Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Goyal, Sanjeev
- Benchmarking Practice for Identification of Internal Supply Chain Management Performance Factors Gap
Abstract Views :195 |
PDF Views:0
Authors
Affiliations
1 Mechanical Engineering, YMCAUST, Faridabad, Haryana, IN
1 Mechanical Engineering, YMCAUST, Faridabad, Haryana, IN
Source
Journal of Supply Chain Management Systems, Vol 6, No 4 (2017), Pagination: 33-38Abstract
The present study deals with summarizing and analysing the current challenges of internal supply chain management in the Indian manufacturing world. Benchmarking practice for internal supply chain management performance factors may be fruitful to overcome supply chain challenges. The main purpose of this research work is to implement the benchmarking practice in internal supply chain performance factors for the identification of gap between them. Internal supply chain management consists of purchase, production, and distribution units between suppliers and customers. Proper coordination between departments is necessary for efficient working of internal supply chain of manufacturing industry. In this research work, the main objective of the authors are to extract internal supply chain factors through history of literature and prepared mean scorecard on the basis of industrial questionnaire survey results; to implement the regular comparative benchmarking practice in finding out performance gap between factors of intern al supply chain until and either the gap is under control or within the limits.Keywords
Benchmarking, Internal Supply Chain Management Elements, Challenges Environment, Industrial Questionnaire Survey and Mean Score Card.References
- Anderson, B. (1994). A benchmarking process model: The benchmarking wheel. Proceedings of the 10th International Conference of the Israel Society for Quality, Jerusalem.
- Bag, S. (2012). Review of supplier selection models: Key success factors and blueprint of supply chain excellence. Journal of Supply Chain Management Systems, 1(1), 56-62.
- Bag, S., Anand, N., & Pandey, K. K. (2014). A framework for the analysis of sustainable supply chain management: An insight from Indian rubber industry. Journal of Supply Chain Management Systems, 3(1), 68-83.
- Balm, G. J. (1996). Benchmarking and Gap analysis: what is the next milestone? Benchmarking for Quality Management and Technology, 3(4), 28-33.
- Bhagwat, R., & Sharma, M. K. (2007). Performance measurement of supply chain management using the analytical hierarchy process. Production Planning & Control, 18(8), 666-680.
- Camp, R. C. (1993). A bible for benchmarking, by Xerox, Financial Executive, 9(4), 23-27.
- Drozdowski, T. E. (1983). GTE uses benchmarking to measure purchasing. Purchasing, 94(6), 21-24.
- Cavenato, J. (1988). How to benchmark logistics operations. Distribution, 87(8), 93-96.
- Cetinkaya, S., Uster, H., Easwaran, G., & Keskin, B. B. (2009). An integrated outbound logistics model for frito-lay: Coordinating aggregate-level production and distribution decisions. Interfaces, 39(5), 460-475.
- Dubey, R. (2014). Supply chain and operations management journals: An overview and need for a new journal in supply chain management. Journal of Supply Chain Management Systems, 3(3), 1-5.
- Foster, T. A. (1992). Searching for the best. Distribution, 91(3), 30-36.
- Gawankar, S., Kamble, S.S., & Raut R. (2015). Performance measurement using balance score card and its applications: A review. Journal of Supply Chain Management Systems, 4(3), 6-21.
- Holloway, J., Francis, G., Hinton, M., & Mayle, D. (1998). Best practice benchmarking delivering the goods?. Total Quality Management, 9(4-5), 121-125.
- Kailash et al. (2017a). Benchmarking framework for internal supply chain management: A case study for comparative analysis. International Journal of Manufacturing Technology and Management, (in press).
- Kailash, Saha, R. K., & Goyal, S. (2017b). Systematic literature review of classification and categorisation of benchmarking in supply chain management. International Journal of Process Management and Benchmarking, 7(2), 183-205.
- Kumar, R., Singh, R. K., & Shankar, R. (2012). Supply chain management issues in an Indian SME: A SAP-LAP analysis. Journal of Supply Chain Management Systems, 1(2), 34-44.
- Le, S., M., & Dale, B. G. (1997). Benchmarking: A study in the supply and distribution of spare parts in a utility. Benchmarking for Quality Management and Technology, 4(3), 189-201.
- Matzko, M., & Wingfield, C. (1995), coming: A source of Competitive benchmarking for retail distribution strategy. Journal of Retail Banking, 17(2), 9-14.
- Nurizman, N. J., & Singla, V. (2017). Investigation of barriers and enablers of supply chain management practices success: Case of Ethiopian textile and garment factories. Journal of Supply Chain Management Systems, 6(2), 14-43.
- Pathak, S. (2016). Benchmarking supplier network collaboration. Journal of Supply Chain Management Systems, 5(1), 1-13.
- Purohit, H., & Kalla, N. (2017). Transforming the agro supply chains of India: The entrepreneurial way. Journal of Supply Chain Management Systems, 6(1), 1-6.
- Richardson, H. L. (1992). Improve quality through benchmarking. Transportation and Distribution, 33(l) 30-37.
- Saad, M., & Patel, B. (2006). An investigation of supply chain performance measurement in the Indian automotive sector. Benchmarking: An International Journal, 13(1/2), 36-53.
- Sharma, A., Garg, D., & Agarwal, A. (2012). Quality management in supply chains: The literature review. International Journal for Quality Research, 6(3), 193-206.
- Singh, S. C., & Pandey, S. K. (2013). Supply chain performance: A review of literature. Journal of Supply Chain Management Systems, 2(4), 1-12.
- Tan, X. C. (2011), Improved methods for production manufacturing processes in environmentally benign manufacturing. Energies, 4, 1391-1409.
- Tutcher, G. (1994). How successful companies can improve through internal benchmarking. Managing Service Quality, 4(2), 44-46.
- Ulusoy, G., & Ikiz, I. (2001). Benchmarking best manufacturing practices: A study into four sectors of Turkish industry. International Journal of Operations & Production Management, 21(7, 6), 1020-1043.
- Vig, S. N. (1995). Benchmarking: a select Bibliography. Productivity, 36(3), 521-524.
- Zairi, M., & Whymark, J. (2000). Transfer of best practices - How to build a culture of benchmarking and continuous learning: Part-II. Benchmarking: An International Journal, 7(2), 146-167.
- Parameter Optimization of Wire EDM Using Low Frequency Vibrations
Abstract Views :160 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, YMCA University of Science & Technology, Faridabad-121006, IN
1 Department of Mechanical Engineering, YMCA University of Science & Technology, Faridabad-121006, IN
Source
Invertis Journals of Science & Technology, Vol 8, No 3 (2015), Pagination: 119-124Abstract
Electrical Discharge Machining (EDM) is a non-contact machining process, which electrically removes material from any conductive workpiece. This is achieved by applying high frequency pulsed current to the workpiece through a tool electrode immersed in a dielectric fluid which subsequently melts and vaporizes the workpiece material. Unlike the traditional machining method, EDM offers many advantages, for instance, it can be used to machine very complex shape by using a simple tool electrode. In addition, the ease of machining in EDM process is only depending on the λ·θ·ρ theory, which is the product of thermal conductivity (λ), melting point (θ) and electrical resistivity (ρ) of workpiece material. As a product of electrical discharge, debris are created and accumulated in the sparking gap between the tool electrode and the workpiece. If the amounts of debris in the machining gap are too large, reduction of resistance occurs and encourages the formation of abnormal discharges, which leads to significant tool wear and slows down the material removal rate.Keywords
WEDM, Performance Parameter.- Critical Analysis of Performance Factor of Wire EDM Machine
Abstract Views :234 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, YMCA University of Science & Technology, Faridabad-121006, IN
1 Department of Mechanical Engineering, YMCA University of Science & Technology, Faridabad-121006, IN
Source
Invertis Journals of Science & Technology, Vol 8, No 3 (2015), Pagination: 132-138Abstract
The challenge of modern industries is mainly focused on the achievement of high quality, in terms of work dimensional accuracy, surface finish and higher MRR. Wire EDM machines are used to cut conductive metals of any hardness or that are difficult or impossible to cut with traditional methods. Wire EDM uses a very thin wire 0.02-0.03 mm in diameter as an electrode and machines a workpiece with electric discharge like a bandsaw by moving either workpiece or wire. The prominent feature of moving wire is that a complicated cut-out can be easily machined without using a forming electrode. This machining process is not limited by hardness, toughness and brittleness of the material and can produce intricate shape on any workpiece by suitable control over the physical parameters of the processes Machine tool industry has made exponential growth in its manufacturing capabilities in last decade but still machine tools are not utilized at their full potential. The main problem arrives in this process is the proper selection of parameters so as to utilize the process capability to full its potential. As in case of wire EDM, the limitation arises due to poor MRR and higher surface roughness which has attracted the attention of the researchers and practising engineers.Keywords
Wire EDM, Performance Parameter.- Integrity of Supplier and Distributor With Manufacturing Company in Supply Chain Management
Abstract Views :140 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, YMCAUST, Faridabad (Haryana), IN
1 Department of Mechanical Engineering, YMCAUST, Faridabad (Haryana), IN
Source
Invertis Journals of Science & Technology, Vol 8, No 2 (2015), Pagination: 95-100Abstract
Supplier selection represents one of the most important processes for an effective inventory management. Vendor selection is a complicated process. This process needs evaluation of multiple criteria and various constraints associated with them. The work represents the systematic identification of the important criteria for supplier selection process. In addition, the results exhibit the application of development of a decision model for evaluation and selection of suppliers with proposed AHP model, which by scoring the performance of suppliers is able to reduce the time taken to select a vendor. This paper is about providing the service to the customers in the material distribution system with the help of supply chain management and an investigation base for further research. Supplier and Distributor both are playing the significant role for enhancing manufacturing supply chain performance. The supply chain manager should identify the criticality of distributors and supplier in manufacturing supply chain management and understand the impact of each critical Success Factor on effective supply chain management. Therefore, a complete and structured methodology is proposed for analysing CSFs in manufacturing supply chain management. The application of decision framework has been demonstrated with an Indian case situation. Findings demonstrate that the decision framework can be useful to all manufacturing firms for prioritizing CSFs of supply chain management.Keywords
Supply Chain Management, Vendor Selection, Analytical Hierarchy Process, Supplier Evaluation, Critical Success Factors.- Factors Analysis of ISCM Benchmarking using DEMATEL Technique
Abstract Views :278 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, YMCAUST, Faridabad, Haryana, IN
1 Department of Mechanical Engineering, YMCAUST, Faridabad, Haryana, IN
Source
Journal of Supply Chain Management Systems, Vol 8, No 1 (2019), Pagination: 1-14Abstract
The present competitive scenario requires high degree of sophistication in the benchmarking practice that helps to improve the performance of internal supply chain management (ISCM) of any organization. Thus, it is necessary to analyze effectively the factors of ISCM benchmarking. The present study deals with the identification of factors of ISCM using literature survey. The influence between the identified factors was evaluated through brainstorming as well as decision making trial and evaluation laboratory [DEMATEL] technique. The internal assessment of factors is decided on the basis of 5 point rating scale, where 0 point indicates less influence of factor, while 5 point indicates high influence of factor. The main goal of this research work is to perform factor’s analysis and finally classify them into cause and effects groups using DEMATEL technique. This research work might be fruitful for researchers as well as managers to identify those factors which are responsible for cause and effect of problem in any type of business.Keywords
DEMATEL Technique, Factor Analysis, Benchmarking Practice, ISCM, Matrix Calculator.References
- Amiri, M., Sadaghiyani, J., Payani, N., & Shafieezadeh, M. (2011). Developing a DEMATEL method to prioritize distribution centers in supply chain. Management Science Letters, 1(3), 279–288.
- Abdullah, H. (2009). Major challenges to the effective management of human resource training and development activities, The Journal of International Social Research, 2(8), 11–25.
- Abdul Adis, A. A., & Jublee, E. (2010). Market orientation and new product performance: The mediating role of product advantage. African Journal of Marketing Management, 2(5), 91–100.
- Al-kuhali, K., Zain, Z. M., & Hussein, M. I. (2012). Production planning of LCDs: Optimal Linear programming and sensitivity analysis. Industrial Engineering Letters, 2(9), 1–10.
- Anwar, R. S., & Ali, S. (2015). Economies of scale. International Interdisciplinary Journal of Scholarly Research, 1(1), 51–57.
- Angkiriwanga, R., Pujawana, N., & Santosaa, B. (2014). Managing uncertainty through supply chain flexibility: reactive vs. proactive approaches. Production & Manufacturing Research, 2(1), 50–70.
- Agboyi, M. R., Yeboah O., & Ackah, D. (2015). The impact of sourcing on the delivery of raw material. International Journal of Advanced Research in Computer Science and Software Engineering, 5(8), 108–122.
- Bhuiyan, N. (2011). A framework for successful new product development. Journal of Industrial Engineering and Management, 4(4), 746–770.
- Balogun, O. S. et al. (2012). Use of linear programming for optimal production in a production line in coca – cola bottling company, Ilorin. International Journal of Engineering Research and Applications, 2(5), 2004–2007.
- Bhutta, Khurrum, S., & Huq, F. (1999). Benchmarking Best practices, an integrated approach. Benchmarking: an International Journal, 6(3), 254–268.
- Bertelsen, S., & Nielsen, J. (1997). Just-in-Time Logistics in the Supply of Building Materials, Proceedings of the 1st International Conference on Construction Industry Development: Building the future Together, 9–11 December, Singapore.
- Bhuiyan, N. (2011). A framework for successful new product development. Journal of Industrial Engineering and Management, 4(4), 746–770.
- Chaghooshi, A. J., et al. (2012). Integration of fuzzy Shannon’s entropy with fuzzy TOPSIS for industrial robotic system selection. Journal of Industrial Engineering & Management, 5(1), 102–114.
- Chen, C. W., & Wong, V. (2012). Design and delivery of new product preannouncement messages. Journal of Marketing Theory & Practice, 20(2), 203–222.
- Cowling, P. (2002). Manufacturing and logistics, using real time information for effective dynamic scheduling. European Journal of Operational Research, 139(2), 230–244.
- Chen, X. (2010). Suggestions on effective corporate new employee orientation program for human resource specialists. Online Journal of Workforce Education and Development, 4(3), 1–11.
- Dangayach G. S., & Deshmukh S. G. (2006). An exploratory study of manufacturing strategy practices of machinery manufacturing companies in India. Omega, 34(3), 254–273.
- Eksioglua, B. et al (2009). The vehicle routing problem: A taxonomic review. Computers & Industrial Engineering, 57(4), 1472–1483.
- Fekete, M., & Hulvej, J. (2015). Production planning and production levelling. Comenius Management Review, 9(1), 41–52.
- Forza, C. (2002). Survey research in operations management: A process based perspectives. International Journal of Operations & Production Management, 22(2), 152–194.
- Foggin, J. H., Mentzer, J. T., & Monroe, C. L. (2004). A supply chain diagnostic tool. International Journal of Physical Distribution & Logistics Management, 34(10), 827–855.
- Fontela, E., & Gabus, A. (1976). The DEMATEL Observer. DEMATEL 1976 Report. Geneva: Battelle Geneva Research Centre.
- Gu, J., Goetschalckx, M., & Mcginnis, L. F. (2007). Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177(1), 1–21.
- Gunasekaran, A., & Ngai, E. W. T. (2004). Information systems in supply chain integration and management. European Journal of Operational Research, 159(2), 269–295.
- Goyal, T. M. (2012). Employment conditions in organised and unorganised retail: Implications for FDI Policy in India with Arpita Mukherjee. Journal of Business and Retail Management Research, 6(2), 26–37.
- Goyal, T. M. (2013). FDI in services sector in India. Foreign Trade Review, 48(3), 413–430.
- Gram, M. (2013). A systematic methodology to reduce losses in production with the balanced scorecard approach. Manufacturing Science and Technology, 1(1), 12–22.
- Grosso, M. G., & Shepherd, B. (2011). Air cargo transport in APEC: Regulation and effects on merchandise trade. Journal of Asian Economics, 22(3), 203–212.
- Goyal, T. M. (2013). FDI in Retail: Implications for India’s trade agreement with Arpita Mukherjee. Foreign Trade Review, 48(1), 143–151.
- Gogi, V. S., & Badarinarayana, K. S. (2016). Flexible Manufacturing Systems Scheduling: A Systematic Review. Bonfring International Journal of Industrial Engineering and Management Science, 6(3), 61–62.
- Grigore, S. D. (2007). Supply chain flexibility. Romanian Economic and Business Review, 2(1), 66–70.
- He, Y. T., & Down, D.G. (2009). On accommodating customer flexibility in service systems. INFOR Information Systems and Operational Research, 47(4), 2009.
- Hessami, Z. H., & Savoji, A. (2011). Risk management in supply chain management. International Journal of Economics and Management Sciences, 1(3), 60–72.
- Hanson, O. Y. (2015). Assessing the impact of efficient inventory management in on organization. International Journal of Advanced Research in Computer Science and Software Engineering, 5(8), 86–103.
- Imam, T., & Hassan, F. (2009). Linear programming and sensitivity analysis in production planning. International Journal of Computer Science and Network Security, 9(2), 456–465.
- Jayant, A., & Ghagra, H. S. (2013). Supply Chain Flexibility Configurations: Perspectives, Empirical Studies and Research Directions. International Journal of Supply Chain Management, 2(1), 21–29.
- Kaushal, A. et al. (2016). Flexible manufacturing system a modern approach to manufacturing technology. International Refereed Journal of Engineering and Science, 5(4), 16–23.
- Kailash, Saha, R. K., & Goyal, S. (2017a). Systematic literature review of classification and categorisation of benchmarking in supply chain management. International Journal of Process Management and Benchmarking, 7(2), 183–205.
- Kailash, Saha, R. K., & Goyal, S. (2017b). Benchmarking practice for identification of internal supply chain management performance factors gap. Journal of Supply Chain Management System (JSCMS), 6(4), 33–38.
- Kailash, Saha, R. K., & Goyal, S. (2017c), Performance indicators for benchmarking of internal supply chain management. World Academy of Science, Engineering and Technology, International Science Index 127, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(7), 1940–1944.
- Kailash, Saha, R. K., & Goyal, S. (2017d). Scope of Internal Supply Chain Management Benchmarking in Indian Manufacturing Industries. World Academy of Science, Engineering and Technology, International Science Index 126, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(6), 1638–1641.
- Kailash, Saha, R. K., & Goyal, S. (2017e). Benchmarking framework for internal supply chain management: A case study for comparative analysis. International Journal of Manufacturing Technology and Management, [In Press].
- Kailash, Saha, R. K., & Goyal, S. (2017f). Benchmarking Model to Analyse ISCM Performance of Selected Indian Manufacturing Industries using Fuzzy AHP Technique. International Journal of Industrial & System Engineering (IJISE), [Inderscience, Accepted].
- Kailash, Saha, R. K., & Goyal, S. (2015). Integrity of supplier and distributor with manufacturing company in supply chain management. Invertis Journal of Science & Technology, 8(2), 95–100.
- Kumar, P., Shankar, R., & Yadav, S. S. (2008). Flexibility in global supply chain: Modeling the enablers. Journal of Modelling in Management, 3(3), 277–297.
- Kotzab, H., Teller, C., Grant, D. B., & Sparks, L. (2011). Antecedents for the adoption and execution of supply chain management. Supply Chain Management: An International Journal, 16(4), 231–245.
- Kwateng, K. O., Manso, J. F., & Osei-Mensah, R. (2014). Outbound logistics management in manufacturing companies in Ghana. Review of Business and Finance Studies, 5(1), 83–92.
- Kumar, S., & Raj, T. (2016). Selection of material handling equipment for flexible manufacturing system using FAHP. International Journal of Recent advances in Mechanical Engineering, 5(1), 25–45.
- Kesavan, S. (2014). Volume flexibility in services: The costs and benefits of flexible labor resources. Management Science, 60(8), 1884-1906.
- Liu, X., & Sun, Y. (2011). Information flow management of vendor managed inventory system in automobile parts inbound logistics based on internet of things. Journal of Software, 6(7), 1374–1380.
- Lenin, K. (2015). A study on the air cargo logistics operations in Dubai. Management, 4(5), 313–315.
- Lin, Y., Li, W., Qiu, F., & Xu, H.(2012). Research on optimization of vehicle routing problem for ride-sharing Taxi. Procedia - Social and Behavioral Sciences, 43, 494–502.
- Lee, Y.-C. Hsieh, Y.-F., & Guo, Y.-B. (2013). Construct DTPB model by using DEMATEL: A study of a university library website. Program: Electronic Library and Information Systems, 47(2), 155–169.
- Murthy, D. N. P. (2006). Product warranty and reliability. Annals of Operations Research, 143(1), 133–146.
- Meehan, J., & Muir, L. (2008). SCM in Merseyside SMEs: Benefits and barriers. The TQM Journal, 20(3), 223–232.
- Matias, J. C. D. O., & Coelho, D. A. (2002). The integration of the standards systems of quality management, environmental management and occupational health and safety management. International Journal of Production Research, 40(15), 3857–3866.
- Murthy, D. N. P. (2007). Product reliability and warranty: an overview and future research. Production, 17(3), 426–434.
- Maleki, R. A., & Reimche, J. (2011). Managing Returnable Containers Logistics - A Case Study Part I - Physical and Information Flow Analysis. International Journal of Engineering Business Management, 3(2), 1–8.
- Neely, A, Gregory, M., & Platts, K. (1995). Performance measurement systems design: A literature review and research agenda. International Journal of Operations & Production Management, 15(4), 80–116.
- Commandeur, H. R., Pattikawa, L. H., & Verwaal, E. (2006). Understanding new product project performance. European Journal of Marketing, 40(11/12), 1178–1193.
- Pekgun, P., Griffin, P., & Keskinocak, P. (2008). Coordination of marketing and production for price and lead time decisions. IIE Transactions, 40(1), 12–30.
- Rushton, A., & Saw, R. (1992). A methodology for logistics strategy planning. The International Journal of Logistics Management, 3(1), 46–62.
- Rakicevic, Z., & Vujosevic, M. (2015). Focus forecasting in supply chain: The case study of fast moving consumer goods company in Serbia. Serbian Journal of Management, 10(1), 3–17.
- Rodrigue, J. P. (2006). Transportation and the geographical and functional integration of global production networks. Growth and Change, 37(4), 510–525.
- Ramaa, A., Subramanya, K. N., & Rangaswamy, T. M. (2012). Impact of warehouse management system in a supply chain. International Journal of Computer Applications, 54(1), 14–20.
- Singh, R. K., & Acharya, P. (2014). Identification and evaluation of supply chain flexibilities in Indian FMCG sector using DEMATEL. Global Journal of Flexible Systems Management, 15(2), 91–100.
- Shieh, J. I., Wu, H.-H., & Huang, K. K. (2010). A DEMATEL method in identifying key success factors of hospital service quality. Knowledge-Based Systems, 23(3), 277–282.
- Sadeh, E., Mousavi, L., & Sadeh, S. (2011). Presenting a framework to study linkages among TQM practices, supply chain management practices, and performance using Dematel technique. Australian Journal of Basic and Applied Sciences, 5(9), 885–890.
- Singh, R. K. (2011). Developing the framework for coordination in supply chain of SMEs. Business Process Management Journal, 17(4), 619–638.
- Shen, Y. C., et al. (2012). A novel multicriteria decisionmaking combining decision making trial and evaluation laboratory technique for technology evaluation. Foresight, 14(2), 139–153.
- Shaw, S., Grant, D. B., & Mangan, J. (2010). Developing environmental supply chain performance measures. Benchmarking: An International Journal, 17(3), 320–339.
- Stevenson, M., & Spring, M. (2009). Supply chain flexibility: An inter-firm empirical study. International Journal of Operations & Production Management, 29(9), 946–971.
- Singh, R. K., & Acharya, P. (2013). Supply chain flexibility: A frame work of research dimensions. Global Journal of Flexible Systems Management, 14(3), 157–166.
- Soon, Q. H., & Udin, Z. M. (2011). Supply chain management from the perspective of value chain flexibility: an exploratory study. Journal of Manufacturing Technology Management, 22(4), 506–526.
- Stefanovic, N., & Stefanovic, D. (2011). Supply chain performance measurement system based on scorecards and web portals. Computer Science & Information Systems, 8(1), 167–192.
- Stawowy, A., & Duda, J. (2012). Models and Algorithms for Production Planning and Scheduling in Foundries – Current State and Development Perspectives. Archives of Foundry Engineering, 12(2), 69–74.
- Sanchez, A. M., & Perez, M. (2005). Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681–700.
- Sadeh, E. et al. (2011). Presenting A Framework To Study Linkages Among Tqm Practices, Supply Chain Management Practices, And Performance Using Dematel Technique. Australian Journal of Basic and Applied Sciences, 5(9), 885–890.
- Svensson, G. (2002). A conceptual framework of vulnerability in firms inbound and outbound logistics flows. International Journal of Physical Distribution & Logistics Management, 32(2), 110–134.
- Senk, M. K. et al. (2010). Development of New Product/Process Development Procedure for SMEs. Organizacija, 43(2), 76–86.
- Scott, C., & Westbrook, R. (1991). New Strategic Tools for Supply Chain Management. International Journal of Physical Distribution & Logistics Management, 21(1), 23–33.
- Sheu, J. B. (2007). Challenges of emergency logistics management. Transportation Research Part E, 43(6), 655–659.
- Shieh, J. I., & Wu, H. H. (2016). Measures of consistency for DEMATEL method. Communications in Statistics Simulation and Computation, 45(3), 781–790.
- Tzeng, G.H. et al. (2007). Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, 32(4), 1028–1044.
- Tilokavichai, V. et al. (2012). Innovative logistics management under uncertainty using Markov model. Information and Knowledge Management, 2(5), 19–30.
- Tan, X.C., Wang, Y. Y., Gu, B. H., Mu, Z. K., & Yang, C. (2011). Improved methods for production manufacturing processes in environmentally benign manufacturing. Energies, 4(9), 1391–1409.
- Vemic, J. (2007). Employee training and development and the learning organization. Economics and Organization, 4(2), 209–216.
- Wei, P.-L., Huang, J.-H., Tzeng, G.-H., & Wu, S.-I. (2010). Causal modeling of web advertising effects by improving SEM based on DEMATEL technique. International Journal of Information Technology & Decision Making, 9(5), 799–829.
- Wu, H. H., Chen, H. K., & Shieh, J. I. (2010). Evaluating performance criteria of employment service outreach program personnel by DEMATEL method. Expert Systems with Applications, 37(7), 5219–5223.
- Wang, C. X., & Webster, S. (2007). Channel coordination for a supply chain with a risk-neutral manufacturer and a loss-averse retailer. Decision Sciences, 38(3), 361–389.
- Wu, H. H., & Tsai, Y. N. (2011). A DEMATEL method to evaluate the causal relations among the criteria in auto spare parts industry. Applied Mathematics and Computation, 218(5), 2334–2342.
- Wu, H. H., & Tsai, Y. N. (2012a). An integrated approach of AHP and DEMATEL methods in evaluating the criteria of auto spare parts industry. International Journal of Systems Science, 43(11), 2114–2124.
- Wu, W. (2008). Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems with Applications, 35(3), 828–835.
- Wang, Y. C. (2008). Evaluating flexibility on order quantity and delivery lead time for a supply chain system. International Journal of Systems Science, 39(12), 1193–1202.
- Yang, Y. P. O., Shieh, H.-M., Leu, J.-D., & Tzeng, G.-H. (2008). A novel hybrid MCDM model combined with DEMATEL and ANP with applications. International Journal Operational Research, 5(3), 160–168.
- Ranking of ISCM Benchmarking Factors using VIKOR Methodology
Abstract Views :265 |
PDF Views:1
Authors
Affiliations
1 PhD Research Scholar, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
2 Assistant Professor, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
3 Assistant Professor, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
1 PhD Research Scholar, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
2 Assistant Professor, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
3 Assistant Professor, Department of Mechanical Engineering, J. C. Bose University of Science & Technology, YMCA, Faridabad, Haryana, IN
Source
Journal of Supply Chain Management Systems, Vol 8, No 4 (2019), Pagination: 18-29Abstract
In a competitive environment, balancing of demand and supply is a typical challenge for an entrepreneur. The continuous internal supply chain benchmarking practice would be helpful in establishing a balance between demand and supply. In this research paper, authors have come across variable factors of internal supply chain management benchmarking through literature review. The identified factors are: Human Resources Orientation, Inbound logistics, Operational logistics, Outbound logistics, Economies of scale, Flexibility, Logistics strategies, New Product development system, Material follow up and Procurement, Production Operation Process, Production Programming, Quality System, Products delivery, Foreign trade and service management and Transport-Reception-Custom decision. The opinions of industrial experts are collected through 15 questionnaire surveys with rating point scales from 1 to 5. VIKOR methodology is used to distinguish factors’ performance gap and stimulate the scope of improvement. The main objective of authors is to establish factors’ ranking using VIKOR methodology, including the calculated weight of factors through the analytical hierarchy process technique.Keywords
Internal Supply Chain Management (ISCM), VIKOR Methodology, Factors Ranking, Analytical Hierarchy Process (AHP) Technique.References
- Abdullah, H. (2009). Major challenges to the effective management of human resource training and development activities. Journal of International Social Research, 2(8), 11-25.
- Adis, A. A. A., & Jublee, E. (2010). Market orientation and new product performance: The mediating role of product advantage. African Journal of Marketing Management, 2(5), 91-100.
- Agboyi, M. R., & Obiri-Yeboah, D. A. (2015). The impact of sourcing on the delivery of raw material. International Journal of Advanced Research in Computer Science and Software Engineering, 5(8), 108-122.
- Agrawal, J., Richardson, P. S., & Grimm, P. E. (1996). The relationship between warranty and product reliability. Journal of Consumer Affairs, 30(2), 421-443.
- Alad, A. H., & Deshpande, V. A. (2014). A review of various tools and techniques for lead time reduction. International Journal of Engineering Development and Research, 2(1), 1159-1164.
- Al-Kuhali, K., Zain, Z. M., & Hussein, M. I. (2012). Production planning of LCDS: Optimal linear programming and sensitivity analysis. Industrial Engineering Letters, 2(9) 1-10.
- Ambe, I. M., & Badenhorst-Weiss, J. A. (2011). An automotive supply chain model for a demand-driven environment. Journal of Transport and Supply Chain Management, 5(1), 1-22.
- Anwar, R. S., & Ali, S. (2015). Economies of scale. International Interdisciplinary Journal of Scholarly Research, 1(1), 51-57.
- Balogun, O. S., Jolayemi, E. T., Akingbade, T. J., & Muazu, H. G. (2012). Use of linear programming for optimal production in a production line in coca-cola bottling company, Ilorin. International Journal of Engineering Research and Applications, 2(5), 2004-2007.
- Banar, M., Kose, B. M., Ozkan, A., & Acar, I. P. (2007). Choosing a municipal landfill site by analytic network process. Environmental Geology, 52(4), 747-751.
- Batson, R. G., & McGough, K. D. (2007). A new direction in quality engineering: Supply chain quality modelling. International Journal of Production Research, 45(23), 5455-5464.
- Beach, R., Muhlemann, A. P., Price, D. H., Paterson, A., & Sharp, J. A. (2000). A review of manufacturing flexibility. European Journal of Operational Research, 122(1), 41-57.
- Bettayeb, B., Bassetto, S. J., & Sahnoun, M. (2014). Quality control planning to prevent excessive scrap production. Journal of Manufacturing Systems, 33(3), 400-411.
- Bhargava, M. G., & Chaitanya Kumar, J. D. (2015). State of art of usage of alternative materials in concrete. International Journal of Engineering Sciences & Management Research, 2(12), 32-37.
- Bhuiyan, N. (2011). A framework for successful new product development. Journal of Industrial Engineering and Management, 4(4), 746-770.
- Bil, M., Vodak, R., Kubecek, J., Bilova, M., & Sedonik, J. (2015). Evaluating road network damage caused by natural disasters in the Czech Republic between 1997 and 2010. Transportation Research Part A: Policy and Practice, 80, 90-103.
- Blanquart, C., & Burmeister, A. (2009). Evaluating the performance of freight transport: A service approach. European Transport Research Review, 1(3), 135-145.
- Celli, M. (2013). Determinants of economies of scale in large businesses - A survey on UE listed firms. American Journal of Industrial and Business Management, 3(3), 255-261.
- Cetinkaya, S., Uster, H., Easwaran, G., & Keskin, B. B. (2009). An integrated outbound logistics model for Frito-Lay: Coordinating aggregate-level production and distribution decisions. Interfaces, 39(5), 460-475.
- Charnsirisakskul, K., Griffin, P. M., & Keskinocak, P. (2004). Order selection and scheduling with lead time flexibility. IIE Transactions, 36(7), 697-707.
- Charnsirisakskul, K., Griffin, P. M., & Keskinocak, P. (2006). Pricing and scheduling decisions with lead time flexibility. European Journal of Operational Research, 171(1), 153-169.
- Chen, C. W., & Wong, V. (2012). Design and delivery of new product preannouncement messages. Journal of Marketing Theory & Practice, 20(2), 203-222.
- Chen, T. (2013). A systematic cycle time reduction procedure for enhancing the competitiveness and sustainability of a semiconductor manufacturer. Sustainability, 5(11), 4637-4652.
- Chod, J., Rudi, N., & Van Mieghem, J. A. (2012). Mix, time and volume flexibility: Valuation and corporate diversification. Review of Business and Economic Literature, 57(3), 262-282.
- Colledani, M., & Tolio, T. (2011). Integrated analysis of quality and production logistics performance in manufacturing lines. International Journal of Production Research, 49(2), 485-518.
- Chen, X. (2010). Suggestions on effective corporate new employee orientation program for human resource specialists. Online Journal of Workforce Education and Development, 4(3), 1-11.
- Cowling, P., & Johansson, M. (2002). Using real-time information for effective dynamic scheduling. European Journal of Operational Research, 139(2), 230-244.
- De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European Journal of Purchasing and Supply Management, 7(2), 75-89.
- Delarue, A., Van Hootegem, G., Procter, S., & Burridge, M. (2008). Teamworking and organizational performance: A review of survey-based research. International Journal of Management Reviews, 10(2), 127-148.
- Deng, H., Yeh, C. H., & Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963-973.
- Deshmukh, A. J., & Chaudhari, A. A. (2011). A review for supplier selection criteria and methods. In Technology Systems and Management (pp. 283-291). Springer, Berlin, Heidelberg.
- Dornhofer, M., Schroder, F., & Gunthner, W. A. (2016). Logistics performance measurement system for the automotive industry. Logistics Research, 9(1), 11-26.
- De Koster, R., Le-Duc, T., & Roodbergen, K. J. (2007). Design and control of warehouse order picking: A literature review. European Journal of Operational Research, 182(2), 481-501.
- Dubey, R., & Gunasekaran, A. (2016). The sustainable humanitarian supply chain design: Agility, adaptability and alignment. International Journal of Logistics Research and Applications, 19(1), 62-82.
- Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., & Childe, S. J. (2018a). Supply chain agility, adaptability and alignment: Empirical evidence from the Indian auto components industry. International Journal of Operations & Production Management, 38(1), 129-148.
- Ertogral, K., & Wu, S. D. (2000). Auction-theoretic coordination of production planning in the supply chain. IIE Transactions, 32(10), 931-940.
- Forslund, H., & Jonsson, P. (2010). Integrating the performance management process of on-time delivery with suppliers. International Journal of Logistics Research and Applications, 13(3), 225-241.
- Gram, M. (2013). A systematic methodology to reduce losses in production with the balanced scorecard approach. Manufacturing Science and Technology, 1(1), 12-22.
- Grigore, S. D. (2007). Supply chain flexibility. Romanian Economic and Business Review, 2(1), 66-70.
- Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21(1/2), 71-87.
- Guo, J., & Zhang, W. (2008, December). Selection of suppliers based on rough set theory and VIKOR algorithm. In International Symposium on Intelligent Information Technology Application Workshops (pp. 49-52). IEEE.
- Hallgren, M., & Olhager, J. (2009). Flexibility configurations: Empirical analysis of volume and product mix flexibility. Omega-International Journal of Management Science, 37(4), 746-756.
- Hanson, O., Ackah, D., & Agboyi, M. (2015). Assessing the impact of efficient inventory management in on organization. International Journal of Advanced Research in Computer Science and Software Engineering, 5(8), 86-103.
- He, Y. T., & Down, D. G. (2009). On accommodating customer flexibility in service systems. INFOR Information Systems and Operational Research, 47(4), 289-295.
- Hicks, D. A. (1997). Manager’s guide to supply chain and logistics problem-solving tools and techniques Part III: End user experiences. IIE Solutions, 29(11), 340-38.
- Jabnoun, N. (2002). Control processes for total quality management and quality assurance. Work Study, 51(4), 182-190.
- Jayant, A., & Ghagra, H. S. (2013). Supply chain flexibility configurations: Perspectives, empirical studies and research directions. International Journal of Supply Chain Management, 2(1), 21-29.
- Jovanovic, J. R., Milanovic, D. D., & Djukic, R. D. (2014). Manufacturing cycle time analysis and scheduling to optimise its duration. Strojniski Vestnik/Journal of Mechanical Engineering, 60(7-8), 512-524.
- Kailash, Saha, R. K., & Goyal, S. (2015). Integrity of supplier and distributor with manufacturing company in supply chain management. Invertis Journal of Science & Technology, 8(2), 95-100. ISSN: 0973-8940.
- Kailash, Saha, R. K., & Goyal, S. (2017a). Systematic literature review of classification and categorisation of benchmarking in supply chain management. International Journal of Process Management and Benchmarking, 7(2), 183-205.
- Kailash, Saha, R. K., & Goyal, S. (2017b). Benchmarking practice for identification of internal supply chain management performance factors gap. Journal of Supply Chain Management System, 6(4), 33-38.
- Kailash, Saha, R. K., & Goyal, S. (2017c). Performance indicators for benchmarking of internal supply chain management, World Academy of Science, Engineering and Technology, International Science Index 127. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(7), 1940-1944.
- Kailash, Saha, R. K., & Goyal, S. (2017d). Scope of internal supply chain management benchmarking in Indian manufacturing industries, World Academy of Science, Engineering and Technology, International Science Index 126. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(6), 1638-1641.
- Kailash, Saha, R. K., & Goyal, S. (2017e). Benchmarking model to analyse ISCM performance of selected Indian manufacturing industries using Fuzzy AHP Technique. International Journal of Industrial & System Engineering, (in press).
- Kailash, Saha, R. K., & Goyal, S. (2018). Benchmarking framework for internal supply chain management: A
- case study for comparative analysis. International Journal of Manufacturing Technology and Management, 32(4-5), 412-429.
- Kannan, V. R., & Choon Tan, K. (2003). Attitudes of US and European managers to supplier selection and assessment and implications for business performance. Benchmarking: An International Journal, 10(5), 472-489.
- Kesavan, S., Staats, B. R., & Gilland, W. (2014). Volume flexibility in services: The costs and benefits of flexible labor resources. Management Science, 60(8), 1884-1906.
- Kim, S. (2009). The toll plaza optimization problem: Design, operations, and strategies. Transportation Research Part E: Logistics and Transportation Review, 45(1), 125-137.
- Krajewska, M. A., & Kopfer, H. (2009). Transportation planning in freight forwarding companies: Tabu search algorithm for the integrated operational transportation planning problem. European Journal of Operational Research, 197(2), 741-751.
- Kristensen, T., Olsen, K. R., Kilsmark, J., & Pedersen, K. M. (2008). Economies of scale and optimal size of hospitals: Empirical results for Danish public hospitals. Syddansk Universitet.
- Kumar, S., & Raj, T. (2016). Selection of material handling equipment for flexible manufacturing system using FAHP. International Journal of Recent Advances in Mechanical Engineering, 5(1), 25-45.
- Kumar, S., Parashar, N., & Haleem, A. (2009). Analytical hierarchy process applied to vendor selection problem: Small scale, medium scale and large scale industries. Business Intelligence Journal, 2(2), 355-362.
- Kwateng, K. O., Manso, J. F., & Osei-Mensah, R. (2014). Outbound logistics management in manufacturing companies in Ghana. Review of Business & Finance Studies, 5(1), 83.
- Leachman, R. C., Kang, J., & Lin, V. (2002). SLIM: Short cycle time and low inventory in manufacturing at Samsung Electronics. Interfaces, 32(1), 61-77.
- Lenin, K. (2015). A study on the air cargo logistics operations in Dubai. Management, 4(5), 313-315.
- Lin, J. H., Tzeng, G. H., & Jen, W. (2005). Utilizing VIKOR to make ERP system supplier selection decision. Agriculture and Economics, 34(11), 69-90.
- Liu, X., & Sun, Y. (2011). Information flow management of vendor managed inventory system in automobile parts inbound logistics based on internet of things. Journal of Software, 6(7), 1374-1380.
- Lonn, S., & Stuart, J. A. (2003). Increasing service through aggressive dealer inventory return policies. International Journal of Physical Distribution & Logistics Management, 33(6), 519-530.
- Maleki, R. A., & Reimche, J. (2011). Managing returnable containers logistics - A case study part I - Physical and information flow analysis. International Journal of Engineering Business Management, 3(2), 1-8.
- McKay, K. N., & Wiers, V. C. (2003). Integrated decision support for planning, scheduling, and dispatching tasks in a focus factory. Computers in Industry, 50(1), 5-14.
- Mehta, N., & Sharma, L. (2013). A modification over ratio estimator using empirical data. Statistics, 2(1), 65-67.
- Min, H. (2009). The best practice supplier diversity program at Caterpillar. Supply Chain Management: An International Journal, 14(3), 167-170.
- Mogre, R., Wong, C. Y., & Lalwani, C. S. (2014). Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information. International Journal of Production Research, 52(17), 5223-5235.
- Montoya-Torres, J. R., Franco, J. L., Isaza, S. N., Jiménez, H. F., & Herazo-Padilla, N. (2015). A literature review on the vehicle routing problem with multiple depots. Computers & Industrial Engineering, 79, 115-129.
- Mukherjee, A., & Goyal, T. M. (2013). FDI in services sector in India. Foreign Trade Review, 48(3), 413-430.
- Mulang, A. (2015). The importance of training for human resource development in organization. Journal of Public Administration and Governance, 5(1), 190-197.
- Murthy, D. N. P. (2007). Product reliability and warranty: An overview and future research. Production, 17(3). 426-434.
- Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of
- VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
- Pekgun, P., Griffin, P. M., & Keskinocak, P. (2008). Coordination of marketing and production for price and lead time decisions. IIE Transactions, 40(1), 12-30.
- Ramaa, A., Subramanya, K. N., & Rangaswamy, T. M. (2012). Impact of warehouse management system in a supply chain. International Journal of Computer Applications, 54(1), 14-20.
- Saaty, T. L. (1986). Axiomatic foundation of the analytic hierarchy process. Management Science, 32(7), 841-855.
- Sahay, B. S., Cavale, V., & Mohan, R. (2003). The “Indian” supply chain architecture. Supply Chain Management: An International Journal, 8(2), 93-106.
- Schlosser, F. K., Templer, A., & Ghanam, D. (2006). An integrated agenda for understanding the impact of HR outsourcing on organisational learning orientation. Journal of Labor Research, Special Issue on Outsourcing Management, 27(3), 291-303.
- Senk, M., Metlikovic, P., Maletic, M., & Gomiscek, B. (2010). Development of new product/process development procedure for SMEs. Organizacija, 43(2), 76-86.
- Shahadat, K. (2003). Supplier choice criteria of executing agencies in developing countries. International Journal of Operations and Production Management, 16(4), 261-285.
- Sheu, J. B. (2007). Challenges of emergency logistics management. Transportation Research Part E: Logistics and Transportation Review, 43(6), 655-659.
- Shih, H. S., Shyur, H. J., & Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7-8), 801-813.
- Sodhi, M. S. (2003). How to do strategic supply-chain planning. Fall Magazine.
- Song, D. P., & Carter, J. (2009). Empty container repositioning in liner shipping. Maritime Policy & Management, 36(4), 291-307.
- Stawowy, A., & Duda, J. (2012). Models and algorithms for production planning and scheduling in foundries -Current state and development perspectives. Archives of Foundry Engineering, 12(2), 69-74.
- Subramani, J., & Kumarap, G. (2012). Modified ratio estimators for population mean using function of quartiles of auxiliary variable. Bonfring International Journal of Industrial Engineering and Management Science, 2(2), 19-23.
- Swain, A. K. P. C., & Das, M. (2015). Some classes of modified ratio type estimators in sample surveys. Statistics in Transition New Series, 16(1), 37-52.
- Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., & Shankar, R. (2008). Designing and managing the supply chain: Concepts, strategies and case studies. Tata McGraw-Hill Education.
- Tan, X. C., Wang, Y. Y., Gu, B. H., Mu, Z. K., & Yang, C. (2011). Improved methods for production manufacturing processes in environmentally benign manufacturing. Energies, 4(9), 1391-1409.
- Tracey, M., & Leng Tan, C. (2001). Empirical analysis of supplier selection and involvement, customer satisfaction, and firm performance. Supply Chain Management: An International Journal, 6(4), 174-188.
- Vinesh, A. (2014). Role of training & development in an organizational development. International Journal of Management and International Business Studies, 4(2), 213-220.
- Wang, Y. C. (2008). Evaluating flexibility on order quantity and delivery lead time for a supply chain system. International Journal of Systems Science, 39(12), 1193-1202.
- Wang, Y., Zhang, D., Liu, Q., Shen, F., & Lee, L. H. (2016). Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions. Transportation Research Part E: Logistics and Transportation Review, 93, 279-293.
- Wijaya, J. (2013). The relationship between price, lead time, and delay toward the order quantity in steel manufacturer. Universal Journal of Industrial and Business Management, 1(1), 1-7.
- Wu, D., & Olson, D. L. (2008). Supply chain risk, simulation, and vendor selection. International Journal of Production Economics, 114(2). 646-655.
- Yadav, S. K, Gupta, S., Mishra, S. S., & Shukla, A. K. (2016). Modified ratio and product estimators for estimating population mean in two-phase sampling. American Journal of Operational Research, 6(3), 61-68.
- Yang, J. L., Chiu, H. N., Tzeng, G. H., & Yeh, R. H. (2008). Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships. Information Sciences, 178(21), 4166-4183.
- Yu, B., Wang, K., Wang, C., & Yao, B. (2017). Ship scheduling problems in tramp shipping considering static and spot cargoes. International Journal of Shipping and Transport Logistics, 9(4), 391-416.