Exchange Of Product Model Data Research Articles

A Methodology for Integrating Hierarchical VMAP-Data Structures into an Ontology Using Semantically Represented Analyses

Integrating physical simulation data into data ecosystems challenges the compatibility and interoperability of data management tools. Semantic web technologies and relational databases mostly use other data types, such as measurement or manufacturing design data. Standardizing simulation data storage and harmonizing the data structures with other domains is still a challenge, as current standards such as the ISO standard STEP (ISO 10303 ”Standard for the Exchange of Product model data”) fail to bridge the gap between design and simulation data. This challenge requires new methods, such as ontologies, to rethink simulation results integration. This research describes a new software architecture and application methodology based on the industrial standard ”Virtual Material Modelling in Manufacturing” (VMAP). The architecture integrates large quantities of structured simulation data and their analyses into a semantic data structure. It is capable of providing data permeability from the global digital twin level to the detailed numerical values of data entries and even new key indicators in a three-step approach: It represents a file as an instance in a knowledge graph, queries the file’s metadata, and finds a semantically represented process that enables new metadata to be created and instantiated.

G-code converter using interface system for a STEP file (ISO 10303)

The STEP file is the “standard for the exchange of product model data,” which is usually used to exchange geometric data in boundary representation (B-rep) between different computer-aided design (CAD) platforms. These data can be fully utilized and integrated into a larger manufacturing organization, such as a computer-aided manufacturing (CAM) environment for computer numerical control (CNC) machining applications based on ISO 6983. The 3D models of 2D machining profiles were created in CAD software and saved as STEP files. The data structure was analyzed by comparing the geometric entities of the CAD model and the STEP file. The algorithm was created using the hypertext preprocessor (PHP) programming language and produced a computer interface system to convert STEP files into G-code format. The machining blocks with profile machining features were simulated using a CNC simulator and PC-based open architecture control (OAC) software. The G-code was validated on a three-axis CNC milling machine, and the result was compared to the CAD model to confirm the machining profile. The integrated interface system I2S demonstrates its ability to interpret all 2D profiles and generate machining tool paths and G-code, allowing data flow between CAD and CAM environments and shortening product development cycles.

Milling Features Recognition Methodology of Rectangular Fillet Blind Pocket for Universal Data Structure

Various studies have focused on developing an interface system that could integrate the machining process with CNC (Computer Numerical Control) machine tools by producing tool paths using STEP (Standard for the Exchange of Product model data) file as an input function. Studies to recognize features in STEP file by encoding the data of geometric entities of a CAD (Computer-Aided Design) design has been done by many researchers. However, they only focus on Cutter Location (CL) which eventually describes the machining profile in the x and y planes without considering the depth of the machining feature in the z-axis. Identifying and recognizing machining features in the STEP file is important since STEP is a platform for converting industry-standard CAD systems and software data models. The aim of this paper is to identify profiles of geometric machining features for rectangular fillet blind pockets using the Geometric Data Extraction (GDE) approach. Three cases have been carried out namely single rectangular fillet blind pocket, double rectangular fillet blind pocket and triple rectangular fillet blind pocket. The results were verified by manual graph plotting and automatic graph plotting using CPM 3D Plotter.

GraphSTEP: concurrent, cloud-based, lifecycle-oriented editing and updating of product data

A product's digital representation enables various activities in its lifecycle. In a neutral, file-based exchange format, like the STandard for the Exchange of Product model data (STEP), asynchronous access is possible throughout different software solutions, increasing the work interoperability across different stakeholders. However, the file-based handling of product data from the top to the shop floor and further lifecycle phases, subject to industrial practice, contradicts the Digital Twin (DT) concept embodying a centralized, single source of trust. To address this deficit, we propose GraphSTEP: a cloud-based platform to store, access, and manipulate product data, enabling concurrent, collaborative data management while preserving history through versioning.

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Abstract Product data sharing is fundamental for collaborative product design and development. Although the STandard for Exchange of Product model data (STEP) enables this by providing a unified data definition and description, it lacks the ability to provide a more semantically enriched product data model. Many researchers suggest converting STEP models to ontology models and propose rules for mapping EXPRESS, the descriptive language of STEP, to Web Ontology Language (OWL). In most research, this mapping is a manual process which is time-consuming and prone to misunderstandings. To support this conversion, this research proposes an automatic method based on natural language processing techniques (NLP). The similarities of language elements in the reference manuals of EXPRESS and OWL have been analyzed in terms of three aspects: heading semantics, text semantics, and heading hierarchy. The paper focusses on translating between language elements, but the same approach has also been applied to the definition of the data models. Two forms of the semantic analysis with NLP are proposed: a Combination of Random Walks (RW) and Global Vectors for Word Representation (GloVe) for heading semantic similarity; and a Decoding-enhanced BERT with disentangled attention (DeBERTa) ensemble model for text semantic similarity. The evaluation shows the feasibility of the proposed method. The results not only cover most language elements mapped by current research, but also identify the mappings of the elements that have not been included. It also indicates the potential to identify the OWL segments for the EXPRESS declarations.

Integrated Interface System of STEP Data Models for the Tool Path Generation

The STEP (STandard for the Exchange of Product model data) is a worldwide standard for exchanging products between diverse computer systems and industrial applications. STEP files (ISO 10303) contain 3D data in the universal data format with a boundary representation (B-rep) that allows the exchange of data models between CAD, CAM, and CNC systems. Traditionally, G-code generation relies on CAM software as an add-on, which incurs significant installation costs. The purpose of this paper is to describe the development of an Integrated Interface System (I2S) for Tool Path Generation (TPG) for the CNC milling operations utilizing neutral STEP files.The algorithm was interpreted in Hypertext Preprocessor (PHP) programming and produced a computer interface system that is capable to convert STEP file geometric data to G-code format.The geometric features of the sample block were modeled using a 3D CAD model. The result was validated using machining simulation, and the machining is performed on a three-axis CNC milling machine with a PC-based controller.In modern manufacturing systems based on Open Architecture Controller (OAC), the development of the I2S provides an alternative to generating machining tool paths and G-code by intercepting CAM software.

An Additive Manufacturing Direct Slicing Algorithm Based on a STEP Model

The Standard Template Library (STL) file is the most common data format for the description of an additive manufacturing (AM) geometric model, but it has some disadvantages, such as large errors of the geometric model description, the easy loss of topology information, data duplication, large file sizes, and so on. Aiming at these problems, a direct slicing algorithm based on a Standard for the Exchange of Product Model Data (STEP) model was proposed. For the parts composed of basic types of surfaces such as boundary curves, spherical surfaces and cylindrical surfaces, the traditional geometric method was used to calculate the intersection. For the parts with complex surfaces, the three-dimensional models were described based on Non-Uniform Rational B-Spline (NURBS) surfaces. The NURBS surfaces were layered using a discrete tracking algorithm, the tracking starting point was determined, the intersection line between the tangent plane and each NURBS sub-surface was obtained, and the closed layer contour was formed. Finally, the slicing simulations and printing experiments of solid parts were carried out using the direct slicing algorithm based on the STEP model. It was shown that the dimensional accuracy and surface quality of the printed parts from this algorithm had been significantly improved.

Adaptive CAM planning to support co-design in the building industry

Co-design describes a collaborative design process between different stakeholders. These stakeholders usually come from various domains. To enable co-design, data has to be exchanged between the stakeholders. Current approaches to data management in the building industry are usually oriented along the process chain and therefore only allow a unidirectional flow of information. This is an obstacle in the implementation of co-design within the building industry.As more and more buildings are built by utilizing prefabricated modules to accelerate the on-site building process and to reduce the cost, a major effort in terms of implementing co-design is to link the design information of the building industry with the production information of the manufacturing industry. The problem occurs as the building industry mainly uses the fndustry Foundation Classes and the manufacturing industry uses the Standard for the Exchange of Product Model Data as a data format to exchange information. This leads to a break in the flow of information. Furthermore, information about the manufacturability of products, that is generated during the computer-aided manufacturing process, cannot be easily returned to the architect who can utilize the information to adapt the design in the computer-aided design process.This paper addresses these problems by defining a data processing pipeline that enables the conversion of the geometric design information stored in IFC into the STEP data format. From there, the CAM strategy can be defined and results in an executable G-Code. The information of the CAM planning is returned to the architect, who can adapt the design by interpreting the results of the CAM processing. To close the co-design loop, the G-Code for the design adaptions can be generated automatically by reusing the predefined CAM strategy.

A New Implementation of ontostep: Flexible Generation of Ontology and Knowledge Graphs of express-Driven Data

Abstract ontostep is a method to translate the STandard for the Exchange of Product Model Data (STEP) schema and its instances to an ontology and knowledge graphs represented in the web ontology language (owl). ontostep models can be integrated with any owl models to enrich their semantics. However, the current implementation has several limitations, mainly in (1) supporting the latest International Organization for Standardization (ISO) 10303 schemas and (2) generating various representation types depending on the purpose of use. We present an improved implementation of ontostep to overcome these limitations. In this article, we demonstrate that the new implementation can successfully translate STEP schemas and instances in a faster and more flexible way, thus furthering the adoption of the full capabilities of ISO 10303. By encoding STEP entities in owl, we facilitate integration with other standards through knowledge graphs.

STEP-NC-Compliant Implementation to Support Mixed-Control Technologies Applied to Stone-Processing Machines Based on Industrial Automation Standards

STEP-NC (Standard for the Exchange of Product Model Data–Numerical Control) for metal milling and turning is not implemented by industrial computer numerical controllers. Solutions reported are prototypes based on post-processing in G-code. Moreover, minority machining processes, such as stone cutting, have not yet been contemplated in the STEP-NC standard. This article takes that sector as a use case. An extended STEP-NC model for circular saw stone-cutting operations is proposed, and a prototype automation implementation is developed to work with this extended model. This article shows how modern technological resources for coordinated axes control provided by many industrial controllers for the automation of general-purpose machines can speed up the processes of implementing STEP-NC numerical controllers. This article proposes a mixed and flexible approach for STEP-NC-based machine automation, where different strategies can coexist when it comes to executing STEP-NC machining files, so controllers do not need to implement the standard in an exhaustive way for all the possible features, but only at selected ones when convenient. This is demonstrated in a prototype implementation which is able to process STEP-NC product files with mixed-feature types: standard milling and non-standard sawblade features for stone processing.

Establishment of a finite element model based on craniofacial soft tissue thickness measurements and stress analysis of medical goggles

In this study, an accurate finite element (FE) stress analysis of head-mounted products for Chinese users was performed. Using craniofacial computed tomography scans of 280 Chinese individuals, the total soft tissue thickness and thickness of the fat and muscle layers for 41 landmarks were measured. The data were used to construct FE head models (FEH). An FE stress test was conducted to analyse the wearing of medical goggles using two FE models based on one-layer (FEH 1) and three-layer (FEH 3) soft tissue material parameters. When compared with the experimental results, the modelling results for FEH 3 were more realistic than those for FEH 1. Wearing medical goggles led to stress concentration over five landmark areas, A: upper medial forehead, B: temporal, C: zygion, D: infraorbital fossa and E: rhinion, of which B, C and D caused the most discomfort during long-term goggle wear. Practitioner summary: A precise FE head model can reflect the complex contact pressure of a head-related product. Two FE models based on one- and three-layer soft tissue material parameters were established and tested separately with medical goggles. The model can be used to improve the comfort of head-related products. Abbreviations: FE: finite element; FEH: FE head models; FEH 1: FE models based on one-layer; FEH 3: FE models based on three-layer; VR: virtual reality; AR: augmented reality; 3D: three-dimensional; WSU: Wayne State University; WSUBIM: Wayne State University Brain Injury Model; CT: computed tomography; MRI: magnetic resonance imaging; CFSTT: craniofacial soft tissue thickness; FSR: force sensing resistor; NURBS: non-uniform rational basis spline; SPSS: statistical product and service solutions; STL: stereolithography; STP: standard for the exchange of product model data; BDF: glyph bitmap distribution format; EEG: electroencephalogram

STEP AP 242 Managed Model-based 3D Engineering: An Application Towards the Automation of Fixture Planning

Fixture design and planning is one of the most important manufacturing activities, playing a pivotal role in deciding the lead time for product development. Fixture design, which affects the part-quality in terms of geometric accuracy and surface finish, can be enhanced by using the product manufacturing information (PMI) stored in the neutral standard for the exchange of product model data (STEP) file, thereby integrating design and manufacturing. The present paper proposes a unique fixture design approach, to extract the geometry information from STEP application protocol (AP) 242 files of computer aided design (CAD) models, for providing automatic suggestions of locator positions and clamping surfaces. Automatic feature extraction software “FiXplan”, developed using the programming language C#, is used to extract the part feature, dimension and geometry information. The information from the STEP AP242 file is deduced using geometric reasoning techniques, which in turn is utilized for fixture planning. The developed software is observed to be adept in identifying the primary, secondary, and tertiary locating faces and locator position configurations of prismatic components. Structural analysis of the prismatic part under different locator positions was performed using commercial finite element method software, ABAQUS, and the optimized locator position was identified on the basis of minimum deformation of the workpiece. The area-ratio (base locator enclosed area (%)/work piece base area (%)) for the ideal locator configuration was observed as 33%. Experiments were conducted on a prismatic workpiece using a specially designed fixture, for different locator configurations. The surface roughness and waviness of the machined surfaces were analysed using an Alicona non-contact optical profilometer. The best surface characteristics were obtained for the surface machined under the ideal locator positions having an area-ratio of 33%, thus validating the predicted numerical results. The efficiency, capability and applicability of the developed software is demonstrated for the finishing operation of a sensor cover – a typical prismatic component having applications in the naval industry, under different locator configurations. The best results were obtained under the proposed ideal locator configuration of area-ratio 33%.

Integrative data processing for cyber-physical off-site and on-site construction promoting co-design

The term co-design describes a collaborative design process, usually across the boundaries of individual areas. A major aspect, and often an obstacle in the implementation of the co-design approach, is the establishment of a centralized data management system. In the past, the data management concept has been approached from different perspectives. Current approaches usually are oriented along the process chain and thus reflect a unidirectional flow of information. Neither the information feedback nor the reaction to adjustments in upstream model steps is supported, which makes continuous collaboration more difficult and at best reduces the co-design approach for continuous data usage. This paper addresses these weaknesses while outlining an integrative data processing concept enabling co-design between the domains of construction and industrial prefabrication.Geometrical information generated during architectural design and construction planning is reused for the production of components, manufacturing-related design adjustments are transferred back into the domain of construction. Changes throughout the entire process are centrally recorded. To ensure independence from the software tools used and to consider their great diversity, data exchange is largely based on standards, namely industry foundation classes and the standard for the exchange of product model data. In order to counteract the sequential processing according to a waterfall model and to support the co-design approach, the industrial prefabrication toolchain, consisting of computer-aided manufacturing software and downstream postprocessors, is largely automated, so that reprocessing of a workpiece for minor geometric adjustments no longer requires any interaction of the production planner.

Application of artificial neural network techniques in computer aided process planning - a review

Computer aided process planning (CAPP) bridges the gap between computer aided design and computer aided manufacturing. CAPP research includes neural network approaches, knowledge-based techniques, Petri nets, agent- based, fuzzy set theory, genetic algorithm, standard for the exchange of product model data (STEP)-Compliant CAPP and internet-based techniques. This study mainly focuses on the application of the artificial neural network (ANN) techniques in CAPP because of their learning ability and huge potential toward dynamic planning. The role of an artificial neural network in feature recognition, machine selection, operation and machine tool selection are emphasised in detail in this survey paper.

Development of the PC-based Integrated Interface System of STEP file for CNC Machining Application: Circular Features

STEP is a general data format that observes the international standard ISO 10303-21. STEP means Standard for the Exchange of Product model data. It consists of the 3D geometry of a computer-aided design (CAD) model in the configuration of boundary representation (B-rep). By extracting, refining and decoding the geometric data correctly, the data can be utilized for writing G-code for Computer Numerical Control (CNC) machining application. Usually G-codes can either be manually generated by skilled machinists or automatically generated by computer-aided manufacturing (CAM) software. However, manually generated G-code is inefficient and susceptible to error. Meanwhile automated generation G-code requires significant setup cost. This paper describes the design and development of an integrated interface system, an instrument aimed to be used to analyze STEP files and generate machining tool path based on ISO 6983 format. This developed interface reduces the need for high setup cost as well as eliminates human limitations. The interface at present is able of detecting circular machining features on the workpiece. Circular machining features are created by 3D modelling software and retained as STEP file. The STEP file which contains geometrical data is then uploaded to the interface system as an input file which is structurally analyzed and processed. Finally, the ideal machining tool path in the G Code format is proposed and generated. By bypassing the CAM software and its proprietary post processor, the outcome of this research is important to enhance compatibility between different CNC machine systems

Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs

Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF), has garnered significant attention as it can bring quality information into the digital thread. Implementing more automated methods for product quality assurance is challenging due to the lack of unified information models from design to inspection. To this end, we propose an approach to fuse as-designed data represented in STEP and as-inspected data represented in QIF in a standards-based digital thread based on ontology with knowledge graphs. Specifically, we present an automated pipeline for generating knowledge graphs representing STEP and QIF data, a mapping implementation to integrate STEP and QIF knowledge graphs, and rules and queries to demonstrate the integration’s potential for better decision making with respect to product quality assurance.

Feature-based translation of CAD models with macro-parametric approach: issues of feature mapping, persistent naming, and constraint translation

Abstract Feature-based translation of computer-aided design (CAD) models allows designers to preserve the modeling history as a series of modeling operations. Modeling operations or features contain information that is required to modify CAD models to create different variants. Conventional formats, including the standard for the exchange of product model data or the initial graphics exchange specification, cannot preserve design intent and only geometric models can be exchanged. As a result, it is not possible to modify these models after their exchange. Macro-parametric approach (MPA) is a method for exchanging feature-based CAD models among heterogeneous CAD systems. TransCAD, a CAD system for inter-CAD translation, is based on this approach. Translators based on MPA were implemented and tested for exchange between two commercial CAD systems. The issues found during the test rallies are reported and analyzed in this work. MPA can be further extended to remaining features and constraints for exchange between commercial CAD systems.

A Design of New Product Database System for Supporting Step-Compliant Total Integration Applications

Computer technology has become a very important element in an advanced manufacturing system. The good and systematic data model for the exchange of manufacturing information between different stages of development of product life cycle is paramount to ensure the product is manufactured and delivered to the market successfully. As a result, ISO 10303, an international standard, or well known as Standard for Exchange of Product Model Data (STEP) is not just for providing a neutral data format within the heterogenous CAD systems, its functionality has extended to the whole life cycle of product. STEP Part 21 is the first implementation method from EXPRESS modelling language and implemented successfully as neutral product data to integrate heterogeneous CAD platform. However, this CAD STEP Part21 text file is hardly to be applied in manufacturing processes since it consists of purely geometrical and topological data. In this research, a nonprocedural approach is presented to translate the EXPRESS language model of STEP CAD data into a new product database system model. A new nonprocedural approach of data enrichment and automated machining feature recognition is proposed and implemented on this newly developed product database system and provide a solution for the interrelated tasks of automated machining feature recognition: (1) extraction of geometrical feature from STEP CAD model data of the part (2) formation of part representation suitable for form feature identification (3) matching of form features. This paper proves the validity of this newly developed product database system by translating STEP Part21 file from a commercial CAD system to database system format, data enrichment, performing automated machining feature recognition and lastly generating STEP standard data according to AP224 for supporting STEP based process planning and manufacturing applications.

Artificial Neural Network Based Machining Operation Selection for Prismatic Components

Computer-aided process planning systems are used to assist human planners in producing better process plans. New artificial intelligence techniques play a significant role in CAPP. CAPP research includes neural network approaches, knowledge-based techniques, Petri nets, agent-based, fuzzy set theory, genetic algorithm, Standard for the Exchange of Product model data (STEP)-Compliant CAPP, and Internet-based techniques. This study deals with the application of the Artificial Neural Network techniques (ANN) in CAPP because of their learning ability and massive potential toward dynamic planning. This study focuses on the usage of artificial neural networks machining operation selection and sequences of operations for prismatic components. The intelligent CAPP system suggests the best machining operation and its sequences for the prismatic components using tolerances, material requirements, and surface finish details. The process planning of machining features in part is the starting point. An enormous amount of knowledge is required for part feature process planning, like selecting proper material, size, stock, dimensional tolerance, and surface finish. In this work, various prismatic features, such as a hole, slot, pocket, boss, chamfer, fillet, and face are taken and details like material, size, stock, dimensional tolerance and surface finish are properly normalized and given as input to neural networks to find the required sequence of machining operation. LevenbergMarquidt algorithm was used to train the networks and was found very effective in operation sequence selection. A sample prismatic component with nine features have been analyzed and found to be more productive. Levenberg Marquidt algorithm is then compared with the conjugant space algorithm, and it is found that the former produces less error in outputs compared to them later.

STEP-NC Architectures for Industrial Robotic Machining: Review, Implementation and Validation

In the manufacturing sector, industrial robots are being increasingly improved to execute machining tasks as they exhibit significant advantages in terms of flexibility, cost-effectiveness, affordability, and larger work-space when compared to traditional computer numeric control (CNC) machines. However, programming this kind of equipment for robotic machining is complex, due to closed architecture controller and proprietary programming languages limitations. For that reason, this work aims at contributing to the adoption of the STEP-NC standard (STandard for the Exchange of Product model data- Numerical Control (ISO 10303-238 and ISO 14649)), generating programs for robotic machining operations. The STEP-NC data model enables the integration of information from design, process planning, simulation, manufacturing, and even inspection in a single platform, which could create new alternatives for industrial robotic machining programming. In this context, several previous studies are described in this manuscript aiming to highlight the contribution of this work, in addition to the analysis, implementation, and validation of six different STEP-NC architectures describing the advantages that each architecture provides for achieving robotic machining capabilities. Each introduced architecture can successfully generate a STEP-NC robotic machining program, either as ISO 10303-238 or ISO 14649, which are validated in a simulation environment with both a virtual robot model and a real industrial robot equipped with a LinuxCNC controller. This approach can be implemented in different industrial robots.