Search

The cyber-physical data of equipment whole life cycle are interrelated and play an important role in decision-making for business activities. However, multi-stage cyber-physical data are numerous, heterogeneous, and massive; non-real-time information data and real-time physical data are challenging to correspond to each other because of the inconsistency in space-time and granularity. As a result, equipment multi-stage heterogeneous cyber-physical data are difficult to effectively integrate and apply. Therefore, multi-stage cyber-physical data fusion of equipment is a key problem to be solved in manufacturing. To the best of our knowledge, a practicable framework and method to effectively fuse and apply equipment multi-stage data are still missing. To overcome this gap, this study proposes a multidimensional and multilevel cyber-physical fusion method for equipment. First, a four-dimensional cyber-physical fusion framework based on time, data, model, and structure is put forward. Then, the four kinds of fusion, including data fusion, model fusion, knowledge fusion, and digital twin (DT) application fusion, are discussed detailedly. Besides, the five types of algorithms set to support the fusion process are given. Finally, equipment life cycle activity is regarded as a DT application process using dynamic association of data and models. Through cyber-physical fusion, the data of equipment multi- stages could be applied for different activities to solve problems by means of DT. As a primary verification of the feasibility of the proposed approach, a case study of metro vehicle performance evaluation has been carried out, and the results have well confirmed that the multi-stage cyber-physical fusion method is feasible. [ABSTRACT FROM AUTHOR]

The forming grinding process is a crucial method for helical flute grinding of the end mill and screw tap, and the grinding wheel profile is the key to ensure the precision of the helical flute, which is constrained by the grinding wheel posture. However, the existing methods have some deficiencies such as the invalidity or uneven wear problems. In this paper, an optimized calculation method of the grinding wheel profile for the forming grinding of the helical flute is proposed, including the suitable grinding posture correspondingly. Firstly, the parametric models of the helical cutting edge and the helical flute surface are established. Secondly, the contact condition between the grinding wheel and the flute is deduced to calculate the grinding wheel profile by the envelop theory. Thirdly, an optimization method for grinding wheel profile is proposed, which could predict of the solution interval, avoid the profile intersection, and improve wear resistance. Finally, the method was verified by a series of simulations and experiments, and the results show that the method could meet the grinding precision requirements and expand the application range of forming grinding technology in helical flute. [ABSTRACT FROM AUTHOR]

With the increasing competition of the manufacturing industry, it is essential for manufacturers to develop a new (or next)-generation product based on their prior product design, product user experience, historical performances, etc. The digital twin (DT) is believed to be a suitable technology to support product lifecycle management with excellent data capture and analysis capabilities and product family design capabilities. However, it remains a challenge to synthesize and incorporate the data and information captured from previous generational product development and stored on their individual digital twin instances (DTIs) into next-generation product design. To address this problem, this study proposes a new nominal digital twin (NDT) concept as a collective digital representation of the current generational product digital mockups (DMUs) and all individual DTIs of the built products in services for new-generational product development. NDT is first defined here as a prototypical and synthesized digital twin (or digital representation) of multiple individual digital twins corresponding to multiple physical products in use or previously used. By analyzing the data and information on their DTIs, NDT can enable the establishment and evolution of a more precise approximated model of many related family products used previously or currently in use in various application scenarios and environments in the physical world. This paper also demonstrates how a NDT model can be first established in the product design phase from various digital mockup models and enhanced later with a stochastic forest meta-model based on Bayesian optimization connected to DTIs. With this NDT model, collaborative exploration for optimal design solutions during new-generation product design and improvement can be performed on NDT through multi-objective optimization, which in turn can make new-generation product design easier and quicker. As a primary verification of the feasibility of our proposed approach, a case study has been carried out, and the results have well confirmed that the NDT-based new-generation product design approach is feasible. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, big data, Internet of Things, and other technologies, digital twin has gained great attention and become a current research topic. Using digital twin technology, the digital twin model can be constructed in the cyber space that is fully equivalent to the physical entity. It is always consistent with the physical entity in the operation process, which greatly improves the dynamic perception and prediction ability of the real world. After the development in recent years, digital twin has gradually changed from the initial concept discussion to the study of model framework and implementation method. However, because the research objects in different industries have great differences in their own composition, service conditions, and application scenarios, they have personalized characteristics in modeling strategies and usage methods. Therefore, based on different industries, this paper reviews the current articles on digital twins and distinguishes the focus of digital twin modeling research; subsequently, the relevant supporting techniques and methods are summarized according to their different importance for digital twin modeling. Based on the review in this paper, future researchers can conduct targeted research on digital twin technology in term of the characteristics of the objects in their industry. [ABSTRACT FROM AUTHOR]

Non-contact R test is an instrument to measure the synchronous errors of five-axis machine tools. However, there are still some deficiencies in its researches, such as the difficult and laborious calibrations. How to systematically improve the measurement accuracy with a good balance to minimum cost is a real problem in guiding practice. This paper proposes a new systematic optimization method to solve this problem based on a comprehensive understanding of the non-contact R test in terms of structure parameters and relations. Firstly, the algorithm for sphere center coordinates is established based on the self-adaptive differential evolution algorithm to obtain the definite computational accuracy and efficiency. Secondly, the parameters of the fixture structure are optimized to maximize the measurement stability, measuring space, and non-interference space. Thirdly, the on-machine calibration is performed to replace pre-calibration and re-calibration and to establish the positional relationships between sensors, the fixture, and the machine tool simultaneously. It can reduce the difficulties of manufacture, maintenance, and application. Fourthly, the measurement accuracy can be evaluated to determine whether the iterative optimization achieves the goal. The proposed method has been verified with case studies to support the setting-up of the optimized non-contact R test, leading to a cost-effective and accurate test on five-axis machine tools. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]