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Geometric errors are common in metallic bent tubular parts. Thus, tubes should be inspected and fixed before welding with the joints first. After welding, the relative position of the joints is also necessary to be inspected to judge whether the tube can be assembled reliably. Therefore, the inspection plays an important role in the tube’s assembly. The purpose of this paper is to propose a multi-vision-based system designed to inspect the tube and the relative position of the joints.

For the tube inspection, the small cylinders are taken as the primitives to reconstruct the tube using the multi- vision-based system. Then, any geometric error in the tube can be inspected by comparing the reconstructed models and designed ones. For joints’ inspection, authors designed an adapter with marked points, by which the system can calculate the relative position of the joints.

The reconstruction idea can recognise the line and arc segments of a tube automatically and resolve the textureless deficiency of the tube’s surface. The joints’ inspection method is simple in operation, and any kinds of joints can be inspected by designing the structure of the adapters accordingly.

By experimental verification, the inspection precision of the proposed system was 0.17 mm; the inspection time was within 2 min. Thus, the system developed can inspect a tube effectively and automatically. Moreover, authors can determine how the springback of the arcs behaves, allowing in-process springback prediction and compensation, which can reduce geometric errors in the tubes given the present bending machine accuracy.

Among the different methodologies used for performance control in precision manufacturing, the measurement of metrological test artefacts becomes very important for the characterization, optimization and performance evaluation of additive manufacturing (AM) systems. The purpose of this study is to design and manufacture several benchmark artefacts to evaluate the accuracy of the selective laser melting (SLM) manufacturing process.

Artefacts consist of different primitive features (planes, cylinders and hemispheres) on sloped planes (0°, 15°, 30°, 45°) and stair-shaped and sloped planes (from 0° to 90°, at 5° intervals), manufactured in 17-4PH stainless steel. The artefacts were measured optically by a structured light scanner to verify the geometric dimensioning and tolerancing of SLM manufacturing.

The results provide design recommendations for precision SLM manufacturing of 17-4PH parts. Regarding geometrical accuracy, it is recommended to avoid surfaces with 45° negative slopes or higher. On the other hand, the material shrinkage effect can be compensated by resizing features according to X and Y direction.

No previous work has been found that evaluates accuracy when printing inwards (pockets) and outwards (pads) geometries at different manufacturing angles using SLM. The proposed artefacts can be used to determine the manufacturing accuracy of different AM systems by resizing to fit the build envelope of the system to evaluate. Analysis of manufactured benchmark artefacts allows to determine rules for the most suitable design of the desired parts.

Despite the fact that there being a large literature on simulation, there is as yet no generic paradigm or architecture to develop a three-dimensional (3-D) simulator which depends on autonomous intelligent objects. This has motivated us to introduce a 3-D simulation system based on intelligent objects for Physics Experimentation. We formulated the system’s components as an object-orientation model. So, the entities in every experiment’s work cell are modeled by characterizing their properties and functions into classes and objects of the system hierarchy. Intelligent objects are realized by developing a knowledge base (KB) that captures a set of rules/algorithms that operate on 3-D objects. Rules fall into two categories: action and property rules. In the simulation layer, the student is allowed, by using the virtual system, to stroll throughout the Physics laboratory in light of a walking model. Student gets to a simulation region to do an experiment through the detection of mathematical collision. From software engineering perspective, the proposed system facilitates the Physics experiment through making the specification of its applicable parts more modular and reusable. Moreover, a major pedagogical objective is achieved by permitting the student tuning parameters, fixing component of a device then visualizing outputs. This provides student well interpretation by viewing how distinct parameters affect the outcomes of the experiment. With the objective of student performance measuring, we utilized an exploratory group relying upon pre- and post-testing. The application results demonstrate that the simulator contributes positively to student performance in regard to practical Physics.

This paper aims to investigate the collision avoidance problem for a mobile robot by constructing an artificial potential field (APF) based on geometrically modelling the obstacles with a new method named the obstacle envelope modelling (OEM).

The obstacles of arbitrary shapes are enveloped in OEM using the primitive, which is an ellipse in a two-dimensional plane or an ellipsoid in a three-dimensional space. As the surface details of obstacles are neglected elegantly in OEM, the workspace of a mobile robot is made simpler so as to increase the capability of APF in a clustered environment.

Further, a dipole is applied to the construction of APF produced by each obstacle, among which the positive pole pushes the robot away and the negative pole pulls the robot close.

As a whole, the dipole leads the robot to make a derivation around the obstacle smoothly, which greatly reduces the local minima and trajectory oscillations. Computer simulations are conducted to demonstrate the effectiveness of the proposed approach.

The purpose of this research is to outline in detail the procedure of remote data capture using laser scanning and the subsequent processing required in order to identify a new methodology for creating full engineering drawings (orthographic and 3D models) from laser scan and image survey data for historic structures.

Historic building information modelling (HBIM) is proposed as a new system of modelling historic structures; the HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital cameras. A range of software programs is then used to combine the image and scan data.

Meshing of the point cloud followed by texturing from the image data creates a framework for the creation of a 3D model. Mapping of BIM objects onto the 3D surface model is the final stage in the reverse engineering process, creating full 2D and 3D models including detail behind the object's surface concerning its methods of construction and material makeup, this new process is described as HBIM.

The future research within this area will concentrate on three main stands. The initial strand is to attempt improve the application of geometric descriptive language to build complex parametric objects. The second stand is the development of a library of parametric based on historic data (from Vitruvius to 18th century architectural pattern books). Finally, while it is possible to plot parametric objects onto the laser scan data, there is need to identify intermediate software platforms to accelerate this stage within the HBIM framework.

The purpose of this paper is to present a methodology that integrates design and assembly planning in an augmented reality (AR) environment. Intuitive bare-hand interactions (BHIs) and a combination of virtual and real objects are used to perform design and assembly tasks. Ergonomics and other assembly factors are analysed during assembly evaluation.

An AR design and assembly (ARDnA) system has been developed to implement the proposed methodology. For design generation, 3D models are created and combined together like building blocks, taking into account the product assembly in the early design stage. Detailed design can be performed on the components and manual assembly process is simulated to evaluate the assembly design.

A case study of the design and assembly of a toy car is conducted to demonstrate the application of the methodology and system.

The system allows the users to consider the assembly of a product when generating the design of the components. BHI allows the users to create and interact with the virtual modes with their hands. Assembly evaluation is more realistic and takes into consideration the ergonomics issues during assembly.

The system synthesizes AR, BHI and a CAD software to provide an integrated approach for design and assembly planning, intuitive and realistic interaction with virtual models and holistic assembly evaluation.

The purpose of this study is to evaluate how accurately a 3D printer could manufacture basic porous models. Geoscience research is evolving toward numerical prediction of porous rock properties, but laboratory tests are still considered a standard practice. 3D printing digital designs of porous models (proxies) is a way to bridge the gap between these two realms of inquiry.

Digital designs of simple porous models have been 3D-printed on an inkjet-style (polyjet) 3D printer. Porosity and pore-throat size distribution of proxies have been measured with helium porosimetry, mercury porosimetry and computed tomography (CT) image analysis. Laboratory results on proxies have been compared with properties calculated on digital designs and CT images.

Bulk volume of proxies was by 0.6-6.7 per cent lower than digital designs. 3D-printed porosity increased from 0.2 to 1.9 per cent compared to digital designs (0-1.3 per cent). 3D-printed pore throats were thinner than designed by 10-31 per cent.

Incomplete removal of support material from pores yielded inaccurate property measurements. The external envelope of proxies has been 3D-printed at higher accuracy than pores.

Characterization of these simple models improves understanding of how more complex rock models can be 3D-printed accurately and how both destructive (mercury porosimetry) and non-destructive (CT and helium porosimetry) methods can be used to characterize porous models.

Validation of 3D-printed porous models using a suite of destructive and non-destructive methods is novel.

Birmingham University's Mechanical Engineering Department has developed a robot and a range of grippers. Brian Rooks examines the commercial possibilities for these products.

Computer aided process planning (CAPP) is an effective way to integrate computer aided design and manufacturing (CAD/CAM). There are two key issues with the integration: design input in a feature‐based model and acquisition and representation of process knowledge especially empirical knowledge. This paper presents a state of the art review of research in computer integrated manufacturing using neural network techniques. Neural network‐based methods can eliminate some drawbacks of the conventional approaches, and therefore have attracted research attention particularly in recent years. The four main issues related to the neural network‐based techniques, namely the topology of the neural network, input representation, the training method and the output format are discussed with the current systems. The outcomes of research using neural network techniques are studied, and the limitations and future work are outlined.