Human-machine cooperation in planning and scheduling: a case study on an unstable environment

Abstract

In an industrial environment, manufacturing systems may be subject to considerable uncertainties which may lead to numerous schedule disturbances. These disturbances prevent the execution of the planned production schedule. 'groups of permutable jobs' is one of the most studied methods that deal with this drawback. It constructs a flexible solution characterised by a set of schedules, allowing a human operator to execute, in real-time, the schedule that best fits the state of the shop. However, because of the limited complexity that one human being can handle, he/she needs to cooperate with the machine in order to take efficient decisions. This paper focuses on investigating the human-machine cooperation for planning and scheduling. A new human-machine interface model assisted with a multi-indicator decision support system has been proposed and evaluated. The results show the usefulness/limits of the proposed model and provide insights into the practice of production planning and scheduling. [Received 27 October 2017; Revised 13 December 2017, 7 June 2018; Accepted 8 June 2018]