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  • 1.
    Babu, Challa
    et al.
    Department of EEE, Siddartha Institute of Science and Technology, Puttur, AP (IND).
    Immanuel, A.
    Department of EEE, Audisankara College of Engineering and Technology, Gudur, AP (IND).
    Jyotheeswara Reddy, K.
    School of EEE, REVA University, Bangalore, Karnataka (IND).
    Kumar, K.
    Department of EEE, SV College of Engineering, Tirupathi, AP (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Venkateswarlu, S.
    School of Electrical Engineering, VIT University, Vellore (IND).
    Performance analysis of flat plate hybrid PV/thermal configurations2022Ingår i: AIP Conference Proceedings, American Institute of Physics (AIP), 2022, Vol. 2461, artikel-id 060007Konferensbidrag (Refereegranskat)
    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. 

  • 2.
    Babu, Challa
    et al.
    Audisankara college of engineering and technology, Department of electrical and electronics engineering, Gudur, A.P, India (IND).
    Kumar, D. Dinesh
    Audisankara college of engineering and technology, Department of electrical and electronics engineering, Gudur, A.P, India (IND).
    Kumar, K
    SV College of Engineering, Tirupathi, AP, India (IND).
    Reddy, K Jyotheeshwara
    Sree Vidayanikethan Engineering College, Tirupathi, A.P., India (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Power Monitoring and Control System for Medium Voltage Smart Grid Using IoT2020Ingår i: IOP Conference Series: Materials Science and Engineering, IOP Publishing , 2020, Vol. 906, artikel-id 12007Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a power monitoring and control system for a medium voltage smart grid system. The smart grid interconnects the power sources between solar PV panel and 220V distribution network. This system consisting major components of inverters, measuring meters, solar charge controllers, relays, Arduino NANO and Raspberry Pi. The Current, power and energy readings are duly recorded. The Internet of Things (IoT) plays the vital role in the data communication between the sensors and electric power system. The voltage and current sensor data is used for the protection of power system network. In the traditional systems only the communication is uni-directional. The reliability of power supply is increased by used the bi directional network communication medium such as IoT. The tabulated results of voltage levels between 203.5V up to 212.8V shows the feasibility and effectiveness of proposed design. The proposed IoT model demonstrated the bidirectional communication from the sensors to the control unit and vice versa.

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  • 3.
    Duraisamy, Palmani
    et al.
    Electronics & Instrumentation Engineering, School of EEE, SASTRA University, Thanjavur, Tamil Nadu (IND).
    Santhanakrishnan, Manigandan Nagarajan
    Electronics & Instrumentation Engineering, School of EEE, SASTRA University, Thanjavur, Tamil Nadu (IND).
    Amirtharajan, Rengarajan
    Electronics and Communication Engineering, School of EEE, SASTRA University, Thanjavur, Tamil Nadu (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling2024Ingår i: Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, ISSN 0954-4062, E-ISSN 2041-2983, Vol. 238, nr 2, s. 572-585Artikel i tidskrift (Refereegranskat)
    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.

  • 4.
    Eriksson, Kristina M.
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Zhang, Xiaoxiao
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Wang, Zhiping
    Research and Technology Development, Volvo Group Trucks Operations, Gothenburg (SWE).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning2022Ingår i: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 107, s. 955-960Artikel i tidskrift (Refereegranskat)
    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.

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  • 5.
    Gopal, Dhivyasri
    et al.
    Department of Biomedical Engineering, Dr NGP Institute of Technology, Coimbatore (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Murugesan, Manikandan
    Department of Electronics and Communication Engineering, Presidency University, Karnataka (IND).
    Venkatesan, Chandran
    Department of Biomedical Engineering, Dr NGP Institute of Technology, Coimbatore (IND).
    Manimegalai Govindan, Sumithra
    Department of Biomedical Engineering, Dr NGP Institute of Technology, Coimbatore (IND).
    Sathyamurthy, Ravishankar
    Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran (SAU); Department of Mechanical Engineering, KPR Institute of Engineering and Technology, Coimbatore (IND); Department of Mechanical Engineering, University Centre for Research & Development, Chandigarh University, Mohali (IND).
    Optimization of processing parameters of cold metal transfer joined 316L and weld bead profile influenced by temperature distribution based on genetic algorithm2022Ingår i: Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science, ISSN 0954-4062, E-ISSN 2041-2983, Vol. 236, nr 19Artikel i tidskrift (Refereegranskat)
    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.

  • 6.
    Gupta, Siddhartha
    et al.
    VIT Vellore,School Of Electrical Engineering (SELECT),Vellore,India.
    Sinha, Neha
    VIT Vellore,School Of Electrical Engineering (SELECT),Vellore,India.
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Babu, Challa
    VIT Vellore,School Of Electrical Engineering (SELECT),Vellore,India.
    Breast Cancer Detection Using Image Processing Techniques2019Ingår i: 2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Institute of Electrical and Electronics Engineers Inc. , 2019, Vol. 1Konferensbidrag (Refereegranskat)
    Abstract [en]

    Cancer is the uncontrolled multiplication of group of cells in a particular location of the body and is the second largest disease leading to the death of women in the world. The disease can be cured if it is detected in early stages. A lot of research has been done to find out the tumor correctly but a 100% accurate method has not been found. Research on breast cancer detection using digital image processing is not new but many new approaches in this field is being considered to accurately predict the tumor region. The present approach is to detect the tumor region visually as well as to figure out in which region the tumor is mostly concentrated. This work majorly focuses on finding out the best algorithm/s to detect the tumor present in the breast. In the proposed work, a variety of algorithms has been applied but the best one suited for cancer detection is the combination of K Means, Closing, Dilation and Canny Edge Detection algorithm. © 2019 IEEE.

  • 7.
    Indragandhi, V.
    et al.
    Vellore Institute of Technology, Vellore, India (IND).
    Raja Singh, R.
    Vellore Institute of Technology, Vellore, India (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Ramanathan, Prabhu K.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Preface2020Ingår i: IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, E-ISSN 1757-899X, Vol. 906, artikel-id 11001Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We would like to present, with great pleasure that the aim of the 2nd Virtual Conference on Advances in Electric Drives, Process Control and Automation (VCADPCA2020) is a platform for researchers, academicians as well as professionals from all over the world to present, discuss and promote advances in knowledge, research and practice in the field of Electric Drives, Process Control and Automation. VCADPCA2020 is offering a fantastic opportunity to attend a global scientific forum from the convenience of your desktop. No travelling, no hotel expenses, no time away from the office. The conference runs fully online, from paper submission, including reviewing, conference discussion and post conference processing. All papers will be referred to double tier approval process, single-blind peer-review and regular check. The online conference is a smart and affordable manner of presenting research results.Three leading universities VIT, India, Aalborg University Fibigerstræde, Denmark and University West, Sweden are organized this conference successfully on 9th June 2020. Keynote sessions are presented virtually from National and International experts in cutting edge technologies. The selected papers are presented by the authors virtually in the emerging fields like smart grid, power electronics, renewable energy, industrial automation, control and robotics. The panel members evaluated the research ideas and recommended for paper publications in IOP conference proceedings.

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  • 8.
    Khabbazi, Mahmood Reza
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Bennulf, Mattias
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Nilsson, Anders
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Model-based Plug & Produce in Assembly Automation2023Ingår i: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA): 12-15 September 2023, IEEE, 2023, Vol. 2023-SeptemberKonferensbidrag (Refereegranskat)
    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.

  • 9.
    Massouh, Bassam
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Khabbazi, Mahmood Reza
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Zhang, Xiaoxiao
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Online Hazard Detection in Reconfigurable Plug & Produce Systems2024Ingår i: 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, s. 889-897Konferensbidrag (Refereegranskat)
    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.

  • 10.
    Massouh, Bassam
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Svensson, Bo
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    A Framework for Hazard Identification of a Collaborative Plug&Produce System2022Ingår i: Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937, Vol. 1616 CCIS, s. 144-155Artikel i tidskrift (Refereegranskat)
    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.

  • 11.
    Muniz, Jorge
    et al.
    Sao Paulo State University, UNESP (BRA).
    Eriksson, Kristina M.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Valemtim, Marta Ligia Pomim
    UNESP (BRA).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Shotaro, Yagi
    University of Tokyo, Tokyo (JPN).
    Marins, Fernando A.S.
    UNESP (BRA).
    Voorwald, Herman J.C.
    UNESP (BRA).
    Ericsson, Mikael
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Zhang, Yufeng
    University of Birmingham, Birmingham (GBR).
    Challenges of Engineering Education 5.0 based on I4.0 Policies in Brazil, India, Japan, and Sweden2022Ingår i: International Conference on Work Integrated Learning: Abstract Book, Trollhättan: University West , 2022, s. 95-96Konferensbidrag (Övrigt vetenskapligt)
    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.

  • 12.
    Ramasamy, Sudha
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Bennulf, Mattias
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Zhang, Xiaoxiao
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Hammar, Samuel
    Graniten, Uddevalla, (SWE).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Online Path Planning in a Multi-agent-Controlled Manufacturing System2023Ingår i: Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364, s. 124-134Artikel i tidskrift (Refereegranskat)
    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. 

  • 13.
    Ramasamy, Sudha
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Eriksson, Kristina M.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Peralippatt, Saptha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Perumal, Balasubramanian
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Optimized Online Path Planning Algorithms Considering Energy2021Ingår i: Proceedings: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE conference proceedings, 2021, s. 1-08Konferensbidrag (Refereegranskat)
    Abstract [en]

    Plug and produce demonstrators handles multiple processes in the industry, appropriate path planning is essential and at the same time there is an increasing emphasis on more sustainable processes. To ensure the sustainability and automate these processes optimized path planning is required. We present an implementation of a path planning algorithm, which creates a smooth collision free path and considers energy use. In the paper, we demonstrated the implementation of PRM (Probabilistic Road Map) path planning and Dijkstra based optimization algorithm in a simulation environment and thereafter test in a real plug and produce demonstrator. To validate the simulated results the real energy was measured through the signal analyzer online. The measured results outlined in this paper includes; computational time, move along path time, and energy use with different loads. From the experiments and results we conclude that the combination of the two algorithms, PRM with Dijkstra, can be used to generate a collision free optimized path. Here we have considered the distance as the cost function for Dijkstra optimization algorithm and measured the energy of the collision free optimized path. The practical implication of this research is as an enabler for any kind of application where there are large variations of orders e.g., kitting techniques in assembly operations for manufacturing industry.

  • 14.
    Ramasamy, Sudha
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Eriksson, Kristina M.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Perumal, Balasubramaniam
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Peralippatt, Saptha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Optimized Path Planning by Adaptive RRT* Algorithm for Constrained Environments Considering Energy2021Ingår i: Proceedings 2021: 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE conference proceedings, 2021, s. 1-8Konferensbidrag (Refereegranskat)
    Abstract [en]

    Optimized path planning of robots are necessary for the industries to thrive towards greater flexibility and sustainability. This paper proposes an implementation of a collision-free path with the shortest distance. The novelty of the work presented is the new ARRT*(Adaptive Rapidly exploring Random Tree Star) algorithm, which is modified from the RRT*(Rapidly exploring Random Tree Star). In a constraint environment, RRT* algorithms tend to fail when searching for suitable collision-free paths. The proposed ARRT* algorithm gives an optimized feasible collision-free paths in a constraint environment. The feasibility to implement RRT* and ARRT* in a Multi Agent System as a path agent for online control of robots is demonstrated. We have created a digital twin simulated environment to find a collision-free path based on these two algorithms. The simulated path is tested in real robots for feasibility and validation purpose. During the real time implementation, we measured the following parameters: the algorithm computation time for generating a collision-free path, move along time of the path in real time, and energy consumed by each path. These parameters were measured for both the RRT* and the ARRT* algorithms and the test results were compared. The test results were showing that ARRT* performs better in a constrained environment. Both algorithms were tested in a Plug and Produce setup and we find that the generated paths for both algorithms are suitable for online path planning applications.

  • 15.
    Ramasamy, Sudha
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Zhang, Xiaoxiao
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Bennulf, Mattias
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Danielsson, Fredrik
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Automated Path Planning for Plug Produce in a Cutting-tool Changing Application2019Ingår i: 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2019, s. 356-362, artikel-id 8869398Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, a path planning algorithm is designed and tested with a real robot for a Plug & Produce demonstrator. The demonstrator is divided into modules that can be connected and removed. Modules are used for various processes like tool change and storage. This paper focuses on the process of cutting-tool change for the production industry. The Plug & Produce demonstrator uses a multi-agent system where parts and resources are agents. A part agent, e.g., a cutting-tool, can request a robot to perform skills like transportation. This requires the robot to be autonomous. The aim of this paper is to automate the path planning for industrial robotics in a Plug & Produce system. This is done by implementing a sampling based RRT algorithm combined with a collision detection function in RobotStudio. With various real time scenarios, the path planning execution time is observed and presented in the paper.

  • 16.
    Reddy, Damodhar
    et al.
    Dept of Electrical & Electronics Engg. Sasi Institute of Technology & Engineering Tadepalligudem (IND).
    Kulkarni, Vikram
    Dept of Electrical & Electronics Engg. SasDept. of Information Technology, MPSTME, NMIMS University, Mumbai (IND).
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Wind Turbine System based on Fuzzy Logic based MPPT Controller and Boost type Vienna2023Ingår i: Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (ICIITCEE 2023), IEEE, 2023, s. 375-379Konferensbidrag (Refereegranskat)
    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.

  • 17.
    Reddy, Damodhar
    et al.
    School of Electrical Engineering, Vellore Institute Technology, Vellore, 632014, India.
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    A back propagation network based MPPT algorithm for grid-tied wind energy system with Vienna Rectifier2019Ingår i: International Journal of Renewable Energy Research, ISSN 1309-0127, Vol. 9, nr 2, s. 1097-1107Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a boost type Vienna Rectifier with a back propagation network algorithm for maximum power point tracking (MPPT) from the wind energy system. The preferred control algorithm deals with non-linear problems with improved conversance precision and reduced learning time. In this system, boost type Vienna Rectifier is employed as a machine side converter for single stage energy conversion of AC to DC with the enhanced output voltage and a grid side converter worked for DC to AC conversion. Vienna Rectifier facilitates power flow with high power density, continuous sinusoidal input current, improved power factor and offers low voltage stress across the switches. The proposed system is designed to meet the load power demand of 1kW Active power with the combined contribution of the wind and the main grid. The resulting analysis of the Vienna Rectifier with the aforementioned control algorithm is validated through Matlab-Simulink for variable wind speeds. © 2019, International Journal of Renewable Energy Research.

  • 18.
    Reddy, Damodhar
    et al.
    HITAM, Department of Electrical and Electronics Engineering, Hyderabad, India.
    Ramasamy, Sudha
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för produktionssystem (PS).
    Comparative Analysis of P & O and RBFN MPPT Controller Based Three Level SEPIC Topology for 1.2kW Solar PV System2019Ingår i: Gazi University Journal of Science, E-ISSN 2147-1762, Vol. 32, nr 3, s. 853-869Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    This paper accords an intelligent controller based 3-level SEPIC configuration for energy transformation in the solar PV system. An artificial intelligence based radial basis function network is engaged as a control algorithm for the maximum power extraction and the converter control can be done based on the duty cycle generated by the controller. In this system, a SEPIC topology is used for high voltage gain with reduced switching losses. In this paper, an RBFN controller based 3-level SEPIC topology is designed for 1.2kW solar PV system over the traditional P & O (Perturb & Observe) control method and the comparative result analysis is done though the simulation output for the corresponding input parameters.

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