Procedia manufacturing最新文献

Serbia is rapidly working on the development and implementation of digital manufacturing models in SMEs, through the national Industry 4.0 Platform. The aim is to create a pilot intelligent workshop which would be used to develop and showcase examples of best practice for digital manufacturing. Currently, most SMEs use CAD, CAM, ERP models, which form the basis for the development of the concept of digital manufacturing through cloud computing, BDA, IIoT and smart supply-chains, as elements of Industry 4.0. This paper gives a practical example of an SME with all the above-mentioned elements of digital manufacturing.

This paper aims to identify and model the sources of operational noise that contribute to unstable and poor flow of materials in production systems. 80 interviews with managers and decision-makers were conducted and analyzed and have revealed that internal technical instabilities, employee variability, and customer and supplier uncertainty are the major sources of operational noise. They have also identified the relationships between the different variables of a production system that contribute to the amplification of operational noise and hence should be managed effectively to ensure a smooth flow in manufacturing operations.

The Aerospace Industry has been undertaking strategic changes towards digital manufacturing. One of the challenges is the lack of rationalisation for a cost-benefit analysis of automating certain manufacturing and assembly processes within a customer order. The rigidness and complexity of aerospace lifecycle, and tight industry restrictions does not leave much room for high risk innovations in manufacturing and production lines. This research addressed this problem by investigating an automation adoption scenario with BAE Systems, Electronic Systems, which is a UK based aeronautical systems integrator. This paper reports findings from the general manufacturing industry via an industrial survey. These findings are compared with original findings from an empirical study carried out with BAE Systems within the New Product Introduction team to automate product transportation logistics in an environmental test facility. The paper describes the challenges particularly related to skills, and labour workforce required to manipulate heavy standing products in and out of a production line and how their requirements can be addressed within an automation solution package. The solution includes key design factors related to intricate handling of aeronautic systems via the gripping interface design, and the rest of the operational issues surrounding the testing objectives such as transportation, and test setup. The findings are presented in the form of a requirements analysis for businesses looking to automate manually-intensive tasks in the future, and provide some insights into the lessons learnt in the development of the solution to benefit UK manufacturing tactics to some similar challenges.

In this work, two methods for predictive shimming based on laser scan technology and point cloud processing software have been presented. The first one is direct measurement method in PolyWorks, and the second one is feature-based modelling method in SolidWorks. Firstly, both component-level and assembly-level scans are collected by a laser scanner. Then, the point clouds are post-processed and registered in PolyWorks. Thirdly, gap information (shape and thickness) is obtained either in PolyWorks or in SolidWorks. Results show that the proposed methods can obtain gap information successfully based on current hardware and software.

The modern dental eHealth system is a complex set of many applicable technological tools, applications and entire scientific fields. These include conventional computer 3D design, CAD/CAM/CAE divisions, as well as open source systems related to the modeling of dental structures, dentures, implants, crowns, bridges and more. In the same way, the application of these modern technical means is involved in the development of dental instruments, where the manufacture of devices often have a characteristic geometry and specific parameters. In this context, an increasingly important role is played by additive technologies, which are a key component in the three-dimensional digitization and, accordingly, three-dimensional real reproduction of dental models, be it final products or working tools. The application of new technologies and modern machines for rapid prototyping is a requirement for every dental clinic, laboratory and research center engaged in offering adequate and sustainable dental healthcare. With all this in mind, Industry 4.0 refers directly to the dental industry, where the optimized and high-quality creation of good dental models used by end customers, patients and stakeholders is needed. This paper aims to cover a significant part of the information in an overview characterizing the main stages and modern technological tools for the needs of dental health, which is a prerequisite for building a comprehensive sustainable concept.

This paper presents the development of a Human-Robot Interface (HRI) that uses an RGB-D sensor to facilitate industrial robot programming. The main aims and functionalities of the HRI are described and subsequently emphasis is placed on two novel user interactions methods through which the operator’s movements and gestures are captured and used to position the joints of a 6 DOF articulated robot arm. In particular, during the first user interaction method the operator’s torso, shoulder and elbow are used to determine the position of the first three robot joints, while the operator’s gestures are used to determine the position of the remaining three joints. During the second user interaction method, a combination of the operator’s movements and gestures are used to select any desirable robot joint and then modify its angle by a user-configurable step. Both interaction methods also allow the operator to control robot speed and gripper position. The HRI is complemented by a virtual model of the robotic arm, created in Unity3D, to evaluate online programming capabilities. Results from using the two developed user interaction methods to position the robot in pre-defined poses are presented and discussed to highlight strengths and weaknesses of each method. Finally, the obtained conclusions are presented and suggestions for future work are made.

In Selective Laser Sintering and Melting it is necessary to protect metal powder deposited on the powder bed from contact with atmospheric air, which may lead to oxidation and downgrading of the properties of the powder in the presence of high temperature that is necessary for achieving full or partial melting. Thus, the building chamber of commercially available SLS/SLM machines is fully isolated and filled with inert shielding gas which may need to be replenished before each build session thereby raising both machine building and consumables costs. In this paper, it is examined using Computational Fluid Dynamics how protection of the powder area around the laser spot can be achieved by locally insulating it from air by gas circulation in a suitably designed box moving with the laser beam. Full coverage of the respective area and at the same time no disturbance of the powder particles within it are critical requirements. Two concept variants are studied and simulated with promising results.

In this work, we investigate the order-restricted Bayesian estimation for a simple step-stress accelerated life tests. Based on the three-parameter gamma distribution as a conditional prior, we ensure that the failure rates increase as the stress level increases. In addition, its conjugate-like structure enables us to derive the exact joint posterior distribution of the parameters without a need to perform an expensive MCMC sampling. Upon these distributional results, several Bayesian estimators for the model parameters are suggested along with their individual/joint credible intervals. Through Monte Carlo simulations, the performance of our proposed inferential methods are assessed and compared. Finally, a real engineering case study for analyzing the reliability of a solar lighting device is presented to illustrate the methods developed in this work.

New technologies such as Unmanned Aerial Vehicles (UAV) are constantly being introduced under the Industry 4.0 framework. Although UAVs are mainly used in civil and military applications, the opportunities for Industrial integration must be examined, namely real-time remote monitoring, wireless coverage, and remote sensing. Therefore, UAVs can be considered as proactive solvers, simultaneously contributing to enhanced decision making as they are considered to be Internet of Things (IoT) platforms for efficient cost-effective data collection and monitoring. However, the use of UAVs in confined and crowded Industrial environments, e.g. machine shops, need further research. Therefore, this paper focuses on highlighting the limitations regarding the integration of UAVs in modern manufacturing systems as well as on presenting an intelligent framework based on Industrial Internet of Things (IIoT) for real-time machine shop monitoring. The applicability of the developed framework is tested in-vitro, in a laboratory-based machine shop.

Dies for high pressure die casting (HPDC) has traditionally been manufactured by machining from slabs of tool steel. Currently, the possibility of manufacturing them using additive manufacturing is being explored. This provides some advantages such as the possibility of making conformal cooling channels. However, the size of the dies is often larger than can be handled in most metal printers Still, it is possible to partly print the die by adding cores with intricate conformal cooling on a traditionally manufactured die base. In this paper, a feasibility study of using selective laser melting (SLM) to print cores of maraging steel directly onto a die base is explored. Results shows that the strength of the bond between the two metals is sufficient, and that the connection between the drilled and printed tooling channels can be made. The paper reasons on the expected impacts on the tooling industry showing potential for extended die life and recovery of die bases via re-manufacturing.