Complexity analysis of an operation in demand-based manufacturing

In demand-based production systems with stochastic demand arrival times, operations often take place in random and long-time intervals. Therefore, traditional learning curve models may not be a good fit for estimating the operation time (OT) in such production environments. Moreover, the complexity of an operation is another influential factor in OT that is not quantified. In this article, human cognitive and complexity factors in demand-based production systems with stochastic demand arrival time are studied. Performing statistical analysis, a double segment learning curve is developed that is a best fit for OT with breakpoint feature. The breakpoint indicates the required number of orders received to reach the mastery level of performing a certain operation. A comparative analysis among existing and the double segment learning curve models is performed and the operation complexity measure is derived from the model.