The National Institute of Standards and Technology, Intelligent Systems Division has collected data measuring human subjects, while performing common, simulated industrial manufacturing tasks with and without wearing an exoskeleton. Five tests were completed as part of a research study to develop measurement science towards standard test methods. For simulated industrial manufacturing tasks were performed using a novel, now standardized apparatus, called the Position and Load Test Apparatus for Exoskeletons (PoLoTAE). In addition, a set of novel optical tracking marker artifacts were worn by the subject for synchronous tracking of exoskeleton and human leg position and orientation. The standard test artifacts were intended to address the challenges of measurement uncertainty variation between different marker clusters and marker movement on soft tissue and marker occlusion when using traditional bio-mechanical marker models while wearing an exoskeleton. The PoLoTAE tests simulated generic industrial tasks (load positioning, load alignment, peg-in-hole, applied force). The knee bend tests were performed to synchronously track the exoskeleton and human lower limb position and orientation for analysis such as comparing the exoskeleton fit to the subject’s leg.Overall, the tests included 116 subjects of which 68 subjects (59% of total subjects) consented to publication of their raw test data described in this paper. While some subjects performed more than one test, at least 30 subjects performed each of the five tests totaling 158 tests performed. To date, aggregate data for the load positioning and knee bend tests have been analyzed and are referenced in this paper. Sensor data was collected from each subject, which included: repetition number, heart rate, videos, skeletal joint pose estimation, and survey data.

NIST is developing metrics and test methods to benchmark the performance of robotic systems when performing manufacturing tasks. The ability to perform simple insertions is critical for robotic systems in manufacturing. A simple peg-in-hole test was designed to measure a robotic system's capability for performing these simple insertions. The dataset captures the performance metrics of a robotic system outfitted with a robotic hand and a robotic gripper to study the effect of next-generation robotic hand technology versus conventional parallel gripper technologies.

NIST is developing metrics and test methods to benchmark the performance of robotic systems when performing manufacturing tasks. The ability to perform simple insertions is critical for robotic systems in manufacturing. A simple peg-in-hole test was designed to measure a robotic system's capability for performing these simple insertions. The dataset captures the performance metrics of a robotic system outfitted with a robotic hand and a robotic gripper to study the effect of next-generation robotic hand technology versus conventional parallel gripper technologies.

Red, Green, and Blue (RGB) and depth markerless body tracking systems were applied for industrial exoskeletons. The original images and their body tracking results are described in this data set. The data set describes the body tracking result changes by exoskeletons, industrial task poses, and camera viewpoints. A full-body exoskeleton, an upper-body exoskeleton, and an exosuit are used in the test. Stand, bend forward, squat, and crouch are defined as industrial poses with stretching arms forward, forward-up, up, forward-down, or down. The original images for body tracking were captured from front, side-front, side, side-back, and back from the subject with straight or top-down vertical viewpoints. The acceptability of body tracking results was evaluated for classifying usable data for exoskeleton performance analysis. The data set includes the original images, body tracking overlaid images, representative body tracking results, and acceptability evaluation results. A manuscript publication associated with his data publication is in progress. DOI will be provided when ready.Disclaimer: Certain commercial equipment, instruments, or materials are identified in this paper to foster understanding. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.

,As part of the research work, algorithms were developed to extract business rules from the content of document texts and an evaluator of these rules was developed to verify whether other related documents are correct in the context of the identified rules. The problem is related to the interpretation of so-called deontic expressions. These expressions have a structure that expresses in natural language certain rules that may or may not be fulfilled when certain events occur. Rule evaluation boils down to the calculation of a logical true/false value depending on the values of the variables associated with the event, which are evaluated according to the definition of the rule algorithm. In scientific work on the subject, a certain classification of these rules is usually adopted, depending on how their implementation affects the events occurring in a given context. Rule modality in the most general terms divides rules into permissive rules (allowing certain events), obligatory rules (specifying that certain events must occur) and invariant rules, which must always be true. Due to the distinctive area of operation, it was assumed that the domain context to be considered would primarily concern the validation of rules set out in contracts defining obligations to counterparties in relation to invoices issued between counterparties. An additional assumption was that the solution should primarily work for the Polish language, which is important for the market on which the Beneficiary operates. The problem thus defined was solved using natural language processing (NLP) techniques.,

ㅇ 한국산업기술시험원이 축적/가공한 업체별 시험검사 진행 실적 데이터입니다.ㅇ 시험인증이란 제조, 수입 및 판매를 목적으로 하는 기자재에 요구되는 기술기준 또는 규정 등에 적합한지 여부를 평가하고, 안전성 및 신뢰성 등을 확보하는 제도입니다.ㅇ 이러한 시험인증을 통해 소비자는 기기안전성을 보장받고, 판매자는 기업과 기기의 신뢰성을 보장받으며, 시장 전체적으로는 불량품 양산 축소 및 기기의 고품질 성장화를 보장 받습니다.ㅇ 제품의 제조, 수입 및 판매에 시험인증이 필수적으로 진행되어야 하기 때문에, 시험인증 접수 데이터를 통해 다양한 산업분야의 동향을 파악할 수 있습니다.

N/A

The work-cell is an essential industrial environment for testing wireless communication techniques in factory automation processes. A graph database approach to storing and analyzing network performance data from a manufacturing factory work-cell is introduced. A robotic testbed performs a pick-and-place task using two collaborative grade robot arms, machine emulators, and wireless communication devices. A graph database is implemented to capture network data and operational event data among the actors within the testbed. Using a proposed schema, the database is then populated with events from the testbed and the resulting graph is constructed. Query commands are then presented to examine and analyze network performance and relationships within the actors of the network. The resulting data from the experiments conducted are included in this dataset.