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Three-dimensional computer-aided design (CAD) assembly model has become important resource for design reuse in enterprises, which implicates plenty of design intent, assembly intent, design experience knowledge and functional structures. To acquire quickly CAD assembly models associated with specific functions by using product function requirement information in the product conceptual design phase for model reuse, this paper aims to find an approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model before functional semantic-based assembly retrieval.

An approach for structure-function correlations analysis and functional semantic annotation of CAD assembly model is proposed. First, the product knowledge model is constructed based on ontology including design knowledge and function knowledge. Then, CAD assembly model is represented by part attributed adjacency graph and partitioned into multiple functional regions. Assembly region and flow-activity region are defined for structure-function correlations analysis of CAD assembly model. Meanwhile, the extraction process of assembly region and flow-activity region is given in detail. Furthermore, structure-function correlations analysis and functional semantic annotation are achieved by considering comprehensively assembly structure and assembled part shape structure in CAD assembly model. After that, a structure-function relation model is established based on polychromatic sets for expressing explicitly and formally relationships between functional structures, assembled parts and functional semantics.

The correlation between structure and function is analyzed effectively, and functional semantics corresponding to structures in CAD assembly model are labeled. Additionally, the relationships between functional structures, assembled parts and functional semantics can be described explicitly and formally.

The approach can be used to help designers accomplish functional semantic annotation of CAD assembly models in model repository, which provides support for functional semantic-based CAD assembly retrieval in the product conceptual design phase. These assembly models can be reused for product structure design and assembly process design.

The paper proposes a novel approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model. Functional structures in assembly model are extracted and analyzed from the point of view of assembly structure and function part structure. Furthermore, the correlation relation between structures, assembled parts and functional semantics is expressed explicitly and formally based on polychromatic sets.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

The development of low-carbon production is impeded by the investment costs of green technology research and development (R&D) and carbon emission reduction while facing the uncertain risk of emission reduction investment. With the government's carbon emission constraints, green manufacturers implement the advance selling strategy to increase both profit and reduction level. However, few studies consider the consumer's green preference and emission constraints in advance selling market and spot market independently. The authors' paper investigates the optimal strategies of advance selling pricing and reduction effort for green manufacturers to maximize profits.

The authors' paper designs a stochastic model and investigates the manufacturer's optimal strategies of advance selling price and emission reduction efforts by categorizing different purchasing periods of low-carbon consumers. With the challenges of uncertain demand and government's emission constraints, the authors' develop the non-linear optimization model to investigate the manufacturer's profit-oriented decisions.

The results show the government's carbon constraints cannot influence the manufacturer's profit, but the consumer's low-carbon preference in the advance selling period can. Interestingly, the manufacturer will make fewer reduction efforts even when the consumers have stronger environmental awareness. In addition, the increasing consumer price sensitivity will exacerbate the profit loss from mandatory emissions reduction. Overall, for achieving a win–win situation between emission reduction and profit growth, green manufacturers should not only consider the sales strategies, market demand, and government constraints in a low-carbon market, but also pay attention to the uncertainty of green technology innovation.

With the consideration of the government's carbon emission constraints, uncertain demand, and low-carbon consumer's preferences, the authors' study innovatively incorporates the joint impacts of advance selling strategy and emission reduction effort strategy and then differentiates between two cases that pertain to the diverse carbon emission regulations.

In order to minimize the impact of variability on performance of the process, proper understanding of factors interdependencies and their impact on process variability (PV) is required. However, with insufficient/incomplete numerical data, it is not possible to carry out in-depth process analysis. This paper presents a qualitative framework for analyzing factors causing PV and estimating their influence on overall performance of the process.

Fuzzy analytic hierarchy process is used to evaluate the weight of each factor and Bayesian network (BN) is utilized to address the uncertainty and conditional dependencies among factors in each step of the process. The weighted values are fed into the BN for evaluating the impact of each factor to the process. A three axiom-based approach is utilized to partially validate the proposed model.

A case study is conducted on fused filament fabrication (FFF) process in order to demonstrate the applicability of the proposed technique. The result analysis indicates that the proposed model can determine the contribution of each factor and identify the critical factor causing variability in the FFF process. It can also helps in estimating the sigma level, one of the crucial performance measures of a process.

The proposed methodology is aimed to predict the process quality qualitatively due to limited historical quantitative data. Hence, the quality metric is required to be updated with the help of empirical/field data of PV over a period of operational time. Since the proposed method is based on qualitative analysis framework, the subjectivities of judgments in estimating factor weights are involved. Though a fuzzy-based approach has been used in this paper to minimize such subjectivity, however more advanced MCDM techniques can be developed for factor weight evaluation.

As the proposed methodology uses qualitative data for analysis, it is extremely beneficial while dealing with the issue of scarcity of experimental data.

The prediction of the process quality and understanding of difference between product target and achieved reliability before the product fabrication will help the process designer in correcting/modifying the processes in advance hence preventing substantial amount of losses that may happen due to rework and scraping of the products at a later stage.

This qualitative analysis will deal with the issue of data unavailability across the industry. It will help the process designer in identifying root cause of the PV problem and improving performance of the process.

The purpose of this paper is to find the optimal power structure that drives green practices in the supply chain and coordinate the costs and benefits of green practices in supply chain under different power structures.

This paper developed a supply chain of one supplier and one manufacturer, in which the supplier and the manufacturer are responsible for the “greening” of products. Then, the game theory modeling method is used to explore the influence of different power structures on green practices in the supply chain. Finally, the authors developed a green cost-sharing contract made by the leader; regarding optimal supply chain profits and green performance, the proposed contracts and the non-coordination situation are compared and tested by a numerical simulation.

The increase of the green practice difficulty of any member in the supply chain will not only reduce the greenness of products at that stage but will also reduce the green investment of the supply chain partner. Becoming a channel leader does not necessarily mean being more profitable than being a follower, and when the green practice difficulty of the leader is less than a certain threshold, ceding dominant power to the follower may benefit both sides. A green cost-sharing contract made by the leader is not necessarily beneficial to all enterprises.

This paper helps to better understand the role of the power relation in realizing the industry's green goals and helps decision-makers to achieve win-win cooperation by adjusting power relations and optimizing green cost-sharing contracts.

China is among one of the oldest civilizations in the world. The massive land mass of China also means that the Chinese people are subject to weather extremes as well as topographical variety in a country which cuts across alpine heights, treacherous deserts, lush valleys, dusty plains and lengthy rivers. With these weather extremes as the backdrop, it is crucial for the Chinese people to develop appropriate environmental control techniques for their dwellings as well as to ensure the structural integrity of their buildings. This paper discusses the protection, heating, anti‐seismic and dampness techniques developed and implemented in ancient China. It also documents the measures taken by the ancient Chinese to ensure the structural integrity of their buildings. The examples highlighted in this paper suggest that the building science principles adopted in ancient China remain relevant in the construction industry today.

The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.

Abutment damage in liquefied ground is an important form of seismic damage of bridge structure. This paper aims to further research the effect of beam restriction on seismic damage mode of abutment in liquefied ground.

Based on the investigation of the seismic damage of Shengli Bridge in Tangshan earthquake, the finite element software dynamic effective stress analysis for ground (UWLC) is used to simulate the seismic damage of Shengli Bridge, and the results were compared with the actual seismic damage results. Then, the influences of the horizontal binding force of the beam, the liquefaction layer thickness, the top weight of the abutment, the peak acceleration, the liquefaction layer buried depth and the type of the foundation soil on the abutment seismic damage model are studied.

The results show that numerical simulation results are consistent with the actual seismic damage, and it is feasible to use UWLC software to simulate seismic damage. The results show that the seismic failure mode of the gravity abutment in liquefied ground is slip–rotation coupling type, not single slip type or rotation type. The large deformation of abutment bottom layer, horizontal binding force of the beam and post-stage soil pressure are the main reasons for abutment rotation or even destruction.

A series of basic assumptions are used in the calculation process in this paper. The gravity abutment is defined as the elastic body and neglects its local deformation. The soil layer is a homogeneous isotropic. The consolidation process and the drainage boundary problem are not considered in the calculation process. Therefore, the paper may have some limitations.

To further research the seismic damage mode and influencing factors of abutment in liquefied ground, in this paper, based on the investigation of the seismic damage of Shengli Bridge in Tangshan earthquake, the finite element software UWLC is used to simulate the seismic damage of Shengli Bridge, and the results were compared with the actual seismic damage results. The seismic damage mode and influencing factors of gravity abutment in liquefied ground have been studied.

The purpose of this paper is to describe a comprehensive modelling technique that supports the assembly of very complex products that require intensive use of both computerized worker guidance and automation. The modelling enables the planning of this complex process.

The proposed approach utilizes and extends typical product documentation (such as route cards and bill of materials (BOM)) to form hierarchical Petri net in a stepwise process. The suggested framework models the dynamic progress of the assembly process, and can generate route card instructions for manual operations, or ladder diagrams (LDs) for automation.

The model can help the generation of computerized control over route cards for manual assembly operations. For automated processes, the translation algorithm of the model to LD enables its application on currently available equipment (programmable logic controllers (PLCs)).

The proposed framework heavily depends on the BOM data quality. So it is crucial to verify that the BOM data is not ill-defined before applying the proposed framework. Future research could report on the implementation of this model in assembly processes, or suggest another modelling technique.

The model enables the integration of computer control over both manual and automated assembly processes. This enables seamless transition between these two very different operations. This ability carries the promise of reducing the cost of code generation and maintenance, and contributes to the progress towards more flexible automation.

This paper presents a new comprehensive modelling technique that may support planning, simulating, tracing, and controlling the assembly process. The technique for the first time integrates modelling of both manual and automated assembly operation.

This paper describes the organic geochemical characteristics and their roles on barium enrichment in the No. 2 Coal from Huanglong Jurassic Coalfield, China. A total of 18 bench samples were taken from Huangling Mine 2. The average content of barium (3701 mg/kg) was about 23 times higher than that of common world coals. Terrestrial higher plants were the main coal-forming parent material. Relying on the parameters of OEP, Pr/Ph and so on, there is little correlation between organic geochemical characteristics and barium enrichment. Therefore, organic material has little influence on the process of coal-forming and the enrichment of barium.