Geometric Dimensioning Research Articles

Measurement systems analysis for beam compensation, scaling factors and geometric dimensioning for a metallic additively manufactured test artifact

Measurement systems analysis for beam compensation, scaling factors and geometric dimensioning for a metallic additively manufactured test artifact

Design and operation of an adiabatic compressed air energy storage system incorporating a detailed heat exchanger model

Heat exchangers (HEXs) are among the key components of adiabatic compressed air energy storage (A-CAES) systems. However, the existing HEX models applied in the A-CAES systems are overly simplistic, limiting research regarding design and operational simulation. For the first time, this study incorporates a comprehensive HEX model, including calculations for geometric dimensioning, heat transfer, and pressure drop, into the A-CAES system model; in addition, a novel layered, interactive system design and operational simulation algorithms are developed. The developed models and algorithms can facilitate the design process and yield reasonable operational simulation results with only basic parameters. The design algorithm can determine all key parameters of the system and assess the effect of the HEX pressure drop and heat transfer area on the system performance. The operational simulation algorithm considers the performance of all key equipment under off-design conditions. The design exergy efficiency and daily net income of the system are 73.15 % and $26,998, respectively; however, these values decrease during operation to 72.15 % and $25,034, respectively. A comprehensive analysis of the key parameters during operation revealed that the primary causes for the degradation were the sliding pressure in the energy storage process and variations in the air storage tank parameters.

Precise Enough For Outer Space

Abstract For manufacturers, the ability to produce parts from designs reliably is critical. Because simple blueprints don’t convey enough information, Geometric Dimensioning and Tolerancing, or GD&T, has become a standard symbolic language for communicating properties such as form, location, orientation, size, and function. The ASME Video Production Team recently visited GT Machine and Tool Co. in Long Island City, N.Y., to talk with company president Dean Theodos about how GD&T enabled its machine shop to produce all kinds of parts.

Characterizing Roundness for Geometric Dimensioning and Analysis

Roundness as a measurable geometric value plays a critical role in a wide variety of applications where precise dimensioning of 2D shapes is essential. Understanding the mathematical bases for defining 2D roundness in general, as well as techniques for roundness measurement, offers us a valuable framework for tackling metrological challenges across scientific and industrial settings.

Research on motor rotation anomaly detection based on improved VMD algorithm

PurposeThe electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.Design/methodology/approachThe VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.FindingsThis paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.Originality/valueBy using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

Automatic raster engineering drawing digitisation for legacy parts towards advanced manufacturing

Mechanical engineering drawings are commonly used in multiple industries, carrying essential information about the design and technical specifications of the parts they define. With large industry sectors shifting to advanced manufacturing processes and technologies such as additive manufacturing, arises the need for systems checking whether legacy parts described by engineering drawings can be optimally produced. To this end, the digitisation of engineering drawings has become the key issue for the following computer-aided engineering tasks towards advanced manufacturing. This paper presents a pipeline for information extraction in raster mechanical engineering drawings through a combination of traditional and deep-learning-based computer vision techniques. Object detection and text recognition techniques are implemented to achieve automatic interpretation of engineering drawings. A dataset of 217 industrial engineering drawings is created to evaluate the proposed method. Different types of information within engineering drawings, including information blocks, views, dimensions, and Geometric Dimensioning and Tolerancing (GD&T) information, are extracted automatically. A case study of engineering drawing digitisation for a complex part is presented to illustrate the effectiveness of the proposed method.

Integration of Deep Learning for Automatic Recognition of 2D Engineering Drawings

In an environment where manufacturing precision requirements are increasing, complete project plans can consist of hundreds of engineering drawings. The presentation of these drawings often varies based on personal preferences, leading to inconsistencies in format and symbols. The lack of standardization in these aspects can result in inconsistent interpretations during subsequent analysis. Therefore, proper annotation of engineering drawings is crucial as it determines product quality, subsequent inspections, and processing costs. To reduce the time and cost associated with interpreting and analyzing drawings, as well as to minimize human errors in judgment, we developed an engineering drawing recognition system. This study employs geometric dimensioning and tolerancing (GD&T) in accordance with the ASME (American Society of Mechanical Engineers) Y14.5 2018 specification to describe the language of engineering drawings. Additionally, PyTorch, OpenCV, and You Only Look Once (YOLO) are utilized for training. Existing 2D engineering drawings serve as the training data, and image segmentation is performed to identify objects such as dimensions, tolerances, functional frames, and geometric symbols in the drawings using the network model. By reading the coordinates corresponding to each object, the correct values are displayed. Real-world cases are utilized to train the model with multiple engineering drawings containing mixed features, resulting in recognition capabilities surpassing those of single-feature identification. This approach improves the recognition accuracy of deep learning models and makes engineering drawing and image recognition more practical. The recognition results are directly stored in a database, reducing product verification time and preventing errors that may occur due to manual data entry, thereby avoiding subsequent quality control issues. The accuracy rates achieved are as follows: 85% accuracy in detecting views in 2D engineering drawings, 70% accuracy in detecting annotation groups and annotations, and 80% accuracy in text and symbol recognition.

AN APPROACH FOR THE INCLUSION OF LOADING CONDITIONS IN A POLYHEDRAL-BASED METHOD FOR EARLY VARIATION MANAGEMENT

AbstractThe variation management and product quality processes are important tasks to guarantee the assemblability of the systems, the scrap reduction and to avoid delays on production and launching. The compound of activities in Geometric Dimensioning and Tolerancing (GD&T) are necessary, especially in the early design stages, to take into account variations of different nature and from different sources. In this paper, an approach for considering the loading conditions in a polyhedral-based approach in tolerancing design is presented. The load boundary conditions are represented as additional displacement restrictions in the deviation space. The restrictions imposed by the physical limits of a system, the ones coming from the loading conditions and the degrees of freedom (DoF) can be all described and represented with a single polyhedron operand. The approach is illustrated using a simplified 2-D model for both ideal and non-ideal geometry. A 3-D model describing an unilateral contact is presented as a case study using Skin Model Shapes. By taking into account geometrical form defects, external loads, and the kinematics of the system, its sensitivity to variations can be reduced even from early design stages.

Using semantic Geometric Dimensioning and Tolerancing (GD &T) information from STEP AP242 neutral exchange files for robotic applications

This article proposes the use of Geometric Dimensioning and Tolerancing (GD &T) information from STEP AP242 for robotic manufacturing applications. This information can be directly added to the relevant features of the 3D model as per Model Based Definition methodology during the design phase of the product life cycle. STEP AP242 neutral exchange files enable the availability of product definition at the downstream operations, thus completing the Digital Thread as part of Industry 4.0 practices. This article discusses two methods; using custom Unicode strings and the standard entities; for including GD &T using the STEP AP242 Edition 2 neutral file exchange format. A method to form a single Unicode string to add all the GD &T information to the STEP files is described in this paper. The GD &T information in the Unicode string is fully semantic and can easily be parsed to extract the relevant PMI for tolerance analysis. A novel process of extracting and interpreting the relevant PMI for robotic manufacturing applications is described in detail. This article discusses various applications of this information for robotic manufacturing through two use-cases using the second edition of the STEP AP242 standard.

The concept of surveying set for geometrical dimensioning of difficultly accessible objects

The concept of surveying set for geometrical dimensioning of difficultly accessible objects

Optical character recognition on engineering drawings to achieve automation in production quality control

Introduction: Digitization is a crucial step towards achieving automation in production quality control for mechanical products. Engineering drawings are essential carriers of information for production, but their complexity poses a challenge for computer vision. To enable automated quality control, seamless data transfer between analog drawings and CAD/CAM software is necessary.Methods: This paper focuses on autonomous text detection and recognition in engineering drawings. The methodology is divided into five stages. First, image processing techniques are used to classify and identify key elements in the drawing. The output is divided into three elements: information blocks and tables, feature control frames, and the rest of the image. For each element, an OCR pipeline is proposed. The last stage is output generation of the information in table format.Results: The proposed tool, called eDOCr, achieved a precision and recall of 90% in detection, an F1-score of 94% in recognition, and a character error rate of 8%. The tool enables seamless integration between engineering drawings and quality control.Discussion: Most OCR algorithms have limitations when applied to mechanical drawings due to their inherent complexity, including measurements, orientation, tolerances, and special symbols such as geometric dimensioning and tolerancing (GD&T). The eDOCr tool overcomes these limitations and provides a solution for automated quality control.Conclusion: The eDOCr tool provides an effective solution for automated text detection and recognition in engineering drawings. The tool's success demonstrates that automated quality control for mechanical products can be achieved through digitization. The tool is shared with the research community through Github.

SYSML4TA: A SysML Profile for Consistent Tolerance Analysis in a Manufacturing System Case Application

Tolerance analysis is a key engineering task that is usually supported by domain-specific analysis models and tools that are generally not connected to the system functionality. The model-based system engineering (MBSE) approach is a potential solution to this limitation, but it has not yet been deeply explored in this type of mechanical analysis, for which some problems need to be explored. One of these issues is the capacity of languages such as SysML to describe solution principles based on active surfaces that participate in functionality and are present for tolerance analysis. Thus, this study explored the possibilities that enable SysML to represent these geometries and their mathematical relationships based on Topologically and Technologically Related Surfaces (TTRS) theory and aligned with Geometric Dimensioning and Tolerancing (GD&T) standards. Additionally, the capacity of SysML to assure the consistency of tolerance analysis models is also explored, due to the limitations identified in analysis languages like Modelica. In this context, this paper presents a SysML profile for tolerance analysis modeling (SysML4TA), containing domain-specific semantics (concepts and constraints) to assure the completeness of the analysis models and consistency between the different models considered in the integrated model of the system. Finally, a case study applied to a manufacturing context is presented to validate the capacity of SysML to solve the identified problems.

Application of the multi-stage centrifugal compressor 1D loss model in the adiabatic compressed air energy storage

A compressor is the core equipment used to convert and store energy in an adiabatic compressed air energy storage system. However, existing compressor models cannot be used for design and detailed loss analyses, which in turn makes simulations of the energy storage process inadequate. In response to this problem, a 1D loss model was developed and applied to an adiabatic compressed air energy storage system to realize compressor design and simulate the compression process. In the design section, based on the 1D loss model and novel optimization algorithms for the stage distribution and single-stage compressor design, we achieved detailed geometric dimensioning of every single-stage compressor and analyzed the energy loss distribution in each representative single-stage compressor. In the simulation session, we generated performance maps of the single-stage and multi-stage compressors under both speed and variable inlet guide vane regulations. Furthermore, the performance maps were combined with heat exchanger and air storage tank models to simulate the entire energy-storage process. The results show that through variable inlet guide vane regulation, the adiabatic compressed air energy storage system has good flexibility to meet different demands under fluctuating renewable energy flows.

A Functional Classification of Text Annotations for Engineering Design

Describing and supplementing geometric shapes (parts) and layouts (assemblies) with relevant information is key for successful product design communication. 3D annotation tools are widely available in commercial systems, but they are generally used in the same manner as 2D annotations in traditional engineering drawings. The gap between technology and practices is particularly evident in plain text annotations. In this paper, we introduce a functional classification of text annotations to provide an information framework for shifting traditional annotation practices towards the Model-Based Definition (MBD) paradigm. In our view, the current classification of dimensions, tolerances, symbols, notes, and text does not stress the inherent properties of two broader categories: symbols and text. Symbol-based annotations use a symbolic language (mostly standardized) such as Geometric Dimensioning and Tolerancing (GD&T) to provide precise information about the implications of geometric imperfections in manufacturing, whereas notes and text are based on non-standardized and unstructured plain text, and can be used to convey design information. We advocate that text annotations can be characterized in four different functional types (objectives, requirements, rationale, and intent), which should be classified as such when annotations are added to a model. The identification and definition of a formalized structure and syntax can enable the management of the annotations as separate entities, thus leveraging their individual features, or as a group to gain a global and collective view of the design problem. The proposed classification was tested with a group of users in a redesign task that involved a series of geometric changes to an annotated assembly model.

Application of evidence theory in fatigue reliability analysis for impellers with consideration of hybrid uncertainties

This paper carries out a fatigue reliability analysis for impellers used in hydraulic pumps, with the consideration of both aleatory uncertainty on the geometric dimensioning, material property, load borne, and epistemic uncertainty on the fatigue strength coefficient and fatigue strength exponent. First of all, the Basquin's law is introduced and utilized as the basis for the fatigue reliability modeling. Afterwards, on the foundation of aleatory uncertainty modeling, a parametric finite element simulation analysis is executed to extract the dispersive characteristics of the strain response combining with the construction of interval model to quantify the epistemic uncertainty of fatigue model parameters. Finally, the fatigue reliability evaluation of the impeller with the hybrid uncertainty of probability-interval is implemented, and the belief and plausibility curves of the impeller fatigue reliability are obtained, respectively. It is found that the reliability evaluation results obtained from the fatigue strain range obeying a lognormal distribution is more conservative, compared with those obtained from the fatigue strain range obeying a Normal distribution. Such an observation can provide guidance for promoting the further reliability design and optimization of impellers.

The Impact of Hands-on Geometric Dimensioning and Tolerancing Intervention Activities on Students in Engineering Design

The Impact of Hands-on Geometric Dimensioning and Tolerancing Intervention Activities on Students in Engineering Design

Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model

ABSTRACT Machining tools are vital components of intelligent manufacturing systems whose state and remaining useful life (RUL) determine product quality. Specifically, the wearing of tool reduces its capability of production yield and diminishes product quality. Therefore, a capability-based RUL prediction approach is proposed in this paper to thoroughly evaluate the state and RUL of machining tools. First, the connotation of tool capability is discussed, and a framework for quality assurance capability-based RUL prediction is proposed. Product quality, which can be used to assess the capability of tool, is modelled and expanded to consider non-geometric dimensioning and tolerancing (non-GD&T) features based on the classic geometric dimensioning and tolerancing (GD&T) system. Second, a physics-based model of process is developed to estimate the non-GD&T features and calculate tool wear. Third, a hybrid data-driven and physics-based model is developed to quantitatively assess the capability of tool based on the comprehensive quality estimation. Finally, a case study of rolling machining tool is carried out to verify the effectiveness and proactiveness of the proposed framework, and the final result highlights its rationality and accuracy in estimating the RUL of machining tools with better interpretation.

Automatic tolerance analyses by generation of assembly graph and mating edges from STEP AP 242 file of mechanical assembly

Purpose This paper aims to propose a method to automate the tolerance analyses of mechanical assembly using STandard for the Exchange of Product model data-Application Protocol Part 242 (STEP AP 242) files derived from the 3-D computer-aided design (CAD) models. Design/methodology/approach Product manufacturing information and mating information available in ISO 10303 STEP AP242 files resulting from the 3-D CAD model of mechanical assembly are extracted. The extracted geometric attributes, geometric dimensioning and tolerancing (GD&T) and mating information are used to automatically generate assembly graph and mating edges required for the tolerance analyses of the mechanical assembly by using the matrix approach. Findings The feasibility of the proposed method is verified through two mechanical assembly case studies. The results of manual calculations and tolerance values computed by the automated method are very closely matching. Practical implications Tolerance analysis is an integral part of product development that directly influences the cost and performance of a product. Apart from the academic interest, the work is expected to have positive implications for the digital design and smart manufacturing industry that involve in the development of solutions for automation of design and manufacturing system functions. Originality/value The approach presented in the paper that aids the automation of tolerance analyses of mechanical assembly is an innovative application of the STEP AP 242 file. The automation of tolerance analyses would improve the productivity and efficiency of the product realization process.

Metrology Benchmarking of 3D Scanning Sensors Using a Ceramic GD&T-Based Artefact.

The use of non-contact scanning equipment in metrology and in dimensional and geometric inspection applications is increasing due to its ease of use, the speed and density of scans, and the current costs. In fact, these technologies are becoming increasingly dominant in the industrial environment, thus moving from reverse engineering applications to metrological applications. However, this planned transfer requires actions to ensure the achievable accuracy by providing traceability of measurements. In the present study, a comparison between the devices is carried out and a specific standard artefact is designed, equipped with multiple ceramic optically friendly entities, and allowing a wide variety of geometric dimensioning and tolerancing (GD&T). Four different 3D scanning sensors are used in the experimentation. Three of them are based on laser triangulation, and the fourth is a structured blue light sensor (fringe pattern projection). The standard artefact is calibrated with a high accuracy, using a coordinate measuring machine (CMM) and probing sensors. With this CMM, reference values of multiple predefined GD&T are obtained. The evaluation methodology maximises the accuracy of each device in measuring the dimensions of the artefact due to the good dimensional (milling and turning), surface (control of machining variables), and the dimensional and spatial distribution characteristics. The procedure also includes the same treatment of the captured point clouds (trimming, filtering, and best-fit algorithm, etc.) in each of the four 3D scanning sensors considered. From this process, very reliable measurements of the maximum achievable accuracy of each device (deviations from the CMM measurements) are finally obtained, and a multi-characteristic comparison between the four sensors is performed, also with high reliability.

A framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes

The combination of reverse engineering (RE) with additive manufacturing (AM) is widely used for solid freeform fabrication and overcomes limitations with the current capabilities of designers and CAD packages that are restricted to classical model shapes. The shape flexibility offered by RE typically leads to the generated CAD models being represented in point cloud formats or stereolithography files. One resulting challenge is the difficulty with tolerance specification for the RE-generated models, especially for freeform shapes. Geometric metrology for the AM-produced parts to determine their geometric conformation can also be involved. Furthermore, conventional process analyses cannot be performed directly after RE because of the complex geometric data structure. We propose to address all these issues with a new tolerance specification and process analysis framework based on volumetric data analysis. The tolerance zone constructed under our framework, and the corresponding geometric measurements, are consistent with the profile tolerance in geometric dimensioning and tolerancing standards. Reverse engineering's process capability is assessed under our methodology via a parametric bootstrap procedure in the size-and-shape space. The performance and utility of the proposed framework are validated via a process capability study on RE-generated CAD models of multiple, additively manufactured freeform objects.