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To find the system with minimum investment and best quality performance that is capable of producing all of the product variants, assessing the complexity of designing assembly system at the early concept stage is an essential step, which helps and instructs a designer to create a product- and system-oriented assembly solution with the least complexity. The purpose of this paper is to propose a quantifying measurement of complexity in the design of a modular automated assembly system.

The configurable assembly system is becoming a trend, which enables companies to quickly respond to changes caused by different product variants but without a large investment. One of the enabling factors is the availability of modular solutions of assembly modules that can be configured according to different technical requirements. This paper develops a methodology using fuzzy evaluation to calculate the design complexity in the design phase for a modular automatic assembly system. Fuzzy linguistic variables are used to measure the interaction among the influence factors, to deal with the uncertainty of the judgement. The proposed method investigates three matrices to present how the function-based assembly modules, design complexity factors, part attributes and product components, which are regarded as the main influence factors, complicate the construction of a modular assembly system. The design complexity is derived and quantified based on these assessments.

The proposed approach presents a formal quantification to evaluate the design complexity with regard to a modular assembly system from beginning, which can be identified and used as criteria to indicate the quality of performance and investment cost in advance. A mathematical model based on the fuzzy logic is established to provide both theoretical and practical guidance for the paper. To validate the predictive model, the statistic relationships between the assessed system design complexity, real assembly defect rate and investment cost are estimated based on regression analysis. The application of the presented methodology is demonstrated with regard to a traditional rear drive unit in the automotive industry.

This paper presents a developed method, which addresses the measures of complexity found in the design of a modular assembly system. It would help to run the design process with better resource allocation and cost estimation in a quantitative approach.

Existing models of product assembly scheme design often ignore the constraint relations among design thinking. In order to grasp the functions of each part and the constraint relations among them in product assembly system macroscopically, further design and variation of product assembly system should be made according to design thinking. This paper seeks to address these issues.

Through analyzing the similarity between biological organization system and product system and taking biology knowledge for reference, product assembly system was expressed as product function gene, product constraint gene, product function protein, product constraint protein and product cell and so on in this paper. The product gene model composed of product function gene groups and constraint genes was established and a modeling method based on it was proposed.

The author applied this method to model the 5‐DOF manipulator of complex diamond manufacturing special equipment with good results which proved the effectiveness of this modeling method.

By identifying constraint relations and design thinking in the gene model, the system makes the modification process which is conducted by the designers automatically identified and varied to achieve computer‐aided design and assembly.

The purpose of this paper is to introduce the realizing process of the fuzzy logical reasoning method in relation to the insulation detection of insulator strings, especially about the establishment of the fuzzy relation matrix.

Utilizing fuzzy logical reasoning method, the online fault diagnosis of the transmission line insulator strings can be realized efficiently, although the insulation status of the insulator strings is influenced by many factors and the relation between the measured electric parameters about the insulator with the degree of the deterioration is ambiguous.

Utilizing the pattern recognition method to build the fuzzy relation matrix after choosing the probability of the corona current, the root‐mean‐square value and the peak value and the pulse frequency of the leakage current as the fuzzy operating input variables, using the fuzzy reasoning method to estimate the insulation status proves to be a practical approach.

The experiments verify the correctness of this method by simulating work conditions of insulator strings on an 110 kV transmission line.

This paper proves that using the fuzzy reasoning method to estimate the insulation status of the online insulator strings is a practical approach. The results of the laboratory and the field tests verify the correctness of this approach and the validity of the identification method to build the fuzzy relation matrix.

The purpose of this paper was to solve the shortage of carrying energy in probing robot and make full use of wind resources in the Antarctic expedition by designing a four-wheel land-yacht. Land-yacht is a new kind of mobile robot powered by the wind using a sail. The mathematical model and trajectory of the land-yacht are presented in this paper.

The mechanism analysis method and experimental modeling method are used to establish a dual-input and dual-output mathematical model for the motion of land-yacht. First, the land-yacht’s model structure is obtained by using mechanism analysis. Then, the models of steering gear, servomotors and force of wing sail are analyzed and validated. Finally, the motion of land-yacht is simulated according to the mathematical model.

The mathematical model is used to analyze linear motion and steering motion. Compared with the simulation results and the actual experimental tests, the feasibility and reliability of the proposed land-yacht modeling are verified. It can travel according to the given signal.

This land-yacht can be used in the Antarctic, outer planet or for harsh environment exploration.

A land-yacht is designed, and the contribution of this research is the development of a mathematical model for land-yacht robot. It provides a theoretical basis for analysis of the land-yacht’s motion.

The purpose of this paper is to optimize the welding parameters: rotating speed and plunging depth of carbon steel and pure copper joints using friction stir spot welding (FSSW) with the aid of the design of experiments (DOE) method.

Carbon steel and pure copper sheets were welded using the FSSW technique with a cylindrical tool and without a probe. The welding parameters were: rotating speed: 1,120, 1,400 and 1,800 RPM and plunging depth: 0.2 and 0.4 mm. The welding process was carried out both with and without pre-heating. The welded specimens were analyzed using a shear tensile test. A microstructural investigation at the optimum conditions was carried out. The results were analyzed and optimized using the statistical software Minitab and following the DOE method.

Pre-heating the sample and increasing the rotating speed and plunging depth increased the tensile shear force of the joint. The plunging depth has the biggest effect on the joint efficiency compared with the rotating speed. The optimum shear force (4,560 N) was found at 1,800 RPM, 0.4 mm plunge depth and with pre-heating. The welding parameters were modified so that the samples were welded at 1,800 RPM and at plunging depths of 0.45–1 mm in 0.05 mm steps. The optimized shear force was 5,400 N. The fractured samples exhibited two types of failure mode: interfacial and nugget pull-out.

For the first time, pure copper and carbon steel sheets were welded using FSSW and a tool without a probe with ideal joint efficiency (95 percent).