able to travel along the warehouse aisle to position themselves at the target column location. Those lifts can lift up/down the autonomous vehicles to/from the target storage compartment when they are in standstill. This novel design is proposed as an alternative to existing AVS/RSs to balance the resource utilizations as well as to provide an inexpensive solution with highly utilized autonomous vehicles (i.e., AGVs). As an initial work, for this novel system, two alternative operating designs under different racking configurations are experimented. We compare those two designs by their throughput rate performance metrics under the arrival rate scenarios with highly utilized AGVs (i.e., 95%). Besides, we experiment with two warehouse capacity scenarios: 900 and 1800 storage compartments. The results show that designs with two separate I/O point locations provide a better throughput rate than designs with single I/O point location. Besides, a decreased number of columns in the system improves the system’s performance. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

15 pages, 3238 KiB  
Article
A Heuristic Storage Location Assignment Based on Frequent Itemset Classes to Improve Order Picking Operations
by Yue Li, Francis A. Méndez-Mediavilla, Cecilia Temponi, Junwoo Kim and Jesus A. Jimenez
Appl. Sci. 2021, 11(4), 1839; https://doi.org/10.3390/app11041839 - 19 Feb 2021
Cited by 9 | Viewed by 3625
Abstract
Most large distribution centers’ order picking processes are highly labor-intensive. Increasing the efficiency of order picking allows these facilities to move higher volumes of products. The application of data mining in distribution centers has the capability of generating efficiency improvements, mainly if these [...] Read more.
Most large distribution centers’ order picking processes are highly labor-intensive. Increasing the efficiency of order picking allows these facilities to move higher volumes of products. The application of data mining in distribution centers has the capability of generating efficiency improvements, mainly if these techniques are used to analyze the large amount of data generated by orders received by distribution centers and determine correlations in ordering patterns. This paper proposes a heuristic method to optimize the order picking distance based on frequent itemset grouping and nonuniform product weights. The proposed heuristic uses association rule mining (ARM) to create families of products based on the similarities between the stock keeping units (SKUs). SKUs with higher similarities are located near the rest of the members of the family. This heuristic is applied to a numerical case using data obtained from a real distribution center in the food retail industry. The experiment results show that data mining-driven developed layouts can reduce the traveling distance required to pick orders. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

20 pages, 3669 KiB  
Article
Identification of Promising Vacant Technologies for the Development of Truck on Freight Train Transportation Systems
by Sungchan Jun, Seong Ho Han, Jiwon Yu, Jumi Hwang, Sangbaek Kim and Chulung Lee
Appl. Sci. 2021, 11(2), 499; https://doi.org/10.3390/app11020499 - 6 Jan 2021
Cited by 10 | Viewed by 3088
Abstract
In this study, we identify promising, currently vacant technologies for a Truck on Flatcar or Truck on Freight Train (TFTFT) system by analyzing the relevant patent information. We then apply network analysis from macro- and microperspectives to establish technology development strategies. We first [...] Read more.
In this study, we identify promising, currently vacant technologies for a Truck on Flatcar or Truck on Freight Train (TFTFT) system by analyzing the relevant patent information. We then apply network analysis from macro- and microperspectives to establish technology development strategies. We first researched the patent database from the United States Patent and Trademark Office (USPTO) by extracting relevant keywords for the TFTFT system. We then preprocessed the patent data to develop a patent-International Patent Classification (IPC) matrix and a patent-keyword matrix. Next, we developed a generative topographic mapping (GTM)-based patent map using the patent-IPC matrix and detected any patent vacuums. Then, in order to confirm the promising patent vacuums, we technically examined criticality and trend analyses. Finally, we designed an IPC-based network and a keyword network with promising patent vacuums to derive a technology development strategy from a macro- and microperspective for the TFTFT system. As a result, we confirmed two promising patent vacuums. The patent vacuums found were defined as the technical field of rail vehicles suitable for TFTFT systems and the technical field of equipment and systems for freight transfer to rail vehicles. The proposed procedure and analysis method provide useful insights for developing a research and development (R&D) strategy and technology development strategy for a TFTFT system. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

29 pages, 5810 KiB  
Article
PickupSimulo–Prototype of Intelligent Software to Support Warehouse Managers Decisions for Product Allocation Problem
by Augustyn Lorenc and Tone Lerher
Appl. Sci. 2020, 10(23), 8683; https://doi.org/10.3390/app10238683 - 4 Dec 2020
Cited by 17 | Viewed by 3787
Abstract
In this paper, a new model supporting decisions about product allocation in an order-picking shelf warehouse is presented. Industry 4.0 pays attention to inciting the processes, self-analysis and self-optimization of the short response time to market changes, and the maximum use of related [...] Read more.
In this paper, a new model supporting decisions about product allocation in an order-picking shelf warehouse is presented. Industry 4.0 pays attention to inciting the processes, self-analysis and self-optimization of the short response time to market changes, and the maximum use of related data. Methods for solving the product allocation problem (PAP) are not enough to meet the requirements of Industry 4.0. The authors present a new approach for solving PAP. The novelty introduced in the model is based on correlated data—products parameters, clients’ orders and warehouse layout. The proposed model contains elements of intelligence. The model, after product classification and allocation, analyzes its effectiveness by a simulation of the order-picking process. The application of artificial neural networks (ANN) as a part of the computing model enables the analysis of large data sets in a short time. The presented study has proved the proposed model, both for practical and scientific purposes. Relying on the research results, the total warehouse cost could be reduced by 10 to 16 per cent. With the use of the proposed model, it is possible to predict the effect of future actions before their execution. The model can be implemented in most conventional warehouses to raise the throughput performance of the order-picking process. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

13 pages, 4957 KiB  
Article
Measurement and Analysis of Vibration Levels in Stacked Small Package Shipments in Delivery Vans as a Function of Free Movement Space
by Péter Böröcz and Bence Molnár
Appl. Sci. 2020, 10(21), 7821; https://doi.org/10.3390/app10217821 - 4 Nov 2020
Cited by 14 | Viewed by 3574
Abstract
In recent years there has been a very significant increase in parcel delivery shipments all over the world. Moreover, this mode of delivery, in some cases, is facing a very intensive flow of goods, such as in annual festive seasons or, for instance, [...] Read more.
In recent years there has been a very significant increase in parcel delivery shipments all over the world. Moreover, this mode of delivery, in some cases, is facing a very intensive flow of goods, such as in annual festive seasons or, for instance, in situations like COVID-19 when personal purchase of goods is strictly limited in malls. This often means that delivery vehicles operate at almost full capacity, and many same or different kinds of packages are therefore stacked in small delivery vehicles. In this study, we measured and analyzed the vibration levels that occur in smaller stacks of packages in parcel delivery shipments, paying particular attention to those circumstances such as stacking layers and free movement spaces that can affect the vibration in different layers of packages. The goal of this paper was to provide information about the vibration levels that occur in smaller stacks of packages that are not unitized and fixed, as is common in parcel transportation. The recorded vibration events were analyzed in terms of power spectral densities (PSDs) and supplied with statistical data of acceleration events to provide an understanding of the variability of intensity. Based on the results of this study, PSD spectra were developed for various free movement conditions, as well as spectra for each layer in the stacked parcel package shipment. The results showed that the vibration level increases in the stacked load upwards and with an increase of free space of possible movement. The results of this study can be used to simulate the measured vibration conditions in laboratory tests conducted on courier express parcel shipments. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

19 pages, 5530 KiB  
Article
Measurement and Analysis of Vibration Levels for Truck Transport Environment in Korea
by Jongmin Park, Sangil Choi and Hyun Mo Jung
Appl. Sci. 2020, 10(19), 6754; https://doi.org/10.3390/app10196754 - 27 Sep 2020
Cited by 31 | Viewed by 10619
Abstract
The first step in the appropriate packaging design of food, agricultural and industrial products is to conduct an accurate simulation of the vehicle transport environment, in which a power spectral density (PSD) profile is applied. Although several researchers have mentioned the limitations of [...] Read more.
The first step in the appropriate packaging design of food, agricultural and industrial products is to conduct an accurate simulation of the vehicle transport environment, in which a power spectral density (PSD) profile is applied. Although several researchers have mentioned the limitations of PSD-based simulation, it is still widely used because accelerated test conditions can be easily generated from the PSD acquired from a particular transport section. In this study, three representative trucks and transport test routes of domestic freight transport were selected to develop a simulation protocol for a truck transport environment in Korea. These studies are needed to compare domestic transport vibration levels with those presented by the International Standards (ASTM: West Conshohocken, USA, ISTA: Chicago, USA) and to simulate damage to packaged products by domestic transport environments. The composite PSD profile for the truck transport environment was established by dividing it into high-and low-level composite PSD profiles representing the top 30% and lower 70%, respectively, of the measured vibration events based on the root-mean-square acceleration (rms G) of the measured vibration events. Also, the effects of these variables on the truck vibration level were analyzed by extracting data corresponding to the truck’s pre-planned travel speed and road conditions in the vibration records measured on the test route. Moreover, kurtosis, skewness, and normal quantile-quantity (Q-Q) analyses were conducted to understand the statistical characteristics of Korea’s truck transport environment. Statistical analysis showed that the measured vibration events had a heavy-tailed distribution and skewed to the right, causing dissymmetry. The overall rms G of the developed high-level and low-level composite PSD profiles in the range from 1 to 250 Hz were 0.47 and 0.32 for leaf-spring trucks and 0.30 and 0.14 for air-ride trucks, respectively. Full article
(This article belongs to the Special Issue Advanced Digital Technology in Logistics Engineering)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop