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This paper investigates a dual-channel supply chain in which a manufacturer offers coupons in the online channel and the retailer in the offline channel. The optimal pricing and coupon promotion policies are explored, and the brand image under different promotion scenarios is studied.

Three differential game models, namely no coupon is offered, coupons offered by the manufacturer and coupons offered by the retailer, are constructed.

The results show that the manufacturer and retailer intend to conduct coupon promotions under a large coupon redemption rate. Coupon promotion derives a higher price and profit for the issuers, and the manufacturer can free-ride on the retailer's coupon promotion. The retailer's profit in the retailer-promotion scenario may be lower than that in the manufacturer-promotion scenario in some special conditions. Besides, price, coupon face value, brand image and profit increase over time. After multiple cycles game, the operational strategy evolves to an optimal equilibrium status.

This paper provides guidance and advice for dual-channel supply enterprises to implement joint pricing and coupon promotion strategies under multiple sales seasons.

This paper aims to investigate the impact of retailer innovation investment and its spillover’s effect on competitive dual-channel supply chain pricing and optimization strategy, and explore the coordination mechanism considering decision maker’s bargaining ability.

The Cournot and Stackelberg game methodology are made use of for the duopoly decentralized and joint decision-making model. The bargaining theory with different negotiation ability was used to analysis the coordination mechanism. Then this paper validates the model by simulation techniques.

The results enlightened some interesting facts, the increase in innovation demand coefficient spur rise in channel pricing, innovation investment level, supply chain profit and consumer welfare. The rise in innovation spillover coefficient leads to increase in online channel pricing, supply chain profit and consumer welfare. Due to the innovation spillover effect, retailer has to maintain channel competitiveness either through low price or high innovation investment strategies. In addition, online channel pricing, supply chain profit and consumer welfare in joint decision-making scenario is greater than that of decentralized decision-making scenario, while the difference in retailer channel pricing depends on parameters value. The increase in retailer’s joint negotiation factor leads to decrease in channel pricing and innovation investment level. Furthermore, there existence of an optimal innovative investment cost sharing proportion threshold indicates the achievement of dual-channel supply chain coordination. A refinement equilibrium can be achieved through Robinstein bargaining game. A larger interest discount factor leads to decrease in profit.

The research provides a theoretical reference for dual-channel supply chain pricing and coordination strategy under channel competition environment. The research can develop innovative investment strategies for retailers and implement response strategies for manufacturers.

Process mining provides a new means to improve processes in a variety of application domains. The purpose of this paper is to abstract a process model and then use the discovered models from process mining to make useful optimization via predictions.

The paper divides the process model into a combination of “pair-adjacent activities” and “pair-adjacent persons” in the event logs. First, two new handover process models based on adjacency matrix are proposed. Second, by adding the stage, frequency, and time for every activity or person into the matrix, another two new handover prediction process models based on stage adjacency matrix are further proposed. Third, compute the conditional probability from every stage to next stage through the frequency. Finally, use real data to analyze and demonstrate the practicality and effectiveness of the proposed handover optimization process.

The process model can be extended with information to predict what will actually happen, how possible to reach the next activity, who will do this activity, and the corresponding probability if there are several people executing the same activity, etc.

The contribution of this paper is to predict what will actually happen, how possible it is to reach the following activities or persons in the next stage, how soon to reach the following activities or persons by calculating all the possible interval time via different traces, who will do this activity, and the corresponding probability if there are several people executing the same activity, etc.

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

Bat algorithm (BA) is a global optimization method, but has a worse performance on engineering optimization problems. The purpose of this study is to propose a novel chaotic bat algorithm based on catfish effect (CE-CBA), which can effectively deal with optimization problems in real-world applications.

Incorporating chaos strategy and catfish effect, the proposed algorithm can not only enhance the ability for local search but also improve the ability to escape from local optima traps. On the one hand, the performance of CE-CBA has been evaluated by a set of numerical experiment based on classical benchmark functions. On the other hand, five benchmark engineering design problems have been also used to test CE-CBA.

The statistical results of the numerical experiment show the significant improvement of CE-CBA compared with the standard algorithms and improved bat algorithms. Moreover, the feasibility and effectiveness of CE-CBA in solving engineering optimization problems are demonstrated.

This paper proposed a novel BA with two improvement strategies including chaos strategy and catfish effect for the first time. Meanwhile, the proposed algorithm can be used to solve many real-world engineering optimization problems with several decision variables and constraints.

This study aims to investigate the effect of post-treatment on anti-corrosion performance of Al coating on the surface of Ti-6Al-4V (TC4) fastener.

The Al coatings with different layer structures were prepared on TC4 by middle-frequency and direct-current combined magnetron sputtering. The cross-sectional morphology and surface roughness of coatings were characterized by scanning electron microscope and atomic force microscope. The corrosion resistance was evaluated by electrochemical method. The monolayer coating was post-treated by Alodine chemical conversion, Ar⁺ bombardment and a combination of two methods above.

The results show that the interfaces in bilayer and trilayer coatings reduce the defects. Ar⁺ bombardment reduces the corrosion current density, and Alodine chemical conversion leads to a higher pitting corrosion potential. The combined post-treatment has the highest polarization resistance.

The corrosion resistance of the Al coating is enhanced as the layer quantity increases. The combination of two post-treatments, Ar⁺ bombardment and Alodine chemical conversion, could achieve an overall improvement in corrosion resistance of Al coating.

The purpose of this study is to develop a monolayer surface coating of stearic acid on Sn-Ag-Cu solder powder to limit oxidation.

Stearic acid was adsorbed onto Sn-Ag-Cu solder powder through liquid-phase adsorption. The isotherm of adsorption was measured and then the microstructure of coated powder was characterized by scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy.

The adsorption isotherm of stearic acid on the powder was “H” type, which revealed the layer-by-layer adsorption on non-porous surface. When the concentration of solution was in the range of 0.001-0.006 mol/L, with an adsorption amount of 0.12 ± 0.1 mg/g, monolayer stearic acid covered the solder powder completely. Uniform and integrated self-assembled monolayer coating was formed through hydrogen bonds between the oxygen ions in surface lattice of Sn3.0Ag0.5Cu solder powder and the —O—H hydroxyl group of stearic acid. The maximum angle of stability of coated powder also reduced by 2.87° compared with that of non-coated powder. The increase rate of oxygen content of coated powder was much slower than that of non-coated powder when they were exposed to humid air.

As a result, oxidation of fine solder powder was effectively limited. Essentially, this method can also be applied to the coating of other types of solder powder and has reference significance to other coating by liquid-phase method.

As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform.

First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced.

Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO.

The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.

The purpose of this paper is to describe the development of a novel mobile monitoring and control (MC) framework with active-push and plug-and-play capabilities. This proposed framework is particularly designed to addresses the shortcomings of the traditional factory MC systems in sharing information over the internet, protecting the system security, delivering warning messages, and deploying monitoring points.

By leveraging web service technology, mobile devices, and wireless communication, this paper describes the methodology and approach for designing a MC server, a wireless monitoring module (WMM), an intelligent v-Machine, two active-push mechanisms, a pocket PC application, and a smart phone application.

The designed WMM enables the monitoring points to be deployed in a mobile manner. The proposed mobile MC framework (MMCF) can timely detect abnormalities of appliances and equipment and turn off appliances in dangerous situations through WMM. It can also instantly deliver various warning contents to the mobile devices carried by the responsible persons. The v-Machine is built based on virtual metrology (VM) technology and can predict production precision of machined workpieces.

With the successful design and testing of the novel MMCF, this framework can obviously be used for many more applications and developments.

The authors' implement a factory MC system based on the proposed framework and conduct various integration tests on two electric appliances and a practical CNC machine tool in a factory. Testing results shows that the factory MC system works smoothly according the design goals and can overcome the shortcomings of traditional factory MC systems. The MC system also presents good performances, instantly delivering warning contents with a size ranging from 1K bytes to 10M bytes to the users within few seconds.

The proposed MMCF exploits various automation technologies to detect equipment's abnormalities, reduce the rate of product defects caused by human errors, reinforce security, prevent accidents, and ensure the safety of operations.

The proposed MMCF can effectively promote existing factory MC systems to achieve the merits of mobile MC, which is a unique contribution of this work, compared to previous studies. The results of this study can be applied to a variety of industrial automation applications, including factory automation and assembly automation.