Proceeding to 21st CIRP Conference on Life Cycle EngineeringConsidering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-Jetting (BJ). This technique can be used to process a variety of materials including stainless steel, ceramic, polymer and glass. However, there is very limited research about this AM technology on sustainability aspect. This paper presents a method to build an energy consumption model for printing stage of BJ process. Mathematical analyses are performed to find out the correlation between the energy consumption and geometry of the manufactured part. Based on the analyses, total energy consumption is calculated as a function of part geometry and printing parameters. Finally, test printing is performed to check the accuracy of the model. This process model provides a tool to optimize part geometry design with respect to energy consumption.International audienceConsidering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-Jetting (BJ). This technique can be used to process a variety of materials including stainless steel, ceramic, polymer and glass. However, there is very limited research about this AM technology on sustainability aspect. This paper presents a method to build an energy consumption model for printing stage of BJ process. Mathematical analyses are performed to find out the correlation between the energy consumption and geometry of the manufactured part. Based on the analyses, total energy consumption is calculated as a function of part geometry and printing parameters. Finally, test printing is performed to check the accuracy of the model. This process model provides a tool to optimize part geometry design with respect to energy consumption

Considering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-Jetting (BJ). This technique can be used to process a variety of materials

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Different from the traditional subtractive manufacturing, additive manufacturing --a more flexible and material saving manufacturing technology has been developed in these recent years. This paper presents a simulation and optimization framework for Additive Manufacturing (AM) processes in practical industry. Starting from multi-level part design, to process optimization and planning, from energy and material consumption to the Key Performance Indicator (KPI) evaluation, the paper presents a complete practical working flow of AM technologies. Four models are developed within the framework: the design model, the process optimization and planning model, the energy and material consumption model and the production model. All the four models connect subsequently one another. Their concepts and corresponding methods will be presented in order in each chapter of the paper. A close optimization loop can be formed by these models. The feedbacks of each model will be used to optimize the design as well as the process planning. Preliminary experiments data are generalized and analysed by each model.

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Damage identification methods for engineering structures based on vibration parameters have the advantages of easy detection and high precision; however, structural strain information is more sensitive to structural damage than displacement information. Traditional resistance strain sensors have low accuracy and poor stability when measuring structural strains. Therefore, this paper uses a highly sensitive polyvinylidene fluoride dynamic strain sensor to identify structural damage in a thin plate. The polyvinylidene fluoride sensor is used to obtain structural strain response information, and structural modal parameters are identified using operational modal identification methods based on the natural excitation technique and the eigensystem realization algorithm. This paper uses a damage index based on mode shape and flexibility. A new damage index based on the LU decomposition of the flexibility matrix is used to identify the damage of the thin plate structure. The effectiveness of the modal identification methods and the new damage index is validated via an elastic thin plate experiment. The results show that the modal identification method and the new damage index proposed in this paper can identify damage in a thin plate structure. Sensor comparison experiments also show that compared with a resistance strain sensor, the polyvinylidene fluoride sensor has higher damage sensitivity, better damage recognition and the ability to recognize farther from the sensor.

Variant design has been recognized as an effective measure to implement mass customization. Assembly consists of different types of parts. Its variant design is a profound issue need to be explored. Three aspects were discussed in this paper, namely, 1) part classification and dimension constraint satisfaction priority, 2) part reuse, 3) dimension conflict and variant postponing. Firstly, dimension constraint network among parts was constructed based on graph. And variant dimension transferring was exploited. Secondly, reusable part can be found from existing parts through similarity analysis. Thirdly, aiming at dimension constraint conflicts, variant postponing was proposed to concentrate variant design to few parts so as to reduce the number of variant part.

Polarization multispectral imaging (PMI) has been applied widely with the ability of characterizing physicochemical properties of objects. However, traditional PMI relies on scanning each domain, which is time-consuming and occupies vast storage resources. Therefore, it is imperative to develop advanced PMI methods to facilitate real-time and cost-effective applications. In addition, PMI development is inseparable from preliminary simulations based on full-Stokes polarization multispectral images (FSPMI). Whereas, FSPMI measurements are always necessary due to the lack of relevant databases, which is extremely complex and severely limits PMI development. In this paper, we therefore publicize abundant FSPMI with 512 × 512 spatial pixels measured by an established system for 67 stereoscopic objects. In the system, a quarter-wave plate and a linear polarizer are rotated to modulate polarization information, while bandpass filters are switched to modulate spectral information. The required FSPMI are finally calculated from designed 5 polarization modulation and 18 spectral modulation. The publicly available FSPMI database may have the potential to greatly promote PMI development and application.