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The constant advances in sciences and technologies encourage industrialist and researchers in manufacturing, to address new challenges relevant to industrial Cyber-Physical Systems (CPS). Human aspects, among others, are of importance and researchers try to take them into account, but they remain to be efficiently dealt with during the design of industrial CPS. The goal of this paper is to highlight how it is possible to integrate "humanin-the-loop" inside the process control of industrial CPS. For that purpose, relevant studies already done in industrial engineering and Human-Machine Systems are presented, completed by an overview of the main cognitive dimensions industrial designers have to integrate in assistance systems definition, in order to benefit from human competencies and capacities while respecting human limits. The main idea is to balance Human and technology involvement, taking advantage of industrial CPS advances and Human capabilities identified and implemented through Human-MachineCooperation principles. The project HUMANISM, which is presented, aims to specify and experiment such principles.

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Humans are currently experiencing the fourth industrial revolution called Industry 4.0. This revolution came about with the arrival of new technologies that promise to change the way humans work and interact with each other and with machines. It aims to improve the cooperation between humans and machines for mutual enrichment. This would be done by leveraging human knowledge and experience, and by reactively balancing some complex or complicated tasks with intelligent systems. To achieve this objective, methodological approaches based on experimental studies should be followed to ensure a proper evaluation of human-machine system design choices. This paper proposes an experimental study based on a platform that uses an intelligent manufacturing system made up of mobile robots, autonomous shuttles using the principle of intelligent products, and manufacturing robots in the context of Manufacturing 4.0. Two experiments were conducted to evaluate the impact of teamwork human-machine cooperation, performance, and workload of the human operator. The results showed a lower level of participants’ assessment of time demand and physical demand in teamwork conditions. It was also found that the team working improves the subjective human operator Know-how-to-cooperate when controlling the autonomous shuttles. Moreover, the results showed that in addition to the work organization, other personal parameters, such as the frequency of playing video games could affect the performance and state of the human operator. They raised the importance of further analysis to determine cooperative patterns in a group of humans that can be adapted to improve human-machine cooperation.