Aggarwal, V., Padhi, S. S., and Bhatnagar, V. (2011). Performance improvement in parallel manufacturing systems through scenario analysis and optimal design of parameters. International Journal of Production Research, 13(6), 85–107.
a H. D. (1960). An Introduction to Mathematical Statistics (vol.2). Michigan: Ginn.
Corte, P., Onieva, L. and Guadix, J. (2010). Optimizing and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study. International Journal of Production Research, 48(3), 3637–3656.
Daniel, K., Amare, M. and Solomon, T. (2010). Assembly line balancing using simulation technique in a garment manufacturing firm. Journal of EEA, 27(1), 69-80.
Drucker, P. F. (1990). The emerging theory of manufacturing. Harvard Business Review, 68 (3), 94-102.
Eryilmaz, M .S. , Kusakci, A. O. , Gavranovich, H. and Findik, F. (2012). Analysis of shoe manufacturing factory by simulation of production processes. Journal of Soft Computing, 1(3), 120- 127.
Garza-Reyes, J. A., Eldridge, S., Barber, K. D., Soriano –Meier, H. (2010). Overall equipment effectiveness (OEE) and process capability (PC) measures: A relationship analysis. International Journal of Quality & Reliability Management, 27 (1), 48 – 62.
Groover, P. (2000). Automation, Production Systems, and Computer-Integrated manufacturing 2nd Ed., Delhi, Pearson Education.
Hassan, M. M., Gruber, S. (2008). Application of discrete-event simulation to study the paving operation of asphalt concrete. Construction Innovation. Journal of Information, Process, Management, 8(1), (109-118).
Ingemansson, A., Bolmsjo, G. S. (2005). Improved efficiency with production disturbance reduction in manufacturing systems based on discrete-event simulation. Journal of manufacturing technology management, 15(3), (267 -274).
James, C., Putra, A. P. , Anggono, N. and Chen, J. (2014). Simulation modeling and analysis for stitching line of footwear industry.International Conference on Industrial Engineering and Operations Management. Bali, Indonesia.
Kuivanen, R. (1996). Disturbance control in flexible manufacturing. International journal of human factors in manufacturing, 6(1), (41-56).
Law, A. M. and Kelton, W. D. (2000). Simulation modeling and analysis 3rd ed. Boston, McGraw-Hill.
Mohamad, E., Salleh, M. R., Nordin, N. A. (2012). Simulation study towards productivity improvement for assembly line. Journal of Human Capital Development,5(1), 59-69.
Padhi, S.S., Wagner, S. M., Niranjan, T. T. and Aggarwal, V. (2013). A simulation-based methodology to analyse production line disruptions.International Journal of Production Research, 51(6), 1885–1897.
Padhi, S. S., Mohapatra, P. K. J. (2010). Process evaluation of award of work contracts in a government department, International journal of electronic governance, 2(3), 118 -130.
Quintero, L. A., Conway, P. P., Velandia, D. M. S., West, A. A. (2011). Root cause analysis support for quality improvement in electronics manufacturing, Assembly automation, 31(1), 38-46
Shang, J. S., Li, S. and Tadikamalla, P. (2004). Operational design of a supply chain system using the taguchi method, response surface methodology, simulation and optimization.International Journal of Production Research, 42(18), 3823 – 3849.
Smet, R. D., Gelders, L. and Pintelon, L. (1997). Case studies on disturbances registration for contineos improvement. Journal of quality in maintenance engineering, 3(2), 91-108.
Toledo, T., Koutsopoulos, A. D., Ben-Akiva, M. E., Burghout, W., Andreasson, I ., Johansson ,T.and Lundin, C. (2003). Calibration and Validation of Microscopic Traffic Simulation Tools: Stockholm Case Study. Transportation Research Record (1831): 65-75.
Temesgen, G. and Nahom, M. (2014). Modeling and performance analysis of manufacturing systems in footwear industry. Science, Technology and Arts Research Journal, 3(1), 132-141.
Wu, B. (1989). Manufacturing systems design and analysis: Context and techniques 2nd Ed. London ,Chapman and Hall.