scholarly journals Assembly Tolerance Design Based on Skin Model Shapes Considering Processing Feature Degradation

2019 ◽  
Vol 9 (16) ◽  
pp. 3216 ◽  
Author(s):  
Ci He ◽  
Shuyou Zhang ◽  
Lemiao Qiu ◽  
Xiaojian Liu ◽  
Zili Wang

To increase the reliability and accuracy of tolerance design, more and more research works are considering not only orientation and position deviations; they are also forming errors in tolerance modeling. As a direct cause of form errors in industrial mass production, the processing features of the machining system degrade over time. Under the Industry 4.0 paradigm, an assembly tolerance design method based on Skin Model Shape is proposed to take the effect of degrading processing features into consideration. A continuous-time multi-dimensional Markov process is trained through maximum likelihood estimation based on the nodal sampling point set on the machined surface. Degradation of the machined surface is modeled based on the joint probability distribution of nodal displacements. Assembly force constraints and assembly entity constraints are applied to spatial assembly simulations. Tolerance synthesis takes the manufacturing cost and assembling probability as design objectives. A design example of the rotary feed component in a five-axis machine tool is proposed for explanation and verification.

2018 ◽  
Vol 165 ◽  
pp. 22028
Author(s):  
Lin Ma ◽  
GuangTao Xu ◽  
Gang Wang ◽  
MingHao Zhao

The Stress concentration factor (SCF) induced by the machined surface is more complex than that resulting from macro-geometry discontinuities and has great effect on fatigue life of structure. However, another important parameter, stress gradient (SG), was always ignored. The notch roots or valleys of the wave surface constitute fatigue hot points, where cracks occur, so it is essential to study the SCF and SG at valleys rather than just the root-mean-square SCF variable. In this work, a new method for evaluating the influences of surface topography on fatigue propriety of the random machined surfaces was given. An analytical method using Fourier transformation to simulate machined surface topography is presented. Analytical formulae for SCF and SG for random machined surfaces are derived subjected to a general loading and validate these formulae via finite element method (FEM). Joint probability-distribution function for SCF and SG at the valleys of the random machined-surface topography of the machined sample was obtained after different cycles fatigue test. This method gave us how the surface topography effect the fatigue properties of machined components. Fatigue test of machined sample for a single crystal nickel based alloy were established for validated this method. The obtained results should be useful in studying and evaluating fatigue properties of machined components.


Author(s):  
Chang-Xue Feng ◽  
Andrew Kusiak

Abstract Design of a product (process) includes system design, parameter design, and tolerance design. Robust design is closely applicable to parameter design and tolerance design. The current literature on robust design is focused on parameter design while little attention has been paid to tolerance design. The current literature on tolerance design has focused on the use of optimization to minimize cost while little attention has been paid to minimizing manufacturing variations. This paper attempts to apply a robust design method, the design of experiments (DOE) approach, in tolerance synthesis to minimize manufacturing variations in the probabilistic case. Both, the manufacturing cost and the number of manufacturing defects are minimized in robust tolerance design. A solution procedure is proposed to apply the DOE approach to probabilistic tolerance design. The procedure is illustrated with an example. Special applications of the DOE approach to tolerance design are discussed. A brief comparison of the DOE approach with optimization, Taguchi methods, and zero defect design is presented.


Author(s):  
André Luís Morosov ◽  
Reidar Brumer Bratvold

AbstractThe exploratory phase of a hydrocarbon field is a period when decision-supporting information is scarce while the drilling stakes are high. Each new prospect drilled brings more knowledge about the area and might reveal reserves, hence choosing such prospect is essential for value creation. Drilling decisions must be made under uncertainty as the available geological information is limited and probability elicitation from geoscience experts is key in this process. This work proposes a novel use of geostatistics to help experts elicit geological probabilities more objectively, especially useful during the exploratory phase. The approach is simpler, more consistent with geologic knowledge, more comfortable for geoscientists to use and, more comprehensive for decision-makers to follow when compared to traditional methods. It is also flexible by working with any amount and type of information available. The workflow takes as input conceptual models describing the geology and uses geostatistics to generate spatial variability of geological properties in the vicinity of potential drilling prospects. The output is stochastic realizations which are processed into a joint probability distribution (JPD) containing all conditional probabilities of the process. Input models are interactively changed until the JPD satisfactory represents the expert’s beliefs. A 2D, yet realistic, implementation of the workflow is used as a proof of concept, demonstrating that even simple modeling might suffice for decision-making support. Derivative versions of the JPD are created and their effect on the decision process of selecting the drilling sequence is assessed. The findings from the method application suggest ways to define the input parameters by observing how they affect the JPD and the decision process.


2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110349
Author(s):  
Huiqiang Guo ◽  
Mingzhe Li ◽  
Pengfei Sun ◽  
Changfeng Zhao ◽  
Wenjie Zuo ◽  
...  

Rotary-wing unmanned aerial vehicles (UAVs) are widespread in both the military and civilian applications. However, there are still some problems for the UAV design such as the long design period, high manufacturing cost, and difficulty in maintenance. Therefore, this paper proposes a novel design method to obtain a lightweight and maintainable UAV frame from configurable design to detailed design. First, configurable design is implemented to determine the initial design domain of the UAV frame. Second, topology optimization method based on inertia relief theory is used to transform the initial geometric model into the UAV frame structure. Third, process design is considered to improve the manufacturability and maintainability of the UAV frame. Finally, dynamic drop test is used to validate the crashworthiness of the UAV frame. Therefore, a lightweight UAV frame structure composed of thin-walled parts can be obtained and the design period can be greatly reduced via the proposed method.


Author(s):  
Barnabás Zoltán Balázs ◽  
Márton Takács

Micro-milling is one of the most essential technologies to produce micro components, but due to the size effect, it has many special characteristics and challenges. The process can be characterised by strong vibrations, relatively large run-out and tool deformation, which directly affects the quality of the machined surface. This paper deals with a detailed investigation of the influence of cutting parameters on surface roughness and on the special characteristics of micro-milled surfaces. Several systematic series of experiments were carried out and analysed in detail. A five-axis micromachining centre and a two fluted, coated carbide micro-milling tool with a diameter of 500 µm were used for the tests. The experiments were conducted on AISI H13 hot-work tool steel and Böhler M303 martensitic corrosion resistance steel with a hardness of 50 HRC in order to gain relevant information of machining characteristics of potential materials of micro-injection moulding tools. The effect of the cutting parameters on the surface quality and on the ratio of Rz/ Ra was investigated in a comprehensive cutting parameter range. ANOVA was used for the statistical evaluation. A novel method is presented, which allows a detailed analysis of the surface profile and repetitions, and identify the frequencies that create the characteristic profile of the surface. The procedure establishes a connection between the frequencies obtained during the analysis of dynamics (forces, vibrations) of the micro-milling process and the characterising repetitions and frequencies of the surface.


2017 ◽  
Vol 31 (2) ◽  
pp. 139-179 ◽  
Author(s):  
Ioannis Dimitriou

We consider a single server system accepting two types of retrial customers, which arrive according to two independent Poisson streams. The service station can handle at most one customer, and in case of blocking, typeicustomer,i=1, 2, is routed to a separate typeiorbit queue of infinite capacity. Customers from the orbits try to access the server according to the constant retrial policy. We consider coupled orbit queues, and thus, when both orbit queues are non-empty, the orbit queueitries to re-dispatch a blocked customer of typeito the main service station after an exponentially distributed time with rate μi. If an orbit queue empties, the other orbit queue changes its re-dispatch rate from μito$\mu_{i}^{\ast}$. We consider both exponential and arbitrary distributed service requirements, and show that the probability generating function of the joint stationary orbit queue length distribution can be determined using the theory of Riemann (–Hilbert) boundary value problems. For exponential service requirements, we also investigate the exact tail asymptotic behavior of the stationary joint probability distribution of the two orbits with either an idle or a busy server by using the kernel method. Performance metrics are obtained, computational issues are discussed and a simple numerical example is presented.


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