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Organization structures are as important to competitiveness as strategy because structures enable both performance and learning. Yet, organization design factors and considerations are often overlooked. The matrix structure and similar types of adhocracies have the potential to transform organizational learning and thereby create a continuous acceleration of innovation. Unlike some adhocracies, the matrix structure focuses on performance and learning. Because of deficiencies in organization culture and management skills, the matrix structure has been less than fully effective. This paper seeks to clarify the issues that continue to block organizational competitiveness as they relate to performance and learning in matrix structures.

Effective collaboration and knowledge management are the major contributors of success in the construction industry. Although a huge amount of interdisciplinary knowledge is exchanged in building design processes, there is a lack of tools for representing information flows. Therefore, this paper focuses on the collaboration between architects and structural engineers and introduces an innovative matrix-based tool named “The Layered Dependency Structure Matrix” for modeling and managing the discipline-specific and collaborative design activities. The proposed method is compared with the conventional techniques used in the industry and its application is demonstrated in a beam design example.

The purpose of this paper is to present a fresh approach to stimulate individual creativity. It introduces a mathematical representation for creative ideas, six creativity operators and methods of matrix-algebra to evaluate, improve and stimulate creative ideas. Creativity begins with ideas to resolve a problem or tackle an opportunity. By definition, a creative idea must be simultaneously novel and useful. To inject analytic rigor into these concepts of creative ideas, the author introduces a feature-attribute matrix-construct to represent ideas, creativity operators that use ideas as operands and methods of matrix algebra. It is demonstrated that it is now possible to analytically and quantitatively evaluate the intensity of the variables that make an idea more, equal or less, creative than another. The six creativity operators are illustrated with detailed multi-disciplinary real-world examples. The mathematics and working principles of each creativity operator are discussed.

The unit of analysis is ideas, not theory. Ideas are man-made artifacts. They are represented by an original feature-attribute matrix construct. Using matrix algebra, idea matrices can be manipulated to improve their creative intensity, which are now quantitatively measurable. Unlike atoms and cute rabbits, creative ideas, do not occur in nature. Only people can conceive and develop creative ideas for embodiment in physical, non-physical forms, or in a mix of both. For example, as widgets, abstract theorems, business processes, symphonies, organization structures, and so on. The feature-attribute matrix construct is used to represent novelty and usefulness. The multiplicative product of these two matrices forms the creativity matrix. Six creativity operators and matrix algebra are introduced to stimulate and measure creative ideas. Creativity operators use idea matrices as operands. Uses of the six operators are demonstrated using multi-disciplinary real-world examples. Metrics for novelty, usefulness and creativity are in ratio scales, grounded on the Weber–Fechner Law. This law is about persons’ ability to discern differences in the intensity of stimuli.

Ideas are represented using feature-attribute matrices. This construct is used to represent novel, useful and creative ideas with more clarity and precision than before. Using matrices, it is shown how to unambiguously and clearly represent creative ideas endowed with novelty and usefulness. It is shown that using matrix algebra, on idea matrices, makes it possible to analyze multi-disciplinary, real-world cases of creative ideas, with clarity and discriminatory power, to uncover insights about novelty and usefulness. Idea-matrices and the methods of matrix algebra have strong explanatory and predictive power. Using of matrix algebra and eigenvalue analyses, of idea-matrices, it is demonstrated how to quantitatively rank ideas, features and attributes of creative ideas. Matrix methods operationalize and quantitatively measure creativity, novelty and usefulness. The specific elementary variables that characterize creativity, novelty and usefulness factors, can now be quantitatively ranked. Creativity, novelty and usefulness factors are not considered as monolithic, irreducible factors, vague “lumpy” qualitative factors, but as explicit sets of elementary, specific and measurable variables in ratio scales. This significantly improves the acuity and discriminatory power in the analyses of creative ideas. The feature-attribute matrix approach and its matrix operators are conceptually consistent and complementary with key extant theories engineering design and creativity.

First to define and specify ideas as feature-attribute matrices. It is demonstrated that creative ideas, novel ideas and useful ideas can be analytically and unambiguously specified and measured for creativity. It is significant that verbose qualitative narratives will no longer be the exclusive means to specify creative ideas. Rather, qualitative narratives will be used to complement the matrix specifications of creative ideas. First to specify six creativity operators enabling matrix algebra to operate on idea-matrices as operands to generate new ideas. This capability informs and guides a person’s intuition. The myth and dependency, on non-repeatable or non-reproducible serendipity, flashes of “eureka” moments or divine inspiration, can now be vacated. Though their existence cannot be ruled out. First to specify matrix algebra and eigen-value methods of quantitative analyses of feature-attribute matrices to rank the importance of elementary variables that characterize factors of novelty, usefulness and creativity. Use of verbose qualitative narratives of novelty, usefulness and creativity as monolithic “lumpy” factors can now be vacated. Such lumpy narratives risk being ambiguous, imprecise, unreliable and non-reproducible, Analytic and quantitative methods are more reliable and consistent. First to define and specify a method of “attacking the negatives” to systematically pinpoint the improvements of an idea’s novelty, usefulness and creativity. This procedure informs and methodically guides the improvements of deficient ideas.

Complex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.

An approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.

The key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.

The approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.

The paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.

The purpose of this paper is to solve the diverse and complex problems of flat-knitting sports upper process design, improve the design ability of upper organization, and realize three-dimensional simulation function.

Firstly, the matrix is used to establish the corresponding pattern diagram and organizational diagram model, and the relationship between the two is established by color coding as a bridge to completed the transformation of the flat-knitted sports upper process design model. Secondly, the spatial coordinates of the loop type value points are obtained through the establishment of loop mesh model, the index of two-dimensional and three-dimensional models of uppers and the establishment of spatial transformation relationship. Finally, using Visual Studio as a development tool, use the C# language to implement this series of processes.

Digitizing the fabric into a matrix model, combined with matrix transformation, can quickly realize the design of the flat-knitting process. Taking the knitting diagram of the upper process as the starting point, the loop geometry model corresponding to the element information is established, and the three-dimensional simulation effect of the flat-knitted upper based on the loop structure is realized under the premise of ensuring that it can be knitted.

This paper proposes a design and modeling method for flat-knitted uppers. Taking the upper design process and 3D simulation effect as an example, the feasibility of the method is verified, which improves the efficiency of the development of the flat-knitted upper product and lays the foundation for the high-end customization of the flat-knitted upper.

Product configurator is a sales and production‐planning tool that helps to transform customer requirements into bills‐of‐materials, lists of features and cost estimations. The purpose of this paper is to introduce a method of how to analyse sales configuration models by using a design structure matrix (DSM) tool. By applying the DSM techniques, the sales configuration managers may sequence the product configuration questions and organize the connection to production.

First, the paper explains a sales configuration system structure from published academic and non‐academic works. These sources employ both theoretical and practical views on the topic of computer‐based sales expert systems. Second, the paper demonstrates an application of using DSM for configuration modelling.

The current sales configuration approaches include constraint‐based, rules‐based, and object‐oriented approaches. Product description methods vary, but the general problem remains the same: the configuration process should be designed in such a way that customer selections do not affect the previous selections. From the user point of view, answering the questions should be smooth and fast. In turn this will lead to the growing importance of building more effective product configuration models. DSM offers a systematic way to organise customer interface in sales configuration systems.

This paper analyses how DSM could help in planning product configuration modelling. Comparison of different sequences is presented. The examples used are hypothetical, but illustrate the suitability of DSM analysis. Companies are trying to establish easily configured product models, which are fast, flexible and cost‐effective for adjustments and modifications. Use of DSM may help in the roll‐out of sales configuration projects. DSM may also be used as a quick view to represent the complexity of product configurability. The future needs for configuration tools will be focused towards product model management from the technical limitations of different data storage approaches.

Configurator software creates product variants, which are logical descriptions of physical products. Variants have parameters which describe the customer‐made selections. The parameter selections may have interconnections between the choices. Some selections may affect further selections and some combinations may not be allowed for incompatibility, cost or safety reasons. There are several commercial software packages available for creating product configurations. Product description methods vary, but the general problem remains the same: the configuration process should be designed in such a way that customer selections do not affect the previous selections. Answering the questions should be smooth and fast. Configuration of complex products, for instance, airplanes, may include several sub‐systems and have various loops within the quotation process. The use of DSM may help in the roll‐out of sales configuration projects. DSM may also be used as a quick view to represent the complexity of product configurability.

The paper helps both researchers and practitioners to obtain a clearer view on the development of sales configuration systems and the potential of systematic DSM‐based product model analysis.

The purpose of this paper is to conceptualize archetypes of engineer-to-order (ETO) to support companies in determining the appropriate degree of design standardization and automation, and as a result achieve superior performance. Products of ETO manufacturers are classified in a 2×2 matrix using annual units sold and engineering complexity as dimensions.

This research adopted a theory refining approach based on multiple case studies. Seven ETO manufacturers from different industry sectors participated in the study. Data collection was primarily based on a series of in-depth interviews supported by observations and archival sources.

The paper proposes four distinct archetypes of ETO (complex, basic, repeatable, and non-competitive) and empirically validates three of them. The organizational structures and processes most suitable for the different archetypes are described, and standardization and automation strategies are linked to the quadrants of the matrix. The matrix can support practitioners in making strategic choices and provides a framework for benchmarking their ETO products and processes.

Existing conceptualizations of ETO consider the company as the primary object of investigation, rather than the product or product family. However, companies often have different product families demanding different strategies. Also, there is little or no focus on the engineering perspective. The authors move the engineering perspective to the center of investigation and identify a set of standardization and automation strategies for different types of ETO products.

As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).

The paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.

The digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.

This research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

Changes in world markets have brought renewed interest in quality management, and a proliferation of quality‐assurance methods. The new methods focus on design rather than inspection, thereby shifting managers’ attention from inspecting quality to designing quality into products and services. A powerful approach to designs for quality is the quality function deployment (QFD) process. QFD’s simplification procedures call for improvement through the analysis of indirect relationships among quality’s ends and means. An illustrative example enhances QFD’s capability of capturing and representing the effects of multiple interdependencies among specifications and design variables, while the computation that matrix multiplication requires is both simple and efficient.

Many recent modular design methods and approaches have focused on the modularization process – decomposition and composition. This paper suggests an integrated methodology that includes additional tools and stages for a complete modular architecture design. The borders of the modular design process are expanded by adding strategic issues, appropriateness to modularity, degree of modularity and modularity strategies, in an operationalized manner. The methodology presents a “requirements analysis‐ decomposition‐composition‐design evaluation” structure. The “modularization process” is designed so as to choose from three different perspectives – customer‐based, function‐based and structure‐based design. To test and validate the methodology it was applied to a domestic gas detector product family. As a result, a new modular product architecture with eight modules was developed.