Explains that the improvement of flowline assembly systems provides the context for this research: to understand and improve the design and control of manually‐intensive flowline assembly in the clothing industry. Constructs a simulation model of the progressive bundle system, incorporating operator performance variations and learning effects, machine failure and repair, operator absenteeism, quality failure and supervisory control. Notes that, while the operator performance data and the stochastic variables are handled satisfactorily within the simulation, the problems of control are not handled well by conventional discrete event modelling techniques. Adopts a knowledge‐based approach to control, in which an online computerized supervisor exercises control over the execution of the simulation run. As complex system models are not easy to validate, uses a four‐stage approach to demonstrate conformance with real‐world systems: qualification, face validity, modular validation and time‐series system behaviour. Discusses applications of the model and the results of experiments with a line starting work on a new style.
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