Manual Robot Structural Analysis 2016
The robot's physical structure is essentially the manipulator. This manipulator is comprised of a structural frame with provisions for supporting mechanical linkage and joints, guides, actuators (linear or rotary), control valves, sensors, and communications within the manipulator. The physical dimensions, reach, and payload (weight carrying ability) depend on robot model and application. The application requirements determine the needed specifications. These specifications can introduce hazards to workers who may be integrating, operating, and/or maintaining the robot application. See the Hazards Associated with Industrial Robot Applications section of this chapter for more about these hazards.
Manual Robot Structural Analysis 2016
Most robot systems are set up for application by programming using a teach pendant (a portable control device) while in manual mode. In manual mode, a trained worker (programmer) typically uses a teach pendant to teach a robot its task(s) manually. During the manual mode of operation, the programmer performing the teaching must have control of the robot and associated equipment and should be familiar with the operations to be programmed, system interfacing, and control functions of the robot system, application, and other equipment. When systems and/or applications are large and complex, it could be possible to improperly activate functions. Since the programmer doing the teaching can be within the restricted space, such mistakes can result in injuries. See the Hazards Associated with Industrial Robot Applications section of the chapter for more about the hazards.
Employers should ensure that the integrator has designed and implemented a safe robot application. This requirement is typically accomplished by including the ANSI/RIA R15.06-2012 and RIA TR R15.606-2016, Collaborative Robot Safety, compliance requirements in the Statement of Work (SOW) for a robotic integration contract. It must then be verified that compliance has been achieved (usually during site acceptance).
Special consideration must be given to the teacher or worker who is programming the robot. In manual mode, a trained programmer programs the robot, typically using a portable control station (a teach pendant). Robot speeds during these programming sessions are at a reduced speed, less than 10 inches (250 mm) per second.
While in manual mode, the teacher must have control of the robot and associated equipment. The teacher should be familiar with what needs to be programmed, system interfacing, and control functions of the robot and other equipment in the application. When systems are large and complex, it could be possible to improperly activate functions. Since the teacher can be within the restricted space, mistakes can result in injuries. Mistakes in programming can result in unintended movement or actions with similar results. For this reason, robot speeds should be placed at a reduced speed of 10 inches per second (250 mm/second) or less on any part of the application during teaching to decrease the likelihood of contact and minimize the potential of injuries.
When maintenance, repairs, and/or troubleshooting must be performed with power on and with maintenance workers performing their work within the safeguarded space, the robot should be in manual mode. Additional hazards can be present during this manual mode because some of the robot application safeguards may not be active and functioning as during automatic mode. To protect maintenance and repair workers, safeguarding techniques and procedures as stated in the ANSI/RIA R15.06-2012 Part 2, Sections 5.9.7, 5.10.2, 5.12.1, 7.2.7 are recommended.
There are two ways that PFL capability can be provided. One is by inherently safe design of the robot (e.g., low energy potential due to very low payload and/or speed capability). Another is by control means, which is described as by safety functions using sensors and safety-related parts of the control system (SRP/CS) (e.g., torque sensors on all joints to safety logic that will slow or stop the robot). PFL robots that have the capability to limit energy transfer have safety functions that are configured, so contact pressures and forces do not exceed acceptable limits. The typical safety functions are speed limiting, force limiting, and power limiting. Collaborative applications using PFL robots usually operate at much lower speeds and payloads than they are physically capable. This is so that when the robot contacts a worker, not only does the robot stop quickly, but also the robot is not moving with enough energy to cause injury. [Note: robot contact with sensitive body regions (e.g., the face, temples, and throat) is to be prevented or avoided per RIA TR R15.606-2016.]
A provision of ANSI/RIA R15.06-2012 is that each robot application should have an RA performed and documented prior to commissioning. However, the presence of an RA is not by itself sufficient to ensure that the application meets the intended purpose of ANSI/RIA R15.06-2012, which is to protect workers from injury. Refer to ANSI/RIA R15.06-2012 and to RIA TR R15.306-2016 for guidance on the RA process.
In most circumstances, the robot application automatically achieves a safe state when a worker enters the safeguarded space (Figure IV-7). However, there are some circumstances in which a worker needs to perform a task that will require them to interact with a robot application that is still active (e.g., programming or teaching the system). In an industrial robot application, worker safety while within the safeguarded space is based on the application being in manual mode while using an enabling device (often integrated into the teach pendant) with the robot operating at a reduced speed. The application layout design needs to provide adequate clearance. Because the enabling device is typically a 3-position device, the worker must hold it in the center-ON position, otherwise the robot system's motion will be inhibited. If the enabling device is interconnected with other equipment in the application, then the other equipment will be similarly inhibited from operation.
As already explained, enabling devices are used during manual mode, sometimes also known as teach or T1 mode. In this mode, the robot system operates at a reduced speed, slow enough for a person to avoid hazardous contact, but not greater than 10 inches/second (250mm/second).
Typically, the manufacturer's manual will list the safety functions provided that can be used to enable the implementation of collaborative application (e.g. safety functions that limit speed, force, positions, and momentum which would be needed for PFL). Additionally, a third-party can certify the safety functions that are provided with a robot and robot application. A robot application can use one or more safety functions to achieve a SSM, HGC, PFL or SSM/PFL application, or a combination of these.
For each of these combinations (type of contact event and body region contacted), RIA TR R15.606-2016 provides the permissible biomechanical limits for force and contact pressure based on the location of the body being contacted. These limits are intended to avoid pain during contact events. [Note: robot contact with sensitive body regions (e.g., the face, temples, and throat) is to be prevented or avoided per RIA TR R15.606-2016.]
RIA TR R15.606-2016 also provides guidance on the allowable speed to stay within the biomechanical limits during a transient contact event. See also RIA TR R15.806-2018, Testing Methods for Power & Force Limited Collaborative Applications, for specific guidance on how to measure pressure and forces. Then use this guidance to compare the pressures and other forces to the permissible biomechanical limits. The integrator should use the robot manufacturer's information (i.e., moving mass of the manipulator, speed capabilities) combined with the payload mass of the end-effector and/or workpiece to determine the maximum allowable speed for contact events.
This appendix outlines key steps to perform during a RA with examples of how to determine the necessary risk reduction measures needed to adequately reduce risk. This appendix is based on RIA TR R15.306-2016 and does not necessarily cover all RA aspects that may be needed for a robot system and/or application. See the Risk Assessments (RAs) and Risk Reduction Measures sections.
Health monitoring of automated manual transmission (AMT) in modern vehicles can play a critical role to avoid its malfunctions and ensure vehicle functional safety. In order to meet this demand, this paper presents a model-based fault detection and identification (FDI) scheme for AMT. After developing the fault model of AMT, structural analysis (SA)-based fault detectability and isolability is realized with the available set of sensors, prior to design and development of residuals. The residuals are generated by employing the theory of SA, where the concepts of analytical redundant relationship (ARR) are utilized to make residuals stable and robust. Finally, the proposed FDI scheme is successfully evaluated to detect and isolate the sensor faults in EcoCAR2 AMT.
Between December 2012 and December 2014, we successfully used the sponge in ten robot-assisted and ten direct manual laparoscopic operations to achieve haemostasis, for blunt dissections, for atraumatic lifting of solid organs, to check for bile leaks, for cleaning the surgical field thus avoiding frequent use of suction or the application of haemostatic agents. The reason of the insertion (RI), the main use (MU) and any further use (FU), once inserted, were registered for each operation and compared between the two groups.
During the manual training, the trainer has to keep watching the rat cyborg and send the control commands of electrical stimuli repeatedly. There are three major problems of manual training. First, the trainer should be professional in rat cyborg training. It is hard for an inexperienced person to train a rat cyborg well. Second, the trainer is required to be highly concentrated all the time. The fatigue may lead to some manual misoperation, since the whole procedure is very time-consuming and tedious. Third, the learning states and behaviors of the rat cyborg cannot be recorded for quantitative analysis and personalized parameter configuration, which may be very helpful for further research. 350c69d7ab