Robotic Cell Research Articles

Modular Hardware/Software Architecture for Edge Units in Highly Flexible Manufacturing Systems

With the increasing demand for individualized production and swift adaptability to changing market needs, new manufacturing system concepts emerge. Aiming for high flexibility and scalability, they rely on universal reconfigurable machines that can be used in various production steps by automatically changing tools and sensors. Consequently, the data processing infrastructure is required to support the frequent exchange of process-specific software applications, ranging from control and monitoring tasks to complex sensor data processing. This can be a major challenge when computation-intensive software is supported by hardware acceleration to achieve the desired performance or latency requirements. In this paper, we present an edge unit architecture that allows for hosting such applications while meeting the needs for modularity and reconfigurability. It builds upon a hypervisor to partition fixed processing resources among the applications. We present a mechanism that extends this partitioning to field-programmable gate arrays (FPGA) by using dynamic partial reconfiguration. This provides the option to deploy application-specific hardware accelerators with computation-intensive applications while maintaining modularity and on-line reconfigurability. We conclude the paper by pointing out the potential of the proposed architecture based on a use case for automated disassembly in a reconfigurable robotic cell.

Smart production system for the process-reliable assembly of hydrogen tube fittings

Large electrolyzer plants are needed to meet the world's demand for hydrogen. Most of the installation costs for an electrolyzer plant are incurred during production. Therefore, this article aims to illustrate a reference process for automation by assembling hydrogen tube fittings. The assembly process has not been automated yet; Thus, the physical operating principle is elaborated and implemented in a demonstrator. The process is examined simulatively and transferred in a robot cell to determine the required functionality. It is mapped entirely and optimized in the simulation, while the real demonstration shows a successful functional test of the physical operating principle.

Two-machine reentrant circular robotic cells with swap ability

Two-machine reentrant circular robotic cells with swap ability

Generation of Configuration Space Trajectories Over Semi-Constrained Cartesian Paths for Robotic Manipulators

Serial-link manipulators are required to execute trajectories that enable a robot end-effector or a tool to track a Cartesian path. Practical applications may not require constraining all six degrees of freedom (position and orientation) of the tool resulting in semi-constrained paths. Semi-constrained paths allow improved success rates and better quality trajectories as the robot has more freedom to meet the kinematic and dynamic constraints. Additionally, robotic applications will need to use multiple tool center points (TCPs) on the tool to generate feasible paths for the robot. We present an iterative graph construction method to find trajectories for semi-constrained Cartesian paths that also use multiple TCPs. Our graph-based method finds multiple inverse kinematic solutions for possible Cartesian poses that the robot can take and connects them to build a graph. The algorithm uses cues from the Cartesian space to prioritize poses that produce a better quality solution. A biasing scheme is also developed to selectively sample the starting Cartesian poses from available choices. Our method finds near-optimal solutions with significantly fewer nodes and edges in the graph. The algorithm’s performance results on complex industrial test cases are provided. Note to Practitioners—Industrial applications permit the relaxation of one or more degrees of freedom of the tool while following the Cartesian paths. The relaxation of constraints is introduced by defining tolerances between the tool and the workpiece. Multiple TCPs have to be employed for many tasks to use different surfaces of the tool. In this paper, we present a planning algorithm for semi-constrained Cartesian paths that can incorporate the use of multiple TCPs. The user can define discrete TCPs over the tool contact points or surfaces. The tolerances can be easily defined as angular limits on tool orientation along the Cartesian path. Our planning algorithm can work with others via point constraints in Cartesian space or joint space of the robot. Practitioners from the industry can use the method presented in this paper to develop automated robotic cells that do cutting, sanding, polishing, welding, painting, composite layup, additive manufacturing, and several other common applications.

Bi-objective speed-scaling robotic cell scheduling with peak power consumption constraint

This article studies the speed-scaling robotic cell scheduling problem with constrained peak power consumption. The objective is to minimize cycle time and peak power consumption simultaneously. First, we formulate a bi-objective mixed integer programming model for the problem and propose a strategy to preprocess overlapping time windows. Then, we analyze the structural properties of the proposed model and develop an iterative $ \varepsilon $-constraint method to generate its complete Pareto front. Numerical experiments demonstrate that the proposed method effectively solves the robotic cell scheduling problem and that appropriate scheduling of speed-scaling machines can make a trade-off between productivity and power consumption.

Digital twin design and analytics for scaling up electric vehicle battery production using robots

As electric vehicle adoption accelerates and demand increases, the inability to produce batteries in sufficient quantities has emerged as a critical bottleneck in the electric vehicle supply chain. Given the impending climate change crisis, resolving this bottleneck is imperative to accelerate the transition to a zero-emission electric mobility future. One potential solution is the use of robotics for fast and cost-effective assembly of batteries at scale. This study proposes a three-stage digital twin design and analysis method to develop robotic workcells for fast and cost-effective assembly of electric vehicle battery modules. Using digital twin design and simulation, robotic assembly line configurations have been developed for battery module production at different scales. Digital twin analytics was used to evaluate and optimise the proposed robotic battery assembly system for speed and cost. Industrial automation experts were consulted to further improve robotic work cell layouts to minimise investment in robots. Because digital twins of robotic workcells have been used, the configurations of the battery assembly line, as designed and validated, are ready for immediate implementation. For practitioners, this study offers heuristic methods to determine the appropriate assembly line configuration, the required number of robots and humans, for a desired production volume. For researchers, this study outlines promising areas for future investigation.

Additive manufacturing of polypropylene micro and nano composites through fused filament fabrication for automotive repair applications

AbstractThe emerging Additive manufacturing technologies are being adopted by different industries, which require developing new materials and procedures. Here we report the development of polypropylene (PP) based composite materials for fused filament fabrication (FFF) process with the aim of enabling fully automatic robotic repair application of plastic components in automotive industry. A key challenge in repair and joining of polyolefins, which are widely used in such applications, is understanding the interplay of microstructural features and the joining mechanisms employed to achieve a uniform and fully functional repaired components. Specifically, for components manufactured from polypropylene based material, we show that the addition of ethylene propylene diene monomer (EPDM), polyisobutylene (PIB) and carbon black (CB) successfully modifies its matrix and produces a composite material ideal for additively repairing of complex geometries found in the automotive applications. This was brought about by effective reduction of the crystallinity of the composite PP matrix from 46.2% to 34.4% and resulting in a net reduction in warpage of the FFF 3D printed samples. Further, the thermal stability of the developed composite was improved with the addition of a moderate amount of carbon filler, enabling an FFF process with higher hot‐end temperatures, which subsequently allowed for tuning of the raw material's viscosity, and hence ensuring consistent deposition of molten filaments for building successive layers. Mechanical properties' analysis revealed that the addition of 10 wt.% CB increased the true stiffness (storage modulus) by 20%, the impact strength by 62%, with the drop in ultimate tensile strength of 11%. The optimal elongation at break and toughness were achieved for the samples containing 2 wt.% CB increasing these key properties by 62% and 58%, respectively. In terms of the melt flow index (MFI), as a key rheological indicator, the measured value ranged between 12.5 and 19.0 for all compositions suitable for the FFF process. Morphological analysis of the extruded filaments and fracture surface of impact test samples showed a mesoscale interspersion of polymer phases and a proper filler dispersion in the matrix material with sizes ranging from hundreds of nanometers to hundreds of microns. The developed 3D‐printable PP composite filament was successfully used in a robotic cell to repair broken plastic lugs of a car headlight assembly.

New Product Development of a Robotic Soldering Cell Using Lean Manufacturing Methodology

With the advent of manufacturing in Industry 4.0 and consumer demand, there has been a trend of mass customization of products. This customization requirement can only be achieved through the flexibility of manufacturing processes that are tailored to meet the quality standards of customers and the large volume of production in a short time. The increase of the production capacity is achieved through the processes of industrial automation of the manufacture which maintains the increased efficiency for the series production. This study was based on the Design for Six Sigma methodology (DMADV—Define, Measure, Analyze, Design and Verify) in order to determine the soldering process characteristics and how the soldering process can be automatized. When planning the implementation of a collaborative robot in a workstation in the production plant, the following must be taken into account: steps in operations that require the most time for the worker and/or that represent factors of physical and moral overload for him; the use of adequate precision fixing devices, delimitation of work areas, sensors as well as spaces for connecting the workstation to the electrical, hydraulic/pneumatic network and constant cycle time. The proposed solution can improve the productivity of the process by integrating advanced robotics and smart devices into the soldering line.

Digital twin of ABB IRB-120 robotic cell based on the industry 4.0

The evolution of virtual commissioning has enabled significant advances in analysis, safety testing, programming and failure anticipation in projects involving industrial robots. To make this possible, a virtual model equal to the real one is needed and our research objective is to develop the Digital Twin of the ABB IRB-120 process and robot to digitally validate the robotic cell and minimize installation and project implementation time in the “shop floor” in the context of I4 .0 Currently, a major problem related to Virtual Commissioning activities is the lack of precision between the virtual model and the physical model (digital twin), due to difficulties related to mechanical fabrication after model generation 3D The use of the Process Simulate software (SIEMENS PLM), allowed more accurate and real results to commission the robotic cell of the Robotics Advanced Institute - I.A.R. The main analysis tools are shown in this study.

Assessing industrial end-user programming of robotic production cells: A controlled experiment

Adapting the behavior of robots and their interaction with other machines on the shop floor is typically accomplished by non-programmers. Often these non-programmers use visual languages to specify the robot’s and/or machine’s control logic. While visual languages are explored as a means to enable novices to program, there is little understanding of what problems novices face when tasked with realistic adaptation programming tasks on the shop floor. In this paper, we report the results of a controlled experiment where domain experts in the injection molding industry inspected and changed realistic programs involving a robot, injection molding machine, and additional external machines. We found that participants were comparably quick to understand the program behavior with a familiar sequential function chart-based language and a Blockly-based language used for the first time. We also observed that these non-programmers had difficulty in multiple aspects independent of language due to the interweaving of physical and software-centric interaction between robot and machine. We conclude that assistance needs to go beyond optimizing available language elements to include suggesting relevant programming elements and their sequence.

Dynamics and vibration suppression of multi-robot collaborative machining system using transfer matrix method for multibody systems

With the advantages of high efficiency and great flexibility, multi-robot collaborative machining systems have been gradually applied to the manufacturing and assembly of large-scale structural parts such as aerospace components, wind turbine blades, etc. However, due to the collaborative operation of multiple robotic machining cells, the weakly rigid components are subjected to multiple excitations, resulting in complex vibration, which seriously affects their shape accuracy and surface quality. Therefore, it is necessary to study the dynamics of multi-robot collaborative machining systems for high-precision and high-quality applications. In this paper, the dynamic model including several mobile robotic machining cells as well as a large-scale aerospace component is established using the transfer matrix method for multibody systems (MSTMM). The machining configuration of the robots is optimized using the NSGA-II to improve their machining stiffness. Furthermore, the propagation law of vibration waves generated by multiple machining excitations on the component is studied and the cooperative vibration suppression strategy for parallel machining is proposed, which effectively reduces the vibration response at the target machining position and ensures the machining quality. This paper provides an alternative for the applications of multi-robot machining systems in the field of high-precision manufacturing of large-scale components.

On the perception and handling of deformable objects – A robotic cell for white goods industry

• Design and implementation of a robotic system for the manipulation and assembly of linear non-rigid components. • Multi-sensor system for flexible part cognition and safe human-robot interaction. • Dexterous gripper for non-rigid material manipulation. • Control framework for process coordination and safe human -robot collaboration. • Validation and testing in a white goods industry case study. Advancements in mechatronics, perception and computational methods allowed robotics to focus on non-rigid part manipulation, which is characterized by high complexity due to the unpredictable and compliant behavior of flexible materials. This paper presents the automation of a manufacturing process involving linear non-rigid components through the implementation of a robotic system that addresses challenges related to flexible material perception and handling. The corresponding technological approach consists of five steps namely safe material supply, detection, grasping, cross section recognition, and assembly. The proposed robotic cell comprises: (1) a multi-sensor system for flexible part recognition and safe human-robot interaction (2) a collaborative robot equipped with a dexterous gripper for flexible material manipulation, and (3) a control framework for process coordination. The robotic system has been tested on a case study originating from the white goods industry, where rubber gaskets are manipulated and assembled on household appliances. Experimental results proved that the implemented robotic system can tackle the challenges of flexible material manipulation with great consistency in the aspects of robustness and repeatability.

Automated End-Effector Alignment in Robotic Micromanipulation

Proper alignment of the end-effector is a critical procedure that determines the success of micromanipulation, such as robotic cell manipulation. Presently, end-effector alignment is performed manually and suffers from large misalignment error and inconsistency. Manual alignment often undesirably moves the end-effector (e.g., a glass micropipette) out of the limited field of view under microscopy and risks breaking the fragile end-effector. This article presents automated end-effector alignment in robotic micromanipulation. A rotational degree of freedom was added to a standard micromanipulator with translational degrees of freedom. The kinematic model of end-effector’s rotation was established, and the unknown model parameters were calibrated. To accommodate model uncertainty and parameter variations, a sliding mode controller was designed to achieve end-effector alignment. Experimental results demonstrate that the robotic alignment technique achieved an accuracy of 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 0.3^{\circ }$</tex-math></inline-formula> and a time cost of 17.9 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 7.3 s, both significantly less than manual alignment. The developed controller based on kinematic modeling and sliding mode control achieved a higher success rate and significantly less time cost for end-effector alignment than the PID controller. Standard micropipettes were used as the end-effectors for sperm immobilization and oocyte penetration, important procedures in cell surgeries. The success rate of sperm immobilization was 98% by robotic micropipette alignment, higher than the success rate of 90% by manual alignment. Oocyte deformation before penetration was 28.1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 7.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m by robotic end-effector alignment, significantly less than the deformation of 54.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 13.2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m by manual alignment.

Flexible skill-based control for robot cells in manufacturing.

Decreasing batch sizes lead to an increasing demand for flexible automation systems in manufacturing industries. Robot cells are one solution for automating manufacturing tasks more flexibly. Besides the ongoing unifications in the hardware components, the controllers are still programmed application specifically and non-uniform. Only specialized experts can reconfigure and reprogram the controllers when process changes occur. To provide a more flexible control, this paper presents a new method for programming flexible skill-based controls for robot cells. In comparison to the common programming in logic controllers, operators independently adapt and expand the automated process sequence without modifying the controller code. For a high flexibility, the paper summarizes the software requirements in terms of an extensibility, flexible usability, configurability, and reusability of the control. Therefore, the skill-based control introduces a modularization of the assets in the control and parameterizable skills as abstract template class methodically. An orchestration system is used to call the skills with the corresponding parameter set and combine them into automated process sequences. A mobile flexible robot cell is used for the validation of the skill-based control architecture. Finally, the main benefits and limitations of the concept are discussed and future challenges of flexible skill-based controls for robot cells are provided.

Pose optimization and path improvement in robotic drilling through minimization of joint reversals

ABSTRACT Industrial robots have been increasingly adopted in precision manufacturing applications such as aerospace drilling. However, achieving the strict tolerance requirements of the aerospace industry has been a major challenge due to the relatively poor accuracy of robots. One of the major sources of error which has a detrimental effect on the quality and circularity of drilled holes is the static friction in robot joints. These errors are particularly pronounced when one or more joints reverse direction. To improve robot motion for better hole quality, this paper proposes an optimization framework to eliminate or minimize joint reversals throughout a drilling motion. A general robotic drilling motion with a redundant degree of freedom due to the twist of the tool is first modeled. Particle Swarm Optimization (PSO) is then used for strategic pose selection considering the entire drilling motion. Experimental tests performed on a KUKA KR 6 R700-2 show a 40% reduction in the tool deviation envelope. The proposed technique can be readily implemented on any commercial robotic drilling cell without interfering with the controller.

Increasing the Sustainability of Manufacturing Processes in Plastic Injection: Recovering Out-Of-Service Robots to Eliminate Manual Assembly Operations

In the 20th century, there was a burst concerning the development of the automobile industry, which has become an essential asset for society. With its evolution, this industry created a foundation that based its competitiveness on satisfying people’s needs with the highest possible quality and always respecting the delivery deadlines. With the growth in demand, the improvement of certain processes was needed to achieve the desired production goals, accomplished through automation and robotics, as production and assembly lines increasingly used fully automated processes. In plastic injection lines, production is constant and carried out quickly, so it is desirable to perform component assembly steps that immediately support the output of the injection mould parts. This work consists of adapting an obsolete robotic cell to be implemented in one of the production lines to insert components into the injected parts, replacing labour work. Through a mechanical project and an automation design, the equipment was concluded and is currently in production, fulfilling the necessary requirements and improving the process’ cycle time. This proves that it is possible to recover old equipment, which is able to improve current tasks and common needs in modern industry, increasing the economic sustainability of the processes and saving resources.

Scheduling of Multi-Robot Job Shop Systems in Dynamic Environments: Mixed-Integer Linear Programming and Constraint Programming Approaches

This paper investigates a dynamic scheduling problem within a job shop robotic cell, wherein multiple robotic arms are responsible for material handling in a U-shaped arrangement. Each robotic arm has access to specific workstations based on their distance in the cell layout. Therefore, a part may need to be exchanged between several robots according to its process plan. For this purpose, intermediate buffers are positioned between each pair of consecutive robots. Due to the dynamic nature of the problem, new jobs arrive at unpredictable times, which in turn necessitates rescheduling taking the system’s current state into account. To tackle this problem, firstly, a Mixed-Integer Linear Programming (MILP) model is devised. Secondly, three distinct Speed-up Constraints (SCs) derived from the problem’s inherent characteristics are designed and implemented to accelerate the MILP model’s solving procedure. Afterward, the problem is formulated using Constraint Programming (CP) approach. The performance of the CP model and the MILP model in presence of all possible combinations of the SCs are evaluated and compared through solving various random instances. Next, an analysis is performed on the buffers’ pick-up criterion and how it is affected by the problem’s size. Besides, the impact of changes in the robots’ speed on the productivity of the cell is assessed. Finally, the extent to which the rescheduling priority affects the output of the model is studied.

Reinforcement Learning Enabled Self-Homing of Industrial Robotic Manipulators in Manufacturing

Industrial robotics has been playing a major role in manufacturing across all types of industries. One common task of robotic cells in manufacturing is called homing, a step that enables a robotic arm to return to its initial / home position (HPos) from anywhere in a robotic cell, without collision or experiencing robot singularities while respecting its joint limits. In almost all industrial robotic cells, an operation cycle starts from, and ends to HPos. The home position also works as a safe state for a cycle to restart when an alarm or fault occurs within the cell. When an alarm occurs, the robot configuration in the cell is unpredictable, thus challenging to bring the robot, autonomously and with safety at HPos and restart the operation. This paper presents a non-vision, reinforcement learning-based approach of a parallel-agent setting to enable self-homing capability in industrial robotic cells, eliminating the need of manual programming of robot manipulators. This approach assumes the sensing of an unknown robotic cell environment pre-encoded in the state definition so that the policies learned can be transferred without further training. The agents are trained in a simulation environment generated by the mechanical design of an actual robotic cell to increase the accuracy of mapping the real environment to the simulated one. The approach explores the impact of certain curriculum on the agent’s learning and evaluates two choices, compared to a non-curriculum baseline. A parallel-agent, multi-process training setting is employed to enhance performance in exploring the state space, where experiences are shared among the agents via shared memory. Upon deployment, all agents are involved with their respective policies in a collective manner. The approach has been demonstrated in simulated industrial robotic cells, and it has been shown that the policies derived in simulation are transferable to a corresponding real industrial robotic cells, and are generalizable to other robotic systems in manufacturing settings.

Green smart manufacturing: energy-efficient robotic job shop scheduling models

ABSTRACT Smart manufacturing has boosted the wide application of mobile robots in robotic cells for automated material delivery. However, the mismatching between machine production process and robot movement process causes extensive energy waste. Nevertheless, most existing robotic job-shop scheduling (RJSP) studies mainly focus on minimising makespan but overlook the low energy efficiency problem faced by robotic cells. Motivated by the importance of green smart manufacturing, in this study, we innovatively propose to achieve robotic cell energy saving through coordinating the machine production process and robot movement process. Specifically, both machines and the mobile robot can flexibly adjust operating speeds with a V-scale speed framework. Two novel energy-efficient RJSP approaches (i.e. the RJSP-E and the RJSP-EM) are thus proposed. The RJSP-E focuses on minimising energy consumption, while the RJSP-EM simultaneously considers makespan (i.e. productivity) and energy consumption. Through computational experiments, the RJSP-E demonstrates superior performances in reducing energy consumption (15% on average), at a loss of productivity (20% on average). On the other hand, the RJSP-EM can select the most suitable energy-saving operating speeds without much sacrifice in productivity. Notably, the RJSP-EM can reduce energy consumption by a mean of 10% even without increasing makespan. The RJSP-EM also demonstrates higher solution efficiency.

Выращивание фибробластов кожи человека с использованием роботизированной системы: сравнение технологий ручного и автоматизированного культивирования

Выращивание фибробластов кожи человека с использованием роботизированной системы: сравнение технологий ручного и автоматизированного культивированияScale-out cultivation of human dermal fibroblasts using robotic cell culture system: comparison of manual and automated processing