CAPACITY ESTIMATION OF A PRODUCTION LINE: A FLP AND CCP APPROACH Fuzzy linear programming and chance constrained programming are used to estimate cycle time of a multiple-product production line in presence of imprecise information combined with stochastic behaviour of system

In a multi-product production system, the cycle time is described as the time that the slowest workstation takes to process the mix of products (Martinich, 1997). Johri (1987) presented a linear programming model to estimate the capacity of a production line manufacturing a variety of products without accidental stoppages of the workstation. The multi-product system is able to follow a predetermined sequence with a predefined lot size for each product. Machines at workstations are not completely flexible. It means they require a certain amount of set-up time in order to switch the production from one part type to another. In order to simplify the problem, Johri described set-up stij and processing times’ pij as deterministic data. Because modeling the stochastic nature of breakdowns would make any possible analysis impractical by linear programming he only considered the cases without machine failures and repairs. Therefore, he stated that the duration of time that a station takes to process the whole batch of a product type must be greater than or equal to the time required to produce the job plus the time required to set-up the machine. More formally