Heterogeneous object modeling and fabrication has been studied in the past few decades. Recently the idea of digital materials has been demonstrated by using Additive Manufacturing (AM) processes. Our previous study illustrated that the mask-image-projection based Stereolithography (MIP-SL) process is promising in fabricating such heterogeneous objects. In the paper, we present an integrated framework for modeling and fabricating heterogenous objects based on the MIP-SL process. Our approach can achieve desired grading transmission between different materials in the object by considering the fabrication constraints of the MIP-SL process. The MIP-SL process planning of a heterogeneous model and the hardware setup for its fabrication are also presented. Test cases including physical experiments are performed to demonstrate the possibility of using heterogeneous materials to achieve desired physical properties. Future work on the design and fabrication of objects with heterogeneous materials is also discussed.
The development of industry 4.0 has spurred the transformation of traditional manufacturing into modern industrial Internet-of-Things. The most notable feature during this transition is the improvement of digitization and intelligence based on the massive data drives. In such a data-driven environment, the processing, storage, and utilization of the industry data get more and more important. Usually, the traditional data processing architecture runs as a one-way streamline, which cannot adapt to the different requirements of the multi-scenario application. This paper proposed a new industrial big data processing architecture called Phi architecture, which can realize many functions such as batch data processing and stream data processing, distributed storage and access, and real-time control. Compared with other data processing architecture, the Phi architecture combined with edge computing and feedback control has the ability to deal with the different demands in aviation manufacturing. Next, the new architecture is designed for microservices pattern, which improves the flexibility and stability of the architecture, and makes it independent operated in multi-scenarios, such as state monitoring of workshop, adaptive data acquisition, feedback control, and user-oriented information classification. As a proof of concept, the architecture has been tested in a simulation digital manufacturing workshop. The results verify the improved effectiveness of the Phi architecture on the data feedback control and real-time processing. And, the development of microservices architecture greatly improves the efficiency, adaptability, and extensibility of the manufacturing process.INDEX TERMS Data processing architecture, real-time feedback, edge computing, microservices, multiscenario application.
Networks of five-axis machine tools produce huge amounts of process data. These data directly reflect the running condition of the machine tool but are seldom used to examine the machine performance. This study proposes a new data acquisition method based on the Object linking and embedding for Process Control protocol without any additional monitoring equipment. The data collection principle is explained, and a client is developed based on the SIEMENS 840D system. Considering less influence on the manufacturing process, a communication architecture for the machine network is designed with a special computer transmitting the data to the server. A compression algorithm is applied to reduce the storage capacity of massive amounts of data. Finally, a method for predicting the future performance of the machine tool is proposed using similarity analysis of the time series. A Petri net model is also established to diagnose possible failure causes. These methods significantly improve the machine tool reliability and find potentially important information from the data in the manufacturing process.
Currently, to satisfy the stringent requirements on the physical properties of sculptured surfaces, workpiece machining attempts to guarantee the level of machining accuracy while improving the efficiency as much as possible. Because of the characteristics of the sculptured surfaces, the machine tool is usually run at a lower feedrate to avoid large impact forces. However, this sacrifices machining time and still may not meet the requirements. This article presents a novel minimum-time feedrate schedule method to improve the machining efficiency for five-axis machining considering the surface characteristic constraints. First, the mapping relationship between the surface characteristic and the kinematical parameters is constructed by analyzing the following error on each axis. After that, the new constraint conditions on machine tool kinematics limitation and its continuity constraints are given to address changes in the curvature. Next, a new acceleration/deceleration feedrate schedule method is presented based on quintic feedrate smooth profile to minimize the impact force as much as possible. Thus, a novel minimum-time feedrate schedule based on the bidirectional feedrate schedule algorithm is proposed to improve machining efficiency while respecting various constraints. Finally, a sculptured surface with varied curvature is used to illustrate the significant reduction in processing time and improvement in surface quality in large curvature region after scheduling. The simulation and experimental results show that the proposed method can improve the machining efficiency while guaranteeing the machining accuracy.
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