Total views : 413

Model of Make in India Possibilities: An Indian Operations Dream

Affiliations

  • School of Management, SASTRA University, Thanjavur - 613401, Tamil Nadu, India

Abstract


Objectives: To know the opinion about possibilities of Make in India program and to study the awareness of Logistics, Quality Management and Production Planning and control concepts among respondents. Methods/Analysis: Descriptive research design was used. The primary data was collected from Urban and Rural areas around Thanjavur city from 390 respondents using structured questionnaire adopting simple random sampling technique. The data was analyzed using descriptive statistics, one-way Analysis of variance and Multiple Regression. Findings: Only 31.53 % of the respondents believe it is possible to make in India. This shows that the study respondents feel that it is impossible to make in India with the present knowledge about the modern manufacturing concepts. Adequate knowledge about the concepts of Logistics Quality Management and Production planning and Control were not found among the respondents. The respondents were also not much aware about the adoption of production concepts in the Indian manufacturing industries. The study revealed that there is no significant difference in the knowledge about the manufacturing concepts between the Rural and Urban people. Applications/Improvements: The novelty lies in estimation of Make in India Possibilities from the awareness towards Production Planning and Control, Logistics and Quality concepts by building Multiple regression model.

Keywords

Logistics, Make in India, Multiple Regression, One-way ANOVA, PPC, Quality Concepts.

Full Text:

 |  (PDF views: 243)

References


  • Jain A, Bhatti R, Singh H. Productivity Improvement through 5S implementation in Indian manufacturing industries; 2014. p. 535–45.
  • Ebrahimpour A. The impact of just-in-time implementation and ISO 9000 certification on total quality management, Dreyfus LP, Ahire SL, Ebrahimpour M, editors; 2004. p. 125–41.
  • Kheirkhah A, Rezaei S. Production engineering. using cross-docking operations in a reverse logistics network design: a new approach; 2015. p. 175–84.
  • Hahn GJ, Kaiser C, Kuhn H, Perdu L, Vandaele NJ. Enhancing aggregate production planning with an integrated stochastic queuing model; 2012. p. 451–56.
  • Chen J-L, Wang L-L, Mu Y-F, Wang J-X. An application study of lean six sigma in logistic service quality management; 2013. p. 843–50.
  • Bourrieres JP, Shin OK, Lhote F. Real time production scheduling and dynamic parts routing for flexible assembly lines; 1991. p. 361–8.
  • Lee K-S, Wang K-J. Using six sigma to improve design quality; 2013. p. 3953–6.
  • Oropesa-Vento M, García-Alcaraz JL, Rivera L, Manotas DF. Effects of management commitment and organization of work teams on the benefits of Kaizen: Planning stage; 2015. p. 76–84.
  • Sanchez PM, Ballesteros NR, Olaya DF. Enhancing synergies in a collaborative environment. Lecture Notes in Management and Industrial Engineering (Pablo Cortés, Elvira Maeso-González, Alejandro EscuderoSantana); 2015. p. 247–55.
  • Chen R, Fan B, Tang G. Scheduling problems in cross docking; 2009. p. 421–9.
  • Boschian V, Paganelli P. Business models for advanced ICT. Logistics in sustainable logistics and supply chains pp- XIV 185; 2016. p. 15–51.
  • Frehe V, Teuteberg F, Mehmann J. The role of ICT in Green. Logistics & Conference Paper: Crowd Logistics, A Literature Review and Maturity Model; 2013. p. 1–13.
  • Bo X-P, Wang Y-Y, Zou J-F. Implementation of six sigma to service quality management in auto after-sale; 2013. p. 1163–71.
  • Sathya N, Muthukumaravel A. A review of the optimization algorithms on traveling salesman problem. 2015 Nov; 8(29). DOI: 10.17485/ijst/2015/v8i1/84652.
  • Pasha N. Production and material planning in the push and pull integrated system for routine products and customers orders. 2015; 8(11). DOI: 10.17485/ijst/2015/v8i11/71793.
  • 16. Shankar R, Sundararajan M. Manufacturing quality improvement with data mining outlier approach against conventional quality measurements. 2015 Jul; 8(15). DOI: 10.17485/ijst/2015/v8i15/73109.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.