The paper concerns the design of a framework for implementing fault-tolerant control of hybrid assembly systems that connect human operators and fully automated technical systems. The main difficulty in such systems is related to delays that result from objective factors influencing human operators’ work, e.g., fatigue, experience, etc. As the battery assembly system can be considered a firm real-time one, these delays are treated as faults. The presented approach guarantees real-time compensation of delays, and the fully automated part of the system is responsible for this compensation. The paper begins with a detailed description of a battery assembly system in which two cooperating parts can be distinguished: fully automatic and semi-automatic. The latter, nonderministic in nature, is the main focus of this paper. To describe and analyze the states of the battery assembly system, instead of the most commonly used simulation, the classic max-plus algebra with an extension allowing one to express non-deterministic human operators’ work is used. In order to synchronize tasks and schedule (according to the reference schedule) automated and human operators’ tasks, it is proposed to use a wireless IoT platform called KIS.ME. As a result, it allows a reference model of human performance to be defined using fuzzy logic. Having such a model, predictive delays tolerant planning is proposed. The final part of the paper presents the achieved results, which clearly indicate the potential benefits that can be obtained by combining the wireless KIS.ME architecture (allocated in the semi-automatic part of the system) with wired standard production networks.
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