Conceptual design has a decisive impact on the product development time, cost and success. This paper presents a new conceptual design method for achieving rapid and effective mapping from product design specification (PDS) to concept design. This method can guide the creation of reasonable mapping among the PDS, behaviour parameters and structure parameters and to evaluate the rationality of performance parameters and structure parameters to confirm a reasonable conceptual design scheme. In this method, we establish a PDS-behaviour-structure conceptual design model to support the conceptual design of multi-disciplinary-oriented complex product system (CoPS) and develop a vector-based mapping tool in this method to support the rapid mapping, and demonstrate its feasibility and effectiveness by a case study. This method is not only supportive to realise the automation of a conceptual design process but also helpful to evaluate the conceptual design in the field of engineering design.

In engineering applications, the effectiveness of rotating machinery fault diagnosis is often disturbed by both vibration noise and labeling noise. Vibration noise makes it more difficult for the model to extract a potential fault impact feature, while labeling noise makes the feature extraction go in the wrong direction through error backpropagation. Both of these factors lead to a decrease in fault diagnosis accuracy. Hence, an adaptive symmetric loss in dynamic wide-kernel ResNet (AS-DWResNet) is proposed to solve the rotating machinery fault diagnosis under noisy labels. Firstly, wider convolution kernels are designed for branch convolution to enhance the extraction of vibration features. Secondly, a parallel network structure is constructed to fully and accurately extract the fault features by dynamically weighting different branches to improve the basic diagnostic performance of the network in the background of vibration noise. Thirdly, an improved adaptive symmetric cross-entropy (ASCE) loss function is adapted to reduce the effect of label noise in training datasets and hyperparameters in loss functions. The experimental results show that in the background of vibration noise and severe noisy labels, the proposed method still keeps more than 99.08% accuracy and has stronger noise robustness and stability than other networks and loss functions.

Ball-end milling cutter with tooth offset center is widely used in machining industry, because it has higher machining efficiency and better stability compared with the ball-end milling cutter without tooth offset center. In addition, the tooth offset center has lower wear rate of the tool tip so the life of the milling cutter is improved. However, up to present, there is no mature and effective theory for the design and manufacture of this kind of milling cutters. This article presents a new mathematical model for S-shaped edge curve of the ball end taking the tooth offset center into account, which can construct accurate S-shaped edge curve for the ball-end cutting tools with tooth offset center as well as without tooth offset center. This model overcomes the complex computation and bad adaptability of the traditional modeling method. At the same time, a five-axis grinding algorithm for rake face of the ball end is also presented in this article. Finally, based on the application programming interface of CATIA™, a three-dimensional computer-aided design and computer-aided manufacturing system is developed. The accuracy and effectiveness of the grinding algorithm are verified by simulation in VERICUT™ and machining experiment in tool grinding machine.