mechanical products
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Jin Li ◽  
Xinsheng Jiang ◽  
Zituo Wang ◽  
Chunhui Wang ◽  
Yunxiong Cai

Aim: To predict the mechanical product maintenance time is difficult in the situation of lack of physical prototype or similar products’ statistics in stage of design Method: According to the theory of time accumulative estimation method, a product maintenance time prediction method framework based on virtual prototype was constructed, which described the prediction process. The virtual maintenance environment which contains virtual prototype, virtual human and maintenance tools was developed. The virtual human’s position and posture information during the maintenance process was obtained by implementing VBScript language. Result: Basic maintenance motions that constitute the whole maintenance process were classified into 4 categories: body movement, upper limb movement, grasp/replace and operation. Based on MODAPTS (Modular arrangement of predetermined time standard) method and virtual maintenance simulation, corresponding time prediction methods for each categories were proposed. Discussion: Take a maintenance dissassembly and assembly task of engine as an example, through the comparison between the measured actual maintenance time and predicted time of several methods, feasibility and effectiveness of proposed method are verified

Chaimae Abadi ◽  
Imad Manssouri ◽  
Asmae Abadi

Over the last decades, there has been growing pressure on industrial companies to offer to their costumers products with high quality, in the minimum deadlines and with reasonable prices. Since the design phase plays a key role to achieve these difficult goals, many traditional, DFX (Design For X) and integrated approaches have been proposed. However, many limits are still present. Thus, the main objectives of this work were first to identify these limits and then to overcome them by proposing and developing an automated framework for integrated product design. In this work, we automated the integrated DFMMA (Design For Materials, Manufacturing and Assembly) approach by developing an architecture composed of four levels, namely: the Common Information Modeling Level, the Selection Systems Level, the Inference and Computation Level and finally the Application Level. The proposed automated system is based on ontologies, on the CBR (Cases Based Reasoning) and the RBR (Rules Based Reasoning). The first main result obtained throughout the contributions consists on the integration of Manufacturing process selection, Assembly solution selection and materials selection in one integrated design approach. The second main result obtained consists on the exploitation of all the previous design studies developed by the design team and the ability to reuse the designers experience throughout the case based reasoning used in the proposed architecture. Another important result consists on the formalization and the automation of the execution of the design rules and the ability to infer new results and to check inconsistencies in the developed product using the data and information modeled in the ontological model and throughout the Cases Based Reasoning that we have incorporated in the developed approach. In this way, the redundancy in work and the difficulties faced in case of having a high number of design alternatives are avoided. Consequently, the product quality increases and wastes of time and money decrease. Finally, to validate the functioning and the efficacy of the proposed DFMMA system, an application on the design of a complex mechanical product is developed in the end of the work.

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Wenting Liu ◽  
Qingliang Zeng ◽  
Lirong Wan ◽  
Jinxia Liu ◽  
Hanzheng Dai

Although some reliability importance measures and maintenance policies for mechanical products exist in literature, they are rarely investigated with reference to weakest component identification in the design stage and preventive maintenance interval during the life cycle. This paper is mainly study reliability importance measures considering performance and costs (RIMPC) of maintenance and downtime of the mechanical hydraulic system (MHS) for hydraulic excavators (HE) with energy regeneration and recovery system (ERRS) and suggests the scheduled maintenance interval for key components and the system itself based on the reliability R i t . In the research, the required failure data for reliability analysis is collected from maintenance crews and users over three years of a certain type of hydraulic excavators. Minitab is used for probable distribution estimation of the mechanical hydraulic system failure times, and the model is verified to obey Weibull distribution. RIMPC is calculated by multiplying the reliability R i t and weighting factor W i and then compared with other classical importance measures. The purpose of this paper is to identify the weakest component for MHS in the design stage and to make appropriate maintenance strategies which help to maintain a high reliability level for MHS. The proposed method also provides the scientific maintenance suggestion for improving the MHS reliability of the HE reasonably, which is efficient, profitable, and organized.

2022 ◽  
pp. 241-266
Seongwoo Woo ◽  
Dennis L. O'Neal ◽  
Yimer Mohammed Hassen

This chapter explains the parametric accelerated life testing (ALT) to recognize design defects in mechanical products. A life-stress model and a sample size formulation are suggested. A compressor is used to demonstrate this method. Compressors were failing in the field. At the first ALT, the compressor failed due to a fractured suction reed valve. The failure modes were similar to those valves returned from the field. The fatigue of the suction reed valves came from an overlap between the suction reed valve and the valve plate. The problematic design was modified by the trespan dimensions, tumbling process, a ball peening, and brushing process for the valve plate. At the second ALT, the compressor locked due to the intrusion between the crankshaft and thrust washer. The corrective action plan performed the heat treatment to the exterior of the crankshaft made of cast iron. After the design modifications, there were no troubles during the third ALT. The lifetime of compressor was secured to have a B1 life 10 years.

2022 ◽  
Vol 355 ◽  
pp. 02018
Menglei Zheng ◽  
Ling Tian

With the rapid increase of multi-source heterogeneous dynamic data of mechanical products, the digital twin technology is considered to be an important method to realize the deep integration of product data and intelligent manufacturing. As a digital archive of the physical entity in entire life cycle, the mechanical product digital twin model is cross-phased and multi-domain. Therefore, safe and stable cooperative modeling has become a basic technical problem that needs to be solved urgently. In this paper, we proposed a blockchain-based collaborative modeling method for the digital twin ontology model of mechanical products. First, an authorization network was constructed among stakeholders. Then modeling processes of the digital twin were mapped to ontology operations and formatted through extensible markup language. Finally, consensuses were obtained based on practical byzantine fault tolerance. And a material modification process of a helicopter damper bearing was taken as an example to verify. The proposed method enables all participants to accurately obtain the latest state of the digital twin model, and has the advantages of tamper-proof, traceability, and decentralization.

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 34
Rongshun Pan ◽  
Jiahao Yu ◽  
Yongman Zhao

In Industry 4.0, data are sensed and merged to drive intelligent systems. This research focuses on the optimization of selective assembly of complex mechanical products (CMPs) under intelligent system environment conditions. For the batch assembly of CMPs, it is difficult to obtain the best combinations of components from combinations for simultaneous optimization of success rate and multiple assembly quality. Hence, the Taguchi quality loss function was used to quantitatively evaluate each assembly quality and the assembly success rate is combined to establish a many-objective optimization model. The crossover and mutation operators were improved to enhance the ability of NSGA-III to obtain high-quality solution set and jump out of a local optimal solution, and the Pareto optimal solution set was obtained accordingly. Finally, considering the production mode of Human–Machine Intelligent System interaction, the optimal compromise solution is obtained by using fuzzy theory, entropy theory and the VIKOR method. The results show that this work has obvious advantages in improving the quality of batch selective assembly of CMPs and assembly success rate and gives a sorting selection strategy for non-dominated selective assembly schemes while taking into account the group benefit and individual regret.

Machines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 2
Menglei Zheng ◽  
Ling Tian

With the development of information and communication technology, massive amounts of data are generated during the entire lifecycle of mechanical products. However, their isolated and fragmented state hinders further empowerment of smart manufacturing. Digital twins have attracted considerable attention as they enable a user to rebuild all elements of a physical entity in a virtual space, targeted at the effective fusion of data from multiple sources with different formats, while its modeling method still needs further research. In this context, we propose a native, full-element digital twin modeling method for mechanical products. This ontology-based method establishes a unified and computer-understandable model framework for mechanical products by abstracting the essential content and relationships of data and by storing them in a graph database efficiently. The developed model could serve as a data center for the entire lifecycle of the product or could be combined with existing data management systems, integrating the previously isolated, fragmented, and scattered data on various platforms. In addition, the model utilizes the structural characteristics of mechanical products and is developed as a hierarchical digital mapping to better meet the application requirements. Finally, a case study of a helicopter digital twin is presented to verify the proposed method.

2021 ◽  
Qin Zhang ◽  
Jinlong Pan ◽  
Hu Chen ◽  
Yixiong Feng ◽  
Zhaoxi Hong

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