Air bubbles can affect the texture of various food products. For example, the number, radii, and radii variance of air bubbles can change the firmness and elasticity of aerated food products. However, the contribution of such geometric features to food texture has not been investigated thoroughly. If the relationship between air bubbles and food texture is clarified, the internal structure of food items can be designed based on its texture. Thus, in this study, we developed an algorithm to analyze the relationship between the geometric features of air bubbles and food textures and to determine the food’s internal structure giving an intended texture. First, the bubbles’ geometric features are analyzed using X-ray CT scan. Second, the textures are quantified using the Temporal Dominance of Sensations (TDS). Finally, the relationship between the geometric features of bubbles and the food texture is calculated via regression analysis. An experiment was performed according to the above procedure, in which aerated chocolates were adopted as specimens because their relatively high densities yield high quality CT datasets. The experimental results demonstrated that the crumbly texture has a high correlation with the number, radii, and radii variance of air bubbles, and the gooey texture exhibited strong correlation with the number of air bubbles, the radii of air bubbles, and sugar content. For these two texture geometry relationships, we computed geometric models of aerated chocolates expected to realize these two textures.

Given the shortcomings of conventional machine vision-based surface defect detection methods, including their low accuracy, long development cycle, and poor generalization ability, this paper proposes a surface defect detection model based on the convolutional block attention module and atrous convolution. This model combines the surface defect segmentation task of the product with the classification task, obtains contextual information of the image at multiple scales using atrous spatial pyramid pooling, and then uses the convolutional block attention module to reallocate the weighting of the network to enhance focus on the defect area and improve the discrimination of extracted features. In addition, atrous convolution was introduced in the deep network to simplify the model when used in defect segmentation tasks and enhances the real-time performance of the model defect detection method. Experiments show the superior accuracy and real-time performance of the proposed model when compared with current mainstream surface defect detection methods and indicate its wide applicability in the detection of surface defects in industrial products.

Customer knowledge of a target image is an important and primary research topic related to the product design and development process. This paper presents research on product target image reasoning based on complex network theory and game theory. First, through an evaluation of the correlations among images, a complex network structure diagram with image words as nodes is constructed, and the network attributes of node degree, betweenness and closeness to the centre of the network are calculated. Then, based on the related methods of game theory, the weights of the three network attributes are evaluated, and a comprehensive calculation is carried out on the image to obtain the target image. Finally, an image entropy algorithm is used to validate the results. Taking a scooter as an example, a complex network of 12 image words is constructed by collecting the evaluations of a total of 12 subjects from different professional fields on 8 scooter samples; thus, the verification of the case is completed. This paper provides a more efficient and accurate target image evaluation method for product design or development, which is a new proposal for the product intelligent design process.

In a real production line, rush orders arise frequently, and they must be produced more quickly than standard production runs. Rush orders may require setup changes to process the order and to resume normal production once the order is completed. Increased setup times are qualitatively understood to decrease production efficiency and to increase the energy required to produce each manufactured unit., Previous studies have not investigated the effects of rush orders on plant productivity and energy consumption. A better understanding of these effects is needed to develop production evaluation methods that can achieve continued reduction in production energy use. In this paper, we proposed a production evaluation method that theoretically formulated the relation between lot size and energy consumption rate while considering rush orders in a production line. A formulation was developed to define this relationship. The formulation was verified using simulation results. We carried out the case studies for the validity of the proposed formulation.

As a new type of magnetic transmission structure, asynchronous permanent magnet coupling has wide prospect application in mechanical transmission field. This paper proposes a squirrel cage asynchronous permanent magnet coupling combined with structural characteristics of permanent magnet motor and asynchronous motor. In order to study its magnetic field model and transmission characteristics, according to coupling and nonlinear characteristics of its magnetic field, a separate analytical iterative method is proposed to decompose air gap magnetic field, on one hand, as magnetic source, permanent magnet magnetomotive force is analyzed by equivalent magnetic circuit, on the other hand, as induction armature, reaction magnetomotive force of squirrel cage rotor is analyzed by magnetic induction principle. Then, based on time-varying electromagnetic field theory, the analytical model of air gap magnetic field is established, the accurate electromagnetic torque equation is deduced, and detailed calculation process is summarized. An 18.5kW prototype is designed. According to prototype parameters, magnetic field simulation model is established by finite element simulation software, correctness of theoretical analysis is verified by simulation. The transmission performance and speed regulation characteristics are further analyzed and discussed individually according to conditions of constant torque, constant power and centrifugal load. Finally, the experimental prototype is developed and loading experimental platform is built, correctness of theoretical analysis and calculation results is verified by experiments.