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Fabrication of semiconductor wafers is a complicated and challenging process with huge system complexity and stochasticity in operations. To improve the above challenges and to enhance the system’s efficiency an effective scheduling technique is indispensable. In recent times Real-time scheduling with dynamic dispatching rules has been widely discussed. However, choosing the appropriate combination of dispatching rules in a dynamic environment is a challenge. In this study, we proposed a multi-objective non-dominated sorting genetic algorithm (MO-NSGA-II) approach for optimizing the dispatching rules by considering the multiple objectives as minimization of work in process, minimization of delay time, and minimization of makespan. To implement the proposed approach, the optimal parameters for the multi-objective evolutionary algorithm (MOEA) are selected based on the hierarchical combination method and by deploying the response surface methodology (RSM) the best combination of rules is generated. Further, a real-time simulated environment is created using Flexsim to check the significance of the proposed approach and the robustness of the generated combinatorial rules. Results stated that the proposed approach can improve the performance of a system to a greater extent.
Suraj Panigrahi; Srijeta Agrahari; José Machado; V. K. Manupati. Production Scheduling of Semiconductor Wafer Fabrication Facilities Using Real-Time Combinatorial Dispatching Rule. International Conference on Reliable Systems Engineering (ICoRSE) - 2021 2021, 78 -90.
AMA StyleSuraj Panigrahi, Srijeta Agrahari, José Machado, V. K. Manupati. Production Scheduling of Semiconductor Wafer Fabrication Facilities Using Real-Time Combinatorial Dispatching Rule. International Conference on Reliable Systems Engineering (ICoRSE) - 2021. 2021; ():78-90.
Chicago/Turabian StyleSuraj Panigrahi; Srijeta Agrahari; José Machado; V. K. Manupati. 2021. "Production Scheduling of Semiconductor Wafer Fabrication Facilities Using Real-Time Combinatorial Dispatching Rule." International Conference on Reliable Systems Engineering (ICoRSE) - 2021 , no. : 78-90.
The coronavirus (COVID-19) pandemic created catastrophic failure on global supply chains, particularly its impact on the food supply chain left havoc across the globe. The objective of this study is to understand the challenges imposed by the pandemic to the agricultural supply chain in the context of the Indian subcontinent and also analyse the variations in the arrivals and costs of the products. As a first step, the conventional flow of perishable food supply chain products from farmers to end customers has been described. Thereafter, the most widely used perishable product (tomato) has been chosen and its availability across the Indian regions has been identified. Consequently, the zones (red, green, and orange) under which these regions are mapped are identified. Later, with several analyses, the effect of zones and its impact on product arrival and its cost are discussed in detail. Finally, several research directions and the challenges to overcome the agricultural supply chain have been discussed.
Nitish Maan; Vijaya Kumar Manupati; Maciel M. Queiroz; Biswajita Mohanty. Challenges Faced and Preparedness of Agriculture Supply Chain During COVID-19. Management and Industrial Engineering 2021, 29 -40.
AMA StyleNitish Maan, Vijaya Kumar Manupati, Maciel M. Queiroz, Biswajita Mohanty. Challenges Faced and Preparedness of Agriculture Supply Chain During COVID-19. Management and Industrial Engineering. 2021; ():29-40.
Chicago/Turabian StyleNitish Maan; Vijaya Kumar Manupati; Maciel M. Queiroz; Biswajita Mohanty. 2021. "Challenges Faced and Preparedness of Agriculture Supply Chain During COVID-19." Management and Industrial Engineering , no. : 29-40.
Six-Sigma, a data-driven methodology, employed to improve the process in terms of Defect reduction or process optimization. In this paper, an experimental study is presented optimizing the cutting parameters while machining of shoulder bolt in a Computer Numerical Control (CNC) turning machine to reduce the cycle time. This study identifies, the effects of cutting speed, feed rate and dwell time on Thread rolling diameter (TRD) in CNC turning machine that was experimentally investigated. The experimentation plan is designed using six sigma D-M-A-I-C methodology, and the subsequent statistical analysis has been done using Minitab-16 software. Shainin based variable search tool has been used to investigate the design parameters that contribute to the reduction of the cycle time and factorial plots are employed to determine the contribution of important parameters. Later, the optimal values for the best cutting conditions are proposed for industrial production using the formulated mathematical model. Finally, this paper documents the analysis and tasks performed that reduced cycle time which resulted in increased productivity and also in annual savings.
Kakarla Manoj; Biswajit Kar; Rajeev Agrawal; Vijay Kumar Manupati; José Machado. Cycle Time Reduction in CNC Turning Process Using Six Sigma Methodology – A Manufacturing Case Study. Recent Advances in Computational Mechanics and Simulations 2021, 135 -146.
AMA StyleKakarla Manoj, Biswajit Kar, Rajeev Agrawal, Vijay Kumar Manupati, José Machado. Cycle Time Reduction in CNC Turning Process Using Six Sigma Methodology – A Manufacturing Case Study. Recent Advances in Computational Mechanics and Simulations. 2021; ():135-146.
Chicago/Turabian StyleKakarla Manoj; Biswajit Kar; Rajeev Agrawal; Vijay Kumar Manupati; José Machado. 2021. "Cycle Time Reduction in CNC Turning Process Using Six Sigma Methodology – A Manufacturing Case Study." Recent Advances in Computational Mechanics and Simulations , no. : 135-146.
Multi-criteria decision-making (MCDM) techniques are being adopted in the supplier selection in the automotive industry. Due to their flexibility to interact with the factors needed in determining the supplier selection. The concept of a balanced scorecard is proposed for rating the supplier while evaluating their performance. Due to limitations in each MCDM technique, it is difficult to find a potential supplier using specific methodologies. Therefore, this paper proposes the integration of Fuzzy TOPSIS, Fuzzy AHP, and Fuzzy VIKOR in determining the potential supplier for a bus body building unit in the Indian context. After finding the rankings using each MCDM technique, spearman rank correlation coefficient is used to test the reliability in the ranks generated by each technique. The output results of this study help the company in establishing a robust supplier selection framework to select the best supplier.
Vijaya Kumar Manupati; G. Rajya Lakshmi; M. Ramkumar; M. L. R. Varela. An Integrated Fuzzy MCDM Approach to Supplier Selection—Indian Automotive Industry Case. Internet of Things (IoT) in 5G Mobile Technologies 2021, 473 -484.
AMA StyleVijaya Kumar Manupati, G. Rajya Lakshmi, M. Ramkumar, M. L. R. Varela. An Integrated Fuzzy MCDM Approach to Supplier Selection—Indian Automotive Industry Case. Internet of Things (IoT) in 5G Mobile Technologies. 2021; ():473-484.
Chicago/Turabian StyleVijaya Kumar Manupati; G. Rajya Lakshmi; M. Ramkumar; M. L. R. Varela. 2021. "An Integrated Fuzzy MCDM Approach to Supplier Selection—Indian Automotive Industry Case." Internet of Things (IoT) in 5G Mobile Technologies , no. : 473-484.
Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies.
Thirupathi Samala; Vijaya Manupati; Bethalam Nikhilesh; Maria Varela; Goran Putnik. Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status. Sustainability 2021, 13, 5295 .
AMA StyleThirupathi Samala, Vijaya Manupati, Bethalam Nikhilesh, Maria Varela, Goran Putnik. Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status. Sustainability. 2021; 13 (9):5295.
Chicago/Turabian StyleThirupathi Samala; Vijaya Manupati; Bethalam Nikhilesh; Maria Varela; Goran Putnik. 2021. "Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status." Sustainability 13, no. 9: 5295.
Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.
Thirupathi Samala; Vijaya Manupati; Maria Varela; Goran Putnik. Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review. Future Internet 2021, 13, 57 .
AMA StyleThirupathi Samala, Vijaya Manupati, Maria Varela, Goran Putnik. Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review. Future Internet. 2021; 13 (3):57.
Chicago/Turabian StyleThirupathi Samala; Vijaya Manupati; Maria Varela; Goran Putnik. 2021. "Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review." Future Internet 13, no. 3: 57.
In recent years, municipal authorities especially in the developing nations are battling to select the best health care waste (HCW) disposal technique for the effective treatment of the medical wastes during and post COVID-19 era. As evaluation of various disposal alternatives of HCW and selection of the best technique requires considering various tangible and intangible criteria, this can be framed as multi-criteria decision-making (MCDM) problem. In this paper, we propose an assessment framework for the selection of the best HCW disposal technique based on socio-technical and triple bottom line perspectives. We have identified 10 criteria on which the best HCW disposal techniques to be selected based on extant literature review. Next, we use Fuzzy VIKOR method to evaluate 9 HCW disposal alternatives. The effectiveness of the proposed framework has been demonstrated with a real-life case study in Indian context. To check the robustness of the proposed methodology, we have compared the results obtained with Fuzzy TOPSIS (Technique of Order Preference Similarity to the Ideal Solution). The results help the municipal authorities to establish a methodical approach to choose the best HCW disposal techniques. Our findings indicate that incineration is the best waste disposal technique among the available alternatives. Even if the dataset indicates 'incineration' is the best method, we must not forget about the environmental concerns arising from this method. In COVID time, incineration may be the best method as indicated by the data analysis, but "COVID" should not be an excuse for causing "Environmental Pollution".
Vijaya Kumar Manupati; M. Ramkumar; Vinit Baba; Aayush Agarwal. Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production 2020, 281, 125175 -125175.
AMA StyleVijaya Kumar Manupati, M. Ramkumar, Vinit Baba, Aayush Agarwal. Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production. 2020; 281 ():125175-125175.
Chicago/Turabian StyleVijaya Kumar Manupati; M. Ramkumar; Vinit Baba; Aayush Agarwal. 2020. "Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era." Journal of Cleaner Production 281, no. : 125175-125175.
Complex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach’s effectiveness has been shown by the simulation results on two different configurations having different scenarios.
V K Manupati; Suraj Panigrahi; Muneeb Ahsan; Somnath Lahiri; Akshay Chandra; J J Thakkar; Goran Putnik; M L R Varela. Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment. Sādhanā 2019, 44, 30 .
AMA StyleV K Manupati, Suraj Panigrahi, Muneeb Ahsan, Somnath Lahiri, Akshay Chandra, J J Thakkar, Goran Putnik, M L R Varela. Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment. Sādhanā. 2019; 44 (2):30.
Chicago/Turabian StyleV K Manupati; Suraj Panigrahi; Muneeb Ahsan; Somnath Lahiri; Akshay Chandra; J J Thakkar; Goran Putnik; M L R Varela. 2019. "Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment." Sādhanā 44, no. 2: 30.
India is witnessing rapid urbanization due to increase in population in cities. This poses a major challenge to the urban renewal process. This paper aims to provide an urban renewal framework for the development of cities in India under the ambit of smart cities mission, an initiative by the Government of India. To guide practices related to management of urban areas and advance policy-making decisions and scientific inquiry in this domain, we identify 7 criteria and 27 sub-criteria mainly from the literature related to socio-technical perspectives. To handle the inter-relations among the identified criteria and sub-criteria, we propose a multi-criteria decision-making (MCDM) approach based on Decision Making Trial and Evaluation Laboratory based Analytic Network Process (DANP). Moreover, the effectiveness of the proposed methodology for urban renewal in South India is demonstrated with a real-life case study. Finally, we establish how the obtained results will help the policy makers to initiate urban renewal in southern India.
Vijaya Kumar Manupati; M. Ramkumar; Digjoy Samanta. A multi-criteria decision making approach for the urban renewal in Southern India. Sustainable Cities and Society 2018, 42, 471 -481.
AMA StyleVijaya Kumar Manupati, M. Ramkumar, Digjoy Samanta. A multi-criteria decision making approach for the urban renewal in Southern India. Sustainable Cities and Society. 2018; 42 ():471-481.
Chicago/Turabian StyleVijaya Kumar Manupati; M. Ramkumar; Digjoy Samanta. 2018. "A multi-criteria decision making approach for the urban renewal in Southern India." Sustainable Cities and Society 42, no. : 471-481.