Abstract
Maintenance management is an integral part of any organization’s overall commercial process that develops administrative operational value. Thus, the maintenance function is of immense importance to ensure the safety and effective operation of a facility and equipment in compliance with a statutory obligation, to maximize equipment life, and to reduce the risk of failure. However, for maintenance success work planning, the perception of human factors, and the interrelation of workers and groups in any organisation must be understood. This in turn would determine the allocation of maintenance tasks to team members. This research focused on the evaluation of key performance indicators in relation to the maintenance effectiveness of selected equipment, in a research institution. The impact of human factors on the maintenance was also investigated. Key performance indicators such as Mean Time to Repair (MTTR), Mean Time Between Failure (MTBF), downtime, repair time, and availability were used to quantitatively evaluate the maintenance effectiveness of the equipment, while the systematic approach to empirical research was used to analyse the effect of human factors on maintenance practices. This study was carried out over a period of 6 months on a 4-tonne hydraulic lift, hydraulic hoist jack lift, tire changing machine, fault diagnostic machine, and computerized alignment gauge. Data collected from the maintenance unit was analysed. A total of 11.92 hours was recorded as the MTTR of the five machines. The machines had a high level of availability and a total downtime of 12.01 hours out of operational time of 2369.8 hours over a period of 6 months. The level of motivation and competence among maintenance personnel was assessed to be very good. This is expected to have contributed largely to the effective maintenance practices of workers in the unit. From this study, it can be deduced that the level of motivation and competence is high among maintenance personnel. In terms of productivity, effectiveness, teamwork, decision-making, execution, safety, and responsiveness, the human factor has been shown to have thrived well. This in turn, stimulated the corresponding increase in the availability of machines over the 6 months- of study.
References
Alberto, D. and Giulio M. 2012. Proceedings of the World Congress on Engineering 2012. A Review of the Role of Maintenance and Facility Management in Logistics. London, U.K. Vol. 3: pp.5
Antonovsky, A.D. 2010. The Relationship between Human Factors and Plant Maintenance Reliability in a Petroleum Processing Organization. Ph.D. Thesis. Curtin University of Technology, August 2010.
An, T., He, Y. and Gao, C. 2014. Research on Maintenance Safety Evaluation of the Aging Aircraft. Proceedings of the First Symposium on Aviation Maintenance and Management. Berlin, Germany. Vol. 2 No. 97: pp. 109-116.
Aquino D. P. G. 2020. ‘‘Employees’ mental health and productivity and its impact on contextual and task performance in organizations,’’ J. Adv. Res. Dyn. Control Syst., vol. 12, no. SP8, pp. 708–719.
Börnfelt, P. 2016. From Passivity to Change Competence in Teams on the Shop Floor, Paper for the 9th International Workshop on team working, University of Göteborg, Sweden.
Bouami, D., & Elfezazi, S. 2016. Improvement maintenance implementation based on Koussaimi downtime analysis approach. Journal of Quality in Maintenance Engineering, 22(4), 378-393.
Bridget, E. 2016. Availability and Utilization of Tools and Equipment for Teaching and Learning Garment Making Trade in the Senior Secondary Schools in Edo State, International Journal of Humanities Social Sciences and Education IJHSSE. Vol. 3 No. 13: pp. 17.
Civil Aviation Safety Authority (CASA). Safety Behaviors: Human Factors for Engineers resource kit - Resource guide for engineers, retrieved from https://www.casa.gov.au/safety-management/standardpage/safety-behaviours-human-factors-engineers-resource-kit. Accessed on 10th January 2016.
Dhillon, B. and Liu. Y. 2006. Human error in maintenance: a review. Journal of Quality in Maintenance Emerald Group Publishing Limited. Vol.12, No. 1: 21‐36.
Dostert, J., & Müller, R. 2021. Motivational assistance system design for industrial production: From motivation theories to design strategies. Cognition, Technology & Work, 23, 507– 535.
Erlantz. L., Aitor., T. E, Leire. B. and José L. M. 2020. “Comprehensive Study of Human Factors, Sensory Principles, and Commercial Solutions” IEEE Access, 10.1109/Access.2023.3280071
Erliza, A., Khairi, A.R., Santoso, M.G., Amanda, T. and Nurcahyo, R. 2022. The Survey of Status Preventive Maintenance Implementation in Government-owned Laboratory in Indonesia. In Proceedings of the International Conference on Industrial Engineering and Operations Management Istanbul (pp. 7-10).
Galar G., Christer S., Aditya P., Rupesh K. and Luis B. 2011. Human Factor in Maintenance Performance Measurement. IEEE, Vol 11. pp. 1569-1576
Hadits, F.A., Anggoro, G.A. and Rifqi, H. 2022. Analysis of Maintenance Management Systems in Steel Manufacturing Industry.
Hobbs, A. 2004. Latent Failures in the Hangar: Uncovering Organizational Deficiencies in Maintenance Operations, SJSU/NASA-Ames Research Center, USA. pp. 1-11.
International Ergonomics Association IEA. 2014. What is Ergonomics, Retrieved 14th January 2020
Johnson, W.B. and Maddox, M.E. 2007. A model to explain human factors in aviation maintenance. Avionics News. pp. 38-41.
Kelly, A. 1989. Maintenance and its Management in Kumar, I. et al 1989. Maintenance Performance Metrics: A State-of-the-Art Review. Zaragoza: Aragon Institute of Engineering Research I3A. University of Zaragoza.
Kiassat, C., Safaei, N. and Banjevic, D. 2014. Choosing the optimal intervention method to reduce human-related machine failures, European Journal of Operational Research, Vol. 2 No. 33: pp. 604-612.
Kreibig S. D. 2010. ‘‘Autonomic nervous system activity in emotion: A review,’’ Biol. Psychol., vol. 84, no. 3, pp. 394–421.
Levitt, J. 2003. Complete guide to preventive and predictive maintenance. New York: Industrial Press. pp. 4
Lind, S. and Nenonen, S. 2008. Occupational risks in industrial maintenance, Journal of Quality in Maintenance Engineering, Vol. 14 No. 2: pp. 194–204.
Lucia, A.D., and Lepsinger, R. 1999. The art and science of competency models. San Francisco: Jossey-Bass. A Case Study from the Electricity Transmission Industry in the South African Journal of Industrial Engineering, Vol. 2 No. 72. Retrieved on August 13, 2019, from http://dx.doi.org/10.7166/27-2-1492
Lundgren, C., Bokrantz, J. and Skoogh, A., 2021. Performance indicators for measuring the effects of Smart Maintenance. International Journal of Productivity and Performance Management, 70(6), pp.1291-1316.
McNeeney, A. 2005. Selecting the Right Key Performance Indicators, Meridium
Mulang, H., 2021. The effect of competences, work motivation, learning environment on human resource performance. Golden Ratio of Human Resource Management, 1(2), pp.84-93.
Müller R, Oehm L. 2019. Process industries versus discrete processing: How system characteristics affect operator tasks. Cognition, Technology & Work, 21:337–356. https://doi.org/10.1007/s10111-018-0511-1
Noroozi, A., Khan, F., Mackinnon, S., Amyotte, P. and Deacon, T. 2014. Determination of human error probabilities in maintenance, Process Safety and Environmental Protection, Vol. 92 No. 2: pp. 131-141.
Nurcahyo, R., 2018. Impact of Training on Maintenance Performance Effectiveness. In Proceedings of the International Conference on Industrial Engineering and Operations Management.
Parida, A., Åhrén, T. and Kumar, U. 2003. Integrating maintenance performance with corporate balanced scorecard, COMADEM 2003, Proceedings of the 16th International Congress, Växjö , Sweden, pp. 27-29.
Parida, A. and Kumar, U. 2004. Application of overall equipment effectiveness (OEE) as a process performance indicator: A case study from Kiruna Mines, ENTMS 2004, Bhubaneswar, India, pp. 3-5.
Parida, A. and Kumar, U. 2006. Maintenance performance measurement (MPM): issues and challenges, Journal of Quality in Maintenance Engineering, Vol. 3 No. 12: pp. 239-251.
Peach, R. Ellis, H. and Visser, J.K. 2016. A Maintenance Performance Measurement Framework That Includes Maintenance Human Factors: A Case Study from The Electricity Transmission Industry in South African Journal of Industrial Engineering, Vol. 2 No.72. Retrieved on August 13, 2019, from http://dx.doi.org/10.7166/27-2-1492
Peach, R.H. and Visser, J.K. 2020. Measuring human factors in maintenance: a literature review. South African Journal of Industrial Engineering, 31(4), pp.104-114.
Raza, T., Muhammad, M.B. and Majid, M.A.A. 2016. A comprehensive framework and key performance indicators for maintenance performance measurement. ARPN Journal of Engineering and Applied Sciences, 11(20), pp.12146-12152.
Reiman, T. 2011. Understanding maintenance work in safety-critical organizations – managing the performance variability, Theoretical Issues in Ergonomics Science, Vol. 12 No. 4: pp. 339-366.
Reiman, T. and Oedewald, P. 2004. Measuring maintenance culture and maintenance core task with CULTURE-questionnaire. A case study in the power industry, Safety Science, Vol. 42: pp. 859-889.
Rothstein, J. 2015. Contextualizing Work: The Influence of Workplace History and Perceptions of the Future on Lean Production at Three GM Plants, Critical Sociology, Vol. 42, No. 7-8: pp. 1143–1161.
Samat, H.A., Kamaruddin, S. and Azid, I.A. 2011. Maintenance performance measurement: a review. Pertanika Journal of Science & Technology, 19(2), pp.199-211.
Sardar S. K., N. Kumar, and S. C. Lee, ‘‘A systematic literature review on machine learning algorithms for human status detection,’’ IEEE Access, vol. 10, pp. 74366– 74382, 2022.
Sheikhalishahi, M., Azadeh, A., Pintelon, L. and Chemweno, P. 2016. Human Factors Effects and Analysis in Maintenance: A Power Plant Case Study. Quality and Reliability Engineering International, DOI:10.1002/qre.2065. Vol.334: pp. 895–903.
Sinha, P. 2015. Towards higher maintenance effectiveness: Integrating maintenance management with reliability engineering. International Journal of Quality & Reliability Management, 32(7), 754-762.
Su, K.W., Hwang, S.L. nd Chou, Y.F. 2006. Applying knowledge structure to the usable fault diagnosis assistance system: A case study of motorcycle maintenance in Taiwan, Expert Systems with Applications, Vol. 31: pp. 370-382.
Unger, R.L. and Conway, K. 1994. Impact of maintainability design on injury rates and maintenance costs for underground mining equipment. In: Improving Safety at Small Underground Mines, compiled by R.H. Peters, Report. US Bureau of Mines, Washington, DC. Vol. 18-94 No. 5: pp. 140–167.
Van Acker B, Parmentier DD, Vlerick P, Saldien J. 2018. Understanding mental workload: from a clarifying concept analysis toward an implementable framework. Cognition, Technology & Work, 20:351–365. https://doi.org/10.1007/s10111-018-0481-3
Zhang, R.Q. and Yang, J.L. 2006. Association Rules Based Research on Man-Made Mistakes in Aviation Maintenance: A Case Study, In Proceedings of the sixth international conference on intelligent systems design and applications, Jinan.Vol. 6: pp 8.
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