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Publications (10 of 18) Show all publications
Massouh, B., Danielsson, F., Ramasamy, S., Khabbazi, M. R. & Zhang, X. (2024). Online Hazard Detection in Reconfigurable Plug & Produce Systems. In: Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G. (Ed.), Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems.: FAIM 2023. Paper presented at International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal (pp. 889-897). Springer Nature
Open this publication in new window or tab >>Online Hazard Detection in Reconfigurable Plug & Produce Systems
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2024 (English)In: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems.: FAIM 2023 / [ed] Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G., Springer Nature, 2024, p. 889-897Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Plug & Produce is a modern automation concept in smart manufacturing for modular, quick, and easy reconfigurable production. The system’s flexibility allows for the configuration of production with abstraction, meaning that the production resources participating in a specific production plan are only known in the online phase. The safety assurance process of such a system is complex and challenging. This work aims to assist the safety assurance when utilizing a highly flexible Plug & Produce concept that accepts instant logical and physical reconfiguration. In this work, we propose a concept for online hazard identification of Plug & Produce systems, the proposed concept, allows for the detection of hazards in the online phase and assists the safety assurance as it provides the hazard list of all possible executable alternatives of the abstract goals automatically. Further, it combines the safety-related information with the control logic allowing for safe planning of operations. The concept was validated with a manufacturing scenario that demonstrates the effectiveness of the proposed concept.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Mechanical Engineering
Keywords
Plug & Produce, reconfigurable manufacturing, safety assessment, hazard identification
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; Production Technology
Identifiers
urn:nbn:se:hv:diva-20884 (URN)10.1007/978-3-031-38241-3_97 (DOI)2-s2.0-85171556008 (Scopus ID)9783031382406 (ISBN)9783031382413 (ISBN)
Conference
International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-01-30
Duraisamy, P., Santhanakrishnan, M. N., Amirtharajan, R. & Ramasamy, S. (2024). Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling. Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, 238(2), 572-585
Open this publication in new window or tab >>Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling
2024 (English)In: Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, ISSN 0954-4062, E-ISSN 2041-2983, Vol. 238, no 2, p. 572-585Article in journal (Refereed) Published
Abstract [en]

This article proposes real-time speed tracking of two-link surface swimming robotic fish using a deep reinforcement learning (DRL) controller. Hydrodynamic modelling of robotic fish is done by virtue of Newtonian dynamics and Lighthill’s kinematic model. However, this includes external unsteady reactive forces that cannot be modeled accurately due to the distributed nature of hydrodynamic behavior. Therefore, a novel data-assisted dynamic model and control method is proposed for the speed tracking of robotic fish. Initially, the cruise speed motion data are collected through experiments. The water-resistance coefficient is estimated using the least mean square fit, which is then adopted in the model. Subsequently, a closed-loop discrete-time DRL controller trained through a soft actor-critic (SAC) agent is implemented through simulations. SAC overcomes the brittleness problem encountered by other policy gradient approaches by encouraging the policy network for maximum exploration and not assigning a higher probability to any single part of actions. Due to this robustness in the policy learning, the convergence error becomes low in RL-SAC than RL-DDPG controller. The simulation results verify that the DRL-SAC control with data-assisted modelling substantially improves the speed tracking performance. Further, this controller is validated in real-time, and it is observed that the SAC-trained controller tracks the desired speed more accurately than the DDPG controller.

Place, publisher, year, edition, pages
Sage Publications, 2024
Keywords
speed tracking, robotic fish, data-assisted modeling
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-20057 (URN)10.1177/09544062231174127 (DOI)001001038500001 ()2-s2.0-85159707159 (Scopus ID)
Available from: 2023-06-13 Created: 2023-06-13 Last updated: 2024-01-15Bibliographically approved
Khabbazi, M. R., Danielsson, F., Bennulf, M., Ramasamy, S. & Nilsson, A. (2023). Model-based Plug & Produce in Assembly Automation. In: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA): 12-15 September 2023. Paper presented at 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2023-September
Open this publication in new window or tab >>Model-based Plug & Produce in Assembly Automation
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2023 (English)In: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA): 12-15 September 2023, IEEE, 2023, Vol. 2023-SeptemberConference paper, Published paper (Refereed)
Abstract [en]

Manual assembly systems are featured with high flexibility but with the risk of lower quality, higher cycle time, inefficient resource employment, and affecting sustainability goals in comparison to fully automated ones. Conventional automated assembly is challenged by the desired level of flexibility when compared to what automation through Plug & Produce system represents. Plug and Produce, during the last few decades aimed at addressing highly flexible automation systems handling rapid changes and adaptations as one dominant solution. Multi-agent System (MAS) as a tool to handle different areas of manufacturing control systems can be used in Plug & Produce representing every physical control entity (e.g., parts, resources) as agents. This article aims to describe a model-based configurable multi-agent design in Plug and Produce system together with a prototype implementation of the actual automated assembly use case of a kitting operation highlighting flexibility and reconfigurability and the model functionality. A model-based approach with a few models using UML standards describes the structure and behavior of the system. Model instantiation is introduced and followed by real prototype use case implementation. The use case study of advanced automated kitting operation in the assembly automation domain has been selected. Agent-based operation control systems have been applied during the assembly process. The evaluation was accomplished by testing several scenarios on Plug & Produce for kitting operation. To conclude, several desirable functionality features of the framework during the demonstration such as rapid instantiation and adaptation, and in particular, the flexibility features have been examined and evaluated with several failure-handling testing scenarios. © 2023 IEEE.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Assembly; Automation; Control systems; Assembly automation; Assembly systems; Automated assembly; High flexibility; Kitting; Kitting operation; Manual assembly; Model-based design; Model-based OPC; Plug & produce; Multi agent systems
National Category
Robotics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-21197 (URN)10.1109/ETFA54631.2023.10275691 (DOI)2-s2.0-85175465641 (Scopus ID)979-8-3503-3991-8 (ISBN)979-8-3503-3990-1 (ISBN)979-8-3503-3992-5 (ISBN)
Conference
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
Available from: 2024-01-19 Created: 2024-01-19 Last updated: 2024-01-19Bibliographically approved
Ramasamy, S., Bennulf, M., Zhang, X., Hammar, S. & Danielsson, F. (2023). Online Path Planning in a Multi-agent-Controlled Manufacturing System. Paper presented at 31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19 June 2022, through 23 June 2022 Code 285199. Lecture Notes in Mechanical Engineering, 124-134
Open this publication in new window or tab >>Online Path Planning in a Multi-agent-Controlled Manufacturing System
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2023 (English)In: Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364, p. 124-134Article in journal (Refereed) Published
Abstract [en]

In recent years the manufacturing sectors are migrating from mass production to mass customization. To be able to achieve mass customization, manufacturing systems are expected to be more flexible to accommodate the different customizations. The industries which are using the traditional and dedicated manufacturing systems are expensive to realize this transition. One promising approach to achieve flexibility in their production is called Plug & Produce concept which can be realized using multi-agent-based controllers. In multi-agent systems, parts and resources are usually distributed logically, and they communicate with each other and act as autonomous agents to achieve the manufacturing goals. During the manufacturing process, an agent representing a robot can request a path for transportation from one location to another location. To address this transportation facility, this paper presents the result of a futuristic approach for an online path planning algorithm directly implemented as an agent in a multi-agent system. Here, the agent systems can generate collision-free paths automatically and autonomously. The parts and resources can be configured with a multi-agent system in the manufacturing process with minimal human intervention and production downtime, thereby achieving the customization and flexibility in the production process needed. 

Place, publisher, year, edition, pages
Springer, 2023
Keywords
Autonomous agents; Computer aided manufacturing; Motion planning; Online systems; Customisation; Manufacturing process; Manufacturing sector; Mass customization; Mass production; Multi agent; On-line path planning; Path planner service; Path planners; Plug & produce; Multi agent systems
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19432 (URN)10.1007/978-3-031-18326-3_13 (DOI)2-s2.0-85141873498 (Scopus ID)
Conference
31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19 June 2022, through 23 June 2022 Code 285199
Funder
Knowledge Foundation, 20200036
Note

CC-BY 4.0

The work was funded by PoPCoRN project by KK-stiftelsen, Sweden.

31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022; Conference date: 19 June 2022 through 23 June 2022; Conference code: 285199

Available from: 2023-09-12 Created: 2023-09-12 Last updated: 2024-01-18Bibliographically approved
Reddy, D., Kulkarni, V. & Ramasamy, S. (2023). Wind Turbine System based on Fuzzy Logic based MPPT Controller and Boost type Vienna. In: Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (ICIITCEE 2023): . Paper presented at International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (ICIITCEE 2023), 27-28 January 2023, BNM Institute of Technology, Bengaluru, India (pp. 375-379). IEEE
Open this publication in new window or tab >>Wind Turbine System based on Fuzzy Logic based MPPT Controller and Boost type Vienna
2023 (English)In: Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (ICIITCEE 2023), IEEE, 2023, p. 375-379Conference paper, Published paper (Refereed)
Abstract [en]

The MPPT (Maximum Power Point Tracking) control topology based on Fuzzy logic, and analysis of the Vienna Rectifier for the small-scale Wind Turbine System (WTS) is proposed in this paper. The PMSG (Permanent Magnet Synchronous Generator) of the WTS generates the output power that is fluctuated due to irregular wind velocity, which has to be controlled for the smooth output power. Many controlstrategies are projected by the researchers for the settled power output, but the conventional control techniques getting more complex. One of the simple and robust methods that enable for the MPPT is fuzzy logic control. The above mechanism regulates the speed of PMSG and the DC power output. Moreover, it is engaged in the parameter optimization and the speed control of the PMSG. A fuzzy logic MPPT controller based Vienna Rectifier is used in this paper for a 1kW WTS with improved efficiency and reduced harmonics, and the results are justified using MATLAB/Simulink.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Maximum power point trackers, Fuzzy logic, Wind speed, Velocity control, Rectifiers, Wind power generation, Harmonic analysis, MPPT, Vienna Rectifier, Wind Turbine System, Fuzzy Logic Controller and SVPWM
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-20017 (URN)10.1109/IITCEE57236.2023.10091023 (DOI)2-s2.0-85156181460 (Scopus ID)978-1-6654-9260-7 (ISBN)978-1-6654-9259-1 (ISBN)978-1-6654-9261-4 (ISBN)
Conference
International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (ICIITCEE 2023), 27-28 January 2023, BNM Institute of Technology, Bengaluru, India
Available from: 2023-05-31 Created: 2023-05-31 Last updated: 2024-01-15Bibliographically approved
Massouh, B., Ramasamy, S., Svensson, B. & Danielsson, F. (2022). A Framework for Hazard Identification of a Collaborative Plug&Produce System. Paper presented at 4th International Conference on Intelligent Technologies and Applications, INTAP 2021; Conference date: 11 October 2021 through 13 October 2021; Conference code: 281209. Communications in Computer and Information Science, 1616 CCIS, 144-155
Open this publication in new window or tab >>A Framework for Hazard Identification of a Collaborative Plug&Produce System
2022 (English)In: Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937, Vol. 1616 CCIS, p. 144-155Article in journal (Refereed) Published
Abstract [en]

Plug&Produce systems accept reconfiguration and have the attribute of physical and logical flexibility. To implement the Plug&Produce system in a manufacturing plant, there is a need to assure that the system is safe. The process of risk assessment provides information that is used to implement the proper safety measures to ensure human and machine safety. An important step in the risk assessment process is hazard identification. Hazard identification of Plug&Produce system is unique as the hazard identification method provided in the safety standards do not consider system flexibility. In this paper, a framework for hazard identification of a collaborative Plug&Produce system is presented. A study case that includes a collaborative Plug&Produce system is presented and the framework is applied to identify the system’s hazards. Also, the generalisation of the framework application is discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2022
Keywords
Collaborative robots; Hazards; Assessment process; Collaborative robots; Hazard identification; Human safety; Identification method; Machine safety; Manufacturing plant; Plug&produce; Risks assessments; Safety measures; Risk assessment
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19172 (URN)10.1007/978-3-031-10525-8_12 (DOI)000894634800012 ()2-s2.0-85135037497 (Scopus ID)
Conference
4th International Conference on Intelligent Technologies and Applications, INTAP 2021; Conference date: 11 October 2021 through 13 October 2021; Conference code: 281209
Available from: 2022-11-08 Created: 2022-11-08 Last updated: 2024-04-12Bibliographically approved
Muniz, J., Eriksson, K. M., Valemtim, M. L., Ramasamy, S., Shotaro, Y., Marins, F. A. .., . . . Zhang, Y. (2022). Challenges of Engineering Education 5.0 based on I4.0 Policies in Brazil, India, Japan, and Sweden. In: International Conference on Work Integrated Learning: Abstract Book. Paper presented at WIL'22 7-9 December 2022, International Conference on Work Integrated Learning, University West, Trollhättan, Sweden (pp. 95-96). Trollhättan: University West
Open this publication in new window or tab >>Challenges of Engineering Education 5.0 based on I4.0 Policies in Brazil, India, Japan, and Sweden
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2022 (English)In: International Conference on Work Integrated Learning: Abstract Book, Trollhättan: University West , 2022, p. 95-96Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

Introduction: Industry and academia have placed increasing attention on implementing Industry 4.0 (I4.0) in the production ofgoods and services. Named as Industry 4.0 in Brazil, Made in India in India, Society 5.0 in Japan, andProduktion2030 in Sweden (Ribeiro et al., 2022). Hereafter, we apply I4.0 to simplify, which promises customizedproducts produced in smaller lots, and that repetitive manufacturing tasks can be automated very soon (Karre etal., 2017).Country policies play an important role in pushing different sectors of the economy, aligned as new with theregulatory framework of national and international trade, especially industrial (Aguinis et al., 2020). The implementation of I4.0 literature indicates different specificities in each country, including culture, R&D targets,education and vocational training, and their research opportunities related to how I4.0 affects workers (Jerman etal., 2020). The research-question is: How do different countries approach the opportunities and challenges of Engineering Education 4.0 through similar or different country policies?This study aims to discuss engineering education related to I4.0 policies. This discussion is based on policies fromBrazil, India, Japan, and Sweden related to education and workers 5.0, which include students and employees.Investigating how these countries are adjusting to I4.0 is relevant for national industrial sectors to wish to actefficiently in this new technological context. Industry 4.0 demands new professional skills and will impactemployment. It is noteworthy that this research is in line with the Sustainable Development Goals (SDGs) proposedby the United Nations (UN): Quality Education (SDG-4); o Decent Work and Economic Growth (SDG-8); andIndustry, Innovation, and Infrastructure (ODS-9) which seeks to promote inclusive and sustainableindustrialization and foster innovation. This research aims to contribute to sustainable o rganizational practices;formulation of public policies that alleviate social problems; guidance of professional curricula affected by I 4.0.

Papers and Data Selection: A literature search was conducted in the Scopus database, which gathers some of the most important journalsrelated to manufacturing technologies with high impact factors, based on the PRISMA method, which refers to aminimum set of evidence-based items to report studies in systematic reviews and meta -analyses (MOHER et al.,2009). The paper set was assembled from the Scopus core collection, using the following search string: “industry4.0” OR “industry 5.0” AND “policies” AND ". The results were narrowed to texts in English, which yielded 1496papers. All titles and abstracts were read, which resulted in a set composed of 14 papers. We also use official documents relating to I4.0 raised from official government websites.

Comparison of Countries’ Education policies and Industry 4.0: The literature addresses difficulties associated with the implementation of I4.0 in emerging economies (Dalagnore,2018; Hong and Muniz Jr., 2022). Not surprisingly, current literature I4.0 related to technology adoption is themost prevalent theme discussed from a hard, technology-oriented perspective rather than a people-oriented.Production systems are sociotechnical systems, with an explicit understanding that all systems involve ongoinginteractions between people and technology, and they are rapidly transforming virtually all areas of human life,work, and interaction.The European Commission’s (Breque et al., 2021) vision for ‘Industry 5.0’ proposes moves past a narrow andtraditional focus on technology-or economic enabled growth of the existing extractive, production andconsumption driven economic model to a more transformative view of growth that is focused on human progressand well-being based on reducing and shifting consumption to new forms of sustainable, circular and regenerativeeconomic value creation and equitable prosperity. This Human-centric production system design and managementapproach (Industry 5.0) is necessary to support skill development, learning, continuous improvement andcollaboration in the organization (Ribeiro et al., 2022).

Conclusion: Brazil, India, Japan and Sweden create policies to support their own technological independence. All countriesindicate concern about education and development of skills related to I4.0.It can be concluded that the four countries studied from the perspective of Industry 4.0 an d Engineering Education4.0 are all embarking on their journeys towards increased digitalization in industry and society as a whole. Therealization of the human-centered Society 5.0 was realized and highlighted comparatively early for Japan, whereasin the Europe Union and thus in Sweden the focus of the importance of Industry 5.0 development in parallelIndustry 4.0 has risen up since year 2021.The results indicate that although there are many initiatives of meeting the needs for new competence andknowledge in the era of I4.0 to accommodate Engineering Education 4.0 there are still challenges for futureresearch to move forward in the nexus between I4.0 and I5.0. The result, of studying different countries'policies, highlights that it is imperative, when approaching novel technologies in I4.0 and designing Engineering Education 4.0, to in parallel consider technological implementations with the inclusion of I5.0 aspects and humancentric perspectives.

Place, publisher, year, edition, pages
Trollhättan: University West, 2022
Keywords
Engineering Education, Policy, Cross-Country, Industry 5.0
National Category
Manufacturing, Surface and Joining Technology Learning Work Sciences
Research subject
Production Technology; Work Integrated Learning
Identifiers
urn:nbn:se:hv:diva-19513 (URN)9789189325302 (ISBN)
Conference
WIL'22 7-9 December 2022, International Conference on Work Integrated Learning, University West, Trollhättan, Sweden
Note

This work was supported by the Sao Paulo Research Foundation (FAPESP, #2021/10944-2); and Coordination ofSuperior Level Staff Improvement (CAPES, #88887.310463/2018-00)

Available from: 2023-01-02 Created: 2023-01-02 Last updated: 2023-06-02Bibliographically approved
Eriksson, K. M., Ramasamy, S., Zhang, X., Wang, Z. & Danielsson, F. (2022). Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning. Paper presented at 55th CIRP Conference on Manufacturing Systems. Procedia CIRP, 107, 955-960
Open this publication in new window or tab >>Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning
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2022 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 107, p. 955-960Article in journal (Refereed) Published
Abstract [en]

Increased environmental awareness is driving the manufacturing industry towards novel ways of energy reduction to become sustainable yet stay competitive. Climate and enviromental challenges put high priority on incorporating aspects of sustainability into both strategic and operational levels, such as production scheduling, in the manufacturing industry. Considering energy as a parameter when planning makes an already existing highly complex task of production scheduling even more multifaceted. The focus in this study is on inverse scheduling, defined as the problem of finding the number of jobs and duration times to meet a fixed input capacity. The purpose of this study was to investigate how scheduling can be formulated, within the environment of discrete event simulation coupled with reinforcement learning, to meet production demands while simultaneously minimize makespan and reduce energy. The study applied the method of modeling a production robot cell with its uncertainties, using discrete event simulation combined with deep reinforcement learning and trained agents. The researched scheduling approach derived solutions that take into consideration the performance measures of energy use. The method was applied and tested in a simulation environment with data from a real robot production cell. The study revealed opportunities for novel approaches of studying and reducing energy in the manufacturing industry. Results demonstrated a move towards a more holistic approach for production scheduling, which includes energy usage, that can aid decision-making and facilitate increased sustainability in production. We propose a conceptual framework for scheduling for minimizing energy use applying discrete event simulation as an environment for deep reinforcement learning.

Keywords
Reinforcement learning; Discrete event simulation; Energy optimal scheduling; Inverse scheduling; Industty 4.0
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Work Integrated Learning; Production Technology
Identifiers
urn:nbn:se:hv:diva-18474 (URN)10.1016/j.procir.2022.05.091 (DOI)2-s2.0-85132264077 (Scopus ID)
Conference
55th CIRP Conference on Manufacturing Systems
Note

The work was carried out at the Production Technology Centre at University West, Sweden supported by the Swedish Governmental Agency for Innovation Systems (Vinnova) under the project SmoothIT and by the KK Foundation under the project Artificial and Human Intelligence through Learning (AHIL). Their support is gratefully acknowledged. Assistance provided by Master's students Maria Vincenta Vivo and Mohammadali Zakeriharandi was greatly appreciated. 

Available from: 2022-06-13 Created: 2022-06-13 Last updated: 2024-04-12
Gopal, D., Ramasamy, S., Murugesan, M., Venkatesan, C., Manimegalai Govindan, S. & Sathyamurthy, R. (2022). Optimization of processing parameters of cold metal transfer joined 316L and weld bead profile influenced by temperature distribution based on genetic algorithm. Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, 236(19)
Open this publication in new window or tab >>Optimization of processing parameters of cold metal transfer joined 316L and weld bead profile influenced by temperature distribution based on genetic algorithm
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2022 (English)In: Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, ISSN 0954-4062, E-ISSN 2041-2983, Vol. 236, no 19Article in journal (Refereed) Published
Abstract [en]

Austenitic stainless steel alloys find the wide range of application in modern industries like pipework, containers, food production and in medical industries for its excellent processing properties and corrosion resistance. There is enormous literature report on the mechanical properties, appropriate joining of materials using different fusion welding processes. Consequently, the cold metal transfer technique appears to weld materials with low heat input which is a noticeable feature of this welding process. In this paper, cold metal transfer welding is performed on austenitic stainless steel material 316L and its bead geometries such as reinforcement height, depth of weld penetration and bead width profile are examined. The temperature distribution at the welding line is observed by means of the data acquisition unit. Genetic algorithm based optimization technique is used to achieve the desired combination of input variables and weld bead geometry. This developed genetic algorithm optimizes the welding process parameters and geometry of the weld bead, by minimizing the least square error based objective function. The investigation outcome of this paper provides an insight into the characterization of the weldment, the effects of weld current and weld travel speed on temperature profile and mechanical properties include hardness, tensile and residual profiles.

Place, publisher, year, edition, pages
Sage Publications, 2022
Keywords
cold metal transfer; genetic algorithm; data acquisition unit; mechanical properties
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-18505 (URN)10.1177/09544062221103372 (DOI)000799712200001 ()2-s2.0-85131005379 (Scopus ID)
Available from: 2022-10-31 Created: 2022-10-31 Last updated: 2022-11-03Bibliographically approved
Babu, C., Immanuel, A., Jyotheeswara Reddy, K., Kumar, K., Ramasamy, S. & Venkateswarlu, S. (2022). Performance analysis of flat plate hybrid PV/thermal configurations. In: AIP Conference Proceedings: . Paper presented at International Conference On Recent Trends In Electrical, Electronics & Computer Engineering For Environmental And Sustainable Development: Icrteec-2021. American Institute of Physics (AIP), 2461, Article ID 060007.
Open this publication in new window or tab >>Performance analysis of flat plate hybrid PV/thermal configurations
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2022 (English)In: AIP Conference Proceedings, American Institute of Physics (AIP), 2022, Vol. 2461, article id 060007Conference paper, Published paper (Refereed)
Abstract [en]

In the recent times many hybrid renewable energy sources are developed. In that, hybrid PV/Thermal gains the more attention than other hybrid sources. In the present work, made a performance analysis of different PV/Thermal configurations. The flat plate configurations have the more feasibility for the domestic applications than the concentrated type. In this paper, liquid, air, nano fluid, phase change material and Thermoelectric generator type configurations are presented. The performance analysis of all configurations done with energy output generation and efficiency of the system. 

Place, publisher, year, edition, pages
American Institute of Physics (AIP), 2022
Keywords
Performance analysis, renewable energy
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19302 (URN)10.1063/5.0092507 (DOI)2-s2.0-85137451284 (Scopus ID)978-0-7354-4357-0 (ISBN)
Conference
International Conference On Recent Trends In Electrical, Electronics & Computer Engineering For Environmental And Sustainable Development: Icrteec-2021
Note

© 2022 Author(s).

Available from: 2022-12-01 Created: 2022-12-01 Last updated: 2022-12-20Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-4091-7732

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