Abstract
The paper identifies the need for human robot collaboration for conventional light weight and heavy payload robots in future manufacturing environment. An overview of state of the art for these types of robots shows that there exists no solution for human robot collaboration. Here, we consider cyber physical systems, which are based on human worker participation as an integrated role in addition to its basic components. First, the paper identifies the collaborative schemes and a formal grading system is formulated based on four performance indicators. A detailed sensor catalog is established for one of the collaboration schemes, and performance indices are computed with various sensors. This study reveals an assessment of best and worst possible ranges of performance indices that are useful in the categorization of collaboration levels. To illustrate a possible solution, a hypothetical industrial scenario is discussed in a production environment. Generalizing this approach, a design methodology is developed for such human robot collaborative environments for various industrial scenarios to enable solution implementation.
Highlights
The manufacturing horizon for Industry 4.0 [1] comprises a paradigm shift from the automated manufacturing toward an intelligent manufacturing concept
A generalized solution cannot be presented here, the table with some variations can be considered as generic for industrial scenarios which range from single robot to multiple robots working together with multiple human workers
A controlling collaborative robotic CPS (CRCPS) structure for human–robot collaboration (HRC) suggests the human worker to be an integrated part for which various interactive technologies can be employed
Summary
The manufacturing horizon for Industry 4.0 [1] comprises a paradigm shift from the automated manufacturing toward an intelligent manufacturing concept. Due to the availability of big data in IoT, the manufacturing system characteristics can be predicted precisely like predictive maintenance, robustness in product design and adaptive logistics In this context, the smart manufacturing setup or a smart factory [3, 4] and logistics system have to fulfill the mass customization [5] demand in a flexible manner. The conventional approach is to expose human workers up to a limited extent to the robot and with appropriate safety control that leads to full stoppage (safe hold) of a machine in case of worker violation of the robot workspace This causes interruptions and resetting procedures to be activated which reduces productivity. The futuristic approach is to implement robotic applications where robot and
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