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Purpose The study aims to evaluate the capability of a machine vision camera and software to recognize fasteners for the purpose of assembly verification. This will enable the current assembly verification system to associate torque verfication with a specific fastener. Design/methodology/approach A small camera is installed at the head of a tool near the socket. The camera is used to capture images surrounding the fastener, and feeding them into machine vision recognition software. By recognizing unique features around the fastener, the fastener can be uniquely identified and therefore verified to be assembled. Additional filtering and multiple frame recognition will improve the reliability of the recognition. Findings The machine vision technology is found to be adequately reliable in identifying fasteners after tuning key threshold parameters and requiring multiple positively recognized frames. The time to verify can be kept around a fraction of a second to prevent impacting assembly speed. Research limitations/implications This experiment was run under simulated assembly line lighting conditions. It also does not explore industrial remote head industrial camera hardware. Practical implications By using a remote-mounted camera in combination with electric tools, a reliable assembly verification system can be used to eliminate torque check processes of critical fasteners, thereby reducing the cost of assembly. Originality/value Currently, assembly verification is done only using the torque values. In automated assembly line, each process might involve fastening multiple fasteners. Using this system, a new level of assembly verification is achieved by recording the assembled fastener and its associated torque.

Purpose -The purpose of this paper is to create an assembly verification system that is capable of verifying complete assembly and torque for each individual fastener. Design/methodology/approach -The 3D position of the tool used to torque the fastener and the assembly pallet will be tracked using an infrared (IR) tracking system. A set of retro-reflective markers are attached to the tool and assembly while being tracked by multiple IR cameras. Software is used to triangulate the relative position of the tool in order to identify the fastener being torqued. The torque value is obtained from the tool controller device. By combining the location of the tool and the torque value from the tool controller, assembly of each individual fastener can be verified and its achieved torque recorded. Findings -The IR tracking is capable of tracking within 2-3 mm for each tracking ball, with a resulting practical resolution of 24 mm distance between fasteners while maintaining 99.9999 per cent reliability without false positive fastener identification. Research limitations/implications -This experiment was run under simulated assembly line lighting conditions. Practical implications -By being able to verify assembly reliably, the need for manual torque check is eliminate and hence yield significant cost savings. This will also allow programming electric tools according in real time based on the fastener in proximity identification. Originality/value -Currently, assembly verification is only done using the torque values. In automated assembly line, each process might involve fastening multiple fasteners. Using this system, a new level of assembly verification is achieved by recording the assembled fastener and its associated torque.

The vision-based approach to mobile robot navigation is considered superior due to its affordability. This paper aims to design and construct an autonomous mobile robot with a vision-based system for outdoor navigation. This robot receives inputs from camera and ultrasonic sensor. The camera is used to detect vanishing points and obstacles from the road. The vanishing point is used to detect the heading of the road. Lines are extracted from the environment using a canny edge detector and Houghline Transforms from OpenCV to navigate the system. Then, removed lines are processed to locate the vanishing point and the road angle. A low pass filter is then applied to detect a vanishing point better. The robot is tested to run in several outdoor conditions such as asphalt roads and pedestrian roads to follow the detected vanishing point. By implementing a Simple Blob Detector from OpenCV and ultrasonic sensor module, the obstacle's position in front of the robot is detected. The test results show that the robot can avoid obstacles while following the heading of the road in outdoor environments. Vision-based vanishing point detection is successfully applied for outdoor applications of autonomous mobile robot navigation.

A mechanical assembly aims to remove 6 degree-of-freedom (DOF) motion between two or more parts using features such as fasteners, integral attachments, and mating surfaces, all of which act as constraints. The locations, orientations, and quantity of these constraints directly influence the effectiveness of a constraint configuration to eliminate DOF; therefore, constraint design decisions are crucial to the performance of a mechanical assembly. The design tool presented in this paper uses an analysis tool developed by the authors to explore a user-specified constraint design space and help the designer make informed decisions based on quantitative data so as to optimize constraint locations and orientations. The utility of the design tool is demonstrated with an assembly case study that contains both threaded fasteners and integral attachments. The results identify the opportunity for significant improvements by separately exploring individual design spaces associated with some constraints and further gains through a search of a multidimensional design space that leverages interaction effects between the location and orientation variables. The example also highlights how the tool can help identify nonintuitive solutions such as nonrectilinear, nonplanar parting lines. A trade-off study demonstrates how the design tool can quantitatively aid in optimizing the total number of constraints. Adding constraints generally improves an assembly's performance at the expense of increased redundancy, which can cause locked-in stresses and assembly inaccuracies, so the design tools helps identify new/removable constraints that offer the greatest/least contribution to the overall part constraint configuration. Through these capabilities, this design tool provides useful data to optimize and understand mechanical assembly performance variables.