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Suresh D. Mane & Dr. N. Nagesha

DRIVERS AND BARRIERS TO ENERGY CONSERVATION IN RAILWAY WORKSHOPS: A CASE STUDY OF TWO MAJOR CENTRES IN SOUTH INDIA. Suresh D. Mane & Dr. N. Nagesha. Outline. Introduction Literature review Objective and Scope Statistical Methodology Results & Discussions Conclusions Acknowledgement

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Suresh D. Mane & Dr. N. Nagesha

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  1. DRIVERS AND BARRIERS TO ENERGY CONSERVATION IN RAILWAY WORKSHOPS: A CASE STUDY OF TWO MAJOR CENTRES IN SOUTH INDIA Suresh D. Mane & Dr. N. Nagesha

  2. Outline • Introduction • Literature review • Objective and Scope • Statistical Methodology • Results & Discussions • Conclusions • Acknowledgement • References

  3. INTRODUCTION • Energy Supplies – Finite & Dwindling • Environmental Issues, Costs – On the rise • CO2 – 350 ppm • India – Annually10,48,533 Million Units (MU) supply is 9,78,301 MU a deficit of 6.7%. • Peak requirement - 1, 44,225 MW, Deficit 6.2% • Installed Capacity Constraints • Oil Imports @ 80% of requirement • Outflow of foreign exchange Rs 5 lakh Crores p.a.

  4. INDIAN RAILWAYS • India's largest energy consumer - 2.5% of nation’s total electricity and 40% of diesel. • 2012-13, 17.15 billion units of electricity and 2.35 billion liters of diesel • 2014-15 – Rs 35,474 Crores i.e. 20% • World's third largest network • Resource Crunch – FDI, PPP • 11 National EC Awards, the highest ever by any industry, BEE in 2012

  5. 11 Departments R&D infrastructure, Expenses marginal Railway Energy Management Company formed in 2013 + PTC

  6. RAILWAY WORKSHOPS • Workshops – Maintenance of Locomotives, coaches and wagons • 41 Workshops , 20 Coach maintenance • Study relates to – Carriage Repair Workshop, (UBLS) Hubli and Central Workshops, Mysore (MYSS) • Established in 1885 and 1924

  7. Abbreviations • PoH – Periodical Overhaul ( 18 months periodicity) • IoH – Intermediate Overhaul ( 9 months , only Bogie) • RSP – Rolling Stock Programme • FA – Factor Analysis • PCA – Principal Component Analysis

  8. Scope of Study 1.Carriage Repair Workshop – Hubli (UBLS) Est. in 1885, 3400 Workforce (ISO-9001) 2. Central Workshop – Mysore (MYSS) Est. in 1924, 1800 Workforce ( ISO 9001,14001,18001) MG, Steam Era, Wooden Coaches, 4 Wheel Stock Suresh D. Mane & Dr. N. Nagesha

  9. UBLS as on 1.1.13 Suresh D. Mane & Dr. N. Nagesha

  10. Wooden Bodied Coach Steel bodied Coach LHB Coach (SS)

  11. MYSS on 1.1.13 Suresh D. Mane & Dr. N. Nagesha

  12. UBLS Activities Mfg of Bogie PoH, IoH, RSP Mfg of brake van

  13. MYSS Activities LHB Coach Maintenance PoH, IoH Mfg of Toy train Brake Block Mfg

  14. TECHNICAL STAFF DEPLOYMENT Suresh D. Mane & Dr. N. Nagesha

  15. Organisational Structure of IR

  16. LITERATURE REVIEW • Nagesha and Balachandra (2006) found that Financial & Economic barrier was the top barrier group followed by Behavioral & Personal barrier in the SSI sector. • Patrick Thollander et al (2013) driving forces were found to be financially related followed by organizational driving forces. EC potential - 7.5%.

  17. Somashekar and Nagesha (2010) -10 factors influencing domestic household energy consumption in India using FA • GuntherEllwanger (UIC, 2013) Average external cost of transport per passenger (in Euros per 1000 km) was least for Rail. The results in Euros per 1000 km for others are; Car – 72, Aviation 52, Bus 32, and Rail -18.

  18. Jenny Palm and Patrik Thollander (2010) Cost effective EETs - lack of information, procedural impediments and routines not favouring energy efficiency. (LCC) • Weber (1997), consumption belongs to the realm of technology but EC to the realm of society. Social factors are relevant, in addition to technology. • Baranzi and Giovannini (1996) link energy consumption to four major factors viz. technological, economic and financial, institutional and cultural.

  19. METHODOLOGY Drivers – 7 drivers identified. Forced ranking methodology was adopted using the weighted average method. Barriers – 25 variables , Factor analysis was applied using SPSS software version 20.

  20. BARRIERS- FACTOR ANALYSISSAMPLE & POPULATION • Total -124 respondents 5 Point Likert Scale • 25 variables, • UBLS has 235 supervising engineers and seven technical officers • MYSS has 157 supervising engineers and six technical officers • 82 from UBLS and 42 from MYSS • Sample - 34 % of population at UBLS • Sample - 26 % population at MYSS.

  21. Chief Workshop Manger (CWM) Dy. Chief Workshop Manager (Dy. CWM) Sr. Material Manager (SMM) Sr. Asst. Finan. Advisor (Sr. AFA) Works Manager (WM) Production Engineer (PE) Divisional Elec. Engr. (DEE) Workshop Personnel Officer (WPO) Asst. Workshop Mgr (AWM) Asst. Workshop Mgr (AWM) Asst. Workshop (AWM) Asst. Electrical Engr. (AEE) Senior Section Engineer (SSE) Junior Engineer (JE) Technicians Support Staff

  22. Factor Analysis • Multivariate Statistical approach to analyze interrelationships among variable • Common dimensions/factors/components • Data reduction • Sample adequacy – 100 acceptable ( Min 50) • Overall Significance of Correlation matrix – KMO & Bartlett test

  23. Kaiser Meyer Olkin (KMO) &Bartlett’s test for sphericity • Compares the magnitude of observed correlation coefficients with the magnitude of partial correlation coefficient. • Higher the better correlation between variables can be explained by other variables. • The Bartlett’s test of sphericity takes the determinant of the correlation matrix into consideration. • KMO value for the combined responses at 0.770 (should be > 0.50), • Bartlett’s test for sphericity - 0.000 level (Should be < 0.05) Meeting the requirements.

  24. PCA methodology • Searches for the weight or factor score coefficient so that the first factor explains the largest population of variance. • This explained variance is subtracted from the original input matrix so as to yield a residual matrix. • A second principal factor is extracted from the residual matrix in such a way that the second takes care of most of the residual variance and so on, and this procedure is repeated until there is a very little variance to be explained.

  25. Factor loading • Correlation coefficient between the factor score and variable is called factor loading. • Factor loadings are used to compute Eigen values for each factor and the communalities of each variable. • For the interpretation of factor, the factor loading matrix is rotated. • The main purpose of rotation is to bring the smallest loadings close to zero and its largest loading towards unity. • Varimaxmethod for rotation. • After completing the rotation, a cut off point for factor loading is selected. > 0.5, and the same is adopted • Thus, variables with a loading of > 0.5 naming the factor appropriately.

  26. VARIABLES

  27. Total Variance explained for combined data from workshops

  28. DRIVERS TO EC • Dedication of Management, Supervisors and Staff towards EC. • Awareness of Associates for Adoption of latest Technologies. • Capacity Utilization of Machinery and equipment. • Top Management viz. Zonal Head Quarters and Railway Boards drive for EC. • Education of Associates, Training provided, and Skill developed due to experience. • Recognition, Motivation by Management for EC activities. • Concern for planet earth, and Environment protection.

  29. Respondents Profile

  30. Results & Discussions

  31. Weighted Average Scores of Drivers by various groups at UBLS

  32. Comparative weighted Average Scores of Drivers by UBLS and MYSS

  33. Acknowledgement The authors also warmly thank all the Officers and Engineers of the Carriage Repair Workshop Hubli and Central Workshops Mysore who have freely given their valuable time for this study. Suresh D. Mane & Dr. N. Nagesha

  34. Thank You and have a good day

  35. References • Abdelaziz, E.A. et.al.(2011), “A review of energy saving strategies in industrial sector”, Renewable and Sustainable Energy Reviews, 15, pp. 150-168 • Baranzini, A. and Giovannini, B. (1996), “Institutional and Cultural Aspects of Energy Consumption Modelling”, Structural Transformation Process towards Sustainable Development in India and Switzerland, INFRAS publication, Zurich, Switzerland • Bureau of Energy Efficiency, EC Awards 2012 available at www.bee-india.nic.in • EIA (Energy Information Administration) (2011), “International Energy Outlook 2011” Website: http://www.eia.doe.gov/oiaf/ieo/world.html. • Energy audit report of South Central Railway Tirupati Workshop, Andhra Pradesh. • Indian Railways Magazine Annual Issue April 2012 pp. 38-40. • Indian Railways Magazine May 2012 issue pp.27 • Indian Railways Budget Speech delivered by Hon’ble Minister of Railways, Feb 2013 available at www.indianrail.gov.in/English_Speech_2013-14.pdf, pp 15 • Jenny Palm, Patrik Thollander, 2010. An interdisciplinary perspective on industry energy efficiency, Applied Energy 87 (2010) 3255-3261 • JIA Shunping, PENG Hongquin, LIU Shuang, ZHANG Xiaojie, 2009. Review of Transportation and Energy Consumption Related Research, J journal of Transportation Systems Engineering & Information Technology, 2009, 9(3), 6-16 • Julie Pallant, (2007), SPSS – Survival Manual- a Step by step guide to data analysis using SPSS for Windows, McGraw Hill, England • N. Nagesha, (2010). “Energy Efficiency and Economic performance in Industries”, Lambert Academic Publishing, Germany. • Nagesha N. and Balachandra P., (2006). “Prioritisation of Barriers to Energy Efficiency in Small Scale Industry Clusters: An Analytical Hierarchy Process Approach”, Energy, Vol 31, No 12, pp.1633-1647

  36. Patrik Thollander et. al., (2013) , “Beyond barriers- A case study of driving forces for improved energy efficiency in foundry industries” Applied Energy 111(2013) 636-643 • Ross, M. (1997). “Energy Efficiency” Bisio, A. and Boots, S. (eds.), “Encyclopedia of Energy and Environment, Vol. I, John Wiley & Sons Inc., New York, pp. 530 -567. • R. Ramanathan and Jyoti K. Parikh Transport Policy (2006) Vol 6 Issue 1 pp 35-46; Transport sector in India: an analysis in the context of sustainable development • Suresh D. Mane and D. Ghosh Roy (2008) “Carriage Repair Workshop – Hubli 1885- 2008, Indian Railways Magazine July 2008 pp 18-19. • Suresh D. Mane and N. Nagesha, (2009) “Energy Conservation and Efficiency Improvement in Indian Railways: A Review”, – Proceedings of National Conference on Advances in Mechanical Engineering, UBDT College of Engineering, Davangere. • Suresh D. Mane and N. Nagesha, (2013) “Carriage Repair Workshops on Indian Railways: Study on Energy Conservation Potential”, International Journal of Emerging Technology and Advanced Engineering Vol. 3, Special Issue 3, ICERTSD 2013, pp. 1-8. • Somashekar S and N. Nagesha (2010). An empirical study of factors influencing urban household energy consumption in India, The Ecoscan 4(4): 339-342, 2010 • Standard Note of Carriage Repair Workshop, Hubli (2010 through 2012) • Standard Note of Central Workshops, Mysore (2010 through 2012) • Weber, L. (1997). Some Reflections on Barriers to the Efficient Use of Energy, Energy Policy, Vol. 25, No. 10, pp. 833- 835. • http://www.worldenergyoutlook.org/ IEA Energy Technology Perspectives 2010 – Scenarios & Strategies to 2050, ISBN 978-92-64-08597-8 (2010)( IEA (International Energy Agency, 2013 World Energy outlook) ( accessed 28. July 2014) • http://www.undp.org/content/india/en/home/operations/projects/environment_and_energy/improving_energyefficiencyintheindianrailwaysystem/ (accessed 25 June 2014) • http://www.energy-efficiency-days.org/.../14_IR_Energy_and_Sustainable_Development. • http://www.cea.nic.in/reports/yearly/lgbr_reports.pdf (accessed on 23.10.13)

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