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Rising energy prices, increasing maintenance costs, and strict environmental regimes have augmented the already existing pressure on the contemporary manufacturing environment. Although the decentralization of supply chain has led to rapid advancements in manufacturing systems, finding an efficient supplier simultaneously from the pool of available ones as per customer requirement and enhancing the process planning and scheduling functions are the predominant approaches still needed to be addressed. Therefore, this paper aims to address this issue by considering a set of gear manufacturing industries located across India as a case study. An integrated classifier-assisted evolutionary multi-objective evolutionary approach is proposed for solving the objectives of makespan, energy consumption, and increased service utilization rate, interoperability, and reliability. To execute the approach initially, text-mining-based supervised machine-learning models, namely Decision Tree, Naïve Bayes, Random Forest, and Support Vector Machines (SVM) were adopted for the classification of suppliers into task-specific suppliers. Following this, with the identified suppliers as input, the problem was formulated as a multi-objective Mixed-Integer Linear Programming (MILP) model. We then proposed a Hybrid Multi-Objective Moth Flame Optimization algorithm (HMFO) to optimize process planning and scheduling functions. Numerical experiments have been carried out with the formulated problem for 10 different instances, along with a comparison of the results with a Non-Dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the feasibility of the approach.
Veera Ramakurthi; V. Manupati; José Machado; Leonilde Varela. A Hybrid Multi-Objective Evolutionary Algorithm-Based Semantic Foundation for Sustainable Distributed Manufacturing Systems. Applied Sciences 2021, 11, 6314 .
AMA StyleVeera Ramakurthi, V. Manupati, José Machado, Leonilde Varela. A Hybrid Multi-Objective Evolutionary Algorithm-Based Semantic Foundation for Sustainable Distributed Manufacturing Systems. Applied Sciences. 2021; 11 (14):6314.
Chicago/Turabian StyleVeera Ramakurthi; V. Manupati; José Machado; Leonilde Varela. 2021. "A Hybrid Multi-Objective Evolutionary Algorithm-Based Semantic Foundation for Sustainable Distributed Manufacturing Systems." Applied Sciences 11, no. 14: 6314.
Due to pressing demand for the quality of care and to maximize the patient satisfaction, traditional scheduling may not cater the needs of patient’s accessibility for mitigating the patient tardiness and social effects. This paper addresses, patient appointment scheduling problem (PASP) in a radiology department in southern India, as a case study. Due to partial precedence constraints between different modalities, the problem is formulated as a static, multi-stage/multi-server system. We proposed a novel social network analysis (SNA) based approach to examine the relationship between identified modalities and their influence with different examination type. To validate the results of SNA model, in a real time environment a simulation analysis is carried out by using FlexSim Healthcare software. Based on the empirical data collected from the radiology department, comparisons between the present condition of the department and the achieved results from proposed approach is performed through discrete event simulation model. The results indicate that the proposed approach has proved its effectiveness on the system performance by reducing the average total completion time of the system by 5% and 38% in patients waiting time.
Veera Babu Ramakurthi; Vijayakumar Manupati; Suraj Panigrahi; M. L. R. Varela; Goran Putnik; P. S. C. Bose. Modelling, Analysis and Simulation of a Patient Admission Problem: A Social Network Approach. Advances in Intelligent Systems and Computing 2020, 41 -51.
AMA StyleVeera Babu Ramakurthi, Vijayakumar Manupati, Suraj Panigrahi, M. L. R. Varela, Goran Putnik, P. S. C. Bose. Modelling, Analysis and Simulation of a Patient Admission Problem: A Social Network Approach. Advances in Intelligent Systems and Computing. 2020; ():41-51.
Chicago/Turabian StyleVeera Babu Ramakurthi; Vijayakumar Manupati; Suraj Panigrahi; M. L. R. Varela; Goran Putnik; P. S. C. Bose. 2020. "Modelling, Analysis and Simulation of a Patient Admission Problem: A Social Network Approach." Advances in Intelligent Systems and Computing , no. : 41-51.
Nowadays, sustainability has gained much attention from economists, environmentalists, consumers, industrialists, government and the academia. The regulatory policies for carbon emissions force the firms to redesign its supply chain. In this paper, different production-distribution and inventory problems in multi-echelon supply chain were critically investigated with three carbon policies (carbon tax, strict carbon capping and carbon cap-and-trade) and lead-time considerations. Then, a non-linear mixed-integer programming based mathematical model has been developed and tested with the proposed heuristic. The obtained results demonstrate the robust performance of the proposed algorithm that can further help the policy makers and experts for designing and evaluation of sustainable supply chain.
V.K. Manupati; Sivakumar Jane Jedidah; Shreya Gupta; Aditi Bhandari; M. Ramkumar. Optimization of a multi-echelon sustainable production-distribution supply chain system with lead time consideration under carbon emission policies. Computers & Industrial Engineering 2018, 135, 1312 -1323.
AMA StyleV.K. Manupati, Sivakumar Jane Jedidah, Shreya Gupta, Aditi Bhandari, M. Ramkumar. Optimization of a multi-echelon sustainable production-distribution supply chain system with lead time consideration under carbon emission policies. Computers & Industrial Engineering. 2018; 135 ():1312-1323.
Chicago/Turabian StyleV.K. Manupati; Sivakumar Jane Jedidah; Shreya Gupta; Aditi Bhandari; M. Ramkumar. 2018. "Optimization of a multi-echelon sustainable production-distribution supply chain system with lead time consideration under carbon emission policies." Computers & Industrial Engineering 135, no. : 1312-1323.
Technology adoption play significant role for good healthcare services. It is very important to understand and identify the requirements and perceptions of hospital employees for the implementation of technology in their work place. This study determines the impact of performance expectancy, effort expectancy and social influence on behavioural intention as well as the impact of facilitating conditions on technical/clinical staff’s perspective. The structured questionnaire is administered to 770 clinical staffs on the usage of telemedicine and electronic health records in hospitals. A valid sample of 568 was returned back for further analysis. Regression analysis using AMOS 20 is performed to examine the effect of the constructs. Findings revealed that performance expectancy, effort expectancy, and social influence have a significant impact on behavioural intention and facilitating condition also significantly impacts behavioural intention which in turn impacts usage behaviour of electronic health records and telemedicine. The limitations and future research are suggested and delineated.
P. Venugopal; S. Aswini Priya; V. K. Manupati; M. L. R. Varela; J. Machado; G. D. Putnik. Impact of UTAUT Predictors on the Intention and Usage of Electronic Health Records and Telemedicine from the Perspective of Clinical Staffs. Lecture Notes in Electrical Engineering 2018, 172 -177.
AMA StyleP. Venugopal, S. Aswini Priya, V. K. Manupati, M. L. R. Varela, J. Machado, G. D. Putnik. Impact of UTAUT Predictors on the Intention and Usage of Electronic Health Records and Telemedicine from the Perspective of Clinical Staffs. Lecture Notes in Electrical Engineering. 2018; ():172-177.
Chicago/Turabian StyleP. Venugopal; S. Aswini Priya; V. K. Manupati; M. L. R. Varela; J. Machado; G. D. Putnik. 2018. "Impact of UTAUT Predictors on the Intention and Usage of Electronic Health Records and Telemedicine from the Perspective of Clinical Staffs." Lecture Notes in Electrical Engineering , no. : 172-177.
With the expeditious growth of unstructured massive data on the World Wide Web (WWW), more advanced tools, techniques, methods, and approaches for information organization and retrieval are desired. Text mining is one such approach to achieve the above mentioned demand. One of the main text mining applications is how to classify data presented by different industries into groups. In this paper, the classification of data into various groups based on the choice of the users at any given point of time is proposed. Here, a support vector machine (SVM) based classification algorithm is established to classify the text data into two broad categories of Manufacturing and Non-Manufacturing suppliers. Later, the performance of the proposed classifier was tested experimentally using most commonly used accuracy measures such as precision, recall, and F-measure. Results proved the efficiency of the proposed approach for classification of the texts.
V. K. Manupati; M. D. Akhtar; M. L. R. Varela; G. D. Putnik; J. Trojanowska; J. Machado. A Text Mining Based Supervised Learning Algorithm for Classification of Manufacturing Suppliers. Advances in Intelligent Systems and Computing 2018, 236 -244.
AMA StyleV. K. Manupati, M. D. Akhtar, M. L. R. Varela, G. D. Putnik, J. Trojanowska, J. Machado. A Text Mining Based Supervised Learning Algorithm for Classification of Manufacturing Suppliers. Advances in Intelligent Systems and Computing. 2018; ():236-244.
Chicago/Turabian StyleV. K. Manupati; M. D. Akhtar; M. L. R. Varela; G. D. Putnik; J. Trojanowska; J. Machado. 2018. "A Text Mining Based Supervised Learning Algorithm for Classification of Manufacturing Suppliers." Advances in Intelligent Systems and Computing , no. : 236-244.
With the recent development of weblogs and social networks, many supplier industries share their data on different websites and weblogs. Even the Small-to-Medium sized enterprises (SMEs) in the manufacturing sector (as well as non-manufacturing sector) are rapidly strengthening their web presence in order to improve their visibility, customer reachability and remain competitive in the global market. Our study aims to classify data into various groups so that users can identify the most appropriate content based on their choice at any given time. To classify and characterize manufacturing suppliers in supply chain through their capability narratives and textual portfolios obtained from websites of such suppliers online source portals for testing and Naïve Bayes and support vector machine (SVM) Classification method at term-level for classification has been used. The performance of the proposed classifier was tested experimentally based on the standard metrics such as precision, recall, and F-measure.
M. D. Akhtar; V. K. Manupati; M. L. R. Varela; G. D. Putnik; A. M. Madureira; Ajith Abraham. Manufacturing Services Classification in a Decentralized Supply Chain Using Text Mining. Advances in Intelligent Systems and Computing 2018, 186 -193.
AMA StyleM. D. Akhtar, V. K. Manupati, M. L. R. Varela, G. D. Putnik, A. M. Madureira, Ajith Abraham. Manufacturing Services Classification in a Decentralized Supply Chain Using Text Mining. Advances in Intelligent Systems and Computing. 2018; ():186-193.
Chicago/Turabian StyleM. D. Akhtar; V. K. Manupati; M. L. R. Varela; G. D. Putnik; A. M. Madureira; Ajith Abraham. 2018. "Manufacturing Services Classification in a Decentralized Supply Chain Using Text Mining." Advances in Intelligent Systems and Computing , no. : 186-193.
M.B.S. Sreekara Reddy; Ch. Ratnam; G. Rajyalakshmi; V.K. Manupati. An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem. Measurement 2018, 114, 78 -90.
AMA StyleM.B.S. Sreekara Reddy, Ch. Ratnam, G. Rajyalakshmi, V.K. Manupati. An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem. Measurement. 2018; 114 ():78-90.
Chicago/Turabian StyleM.B.S. Sreekara Reddy; Ch. Ratnam; G. Rajyalakshmi; V.K. Manupati. 2018. "An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem." Measurement 114, no. : 78-90.
M.B.S. Sreekara Reddy; C.H. Ratnam; Rajeev Agrawal; Maria Leonilde Varela; Ila Sharma; V.K. Manupati. Investigation of reconfiguration effect on makespan with social network method for flexible job shop scheduling problem. Computers & Industrial Engineering 2017, 110, 231 -241.
AMA StyleM.B.S. Sreekara Reddy, C.H. Ratnam, Rajeev Agrawal, Maria Leonilde Varela, Ila Sharma, V.K. Manupati. Investigation of reconfiguration effect on makespan with social network method for flexible job shop scheduling problem. Computers & Industrial Engineering. 2017; 110 ():231-241.
Chicago/Turabian StyleM.B.S. Sreekara Reddy; C.H. Ratnam; Rajeev Agrawal; Maria Leonilde Varela; Ila Sharma; V.K. Manupati. 2017. "Investigation of reconfiguration effect on makespan with social network method for flexible job shop scheduling problem." Computers & Industrial Engineering 110, no. : 231-241.
Online shopping is nowadays is a highly frequent action but there are several critical factors that have to be considered for enabling websites and platforms to be able to offer all necessary requisites for guaranteeing user friendly, secure and also enjoyable shopping experiences to clients, offering them exactly what they expect to buy, and quickly find, among a huge offer available online. In this paper, a set of considered critical success factors are analysed on a set of top ranked websites, about luxurious furniture, to understand to what extent these critical factors are satisfied. The results can be taken into consideration for implementing a successful business through e-commerce from herein analysed perspectives.
Maria Leonilde Varela; Goran Putnik; Maria Carvalho; Luís Ferreira; Maria Manuela Cruz-Cunha; V. K. Manupati; K. Manoj. Analysing Critical Success Factors for Supporting Online Shopping. International Journal of Web Portals 2017, 9, 1 -19.
AMA StyleMaria Leonilde Varela, Goran Putnik, Maria Carvalho, Luís Ferreira, Maria Manuela Cruz-Cunha, V. K. Manupati, K. Manoj. Analysing Critical Success Factors for Supporting Online Shopping. International Journal of Web Portals. 2017; 9 (2):1-19.
Chicago/Turabian StyleMaria Leonilde Varela; Goran Putnik; Maria Carvalho; Luís Ferreira; Maria Manuela Cruz-Cunha; V. K. Manupati; K. Manoj. 2017. "Analysing Critical Success Factors for Supporting Online Shopping." International Journal of Web Portals 9, no. 2: 1-19.
V. K. Manupati; P. K. C. Kanigalpula; M. L. R. Varela; Goran D. Putnik; A. F. Araújo; G. G. Vieira; Álvaro Rocha; Luís Paulo Reis. Web-Based Decision System for Distributed Process Planning in a Networked Manufacturing Environment. Artificial Intelligence: Foundations, Theory, and Algorithms 2017, 718, 111 -118.
AMA StyleV. K. Manupati, P. K. C. Kanigalpula, M. L. R. Varela, Goran D. Putnik, A. F. Araújo, G. G. Vieira, Álvaro Rocha, Luís Paulo Reis. Web-Based Decision System for Distributed Process Planning in a Networked Manufacturing Environment. Artificial Intelligence: Foundations, Theory, and Algorithms. 2017; 718 ():111-118.
Chicago/Turabian StyleV. K. Manupati; P. K. C. Kanigalpula; M. L. R. Varela; Goran D. Putnik; A. F. Araújo; G. G. Vieira; Álvaro Rocha; Luís Paulo Reis. 2017. "Web-Based Decision System for Distributed Process Planning in a Networked Manufacturing Environment." Artificial Intelligence: Foundations, Theory, and Algorithms 718, no. : 111-118.
This paper addresses a fuzzy mixed-integer non-linear programming (FMINLP) model by considering machine-dependent and job-sequence-dependent set-up times that minimize the total completion time, the number of tardy jobs, the total flow time and the machine load variation in the context of unrelated parallel machine scheduling (UPMS) problem. The above-mentioned multi-objectives were considered based on non-zero ready times, machine- and sequence-dependent set-up times and secondary resource constraints for jobs. The proposed approach considers unrelated parallel machines with inherent uncertainty in processing times and due dates. Since the problem is shown to be NP-hard in nature, it is a challenging task to find the optimal/near-optimal solutions for conflicting objectives simultaneously in a reasonable time. Therefore, we introduced a new multi-objective-based evolutionary artificial immune non-dominated sorting genetic algorithm (AI-NSGA-II) to resolve the above-mentioned complex problem. The performance of the proposed multi-objective AI-NSGA-II algorithm has been compared to that of multi-objective particle swarm optimization (MOPSO) and conventional non-dominated sorting genetic algorithm (CNSGA-II), and it is found that the proposed multi-objective-based hybrid meta-heuristic produces high-quality solutions. Finally, the results obtained from benchmark instances and randomly generated instances as test problems evince the robust performance of the proposed multi-objective algorithm.
V K Manupati; G Rajyalakshmi; Felix T S Chan; J J Thakkar. A hybrid multi-objective evolutionary algorithm approach for handling sequence- and machine-dependent set-up times in unrelated parallel machine scheduling problem. Sādhanā 2017, 42, 391 -403.
AMA StyleV K Manupati, G Rajyalakshmi, Felix T S Chan, J J Thakkar. A hybrid multi-objective evolutionary algorithm approach for handling sequence- and machine-dependent set-up times in unrelated parallel machine scheduling problem. Sādhanā. 2017; 42 (3):391-403.
Chicago/Turabian StyleV K Manupati; G Rajyalakshmi; Felix T S Chan; J J Thakkar. 2017. "A hybrid multi-objective evolutionary algorithm approach for handling sequence- and machine-dependent set-up times in unrelated parallel machine scheduling problem." Sādhanā 42, no. 3: 391-403.
Effective and efficient implementation of intelligent and recently emerged networked manufacturing systems requires enterprise-level integration. The first step in this direction is to integrate the manufacturing functions such as process planning and scheduling for multi-jobs in order to generate optimal or near optimal solutions. Addressed in this paper is multi-objective optimisation in the context of a network-based manufacturing system to optimise multiple objectives, i.e. minimisation of makespan and minimisation of variation of workload, simultaneously. This paper introduces a mathematical model for calculating the above-mentioned objectives with consideration of alternative machines, as well as tools and tool approach directions. The authors propose a new modified block-based genetic algorithm (MBBGA) and modified non-dominated sorting genetic algorithm (MNSGA-II) to resolve the above-mentioned complex problem and compare the proposed algorithms’ performance and their effectiveness with the non-dominated sorting genetic algorithm (NSGA-II). An illustrative example with complex scenarios is carried out to demonstrate the feasibility of the proposed MBBGA and MNSGA-II. The experimental results presented show that the proposed algorithms perform better in comparison with NSGA-II.
V.K. Manupati; P.C. Chang; M.K. Tiwari. Intelligent search techniques for network-based manufacturing systems: multi-objective formulation and solutions. International Journal of Computer Integrated Manufacturing 2016, 29, 1 -20.
AMA StyleV.K. Manupati, P.C. Chang, M.K. Tiwari. Intelligent search techniques for network-based manufacturing systems: multi-objective formulation and solutions. International Journal of Computer Integrated Manufacturing. 2016; 29 (8):1-20.
Chicago/Turabian StyleV.K. Manupati; P.C. Chang; M.K. Tiwari. 2016. "Intelligent search techniques for network-based manufacturing systems: multi-objective formulation and solutions." International Journal of Computer Integrated Manufacturing 29, no. 8: 1-20.
In a wafer fabrication facility, automated material handling system (AMHS) to dispatch the material flow is a critical and challenging task. This paper investigates the integrated delivery of automated material handling system (AMHS) and processing tools for a large-scale complex wafer fabrication facility. Although the dispatching rules are one of the most frequently used approach for effective semiconductor manufacturing schedule, it is necessary to adapt new techniques due to time-consuming nature of dispatching rules when the number of variables and iterations increases. There are very few studies on enhancing the rule-based scheduling system. To address this issue, we proposed an evolutionary algorithmic approach for enhancing the rule-based scheduling system. We explored the best possible genetic algorithm parameters from famous approach called Taguchi, and then, statistical analysis, i.e., regression analysis, has been conducted to find out the significance of the parameters. Later, with hierarchical rule-based scheduling approach, the combined sequential dispatching rules are formed to achieve better efficiency and effectiveness of the scheduling.
V. K. Manupati; A. S. Revanth; K. S. S. L. Srikanth; A. Maheedhar; M. B. S. Sreekara Reddy. Real-Time Rule-Based Scheduling System for Integrated Delivery in a Semiconductor Manufacturing Using Evolutionary Algorithm-Based Simulation Approach. Advances in Intelligent Systems and Computing 2016, 981 -989.
AMA StyleV. K. Manupati, A. S. Revanth, K. S. S. L. Srikanth, A. Maheedhar, M. B. S. Sreekara Reddy. Real-Time Rule-Based Scheduling System for Integrated Delivery in a Semiconductor Manufacturing Using Evolutionary Algorithm-Based Simulation Approach. Advances in Intelligent Systems and Computing. 2016; ():981-989.
Chicago/Turabian StyleV. K. Manupati; A. S. Revanth; K. S. S. L. Srikanth; A. Maheedhar; M. B. S. Sreekara Reddy. 2016. "Real-Time Rule-Based Scheduling System for Integrated Delivery in a Semiconductor Manufacturing Using Evolutionary Algorithm-Based Simulation Approach." Advances in Intelligent Systems and Computing , no. : 981-989.
The network-based manufacturing offers various advantages in current competitive atmosphere by way to reduce the short manufacturing cycle time and to maintain the production flexibility. In this paper, a multi-objective problem whose objectives are to minimize the makespan and maximize the machine utilization for generating feasible process plans of multiple jobs in the context of network-based manufacturing system has been addressed. A mobile agent-based negotiation approach is proposed to the integration of manufacturing functions in a distributed manner, and the fundamental framework to support the functionality of the approach is presented in detail. With the help of an illustrative example along with varied production, environments that include production demand fluctuations are described, and the proposed approach has been validated. Finally, the computational results are analyzed to the benefit of the manufacturer.
Vijaya Kumar Manupati; S. N. Dwivedi; Manoj Kumar Tiwari. Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile-Agent Based Approach Mobile-agent. Handbook of Manufacturing Engineering and Technology 2014, 3475 -3485.
AMA StyleVijaya Kumar Manupati, S. N. Dwivedi, Manoj Kumar Tiwari. Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile-Agent Based Approach Mobile-agent. Handbook of Manufacturing Engineering and Technology. 2014; ():3475-3485.
Chicago/Turabian StyleVijaya Kumar Manupati; S. N. Dwivedi; Manoj Kumar Tiwari. 2014. "Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile-Agent Based Approach Mobile-agent." Handbook of Manufacturing Engineering and Technology , no. : 3475-3485.
This paper seeks to address an approach called the social network analysis method (SNAM) to evaluate the effect of resource scalability on networked manufacturing system. Considering the case of networked manufacturing mode, we have proposed a framework of SNAM for generating the collaborative networks. The collaborative networks have been obtained by transferring the input data in the form of an affiliation matrix to the UCINET and Netdraw software packages. Subsequently, we have conducted various tests to analyze the collaborative networks for finding the network structure, size, complexity and its functional properties. In this paper, a social network based greedy k-plex algorithm has been applied to evaluate the scalability effect on different data sets of networked manufacturing system. Experimental studies have been conducted and comparisons have been made to demonstrate the efficiency of the proposed approach.
Vijaya Kumar Manupati; Goran Putnik; Manoj Kumar Tiwari. Resource Scalability in Networked Manufacturing System: Social Network Analysis Social network analysis Based Approach. Handbook of Manufacturing Engineering and Technology 2014, 3439 -3450.
AMA StyleVijaya Kumar Manupati, Goran Putnik, Manoj Kumar Tiwari. Resource Scalability in Networked Manufacturing System: Social Network Analysis Social network analysis Based Approach. Handbook of Manufacturing Engineering and Technology. 2014; ():3439-3450.
Chicago/Turabian StyleVijaya Kumar Manupati; Goran Putnik; Manoj Kumar Tiwari. 2014. "Resource Scalability in Networked Manufacturing System: Social Network Analysis Social network analysis Based Approach." Handbook of Manufacturing Engineering and Technology , no. : 3439-3450.
The network-based manufacturing offers various advantages in current competitive atmosphere by way to reduce the short manufacturing cycle time and to maintain the production flexibility. In this paper, a multi-objective problem whose objectives are to minimize the makespan and maximize the machine utilization for generating feasible process plans of multiple jobs in the context of network-based manufacturing system has been addressed. A mobile agent-based negotiation approach is proposed to the integration of manufacturing functions in a distributed manner, and the fundamental framework to support the functionality of the approach is presented in detail. With the help of an illustrative example along with varied production, environments that include production demand fluctuations are described, and the proposed approach has been validated. Finally, the computational results are analyzed to the benefit of the manufacturer.
V. K. Manupati; S. N. Dwivedi; M. K. Tiwari. Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile Agent-Based Approach. Handbook of Manufacturing Engineering and Technology 2014, 1 -11.
AMA StyleV. K. Manupati, S. N. Dwivedi, M. K. Tiwari. Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile Agent-Based Approach. Handbook of Manufacturing Engineering and Technology. 2014; ():1-11.
Chicago/Turabian StyleV. K. Manupati; S. N. Dwivedi; M. K. Tiwari. 2014. "Process Plan and Scheduling Integration for Networked Manufacturing Using Mobile Agent-Based Approach." Handbook of Manufacturing Engineering and Technology , no. : 1-11.
This paper seeks to address an approach called the social network analysis method (SNAM) to evaluate the effect of resource scalability on networked manufacturing system. Considering the case of networked manufacturing mode, we have proposed a framework of SNAM for generating the collaborative networks. The collaborative networks have been obtained by transferring the input data in the form of an affiliation matrix to the UCINET and Netdraw software packages. Subsequently, we have conducted various tests to analyze the collaborative networks for finding the network structure, size, complexity and its functional properties. In this paper, a social network based greedy k-plex algorithm has been applied to evaluate the scalability effect on different data sets of networked manufacturing system. Experimental studies have been conducted and comparisons have been made to demonstrate the efficiency of the proposed approach.
Vijaya Kumar Manupati; Goran Putnik; Manoj Kumar Tiwari. Resource Scalability in Networked Manufacturing System: Social Network Analysis Based Approach. Handbook of Manufacturing Engineering and Technology 2013, 1 -11.
AMA StyleVijaya Kumar Manupati, Goran Putnik, Manoj Kumar Tiwari. Resource Scalability in Networked Manufacturing System: Social Network Analysis Based Approach. Handbook of Manufacturing Engineering and Technology. 2013; ():1-11.
Chicago/Turabian StyleVijaya Kumar Manupati; Goran Putnik; Manoj Kumar Tiwari. 2013. "Resource Scalability in Networked Manufacturing System: Social Network Analysis Based Approach." Handbook of Manufacturing Engineering and Technology , no. : 1-11.
Real-time adaptive production control in the flexible manufacturing cell (FMC) is a complex issue that needs to be addressed to realize good performance and high productivity. In this paper, we have considered a support vector machine (SVM)-based simulation approach to resolve a production control problem in an FMC that operates in a dynamic environment. A SVM-based simulation approach chooses the most relevant scheduling rule out of several predefined ones on the basis of the current states of the system. This paper examines and compares the performance of the SVM-based simulation approach with the competent scheduling rules under two different operational environments which are characterized by the uncertainty of demand. We have also developed a Visual Basic-based simulation approach for scheduling of component parts in the context of FMC under different situations. The SVM methodology to control the production offers better performance than the single-rule-based production control system.
V. K. Manupati; Rohit Anand; J. J. Thakkar; Lyes Benyoucef; Fausto P. Garsia; M. K. Tiwari. Adaptive production control system for a flexible manufacturing cell using support vector machine-based approach. The International Journal of Advanced Manufacturing Technology 2012, 67, 969 -981.
AMA StyleV. K. Manupati, Rohit Anand, J. J. Thakkar, Lyes Benyoucef, Fausto P. Garsia, M. K. Tiwari. Adaptive production control system for a flexible manufacturing cell using support vector machine-based approach. The International Journal of Advanced Manufacturing Technology. 2012; 67 (1-4):969-981.
Chicago/Turabian StyleV. K. Manupati; Rohit Anand; J. J. Thakkar; Lyes Benyoucef; Fausto P. Garsia; M. K. Tiwari. 2012. "Adaptive production control system for a flexible manufacturing cell using support vector machine-based approach." The International Journal of Advanced Manufacturing Technology 67, no. 1-4: 969-981.
The networked based manufacturing offers various advantages in current competitive atmosphere by way to reduce the short manufacturing cycle time and to maintain the production flexibility. In this paper, we have addressed a multi-objective problem whose objectives are to minimize the makespan and maximization of machine utilization for generating feasible process plans of multiple jobs in the context of networked based manufacturing system. In more specific, with two powerful multi-objective evolutionary algorithms (MOEAs) namely controlled elitist-NSGA-II (CE-NSGA-II), and territory defining evolutionary algorithm (TDEA), were proposed to find the better performance of the system. With the help of an illustrative example along with two complex scenarios these algorithms has been implemented, tested and compared. Finally, the computational results are analyzed to the benefit of the manufacturer.
V. K. Manupati; J. J. Thakkar; Priyabrata Mohapatra; Ajay Kumar; M. K. Tiwari. Process Plan and Scheduling Integration for Near Optimal Process Plans in Networked Based Manufacturing Using Controlled Elitist NSGA-II and Territory Defining Algorithms. Computer Vision 2012, 7677, 754 -760.
AMA StyleV. K. Manupati, J. J. Thakkar, Priyabrata Mohapatra, Ajay Kumar, M. K. Tiwari. Process Plan and Scheduling Integration for Near Optimal Process Plans in Networked Based Manufacturing Using Controlled Elitist NSGA-II and Territory Defining Algorithms. Computer Vision. 2012; 7677 ():754-760.
Chicago/Turabian StyleV. K. Manupati; J. J. Thakkar; Priyabrata Mohapatra; Ajay Kumar; M. K. Tiwari. 2012. "Process Plan and Scheduling Integration for Near Optimal Process Plans in Networked Based Manufacturing Using Controlled Elitist NSGA-II and Territory Defining Algorithms." Computer Vision 7677, no. : 754-760.