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Applied Sciences
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Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM)
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Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM)

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

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 11630

Special Issue Editors

Prof. Dr. Antoni Świć

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Lublin University of Technology, Nadbystrzycka 38 D, 20-618 Lublin, Poland
Prof. Dr. Justyna Patalas-Maliszewska

E-Mail Website
Guest Editor
Institute of Mechanical Engineering, University of Zielona Góra, Zielona Góra, Poland
Interests: additive manufacturing technology; manufacturing systems; serial production line
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to changes in the working environment, it is necessary to undertake activities that will encourage manufacturing enterprises to conduct processes consistent with the idea of sustainable development. This Special Issue aims to seek high-quality papers from academics and industry-related researchers in the areas of sustainability development in manufacturing enterprises.

The scope includes (but is not limited to) the following:

  • Simulation of discrete manufacturing systems;
  • Modeling of manufacturing processes;
  • Multi-skill resource-constrained project scheduling;
  • Digital twin for a production;
  • Data, information, and knowledge management in production;
  • Computational intelligence methods and application;
  • Manufacturing systems capacity balancing;
  • Intelligent web mining and applications;
  • Sustainable development of manufacturing enterprises;
  • Sustainability assessment in production. 

Prof. Dr. Antoni Świć
Prof. Dr. Justyna Patalas-Maliszewska
Guest Editors

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.

Published Papers (4 papers)

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Research

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23 pages, 3960 KiB  
Article
Motion Planning for a Mobile Humanoid Manipulator Working in an Industrial Environment
by Iwona Pajak and Grzegorz Pajak
Appl. Sci. 2021, 11(13), 6209; https://0-doi-org.brum.beds.ac.uk/10.3390/app11136209 - 05 Jul 2021
Cited by 2 | Viewed by 1821
Abstract
This paper presents the usage of holonomic mobile humanoid manipulators to carry out autonomous tasks in industrial environments, according to the smart factory concept and the Industry 4.0 philosophy. The problem of transporting lengthy objects, taking into account mechanical limitations, the conditions for [...] Read more.
This paper presents the usage of holonomic mobile humanoid manipulators to carry out autonomous tasks in industrial environments, according to the smart factory concept and the Industry 4.0 philosophy. The problem of transporting lengthy objects, taking into account mechanical limitations, the conditions for avoiding collisions, as well as the dexterity of the manipulator arms was considered. The primary problem was divided into three phases, leading to three different types of robotic tasks. In the proposed approach, the pseudoinverse Jacobian method at the acceleration level to solve each of the tasks was used. The redundant degrees of freedom were used to satisfy secondary objectives such as robot kinetic energy, the maximization of the manipulability measure, and the fulfillment mechanical and collision-avoidance limitations. A computer example involving a mobile humanoid manipulator, operating in an industrial environment, illustrated the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM))
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13 pages, 1606 KiB  
Article
Scheduling the Process of Robot Welding of Thin-Walled Steel Sheet Structures under Constraint
by Łukasz Sobaszek and Antoni Świć
Appl. Sci. 2021, 11(12), 5683; https://0-doi-org.brum.beds.ac.uk/10.3390/app11125683 - 19 Jun 2021
Cited by 3 | Viewed by 1614
Abstract
Industrial robot work optimization has been extensively studied. The main reason for analysis is the growing number of robots implemented in the different manufacturing processes. In order to benefit from the implementation of industrial robots, each implementation process ought to be preceded by [...] Read more.
Industrial robot work optimization has been extensively studied. The main reason for analysis is the growing number of robots implemented in the different manufacturing processes. In order to benefit from the implementation of industrial robots, each implementation process ought to be preceded by an in-depth analysis of the stand work. Often the integrator’s intuition is the only base for decisions. This work focuses on the need for individualized scheduling and analysis of robotic production tasks in the context of overall production scheduling. The method of alternative schedules analysis was presented. The paper presents a scheduling process for an industrial robot in the process of robot welding of thin-walled steel sheet structures under constraints caused by the process technology. The proposed method allowed to reduce the assumed time criterion at the level of 5.4% for one detail. The obtained value of technological operation time reduction resulted in increased time savings throughout the entire production process. Full article
(This article belongs to the Special Issue Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM))
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17 pages, 1705 KiB  
Article
Modelling the Demand for AM Technologies in Polish Manufacturing Enterprises Using Bayesian Networks
by Justyna Patalas-Maliszewska, Małgorzata Śliwa and Marcin Topczak
Appl. Sci. 2021, 11(2), 601; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020601 - 10 Jan 2021
Cited by 3 | Viewed by 1724
Abstract
Combining the knowledge about additive manufacturing technologies available in the literature with the results of empirical research in Polish manufacturing enterprises, regarding the implementation of AM, using the Bayesian network, will allow the recent demand for AM technologies to be defined in the [...] Read more.
Combining the knowledge about additive manufacturing technologies available in the literature with the results of empirical research in Polish manufacturing enterprises, regarding the implementation of AM, using the Bayesian network, will allow the recent demand for AM technologies to be defined in the context of an industry’s needs. The main purpose of the study is to build a new model that integrates: (1) knowledge about the implementation of AM in manufacturing companies, gained from the literature, (2) knowledge about the demands and state of the use of AM from 250 Polish metal and automotive manufacturing enterprises, and (3) Bayesian networks. The results reveal that the model developed is able to accurately detect the key determinants of the implementation process of AM technologies within a manufacturing company and identify the specific requirements for the further implementation of additive technologies. The freshness of our work is defining the demand for AM technology based on the knowledge gained from literature and knowledge received through empirical study. The possibilities of using the results of research in economic practice were demonstrated. This new approach can be treated as a solution, which will both direct and help mangers to take the decision to implement AM technologies. Full article
(This article belongs to the Special Issue Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM))
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Review

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47 pages, 3645 KiB  
Review
Graph-Based Modeling in Shop Scheduling Problems: Review and Extensions
by Jacqueline Otala, Alden Minard, Golshan Madraki and Seyedamirabbas Mousavian
Appl. Sci. 2021, 11(11), 4741; https://0-doi-org.brum.beds.ac.uk/10.3390/app11114741 - 21 May 2021
Cited by 8 | Viewed by 5722
Abstract
Graphs are powerful tools to model manufacturing systems and scheduling problems. The complexity of these systems and their scheduling problems has been substantially increased by the ongoing technological development. Thus, it is essential to generate sustainable graph-based modeling approaches to deal with these [...] Read more.
Graphs are powerful tools to model manufacturing systems and scheduling problems. The complexity of these systems and their scheduling problems has been substantially increased by the ongoing technological development. Thus, it is essential to generate sustainable graph-based modeling approaches to deal with these excessive complexities. Graphs employ nodes and edges to represent the relationships between jobs, machines, operations, etc. Despite the significant volume of publications applying graphs to shop scheduling problems, the literature lacks a comprehensive survey study. We proposed the first comprehensive review paper which (1) systematically studies the overview and the perspective of this field, (2) highlights the gaps and potential hotspots of the literature, and (3) suggests future research directions towards sustainable graphs modeling the new intelligent/complex systems. We carefully examined 143 peer-reviewed journal papers published from 2015 to 2020. About 70% of our dataset were published in top-ranked journals which confirms the validity of our data and can imply the importance of this field. After discussing our generic data collection methodology, we proposed categorizations over the properties of the scheduling problems and their solutions. Then, we discussed our novel categorization over the variety of graphs modeling scheduling problems. Finally, as the most important contribution, we generated a creative graph-based model from scratch to represent the gaps and hotspots of the literature accompanied with statistical analysis on our dataset. Our analysis showed a significant attention towards job shop systems (56%) and Un/Directed Graphs (52%) where edges can be either directed, or undirected, or both, Whereas 14% of our dataset applied only Undirected Graphs and 11% targeted hybrid systems, e.g., mixed shop, flexible, and cellular manufacturing systems, which shows potential future research directions. Full article
(This article belongs to the Special Issue Modeling and Algorithms for Innovative Sustainable Manufacturing Modes (MASM))
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