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Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine

Year 2023, Volume: 62 Issue: 2, 67 - 76, 31.07.2023
https://doi.org/10.30797/madencilik.1160266

Abstract

The traditional way of coal production and management is still predominant in the Indian coal mining industry which has led to a widespread waste of resources both materials and humans. Operational loss of the mining machinery and equipment is one of the key factors for the low performance and productivity of mines. This research presents an application of the integrated approach of the Mine Production Index and Ishikawa Diagram in an Indian coal mine to study the bottleneck equipment in the mining operation among the fleet of the shovel, dumper, and dozer. Mine Production Index (MPI) identifies the bottleneck equipment in the mining operation, and Ishikawa Diagram presents the Root Cause Analysis of bottleneck equipment. The fuzzy Analytic Hierarchy Process (FAHP) is used to determine weights for MPI calculation using information gathered from a group of 11 experts through Structured interviews. The study found that the dozer fleet is the bottleneck equipment and the ineffectiveness of the dozer fleet can be grouped into 4 categories as enumerated on the Ishikawa diagram. The study proposes that the ineffectiveness of the dozer fleet can be improved with an increase in its performance rate. The study is based on the judgments of the experts for the case mine, which may limit the external validity. This paper is an original contribution to the analysis of mining equipment using the Mine Production Index and Ishikawa Diagram in an Indian coal mine.

References

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  • Ahmed, M. and Ahmad, N. (2011), “An application of Pareto analysis and cause-and-effect diagram (CED) for minimizing rejection of raw materials in lamp production process”, Management Science and Engineering, Vol. 5 No. 3, pp. 87.
  • Andersen, B. and Fagerhaug, T. (2006), Root cause analysis: simplified tools and techniques, ASQ Quality Press.
  • Arputharaj, M. M. (2015), “Studies on availability and utilization of mining equipment-an overview”, International Journal of Advanced Research in Engineering and Technology, Vol. 6 No. 3, pp. 14-21.
  • Ayag Z. and Gurcan Ozdemir, R. (2012), “Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP”, International Journal of Production Economics, Vol. 140 No. 2, pp. 630-636.
  • Belhadi, A., Touriki, F.E. and Fezazi, S.E. (2017), “Prioritizing the solutions of lean implementation in SMEs to overcome its barriers: An integrated fuzzy AHP-TOPSIS approach”, Journal of Manufacturing Technology Management, Vol. 28 No. 8, pp. 1115-1139.
  • Beikkhakhian, Y., Javanmardi, M., Karbasian, M. and Khayambashi, B. (2015), “The application of ISM model in evaluating agile supplier’s selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods”, Expert Systems with Applications, Vol. 42 No.15, pp. 6224-6236.
  • Buckley, J.J. and Qu, Y. (1990), “On using alpha-cuts to evaluate fuzzy functions”, Fuzzy Sets System, Vol. 38, pp. 309–312.
  • Chang, D.Y. (1996), “Applications of the extent analysis method on fuzzy AHP”, European Journal of operational research, Vol. 95 Vol. 3, pp. 649-655.
  • Cheng, C. H. (1999), “Evaluating weapon systems using ranking fuzzy numbers”, Fuzzy Sets and Systems, Vol. 107 No.1, pp. 25–35.
  • Duggett, A. M. (2004), “A statistical Comparison of Three Root Cause Tools”, Journal of Industrial Technology, Vol. 20 No. 2, pp. 1-9.
  • Elevli, S. and Elevli, B. (2010), “Performance measurement of mining equipment by utilizing OEE”, Acta Montanistica Slovaca, Vol. 15 No. 2, pp. 95-101.
  • Farhan, U.H., Tolouei-Rad, M. and Osseiran, A. (2016) “Use of AHP in decision-making for machine tool configurations”, Journal of Manufacturing Technology Management, Vol. 27 No. 6, pp. 874-888.
  • Guerin, T. (2015), “An investigation into the cause of loss of containment from the supply of mini-bulk lubricants”, Engineering Failure Analysis, Vol. 54, pp. 1–12. Huang, Y.P., Basanta, H., Kuo, H.C. and Huang, A. (2018), “Health symptom checking system for elderly people using fuzzy analytic hierarchy process”, Applied System Innovation, Vol. 1 No. 2, pp.10.
  • Ishikawa, K. (1990), Introduction to quality control, Productivity Press.
  • Kang, H.Y., Lee, A.H.I. and Yang, C.Y. (2012), “A fuzzy ANP model for supplier selection as applied to IC packaging”, Journal of Intelligent Manufacturing, Vol. 23 No. 5, pp. 1477-1488.
  • Kamaruzzaman, S.N., Lou, E.C.W., Wong, P.F., Wood, R. and Che-Ani, A.I. (2018), “Developing weighting system for refurbishment building assessment scheme in Malaysia through analytic hierarchy process (AHP) approach”, Energy Policy, Vol. 112, pp. 280-290.
  • Kellogg, K.M., Hettinger, Z., Shah, M., Wears, R.L., Sellers, C.R., Squires, M. and Fairbanks, R.J. (2017), “Our current approach to root cause analysis: is it contributing to our failure to improve patient safety?”, BMJ Quality Safety, Vol. 26 (5), pp. 381-387.
  • Kesimal, A. and Bascetin A. (2002), “Application of Fuzzy Multiple Attribute Decision Making in Mining Operations”, Mineral Resources Engineering, Vol. 11 No. 1, pp. 59-72. Khaba, S. and Bhar, C. (2017) “Quantifying SWOT analysis for the Indian coal mining industry using Fuzzy DEMATEL”, Benchmarking: An International Journal, Vol. 24 No. 4, pp. 882-902.
  • Kim, J., Lee, J., Kim, B. and Kim, J. (2019), “Raw material criticality assessment with weighted indicators: An application of fuzzy analytic hierarchy process”, Resources Policy, Vol. 60, pp. 225-233.
  • Kutlu, A.C. and Ekmekçioğlu, M. (2012), “Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP”, Expert Systems with Applications, Vol. 39 No. 1, pp. 61-67.
  • Lanke, A. A., Hoseinie, S. H. and Ghodrati, B. (2016), “Mine production index (MPI)-extension of OEE for bottleneck detection in mining”, International Journal of Mining Science and Technology, Vol. 26 No.5, pp. 753-760.
  • Lanke, A., Hoseinie, H. and Ghodrati, B. (2014) “Mine production index (MPI): new method to evaluate effectiveness of mining machinery”, In International conference on mining and mineral engineering (ICMME 2014), pp. 755-759.
  • Lee, A., Lin, C.Y., Wang, S. R. and Tu, Y. M. (2010), “The construction of a comprehensive model for production strategy evaluation”, Fuzzy Optimization and Decision Making, Vol. 9 No. 2, pp. 187–217.
  • Lee, T. R, Thi P. H. L., Andrea G. and Lenny S. C. K. (2011), “Using FAHP to determine the criteria for partner's selection within a green supply chain: The case of hand tool industry in Taiwan”, Journal of Manufacturing Technology Management, Vol. 23 No. 1, pp. 25-55.
  • Lundberg, A. and Dangel, R.F. (2019), “Using root cause analysis and occupational safety research to prevent child sexual abuse in schools”, Journal of child sexual abuse, Vol. 28 No. 2, pp.187-199.
  • Mowafi, Y.A., Alaqarbeh, T. and Alazrai, R. (2019) “Putting Context in the Network Access of Mobile Applications Using Fuzzy Analytic Hierarchy Process”, International Journal of Decision Support System Technology, Vol. 11 No. 2, pp. 13-26.
  • Nazari, S., Fallah, M., Kazemipoor, H. and Salehipour, A. (2018), “A fuzzy inference-fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases”, Expert Systems with Applications, Vol. 95, pp. 261-271.
  • Papic, L., Kovacevic, S., Galar, D. and Thaduri, A. (2016), Investigation of Causes of Mining Machines Maintenance Problems, Current Trends in Reliability, Availability, Maintainability and Safety, pp. 283–299, Springer.
  • Prakash, C., Barua, M. K. and Pandya, K. V. (2015), “Barriers analysis for reverse logistics implementation in Indian electronics industry using fuzzy analytic hierarchy process”, Procedia-Social and Behavioral Sciences, Vol. 189, pp. 91-102.
  • Pendred, S., Fischer, A. and Fischer, S. (2016), “Improved management effectiveness of a marine protected area through prioritizing performance indicators”, Coastal Management, Vol. 44 No. 2, pp. 93-115.
  • Reid, I. and Smyth-Renshaw, J. (2012), “Exploring the fundamentals of root cause analysis: are we asking the right questions in defining the problem?”, Quality and Reliability Engineering International, Vol. 28 No. 5, pp. 535–545.
  • Saaty. T. L. (1980), The Analytic Hierarchy Process, McGraw Hill, New York.
  • Sharma, R. K. and Sharma, P. (2010), “System failure behavior and maintenance decision making using, RCA, FMEA and FM”, Journal of Quality in Maintenance Engineering, Vol. 16, pp. 64–88.
  • Shaw, K., Shankar, R., Yadav, S. S. and Thakur, L. S. (2012) “Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain”, Expert systems with applications, Vol. 39 No. 9, pp. 8182-8192.
  • Wilson, P. F., Dell, L. D. and Anderson, G. F. (1993), Root Cause Analysis: A Tool for Total Quality Management, ASQC Quality Press.
  • Yu, M.C., Goh, M. and Lin, H. C. (2012), “Fuzzy multi-objective vendor selection under lean procurement”, European Journal of Operational Research, Vol. 219 No. 2, pp. 305–311.
  • Zadeh, L. A. (1965), “Fuzzy sets”, Information and control, Vol. 8 No. 3, pp. 338-353.
  • Zyoud, S.H., Kaufmann, L.G., Shaheen, H., Samhan, S. and Fuchs-Hanusch, D. (2016), “A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS”, Expert Systems with Applications, Vol. 61, pp. 86-105.
Year 2023, Volume: 62 Issue: 2, 67 - 76, 31.07.2023
https://doi.org/10.30797/madencilik.1160266

Abstract

References

  • Aboumrad, M., Shiner, B., Riblet, N., Mills, P.D. and Watts, B.V. (2018), “Factors contributing to cancer‐related suicide: A study of root‐cause analysis reports”, Psycho‐Oncology, Vol. 27 No. 9, pp. 2237-2244.
  • Ahmed, M. and Ahmad, N. (2011), “An application of Pareto analysis and cause-and-effect diagram (CED) for minimizing rejection of raw materials in lamp production process”, Management Science and Engineering, Vol. 5 No. 3, pp. 87.
  • Andersen, B. and Fagerhaug, T. (2006), Root cause analysis: simplified tools and techniques, ASQ Quality Press.
  • Arputharaj, M. M. (2015), “Studies on availability and utilization of mining equipment-an overview”, International Journal of Advanced Research in Engineering and Technology, Vol. 6 No. 3, pp. 14-21.
  • Ayag Z. and Gurcan Ozdemir, R. (2012), “Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP”, International Journal of Production Economics, Vol. 140 No. 2, pp. 630-636.
  • Belhadi, A., Touriki, F.E. and Fezazi, S.E. (2017), “Prioritizing the solutions of lean implementation in SMEs to overcome its barriers: An integrated fuzzy AHP-TOPSIS approach”, Journal of Manufacturing Technology Management, Vol. 28 No. 8, pp. 1115-1139.
  • Beikkhakhian, Y., Javanmardi, M., Karbasian, M. and Khayambashi, B. (2015), “The application of ISM model in evaluating agile supplier’s selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods”, Expert Systems with Applications, Vol. 42 No.15, pp. 6224-6236.
  • Buckley, J.J. and Qu, Y. (1990), “On using alpha-cuts to evaluate fuzzy functions”, Fuzzy Sets System, Vol. 38, pp. 309–312.
  • Chang, D.Y. (1996), “Applications of the extent analysis method on fuzzy AHP”, European Journal of operational research, Vol. 95 Vol. 3, pp. 649-655.
  • Cheng, C. H. (1999), “Evaluating weapon systems using ranking fuzzy numbers”, Fuzzy Sets and Systems, Vol. 107 No.1, pp. 25–35.
  • Duggett, A. M. (2004), “A statistical Comparison of Three Root Cause Tools”, Journal of Industrial Technology, Vol. 20 No. 2, pp. 1-9.
  • Elevli, S. and Elevli, B. (2010), “Performance measurement of mining equipment by utilizing OEE”, Acta Montanistica Slovaca, Vol. 15 No. 2, pp. 95-101.
  • Farhan, U.H., Tolouei-Rad, M. and Osseiran, A. (2016) “Use of AHP in decision-making for machine tool configurations”, Journal of Manufacturing Technology Management, Vol. 27 No. 6, pp. 874-888.
  • Guerin, T. (2015), “An investigation into the cause of loss of containment from the supply of mini-bulk lubricants”, Engineering Failure Analysis, Vol. 54, pp. 1–12. Huang, Y.P., Basanta, H., Kuo, H.C. and Huang, A. (2018), “Health symptom checking system for elderly people using fuzzy analytic hierarchy process”, Applied System Innovation, Vol. 1 No. 2, pp.10.
  • Ishikawa, K. (1990), Introduction to quality control, Productivity Press.
  • Kang, H.Y., Lee, A.H.I. and Yang, C.Y. (2012), “A fuzzy ANP model for supplier selection as applied to IC packaging”, Journal of Intelligent Manufacturing, Vol. 23 No. 5, pp. 1477-1488.
  • Kamaruzzaman, S.N., Lou, E.C.W., Wong, P.F., Wood, R. and Che-Ani, A.I. (2018), “Developing weighting system for refurbishment building assessment scheme in Malaysia through analytic hierarchy process (AHP) approach”, Energy Policy, Vol. 112, pp. 280-290.
  • Kellogg, K.M., Hettinger, Z., Shah, M., Wears, R.L., Sellers, C.R., Squires, M. and Fairbanks, R.J. (2017), “Our current approach to root cause analysis: is it contributing to our failure to improve patient safety?”, BMJ Quality Safety, Vol. 26 (5), pp. 381-387.
  • Kesimal, A. and Bascetin A. (2002), “Application of Fuzzy Multiple Attribute Decision Making in Mining Operations”, Mineral Resources Engineering, Vol. 11 No. 1, pp. 59-72. Khaba, S. and Bhar, C. (2017) “Quantifying SWOT analysis for the Indian coal mining industry using Fuzzy DEMATEL”, Benchmarking: An International Journal, Vol. 24 No. 4, pp. 882-902.
  • Kim, J., Lee, J., Kim, B. and Kim, J. (2019), “Raw material criticality assessment with weighted indicators: An application of fuzzy analytic hierarchy process”, Resources Policy, Vol. 60, pp. 225-233.
  • Kutlu, A.C. and Ekmekçioğlu, M. (2012), “Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP”, Expert Systems with Applications, Vol. 39 No. 1, pp. 61-67.
  • Lanke, A. A., Hoseinie, S. H. and Ghodrati, B. (2016), “Mine production index (MPI)-extension of OEE for bottleneck detection in mining”, International Journal of Mining Science and Technology, Vol. 26 No.5, pp. 753-760.
  • Lanke, A., Hoseinie, H. and Ghodrati, B. (2014) “Mine production index (MPI): new method to evaluate effectiveness of mining machinery”, In International conference on mining and mineral engineering (ICMME 2014), pp. 755-759.
  • Lee, A., Lin, C.Y., Wang, S. R. and Tu, Y. M. (2010), “The construction of a comprehensive model for production strategy evaluation”, Fuzzy Optimization and Decision Making, Vol. 9 No. 2, pp. 187–217.
  • Lee, T. R, Thi P. H. L., Andrea G. and Lenny S. C. K. (2011), “Using FAHP to determine the criteria for partner's selection within a green supply chain: The case of hand tool industry in Taiwan”, Journal of Manufacturing Technology Management, Vol. 23 No. 1, pp. 25-55.
  • Lundberg, A. and Dangel, R.F. (2019), “Using root cause analysis and occupational safety research to prevent child sexual abuse in schools”, Journal of child sexual abuse, Vol. 28 No. 2, pp.187-199.
  • Mowafi, Y.A., Alaqarbeh, T. and Alazrai, R. (2019) “Putting Context in the Network Access of Mobile Applications Using Fuzzy Analytic Hierarchy Process”, International Journal of Decision Support System Technology, Vol. 11 No. 2, pp. 13-26.
  • Nazari, S., Fallah, M., Kazemipoor, H. and Salehipour, A. (2018), “A fuzzy inference-fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases”, Expert Systems with Applications, Vol. 95, pp. 261-271.
  • Papic, L., Kovacevic, S., Galar, D. and Thaduri, A. (2016), Investigation of Causes of Mining Machines Maintenance Problems, Current Trends in Reliability, Availability, Maintainability and Safety, pp. 283–299, Springer.
  • Prakash, C., Barua, M. K. and Pandya, K. V. (2015), “Barriers analysis for reverse logistics implementation in Indian electronics industry using fuzzy analytic hierarchy process”, Procedia-Social and Behavioral Sciences, Vol. 189, pp. 91-102.
  • Pendred, S., Fischer, A. and Fischer, S. (2016), “Improved management effectiveness of a marine protected area through prioritizing performance indicators”, Coastal Management, Vol. 44 No. 2, pp. 93-115.
  • Reid, I. and Smyth-Renshaw, J. (2012), “Exploring the fundamentals of root cause analysis: are we asking the right questions in defining the problem?”, Quality and Reliability Engineering International, Vol. 28 No. 5, pp. 535–545.
  • Saaty. T. L. (1980), The Analytic Hierarchy Process, McGraw Hill, New York.
  • Sharma, R. K. and Sharma, P. (2010), “System failure behavior and maintenance decision making using, RCA, FMEA and FM”, Journal of Quality in Maintenance Engineering, Vol. 16, pp. 64–88.
  • Shaw, K., Shankar, R., Yadav, S. S. and Thakur, L. S. (2012) “Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain”, Expert systems with applications, Vol. 39 No. 9, pp. 8182-8192.
  • Wilson, P. F., Dell, L. D. and Anderson, G. F. (1993), Root Cause Analysis: A Tool for Total Quality Management, ASQC Quality Press.
  • Yu, M.C., Goh, M. and Lin, H. C. (2012), “Fuzzy multi-objective vendor selection under lean procurement”, European Journal of Operational Research, Vol. 219 No. 2, pp. 305–311.
  • Zadeh, L. A. (1965), “Fuzzy sets”, Information and control, Vol. 8 No. 3, pp. 338-353.
  • Zyoud, S.H., Kaufmann, L.G., Shaheen, H., Samhan, S. and Fuchs-Hanusch, D. (2016), “A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS”, Expert Systems with Applications, Vol. 61, pp. 86-105.
There are 39 citations in total.

Details

Primary Language English
Subjects Mining Engineering
Journal Section Research Article
Authors

Sorokhaıbam Khaba 0000-0002-5608-0180

Publication Date July 31, 2023
Submission Date August 10, 2022
Published in Issue Year 2023 Volume: 62 Issue: 2

Cite

APA Khaba, S. (2023). Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine. Bilimsel Madencilik Dergisi, 62(2), 67-76. https://doi.org/10.30797/madencilik.1160266
AMA Khaba S. Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine. Mining. July 2023;62(2):67-76. doi:10.30797/madencilik.1160266
Chicago Khaba, Sorokhaıbam. “Analysis of Bottleneck Using Mine Production Index and Ishikawa Diagram: A Case of Indian Coal Mine”. Bilimsel Madencilik Dergisi 62, no. 2 (July 2023): 67-76. https://doi.org/10.30797/madencilik.1160266.
EndNote Khaba S (July 1, 2023) Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine. Bilimsel Madencilik Dergisi 62 2 67–76.
IEEE S. Khaba, “Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine”, Mining, vol. 62, no. 2, pp. 67–76, 2023, doi: 10.30797/madencilik.1160266.
ISNAD Khaba, Sorokhaıbam. “Analysis of Bottleneck Using Mine Production Index and Ishikawa Diagram: A Case of Indian Coal Mine”. Bilimsel Madencilik Dergisi 62/2 (July 2023), 67-76. https://doi.org/10.30797/madencilik.1160266.
JAMA Khaba S. Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine. Mining. 2023;62:67–76.
MLA Khaba, Sorokhaıbam. “Analysis of Bottleneck Using Mine Production Index and Ishikawa Diagram: A Case of Indian Coal Mine”. Bilimsel Madencilik Dergisi, vol. 62, no. 2, 2023, pp. 67-76, doi:10.30797/madencilik.1160266.
Vancouver Khaba S. Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine. Mining. 2023;62(2):67-76.

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