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Applications in Automobile Industries
Published in S. S. Nandhini, M. Karthiga, S. B. Goyal, Computational Intelligence in Robotics and Automation, 2023
G. Sathish Kumar, D. Prabha Devi, R. Ramya, P. Rajesh Kanna
Most of the companies use the augmented reality and virtual reality to focus on the manufacturing issues. These technologies have minimised the cost of error during the production stage. The automated automobile industries have become the benchmark for other industries. They are visualising and transforming the plants into a high-class manufacturing hub along with the digitalisation. The digitalisation in the automobile industries results in highly transparent, highly visual and much organised way in industry development. The business needs in the automotive industry is to create the optimum way for the faster product development and quick adaptability. The use of autonomous mobile robots (AMRs) is the clear tendency in the automobile industries. The AMRs do not require the magnetic strips for the guidance for the mobility inside the manufacturing unit. Instead, they require only the internal maps for the navigation, and it is very easy to update. The autonomous robots are mainly used in robotic vision, spot and arc welding, assembly, painting, sealing, coating, machine tending and part transfer, materials removal and internal logistics.
Industry 4.0
Published in Pau Loke Show, Kit Wayne Chew, Tau Chuan Ling, The Prospect of Industry 5.0 in Biomanufacturing, 2021
Khalisanni Khalid, Shir Reen Chia, Kit Wayne Chew, Pau Loke Show
Autonomous robots are similar to humans. Robots are able to make their own decision and perform actions accordingly. It can manipulate and actuate itself within the environment through the program installed in the autonomous robotic system (Indri, Grau, and Ruderman 2018). In the case of mobility, the decision making is incorporated with the maneuvering decision-based support systems such as stop, start, and manipulate the dynamic of its surrounding. AI technology is installed in the robotic system network to ensure autonomous decision making is applicable. Autonomous robots is use to execute routine work, high-risk schedule, complex programming, and repetitive assignments in the manufacturing and production process where the tasks are hardly executed by human (Benotsmane, Kovács, and Dudás 2019).
Smart irrigation in farming using internet of things
Published in Govind Singh Patel, Amrita Rai, Nripendra Narayan Das, R. P. Singh, Smart Agriculture, 2021
Devesh Kumar Srivastava, Priyanka Nair
With the new technologies, it has become easier to record and measure the environmental changes and find suitable solutions to them. These newly derived wireless networks, devices and sensors consume a lot of energy because of the batteries that are boarded with actuators (Cambra et al., 2017). Autonomous robots are sensor-based and capable of navigation as well as seed sowing along with vision systems, Radio-Frequency Identification (RFID) wireless sensors, GSM (Global System for Mobile Communications), Bluetooth and GPS (Global Positioning System) technology. The data captured from these devices are further transferred for further research. There are many factors that limit the agricultural development such as natural resources availability, agricultural land suitability, increase in population, depletion of biofuels etc. Land employment has significantly declined in the past 10 years. In 1991, land for production of food was approximately 39% of the world’s landmass, but later according to the 2013 statistics it reduced to 37% and has been declining continuously with time.
Application of supportive and substitutive technologies in manual warehouse order picking: a content analysis
Published in International Journal of Production Research, 2023
Similar to digital manufacturing, a digital skills gap (lacking experience with new technologies) and fear of job and competence losses may exist when implementing new technologies in order picking, such as autonomous robots (Molino et al. 2020; Mukhuty et al. 2022). Further investigations are necessary on these psychosocial implications, as demonstrated by the nonmention of the term ‘digital skill’ in the sample. Moreover, ‘job loss’ and ‘resistance’ received only 1 and 12 hits, respectively, among which only half were associated with user resistance. Consequently, workers may experience oppression when technology leads to a lack of autonomy, competence, and relatedness, increasing stress, counterproductive work behaviours, and demotivation among employees (Cascio and Montealegre 2016).
The impact of Operations and IT-related Industry 4.0 key technologies on organizational resilience
Published in Production Planning & Control, 2022
Giulio Marcucci, Sara Antomarioni, Filippo Emanuele Ciarapica, Maurizio Bevilacqua
Autonomous Robots is the last Industry 4.0 Operations-related key technology taken into consideration in the survey. Autonomous Robots can gain information about their environment and work for an extended period without human intervention. These trends towards robotic involvement in industry processes will allow companies to improve productivity and customer experience and gain a competitive advantage (Amigoni, Luperto, and Schiaffonati 2017). However, literature has also highlighted some problems that need to be addressed. Dalenogare et al. (2018), in a survey on Brazilian companies, found that this technology was not significantly associated with the expected benefits because it is in a very early stage of adoption in the Brazilian industry. According to the CNI report (CNI 2016), only around 8% of the industry has adopted these technologies for operations processes. Hence, several industrial sectors may not be aware of their contribution to operations benefits.
Emerging technologies and their potential for generating new assistive technologies
Published in Assistive Technology, 2021
Sarah Abdi, Irene Kitsara, Mark S. Hawley, L. P. de Witte
Robotics is an emerging technological field that could have a transformative socio-economic impact (PA consulting, 2017; United Nation, 2018; WEF, 2019a). Advances in AI and sensor technology have enabled the development of more autonomous robots that can interact, adapt and respond to their environments (PA consulting, 2017; WEF, 2015a). These new adaptive capabilities of robots are said to enhance human-machine collaborations, enabling new developments and potential AT applications for robots. Some of the developments that were mentioned in the reviewed documents included companion robots, exoskeletons and autonomous vehicles (EPSRC, 2019b; MIT, 2016c, 2017d, 2019a; NHS, 2019; WEF, 2019b). For example, companion robots embed AI and are able to perform tasks of health and emotion monitoring, entertaining, navigating, communicating and assisting in everyday activities. Robotic dexterity has also improved significantly, enabling potential applications in areas like self-care and household activities (MIT, 2017d, 2019a). Other recent robotic advances include the development of autonomous soft robots (EPSRC, 2019c; MIT, 2017f). Soft robots are flexible robots whose development are inspired by the way living organisms move and adapt (e.g., octopuses) (MIT, 2017f). However, these advances are still at very early stages of development and there is some significant ambiguity around potential AT applications in the near future (MIT, 2017f).