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Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process.

To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process.

The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine.

The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design.

The purpose of this exploratory paper is to analyze how complexity of an artifact affects designing processes of its mechanical, electric, and software sub‐systems.

Based on existing empirical research and frameworks of axiomatic design, product architecture, and product development process, the paper proposes a simple model of functional and structural design to examine how engineers' ways of thinking differ among mechanical, electric and software engineers.

This paper argues that products and artifacts tend to become complex (often with integral architecture) when customers' functional requirements become more demanding and societal/technological constraints become stricter, and that complex mechanical products are often accompanied by electronic control units with complex functions. This implies that designing complex mechanical products often requires intensive coordination among mechanical, electric and software engineers. This, however, is not easy, as engineers' way of thinking is often different among the three areas: mechanical engineers want to complete structural design information first to build prototypes; electrical and software engineers (the latter in particular) request complete functional information first.

In order to solve the above‐mentioned mechanical‐electrical‐software coordination problem, engineers need to share basic design concept of the product in question. Heavy‐weight product managers who infuse the product concept to the project members might be the key to this coordination. Companies may need to make sure that their product development processes are friendly to all of the three groups of engineers.

Although designing complex artifacts has been a popular research theme since H. Simon's seminal work, issues of organizational coordination for developing complex products, with increasing managerial importance, need further research. With an empirical case of the automobile and electronic products, the present paper is unique in that it combines frameworks of product development processes, product architectures, and organizational capabilities.

The development of complex products and systems is a continuously iterative process from customer requirements to a mature design. Design changes derived from multisources occur frequently during the design process. Furthermore, change propagation will impose impacts on design costs and lead times. In view of this, how to predict and control the propagation of multisource design change to reduce the changes impact is an urgent issue in the development of complex product.

In this paper, a new four-phase routing approach based on weighted and directed complex networks is proposed for multisource design change propagation. Phase I: as the foundation of this research, a product network model is established to quantify describe the complex product. Phase II: the hub nodes are identified based on the LeaderRank algorithm, which can be regarded as multisource nodes of design changes. Phase III: a calculation method for change propagation intensity is proposed, which improves the systematicness and accuracy of the evaluation results. In this paper, change propagation intensity is defined by four assessment factors: importance degree of parts, execution time of design tasks, coupling strength between parts and propagation likelihood. Phase IV: a routing method of multisource design change propagation and ant colony optimization algorithm are proposed in this paper, which can solve the coupling conflicts among change propagation paths and improve the search efficiency by using the parallel search strategy.

The proposed method and another method are used to search the optimal propagation path of multisource design change of a motorcycle engine; the results indicate that this method designed in this study has a positive effect on reducing the change impact, market response time and product design costs when design change occurs in the products design process.

The authors find a new method (a network-based four-phase routing approach) to search the optimal propagation path of multisource design change in complex products design.

Improving the prediction accuracy of design time for complex products is significant for improving the accuracy of product development and control plans. The purpose of this study is to propose an intelligent pre-estimation method of design time for complex products based on v-SVM.

First, an evaluation model for designer knowledge abilities based on v-SVM is built, which considers the fuzziness and dynamics of designer knowledge abilities. Next, a pre-estimation method for the design time of complex products based on v-SVM is built. This method takes into account the impacts of designer knowledge abilities and design task characteristics on the design time. Then, an adaptive genetic algorithm is programmed to optimize the parameters in the evaluation model and the pre-estimation method. Finally, a practical application and comparative analysis of the proposed pre-estimation method is suggested to verify the validity and applicability of this research.

First, the evaluation of designer knowledge abilities is a prediction problem that is both fuzzy and multivariate time series. Second, the pre-estimation of design time is a problem that is fuzzy and multivariate. Third, the pre-estimation accuracy of the proposed method is higher when compared with traditional methods.

This paper presents an intelligent pre-estimation method of design time for complex products. Unlike previous research, the pre-estimation method takes into account the impacts of both the designer knowledge abilities and the design task characteristics on the design time.

With the development of science and technology, more creators are trying to use new crafts to represent the cultural trends of the social media era, which makes cultural heritage innovative and new genres emerge. This compels the academic community to examine craft from a new perspective. It is very helpful to understand the hidden representational structure of craft more deeply and improve the craft innovation system of cultural and creative products that we deconstruct the craft based on Complex Network and discover its intrinsic connections.

The research crawled and cleaned the craft information of the top 20% products on the Forbidden City’s cultural and creative products online and then performed Complex Network modeling, constructed three craft representation networks among function, material and technique, quantified and analyzed the inner connections and network structure of the craft elements, and then analyzed the cultural inheritance and innovation embedded in the craft representation networks.

The three dichotomous craft representation networks constructed by combining function, material and technique: (1) the network density is low and none of them has small-world characteristics, indicating that the innovative heritage of the craft elements in the Forbidden City’s cultural and creative products is at the stage of continuous exploration and development, and multiple coupling innovation is still insufficient; (2) all have scale-free characteristics and there is still a certain degree of community structure within each network, indicating that the coupling innovation of craft elements of the Forbidden City’s cultural and creative products is seriously uneven, with some specific “grammatical combinations” and an Island Effect in the network structure; (3) the craft elements with high network centrality emphasize the characteristics of decorative culture and design for the masses, as well as the pursuit of production efficiency and economic benefits, which represent the aesthetic purport of contemporary Chinese society and the ideological trend of production and life.

The Forbidden City’s cultural and creative products should continue to develop and enrich the multi-coupling innovation of craft elements, clarify and continue their own brand unique craft genes, and make full use of the network important nodes role.

In this paper, we seek to understand how changes in product architecture affect the innovation performance of firms in a complex product ecosystem. The canonical view in the literature is that changes in the technological dependencies between components, which define a product’s architecture, undermine the innovation efforts of incumbent firms because their product development efforts are built around existing architectures. We extend this prevailing view in arguing that component dependencies and changes in them affect firm innovation efforts via two principal mechanisms. First, component dependencies expand or constrain the choice set of firm component innovation efforts. From the perspective of any one component in a complex product (which we label the focal component), an increase in the flow of design information to the focal component from other (non-focal) components simultaneously increases the constraint on focal component firms in their choice of profitable R&D projects while decreasing the constraint on non-focal component firms. Second, asymmetries in component dependencies can confer disproportionate influence on some component firms in setting and dictating the trajectory of progress in the overall system. Increases in such asymmetric influence allow component firms to expand their innovation output. Using historical patenting data in the personal computer ecosystem, we develop fine-grained measures of interdependence between component technologies and changes in them over time. We find strong support for the empirical implications of our theory.

Existing research on product design has found that a design’s complexity is an important antecedent of consumers’ aesthetic and behavioural responses. This paper aims to shed new light on the relationship between design complexity and perceptions of design quality by taking the effects of consumers’ naïve theories into account.

The hypotheses of this paper are tested in a series of three experiments.

The findings from three studies show that the extent to which consumers prefer more complex product designs to simpler ones depends on the extent to which they believe that the complexity of a design is indicative of the effort or of the talent of the designers involved in the design process. These competing naïve theories, in turn, are triggered by contextual information that consumers have at their disposal, such as the professional background of a designer or the brand that is associated with a particular design.

This research was limited to a design's complexity as the central design element and to the effects of two naïve theories. Future research may also take other design factors and consumer heuristics into account.

This research reveals that the extent to which managers may successfully introduce both complex and simple designs may depend on the reputation of a company’s designers and the prestige of a brand.

This research examines design complexity from a novel theoretical perspective and shows that the effect of design complexity on perceptions of design quality is contingent on two specific naïve theories of consumers.

The purpose of this paper is to find a method for key assembly structure identification in complex mechanical assembly. Three-dimensional model reuse plays an increasingly important role in complex product design and innovative design. Assembly model has become important resource of models reuse in enterprises, which contains certain function assembly structures. These assembly structures implicating plenty of design intent and design experience knowledge can be used to support function-structure design, modular design reuse and semantics analysis for complex product.

A method for identifying key assembly structures in assembly model is presented from the viewpoint of assembly topology and multi-source attributes. First, assembly model is represented based on complex network. Then, a two-level evaluation model is put forward to evaluate importance of parts assembled, and the key function parts in assembly can be obtained. After that, on the basis of the function parts, a heuristic algorithm upon breadth first searching is given to identify key assembly structures.

The method could be used to evaluate key function parts and identify key assembly structures in complex mechanical assembly according to the specific circumstances.

The method can not only help designers find the key assembly structure in complex mechanical assembly model, facilitate the function-structure designing and semantics analyzing, and thereby improve the efficiency of product knowledge reuse, but also assist in analyzing influence scope of key function part changing and optimization of the assembly process for complex mechanical assembly.

The paper is the first to propose a method for key assembly structure identification in complex mechanical assembly, where the key function parts can be evaluated through a two-level evaluation model, and the key assembly structures are identified automatically based on complex network.

The purpose of this paper is to achieve the capability of redesigning complex products system with enhanced efficiency and effectiveness.

It is noted that, by changing one subsystem in a complex product design architecture, the change effects can be propagated to other subsystems through their interrelationships. This condition has to be taken into account when deciding on which subsystems to be modified in the redesign plan because the subsequent effects might be too risky for the development process. Estimating redesign risk for complex product architectures is not an easy task, thus designers often need a decision-making aid to efficiently select the best “change initiating” subsystems. This can be done by providing the designers with a ranking of subsystems based on their estimated redesign risk. Moreover, this decision-making process is taking place during early redesign stages whereby the uncertainties related to the actual level and type of changes to be made on the subsystems are high. Because of this, a stochastic approach is taken to be more appropriate in deriving the redesign risk estimates. This leads to the proposed application of the Monte Carlo method to estimate the subsystem redesign risk for complex products, as demonstrated through an example case study of aircraft redesign.

This use of the Monte Carlo method helps to distinguish the level of risks associated with each subsystem in the complex product design architecture, which is helpful for designers while making decisions on which subsystems to be changed for the redesign task at hand.

This technique can be applied to assist designers in making decisions during the early stages of the redesign process under high design uncertainties.

The work presents a new alternative method to estimate the redesign risks of subsystems in complex products that can improve the effectiveness of the designer’s decision-making process in the early redesign stages. While many other available change methods tend to ignore the uncertainty associated with the decision-making process, the method presented here directly takes into account the stochastic nature of the process.

For decades now, industrial manufacturers’ complex product development (CPD) activities have seen various improvement approaches as well as product development (PD) support processes all in the quest to achieve shorter PD lead-times and higher return on investments. CPD process improvements, in terms of complex engineering design and delivery, still lack a lot more variance to be addressed on the “better, faster and cheaper” paradigm for efficient communication and information exchange flow processes. The paper aims to discuss these issues.

This paper presents employing social network theory analysis and statistical Pearson (r) correlation analysis in a triangulation approach to a proposed optimum conceptual information technology systems’ architecture and a “best practice” information flow process toward enhancing an industrial sustainable competitive advantage. Closed-end questionnaires were used to collect data for the scale or level of communication network from a sample size of eight Ship Power supply chain network complex engineering design and delivery systems-design teams with at least five members from each team.

Two extremely interesting findings and observations were identified from the analysis carried out (isolates and close-harmonic analysis) as well as the findings from the hypotheses’ testing. These essential analyses of the engineering systems-design teams were conducted by using the triangulation or mixed-method described in the abstract methodology identified above.

Effective and efficient real-time communication is seen as the vehicle for effective organization management. Although there may be some studies on effective technical communication in organizational and enterprise supply chain management settings, this research identifies a new robust and extensive analysis and feasible solutions to most of the communication bottlenecks and inefficient socio-industrial information flow processes, which need enhancement for industrial competitive advantage. Furthermore, the contribution of this paper further enhances the level 4 implementation aspect of the supply chain operation reference model in a replicable industry-specific perspective.