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![Example of man-machine multiple activity chart for reading a deck of cards in a card reader (adapted from [35])](publication/349489437/figure/fig2/AS:993877322383360@1613970227007/Example-of-man-machine-multiple-activity-chart-for-reading-a-deck-of-cards-in-a-card.png)
Example of man-machine multiple activity chart for reading a deck of cards in a card reader (adapted from [35])
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Industrial collaborative robotics is an enabling technology and one of the main drivers of Industry 4.0 in industrial assembly. It allows a safe physical and human-machine interaction with the aim of improving flexibility, operator’s work conditions, and process performance at the same time. In this regard, collaborative assembly is one of the most...
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Synthesis and tasks execution is a well known problem pertaining to different fields. With the advent of Industry 4.0, the need to schedule and execute very complex tasks that involve different machinery or robots has become a key topic. In this article we propose a methodology that allows to define and monitor the execution of high-level tasks for...
Citations
... Gualtieri developed a human-centered approach for collaborative assembly systems, aiming to optimize the assembly cycle time while considering the characteristics of the product and process [104]. This approach involves assigning specific tasks to both humans and robots. ...
Collaborative robots, also known as cobots, are designed to work alongside humans in a shared workspace and provide assistance to them. With the rapid development of robotics and artificial intelligence in recent years, cobots have become faster, smarter, more accurate, and more dependable. They have found applications in a broad range of scenarios where humans require assistance, such as in the home, healthcare, and manufacturing. In manufacturing, in particular, collaborative robots combine the precision and strength of robots with the flexibility of human dexterity to replace or aid humans in highly repetitive or hazardous manufacturing tasks. However, human–robot interaction still needs improvement in terms of adaptability, decision making, and robustness to changing scenarios and uncertainty, especially in the context of continuous interaction with human operators. Collaborative robots and humans must establish an intuitive and understanding rapport to build a cooperative working relationship. Therefore, human–robot interaction is a crucial research problem in robotics. This paper provides a summary of the research on human–robot interaction over the past decade, with a focus on interaction methods in human–robot collaboration, environment perception, task allocation strategies, and scenarios for human–robot collaboration in manufacturing. Finally, the paper presents the primary research directions and challenges for the future development of collaborative robots.
... Literature Digital twin in manufacturing [1][2][3][4][5][6][7][8] Virtual commissioning [9][10][11][12][13][14] Human-robot interaction [15][16][17][18] Line balancing of HRI assembly lines [19][20][21][22] Bin-picking [23][24][25][26][27][28] After giving an overview of the relevant literature, the following section deals with various research potentials that have been elaborated based on the literature. In particular, the intersections between the three domains production systems, HRI, and virtual commissioning are addressed. ...
... Digital twin in manufacturing [1][2][3][4][5][6][7][8] Virtual commissioning [9][10][11][12][13][14] Human-robot interaction [15][16][17][18] Line balancing of HRI assembly lines [19][20][21][22] Bin-picking [23][24][25][26][27][28] ...
... Gualteri et al. propose a methodology to optimise the assembly cycle time in the HRI assembly line in six steps. The procedure includes the analysis of the assembly system and tasks, the static task allocation between robot and human, the definition of the robot execution time based on coefficients, the identification of the assembly scenarios, and the calculation of an optimised assembly cycle time [21]. ...
Increasing volatility in manufacturing and rising sustainability requirements demand more efficient processes in production, especially in employee qualification and engineering during development and on-site adjustments before and after the start of production. One possible solution is using digital twins for virtual commissioning, which can speed up engineering processes, qualify employees, and save valuable resources. To solve these challenges, it is necessary to identify promising approaches for using the digital twin and virtual commissioning. Furthermore, creating an environment where these approaches can be optimally explored is essential. This paper presents promising research approaches and demonstrates the development of an assembly process and a production system with a digital twin designed to explore these aspects. The presented system is an interlinked production system for assembling an actual industrial product. It includes different levels of human–robot interaction and automation, which can be implemented virtually in the digital twin.
... Malik and Bilberg worked on the same perspective of assigning tasks to humans and low payload robots, but the author considers the direction of the tool (Malik & Bilberg, 2019). Gualtieri et al. worked on testing the assembling of a large touchscreen cash register in six steps with lighter parts; here author did not simulate any environment (Gualtieri et al., 2021). Majority of research is focussed on the scheduling of Human-robot collaborative tasks (HRT), but no works observed for optimality in the scheduling of the tasks. ...
... In cooperative robotics, DTs have been used both as an integral part of controlling and monitoring the physical robot [25] and as a central tool in setting up truly collaborative tasks with overlapping workspace between the human and the robot [26], [27]. An application of composed DTs is presented in [25], where a DT of a mobile manipulator is implemented using the Robot Operating System (ROS) framework. ...
... Different cost functions have been defined for modelling the time spent to perform each activity considering the implemented technologies. Gualtieri et al. (2021) have evaluated potential assembly scenarios of a human-centred collaborative system using cycle time and payback period. Fager et al. (2021) have designed a cost model for comparing a manual and a cobot picking system; the cost model considered the cost of workers, equipment, and the costs associated with the manual errors in the picking process and returned the productivity of the system. ...
... The present results thus add to the literature by providing further evidence of the positive association between HRI and operating costs. Although the high initial investment, in the long period industrial robots can be more cost-effective than human workers, as also emerged in related empirical research (Gualtieri et al., 2021). Similar considerations hold for the return on investment. ...
... However, it is less considered by the current HRI literature, which tends to point to improvements in operations rather than benefits in financial aspects (Hjorth andChrysostomou, 2022, Gopinath andJohansen, 2019). The available literature has provided positive evidence of the expected return on HRI investment (Gualtieri et al., 2021). Our empirical results confirm those findings and show that the economic convenience of the HRI depends on the degree of automation and, in general, it increases when more tasks are assigned to the robot. ...
This paper proposes an empirical investigation for evaluating the sustainability of different degrees of Human-Robot cooperation (HRC) considering economic, environmental, and social pillars. A connection between human factors and sustainable goals has been defined for integrating human-centricity, sustainability, and Industry 4.0 paradigms. To show how HRC can be implemented sustainably in practice, a combination of multi-criteria technique and case study-based research has been designed. The selected method compares the alternative’s performance by combining numerous and conflicting criteria. The case study with a company belonging to the aerospace sector shows how performance changes according to the degree of automation. Results demonstrate that the introduction of cooperation can offer economic benefits linked to productivity, efficiency, and profitability. Positive effects in social sustainability have also been identified in terms of safety and physical ergonomics. However, the presence of the robot could cause work-related stress and decrease the level of mental well-being. Finally, the introduction of HRC slightly affects environmental sustainability, increasing energy consumption, but decreasing waste due to manual errors. This study also helps practitioners in identifying the relevant factors to evaluate sustainability in HRC and provides findings to better understand the benefits and drawbacks of the adoption of HRC in practice.
... An evaluation proposal that consisted in the reformulation of the work methodology based on the requirements of the task and its evaluation could reach a 22% reduction in the production cycle of the study station [26]. Also, a time study to calculate the cycle time of a robot assembly can determine the optimal scenario in a cycle time, for example, it aims to find a time reduction of 17.16% of cycle time that implies the possibility of increasing annual productivity by more than 17.2% [27]. ...
... Nowadays, there is a lack of simple and practical tools for helping system designers overcome such limiting conditions (Gualtieri et al., 2022). Consequently, safety requirements and measures for collaborative robotics must be studied and harmonized (Gualtieri et al., 2021). In 2016, a new ISO technical report, ISO TS 15066 (ISO 2016), was published in order to help production technicians and safety experts with the development of safe shared workspaces and with the risk assessment process. ...
The fourth industrial revolution (I4.0) implies more collaborative and connected manufacturing. Industry 4.0 and smart manufacturing integrate human and intelligent devices to enhance workplace safety in a collaborative industrial environment (Safety 4.0). Collaborative robots (or cobots) have been developed with intuitive interfaces that support human operators in the physical workload of manufacturing tasks, such as handling hazardous materials or executing repetitive and monotonous actions with high reliability, such as assembly activities. However, the deployment of cobots must include application safety criteria to be taken into account in order to improve their interaction with operators. In this way, Human-robot collaboration (HRC) is being adopted in the smart manufacturing industry as a solution that mixes, within a shared workspace, the dexterity and cognitive faculties of human operators and the accuracy and repeatability skills of robots, guaranteeing no-danger conditions and absence of collision during this type of collaboration. The aim of this paper is to propose human-robot collaboration architecture and show how it will be possible to improve workers’ safety through implementation of the proposed architecture. Intelligent devices are integrated in human-robot workstations in order to protect the operator from hazards, injuries and occupational diseases. The proposed paper highlights safety guidelines regarding HRC and their application using smart equipment, such as sensors, computer vision systems, and so on. Overall, interaction with different degrees of collaboration and technologies increases not only the flexibility but also the complexity of the system. Therefore, this paper also focuses on identifying the main safety requirements in human-robot collaborative systems design
... Nowadays, collaborative robotics is one of the enabling technologies of Industry 4.0 [1]. This paradigm allows a manipulator to work side-by-side with a human operator and to realize a safe sharing of workspace during manufacturing activities. ...
Industrial collaborative robotics is promising for manufacturing activities where the presence of a robot alongside a human operator can improve operator’s working conditions, flexibility, and productivity. A collaborative robotic application has to guarantee not only safety of the human operator, but also fluency in the collaboration, as well as performance in terms of productivity and task time. In this paper, we present an approach to enhance fluency and productivity in human-robot collaboration through online scaling of dynamic safety zones. A supervisory controller runs online safety checks between bounding volumes enclosing robot and human to identify possible collision dangers. To optimize the sizes of safety zones enclosing the manipulator, the method minimizes the time of potential stop trajectories considering the robot dynamics and its torque constraints, and leverages the directed speed of the robot parts with respect to the human. Simulations and experimental tests on a seven-degree-of-freedom robotic arm verify the effectiveness of the proposed approach, and collaborative fluency metrics show the benefits of the method with respect to existing approaches.
... A systematic method for switching from a manual assembly line into a collaborative one was proposed by Gualtieri et al. [9], where one robot and one human were allowed at stations. A mathematical model for HRC was proposed by Koltai et al. [10]. ...
Originated by a real-world case study from the automotive industry, this paper attempts to address the assembly lines balancing problem with human-robot collaboration and heterogeneous operators while optimizing the cycle time. A genetic algorithm (GA) with customized parameters and features is proposed while considering the characteristics of the problem. The computational results show that the developed GA can provide the decision-makers with efficient solutions with heterogeneous humans and robots. Furthermore, the results reveal that the cycle time is highly influenced by order of the operators’ skills, particularly when a fewer number of humans and robots exist at the stations.
... Furthermore, the algorithm proceeds with the subsequent merging favoring the joining between the pairs with the highest S ij . In particular, the UPGMA hierarchical algorithm is adopted to define S ij [34][35][36][37][38][39][40][41][42][43][44]. The algorithm repeats such step until all the accessories are grouped into a single cluster. ...
Nowadays, end customers require personalized products to match their specific needs. Thus, production systems must be extremely flexible. Companies typically exploit assembly lines to manufacture produces in great volumes. The development of assembly lines distinguished by mixed or multi models increases their flexibility concerning the number of product variants able to be manufactured. However, few scientific contributions deal with customizable products, i.e., produces which can be designed and ordered requiring or not a large set of available accessories.
This manuscript proposes an original two-step procedure to deal with the multi-manned assembly lines for customized product manufacturing. The first step of the procedure groups the accessories together in clusters according to a specific similarity index. The accessories belonging to a cluster are typically requested together by customers and necessitate a significant mounting time. Thus, this procedure aims to split accessories belonging to the same cluster to different assembly operators avoiding their overloads.
The second procedure step consists of an innovative optimization model which defines tasks and accessory assignment to operators. Furthermore, the developed model defines the activity time schedule in compliance with the task precedencies maximizing the operator workload balance. An industrial case study is adopted to test and validate the proposed procedure. The obtained results suggest superior balancing of such assembly lines, with an average worker utilization rate greater than 90%. Furthermore, in the worst case scenario in terms of customer accessories requirement, just 4 line operators out of 16 are distinguished by a maximum workload greater than the cycle time.
