A finite state method in improvement and design of lean Bernoulli serial production lines

Production systems have a significant impact on national and global economies. It is, therefore, of particular interest to develop, master, and apply new methodologies improving the performance of the production systems. A systematic approach to the improvability and design for lean production in the case of the serial Bernoulli production lines is presented in this research using the finite state method and application of the Markovian modeling approach. A new concept of the bottleneck identification procedure is presented based on the analytical relationship between line properties and performance measures. Also, a new design methodology combining features of the finite state method and genetic evolution algorithm is developed to enable the efficient lean design of the serial Bernoulli production lines. The developed procedures are applied in the case of an automotive paint shop system including bottleneck identification concerning the production rate, the work-inprocess, and the probabilities of blockage and starvation. Finally, the lean automotive paint shop system is obtained in an efficient and designer-friendly way.