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Performance Evaluation of Supply Chain and Logistics Management System using Balanced Score Card for Efficiency Enhancement in Indian Automotive Industries

Affiliations

  • Department of Mechanical Engineering, Sri Muthukumaran Institute of Technology, Chennai - 600069, Tamil Nadu, India
  • Departments of Mechanical Engineering, Dr. M.G.R. Educational and Research Institute, Chennai - 600095, Tamil Nadu, India
  • Department of Adult and Continuing Education and Extension, India
  • Department of Mechanical Engineering, Jadavpur University, Kolkata - 700032, West Bengal, India

Abstract


Objective: In universal spirited environment, automotive industries are desired to perform efficiently to meet the maximum percentage of demand by minimum cost. The objective of this article is to create a balance scorecard model for the evaluation of reliability and performance of automotive manufacturing industries to evaluate their supply and demand chain system. Method/Analysis: Using this new idea, the performance of industries should be assessed regarding their supply and demand chain system with the major four criteria like design and development, manufacturing point, financial requirement and consumer’s point of view. The main four features of the industries are policies and firm coordination, design and execution, effectiveness of shipment and information technology usagetotally covers by the new designed balanced scorecard with twenty five evaluation points. Findings: Abroad survey was carried out in Indian automotive manufacturingindustries with well structured questionnaires to collect the necessary data. Application/Improvements: The comparison between multinational, public limited, private limited and small scale organizations were carried out tomeasure the performance variation of their supply and demand chain system. Based on the correlation of above four features, a structural equation model was designed toimprove the supply and demand chain management systemfor automotive manufacturing industries and found that the α coefficient was above 0.80 hence, the balanced score card was reliable.

Keywords

Evaluation, Efficiency, PSPP Software, Reliability, SCM, Score Card.

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References


  • Birhanu D, Rao L. A survey of classifications in supply chain strategies. Procedia Engineering. 2014; 97:2289–97.
  • Gandhi A. Literature review on impact of CRM, SRM, information sharing and goal congruence on retail-SCM. Indian Journal of Science and Technology. 2016; 9(22):1–9.
  • Balakannan K, Nallusamy S, Chakraborty, Majumdar G. Selection and evaluation of supplier by decision model of hybrid data envelopment analysis. International Journal of Applied Engineering Research. 2015; 10(62):123–7.
  • Khodakarami, Shabani, Farzipoor and Azadi. Developing distinctive two stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management. Measurement. 2015; 70:62–74.
  • Hudnurkar M, Jakhar, Rathod. Factors affecting collaboration in supply chain: A literature review. Procedia- Social and Behavioral Sciences. 2014; 133:189–202.
  • Nallusamy S, et al. A proposed agile based supply chain model for poultry based products in India. International Journal of Poultry Science. 2015; 14(1):57–62.
  • Miranda MG, Ramachandran S. A detailed study on the milk supply chain process. Indian Journal of Science and Technology. 2014; 7(S3):16–8.
  • Nallusamy S. Lean manufacturing implementation in a gear shaft manufacturing company using value stream mapping. International Journal of Engineering Research in Africa. 2015; 21:231–7.
  • Soltany MR, Sayadi. Productivity improvement in a steel industry using supply chain management technique. International Journal of Mining and Geo-Engineering. 2013; 47(1):51–60.
  • Nallusamy S, Umarmukdhar, Rekha S. A proposed supply chain model for productivity enhancement in medium scale foundry industries. International Journal of Engineering Research in Africa. 2015; 20:248–58.
  • Miguel L, Silva and Azevedo. An environmental balanced scorecard for supply chain performance measurement. Benchmarking: An International Journal. 2016; 23(6):1398–422.
  • Nallusamy S, Prabu M, Balakannan, Majumdar. Analysis of static stress in an alloy wheel of the passenger car. International Journal of Engineering Research in Africa. 2015; 16:17–25.
  • Yuan FC, Chiu C. A hierarchical design of case-based reasoning in the balanced scorecard application. Expert Systems with Applications. 2009; 36:333–42.
  • Nallusamy S, Dinagaraj, Balakannan, Satheesh. Sustainable green lean manufacturing practices in small scale industries-A case study. International Journal of Applied Engineering Research. 2015; 10(62):143–6.
  • Dornhofer M, Schroder, Gunthner. Logistics performance measurement system for the automotive industry. Logistics Research. 2016; 9(11):1–26.
  • Nallusamy S, Ganesan, Balakannan, Shankar. Environmental sustainability evaluation for an automobile manufacturing industry using multi-grade fuzzy approach. International Journal of Engineering Research in Africa. 2015; 19:123–9.
  • Bhattacharya, et al. Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: A collaborative decision-making approach. Production Planning and Control. 2014; 25(8):698–714.
  • Nallusamy S, Satheesh, Chakraborty, Balakannan. A review on supplier selection problem in regular area of application. International Journal of Applied Engineering Research. 2015; 10(62):128–32.
  • Schmitz J, Platts. Supplier logistics performance measurement: Indications from a study in the automotive industry. International Journal of Production Economics. 2004; 89(2):231–43.
  • Nallusamy S, Kumar L, Balakannan, Chakraborty. MCDM tools application for selection of suppliers in manufacturing industries using AHP, Fuzzy Logic and ANN. International Journal of Engineering Research in Africa. 2015; 19:130–7.
  • Prashant, Anbuudayasankar. An investigation on the benefits of ICT deployment in supply chain management. Indian Journal of Science and Technology. 2016; 9(30):1–7.
  • Nallusamy S. A proposed model for lead time reduction during maintenance of public passenger transport vehicles. International Journal of Engineering Research in Africa. 2016; 23:174–80.
  • Melnyk, et al. Is performance measurement and management fit for the future? Management Account Research. 2014; 25:173–86.
  • Nallusamy S. A proposed model for sustaining quality assurance using TQM practices in small and medium scale industries. International Journal of Engineering Research in Africa. 2016; 22:184–90.
  • Neto, Pires. Performance measurement in supply chains: A study in the automotive industry. Management and Production. 2012; 19(4):733–46.
  • Nallusamy S. Frequency analysis of lean manufacturing system by different critical issues in Indian automotive industries. International Journal of Engineering Research in Africa. 2016; 23:181–7.
  • Okongwu, Brulhart, Moncef. Causal linkages between supply chain management practices and performance: A balanced scorecard strategy map perspective. Journal of Manufacturing Technology Management. 2015; 26(5):678–702.
  • Nallusamy S, Balakannan K, Chakraborty, Majumdar G. Reliability analysis of passenger transport vehicles in public sector undertaking. International Journal of Applied Engineering Research. 2015; 10(68):843–50.

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