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Rapid changes in customer needs (CNs) and technology force businesses to develop new products to compete. Functional requirements (FRs) and non-functional requirements (NFRs) are created when CNs are correctly interpreted. FRs specify what the product must do, whereas NFRs specify how a system must behave. The study presents a comprehensive framework that helps product developers accurately and quickly extract the essential NFRs. This is because there is still no agreement in the requirements engineering community regarding which NFRs should be elicited for developing a system and how they should be applied and documented. Moreover, the majority of research in this area has either concentrated more on the field of software development or given more attention to applying FRs and less attention to NFRs. The presented framework applies the integrated approaches of QFD, DSM, and hesitant fuzzy sets (HFS). Design for eXcellence is also used to ensure that system quality attributes, such as NFRs, are considered during the development process. The framework was used to develop a solar power system, and the results indicated that the primary NFRs essential for system development are availability, reliability, maintainability, modularity, flexibility, and extensibility. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To improve the detachability performance and remanufacturing capability of existing agricultural micro-tillers, a modular design concept is introduced into the product design and development process, with Axiomatic Design (AD) and the Design Structure Matrix (DSM) serving as the methodological guidance and theoretical framework. In the design process, "Z-mapping" is used to reconstruct the demand/function/structure of the agricultural micro-tiller, decompose the total functions step by step, and establish a design matrix to transform the initial user requirements into specific functional indicators and design parameters. Geometric correlation is used as the design evaluation index to assign values to the matrix to establish a DSM for the correlations between agricultural micro-tiller design parameters. Using system clustering to optimize the distribution of matrix values, a total of five functional modules were identified to achieve a modular design scheme and design a prototype for agricultural micro-tillers. This design solution has significantly better disassembly performance than existing products, effectively enhancing the remanufacturing capability of existing equipment, proving the effectiveness of the Kano-AD-DSM-based design strategy, and providing a new theoretical reference for the innovative design of other small agricultural equipment. [ABSTRACT FROM AUTHOR]

The complexity of mechatronic systems has increased with the significant advancements of technology in their components which makes their design more challenging. This is due to the need for incorporating expertise from different domains as well as the increased number and complexity of components integrated into the product. To alleviate the burden of designing such products, many industries and researchers are attracted to the concept of modularization which is to identify a subset of system components that can form a module. To achieve this, a novel product-related dependency management approach is proposed in this paper with the support of an augmented design structure matrix. This approach makes it possible to model positive and negative dependencies and to compute the combination potency between components to form modules. This approach is then integrated into a modified non- dominated sorting genetic algorithm III to concurrently optimize the design and identify the modules. The methodology is exemplified through the case study of a layout design of an automatic greenhouse. By applying the proposed methodology to the case study, it was possible to generate concepts that decreased the number of modules from 9 down to 4 while ensuring the optimization of the design performance. [ABSTRACT FROM AUTHOR]

The growing demand for lithium‐ion batteries in electric vehicles pose challenges, particularly for the use of critical materials such as cobalt in electrode slurry mixing. Due to regulatory requirements such as the battery passport, an accurate traceability system is mandatory. However, there is no solution for the continuous mixing process, which is a major challenge in electrode production. This article describes an approach to solve this problem. Based on the results of a literature review, a design structure matrix is constructed to analyze parameter influences. The overall result is a list of relevant parameters that should be recorded in the continuous mixing process in order to characterize the mixing process. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The transformation of the manufacturing industry over the last two decades has been largely inspired by data. Digitisation has made its mark in different areas of manufacturing, from digital materials and processes to data science in decision-making. The digital manufacturing is evolving towards universal manufacturing that is highlighted in this paper. Different manufacturing initiatives are benchmarked and their relationship to universal manufacturing is demonstrated. The representation of enterprises in the universal manufacturing cloud is discussed. Product- and process-based specifications of digital enterprises are defined. Using these specifications, the enterprise configuration algorithm proposed in the paper is applied for the selection of component models. Two different representations, a node–node and an input–output matrix, of the digital component models are considered. The extended topological sorting algorithm is applied to construct an integrated digital model. [ABSTRACT FROM AUTHOR]

With the gradual diversification of personalized usage scenarios, user requirements play a direct role in product design decisions. Due to the problem of fuzzy demand caused by user cognitive bias, traditional design methods usually focus on realizing product functions and cannot effectively match user requirements. Therefore, this paper proposes a complex product module division method for user requirements. The method constitutes of three tasks, requirement analysis of module division, design mapping of module division and scheme implementation of module division. Firstly, based on the progressive architecture from initial requirements to precise requirements, the effective user requirements are obtained through similarity recommendation. Secondly, according to the four types of knowledge of function, geometry, physics and design, the design structure matrix is constructed to complete the Requirement-Function-Structure mapping. The improved Fuzzy C-means Algorithm is used to solve the mapping model, and finally a module division scheme that meets the user requirements is obtained. Taking the chip removal machine as an example, the rationality and effectiveness of the method are verified. The results show that the product modules divided by this method can effectively meet the multiple user requirements.

There are many well-known systematic approaches to design the digital systems used in manufacturing. However, there are only a few approaches that specifically deal with low-cost components. Such components may not provide the same level of completeness as more expensive industrial alternatives and may need to be combined with other components to become comparable. Consequently, common design challenges for systems comprising such low-cost components revolve around extendability and interface standardisation. There is a need for analysing the capability of the existing approaches to design these systems. This study aims to evaluate the effectiveness of designs for low-cost digital manufacturing systems that have been derived from a particular design approach. The proposed evaluation methodology is used for the special case of designs that are directly based on reference architectures and for the development of specific metrics for that purpose. To quantify the effectiveness, these metrics are applied to a number of design scenarios. Although focusing on reference-architecture-based designs, the proposed methodology can also be used for other design approaches. The evaluation and structured implementation comparison helps practitioners in selecting an effective design approach to low-cost digital manufacturing systems and provides insights into how a particular design approach can become more effective. [ABSTRACT FROM AUTHOR]

With the gradual diversification of personalized usage scenarios, user requirements play a direct role in product design decisions. Due to the problem of fuzzy demand caused by user cognitive bias, traditional design methods usually focus on realizing product functions and cannot effectively match user requirements. Therefore, this paper proposes a complex product module division method for user requirements. The method constitutes of three tasks, requirement analysis of module division, design mapping of module division and scheme implementation of module division. Firstly, based on the progressive architecture from initial requirements to precise requirements, the effective user requirements are obtained through similarity recommendation. Secondly, according to the four types of knowledge of function, geometry, physics and design, the design structure matrix is constructed to complete the Requirement-Function-Structure mapping. The improved Fuzzy C-means Algorithm is used to solve the mapping model, and finally a module division scheme that meets the user requirements is obtained. Taking the chip removal machine as an example, the rationality and effectiveness of the method are verified. The results show that the product modules divided by this method can effectively meet the multiple user requirements. [ABSTRACT FROM AUTHOR]

Engineering changes (ECs) are inevitable for businesses due to increasing innovation, shorter lifecycles, technology and process improvements and cost reduction initiatives. The ECs could propagate and cause further changes due to existing system dependencies, which can be challenging. Hence, change management (CM) is a relevant discipline, which aims to reduce the impact of changes. EC assessment methods form the basis of CM that support in assessing system dependencies and the impact of changes. However, understanding of which factors influence the changeability across value chains (VCs) is limited. This research adopted a VC approach to EC assessment. Dependencies in products and processes were captured, followed by risk (i.e. likelihood x impact) assessment of ECs using change prediction method (CPM). Four industrial case studies were conducted (3x automotive, 1x furniture manufacturing) to identify design (product) and manufacturing (process) elements with high risk to be affected by ECs. Based on the case results, characteristics were identified that influence changeability across VC. This contributed to the CM domain while businesses could also use the results to assess ECs across VC, and improve the design of products and processes by increasing their changeability across VC e.g. by proactive decoupling or reactive handling of system dependencies. [ABSTRACT FROM AUTHOR]

Increasingly fierce market competition and rapidly changing customer demand has led many manufacturing enterprises to actively adopt modular architecture for product design and development. This helps them to effectively control their production costs while maintaining the diversity of product variants. However, there are considerable differences between the structure of different products; the degree to which each product is suitable for adopting a modular architecture also varies. Here, we explored the impact of product structural features (the number of parts and the average number of connected nodes) on its modular performance, based on virtual product design structure matrix (DSM) data. We first propose a method for constructing a DSM of a virtual product and randomly generate a database of DSMs with different structural parameters. We then carry out hierarchical clustering and modularity evaluation on a DSM model to obtain the optimal modularity scheme and corresponding Q value. Finally, based on numerical simulation data, the relationship between the structural features of virtual products and their modular performance was analyzed. In addition, eight actual products were selected to verify the simulation results and ensure the credibility of these results. Abbreviations: ANCN, Average number of connected nodes; CE, Clustering efficiency index; DSM, Design structure matrix; HC, Hierarchical clustering; IC, Integrative complexity; LCA, Life cycle assessment; MDL, Minimum description length; MDS, Multi-dimensional scaling; MI, Modular index; MSI, Module strength indicator; PC(c), Partition coefficient c; PDM, Product data management; PLM, Product lifecycle management. [ABSTRACT FROM AUTHOR]

Modularization is an approach for system architecting and design simplification by encapsulating complex interactions among components within modules and reducing dependencies across modules. Design structure matrix (DSM) based clustering algorithms have proven helpful for such analysis, owing to their convenience in manipulating a large number of elements using conventional software. However, there are problems where constraints must be maintained in the modularization, for example, coping with functions or systems that either cannot or must be performed in regions with excessive heat, pressure, magnetic or other fields. Excluding such field boundary considerations can result in DSM computed modular architectural solutions that bundle field‐incompatible functions or components that are not practical. Such regional field constraint considerations are not taken into account using conventional DSM clustering algorithms. We introduce a DSM‐based clustering algorithm that incorporates these practical embodiment constraints through a constraint matrix indicating which elements can or cannot be placed in the same field region. We then employ reinforcement learning to allow the clustering algorithm to exploit its learnings from the previous attempts and during the clustering to facilitate the optimization under constraints. We demonstrate two examples of a medical contrast injector and the controller board of a three‐phase pump motor. [ABSTRACT FROM AUTHOR]

Lunar habitat design is a complex endeavor characterized by complicated task-composition, numerous internal iterations, and intense task-coupling. The design process of assembled building in terrestrial construction and the system composition of lunar habitats have been constructed. However, there is insufficient experience to fully understand lunar habitat design missions and likewise there is insufficient coordination between architects and various disciplines. The task flow for sequencing optimization can be determined using a design structure matrix (DSM), which is widely used in engineering. The DSM can reveal necessary interfaces within the lunar habitat system as per relevant interface variables and processes. By decomposing the lunar habitat design process, an initial activity-based DSM is established in the present study. Informational interactions between each design task and its respective intensity are statistically investigated to clarify them across the four dimensions of energy, space, materials, and information. A sequencing algorithm is applied to optimize the design process. Finally, 20 design tasks of lunar habitat design are clarified among four phases: Pre-planning, spatial design, environmental design, and optimization. Related disciplines should coordinate in the design process according to the optimization results, and use the optimized task coupling relationship to build the requirement model and design model in an orderly manner to improve the design efficiency. [ABSTRACT FROM AUTHOR]

When a product variant offers functionality that is high in demand, firms may decide to leverage that design to enhance other variants in their product line. This can be achieved by extracting functions and their realisations from one product variant and integrating them into another variant, resulting in a third product variant that has a new combination of functions and physical features. This article introduces a systematic approach called the Adaptive Redesign Method (ARM) to support this function integration process. The ARM is based on a new product model called the Detailed Design Model (DDM). In comparison to existing approaches, the DDM allows the architecture of an existing product to be modelled on a sufficiently detailed level to identify geometric features and parts that realise particular operating functions of a product. This detailed information provides a basis for systematic determination of the redesign activities needed to derive a new variant design, down to the detailed level of adding, removing and integrating specific parts and features. The main benefit is to assist with planning the redesign process while ensuring nothing is overlooked, which might be especially useful if the task is to be divided among several designers or if designers are not fully familiar with the designs at hand. A secondary benefit is to show how this type of redesign process can be decomposed into systematic steps, which could potentially reveal opportunities for computer support. The new approach has been developed and tested through reverse engineering studies of consumer products, confirming its applicability. [ABSTRACT FROM AUTHOR]

Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, scheduling interrelated activities in an appropriate sequence is an important issue for project managers. This study develops a double-decomposition based parallel branch-and-prune algorithm, to determine the optimal activity sequence that minimizes the total feedback length (FLMP). This algorithm decomposes FLMP from two perspectives, which enables the use of all available computing resources to solve subproblems concurrently. In addition, we propose a result-compression strategy and a hash-address strategy to enhance this algorithm. Experimental results indicate that our algorithm can find the optimal sequence for FLMP up to 27 activities within 1 h, and outperforms state of the art exact algorithms.

Planning the sequence of interrelated activities of production and manufacturing systems has become a challenging issue due to the existence of cyclic information flows. This study develops efficient exact algorithms for finding an activity sequence with minimum total feedback length in a design structure matrix. First, we present two new properties of the problem. Second, based on the properties, we develop an efficient Parallel Branch-and-Prune algorithm (PBP). Finally, the proposed PBP is further improved by adopting hash functions representing activity sequences, which is referred as hash function-based PBP. Experimental results indicate that the proposed hash function-based PBP can find optimal solutions for problems up to 25 interrelated activities within 1 h, and outperforms existing methods. [ABSTRACT FROM AUTHOR]

In the design process, design changes are unavoidable due to the need to meet customers' requirements and support future change through technology development. Although components are supposed to be renewed within existing designs, these changes can propagate into other parts due to their interfaces. Propagation makes it difficult for a designer to identify these changes. This study aimed to introduce the integration matrix (I-DSM), an approach to the design of mechatronic products that involves determining changes in existing products with an axiomatic design. Reverse zigzagging was used to break down the entire product to its lowest level. A design matrix (DM) was constructed and then transformed into a design structure matrix (DSM). The I-DSM consists of three layers: information technology, electrical technology, and mechanical technology. The breadth-first search (BFS) method was employed to ascertain the change propagation path in order to consider it. After this, the changing workload was analyzed, and the decision-making process was used to determine the best possible option. Finally, an automatic guided vehicle was used in a case study to demonstrate the use of this methodology by showing how changes in a product can affect it and how a designer can prioritize activities. [ABSTRACT FROM AUTHOR]

In this paper, we introduced the integration of well-known TD tools that have been applied in many fields including product development, project management, many engineering disciplines, design of the organization, sustainable development, social issues, environmental issues, and others across many industries including automotive, aerospace, telecom, semiconductor, defense, transportation, energy, healthcare, agriculture, and more. The main objective of this paper is to introduce a new transdisciplinary (TD) engineering-based integrated approach to designing and developing a 3D silicone printing machine (SPM). Factors in designing and developing 3D SPM were simplified by considering the main factors affecting the performance of 3D SPM. Results are discussed and the modular 3D silicone printing machine design was presented. Using the Axiomatic Design (AD) tool, components of each module were identified to satisfy the functional requirements of the 3D SPM. Six TD-integrated tools were used to design the 3D SPM in this research. They are Quality Function Deployment (QFD), House of Quality (HOQ), TRIZ, AD, Interpretive Structural Modeling (ISM), and Design Structure Matrix (DSM). [ABSTRACT FROM AUTHOR]

Light small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of these UAVs have adopted a series development strategy based on the concept of commonality in design. However, there is currently a lack of effective methods to quantify the commonality in UAV designs, which is key to guiding commonality design. In view of this, our study innovatively proposes a new UAV commonality evaluation model based on the basic composition of light small-sized multi-rotor UAVs and the theory of design structure matrices. Through cross-evaluations of four models, the model has been confirmed to comprehensively quantify the degree of commonality between models. To achieve commonality prediction in the early stages of multi-rotor UAV design, we constructed a commonality prediction dataset centered around the commonality evaluation model using data from typical light small-sized multi-rotor UAV models. After training this dataset with convolutional neural networks, we successfully developed an effective predictive model for the commonality of new light small-sized multi-rotor UAV models and verified the feasibility and effectiveness of this method through a case application in UAV design. The commonality evaluation and prediction models established in this study not only provide strong decision-making support for the series design and commonality design of UAV products but also offer new perspectives and tools for strategic development in this field.

There are many well-known systematic approaches to design the digital systems used in manufacturing. However, there are only a few approaches that specifically deal with low-cost components. Such components may not provide the same level of completeness as more expensive industrial alternatives and may need to be combined with other components to become comparable. Consequently, common design challenges for systems comprising such low-cost components revolve around extendability and interface standardisation. There is a need for analysing the capability of the existing approaches to design these systems. This study aims to evaluate the effectiveness of designs for low-cost digital manufacturing systems that have been derived from a particular design approach. The proposed evaluation methodology is used for the special case of designs that are directly based on reference architectures and for the development of specific metrics for that purpose. To quantify the effectiveness, these metrics are applied to a number of design scenarios. Although focusing on reference-architecture-based designs, the proposed methodology can also be used for other design approaches. The evaluation and structured implementation comparison helps practitioners in selecting an effective design approach to low-cost digital manufacturing systems and provides insights into how a particular design approach can become more effective.

The topic of critical success factors draws high attention of both academia and practitioners working in the software industry. Literature review shows that existing models of critical success factors for software projects are more concentrated on specific categories of success factors, neglecting the interaction that exists within these models between different groups of factors. The purpose of this paper is to present a new concept of interaction-based model for identification and evaluation of critical success factors for software projects. The approach is based on conjoint use of graph theory and Design Structure Matrices to highlight important interactions of a project system. The key result of the paper is the tool for evaluation of the interaction between critical success factors through quantification and the analysis of the possible propagation of specific factor within project success factor network, which will make possible the identification of the critical factors with the highest influence on the entire project system.

Due to high acquisition costs of new units, defence products can be subjected to life extension processes, sometimes not previously planned during their life cycle. These processes are characterised by widespread maintenance tasks and they can be denominated as major overhauls. The main objective of this paper is to propose a methodology to aid the major overhaul technical management. In general, the major overhaul defines the scope of maintenance and modernisation. Main problems about maintenance are managed by risk-based decision-making for determination of replacement rules and quantities of spares. The need for redesign of parts that interacts with the upgraded subsystems is evaluated by design structure matrix and a HAZOP-based analysis aiming at achieving product performance requirements. The proposed method is a support tool to the major overhaul manager, not replacing technical methodologies that are specific to each branch of the overhauled product. The proposed method was applied to a major overhaul project of an armoured personnel carrier. The results enabled a better characterisation of detailed design, analysing risks in the context of maintenance and modernisation aiming at controlling modernised product life cycle. [ABSTRACT FROM AUTHOR]

Systems integration is a central element of the complex systems development effort. The integration readiness levels (IRL) scale complements technology readiness levels (TRL) to assess the system development maturity, representing risk levels for integrating technologies in a system. The increasing complexity of systems, due to multiple interfaces and an information-centric architecture, demands new systemic approaches to analyze the architecture and communicate IRL assessments. Therefore, this article developed a methodology to apply IRL using architecture views through the design structure matrix and domain mapping matrix. A case study analyzed technology introduction impacts and different integration strategies for space systems from China–Brazil Earth Resources Satellite program at the system and system-of-systems levels. Through the design science method, results show the pragmatic evaluation and validation for the proposed method and for the IRL scale itself, by professionals of the case study projects. The research draws suggestions for holistic system analysis and managerial communication applications using the proposed method and suggests a rationale for IRL assessment of legacy systems. [ABSTRACT FROM AUTHOR]

As a cost-saving and environmental-friendly product strategy, modular design is an effective approach to shorten lead-time and reduce cost for development of products. However, the modular design of products with complex structure might be plagued by the difficulty of product structure modeling and unreasonable structural modular schemes. In this study, a core components-oriented modularisation method is presented to solve the problem of module division of complex products. The structural model of complex products is reasonably simplified by screening core components, which further reduces the modeling difficulty and improves the solution efficiency of module division scheme. Firstly, a hybrid structure decomposition method is proposed to obtain all components of complex products according to the different structure characteristics of each subsystem of complex products. Secondly, the core components of complex products are screened by calculating the whole life cycle cost (WLCC) of each component, and the design structure matrix (DSM) model of complex products is established according to the relationship between the core components. Finally, the module division scheme of complex products is obtained via hierarchical clustering and modularity evaluation. Effectiveness and robustness of the method are demonstrated through comparison experiments for the modular design of a hydraulic excavator case. [ABSTRACT FROM AUTHOR]

Product modularization is an architecture design scheme for a product to manage its complexity as a system. The design methods for modularization often employ mathematical operations to achieve better modularization. Although multiple objectives result in various alternatives, identifying the superior one best suited for their tradeoff relationships and ambiguity in their interpretation is challenging. Moreover, the decision-maker is required to explore the design space and determine the preferred solution with a rational reason. This study proposes a decision support method for product modularization based on the design structure matrix (DSM). The method is directed by the hierarchical clustering of alternatives into a dendrogram, and it facilitates the interpretation of alternatives over a decision bifurcation diagram. It is assumed that an optimal solution can be represented as a piling-up of smaller pieces, which correspond to building blocks in the combinatorial solution space. The distance of alternatives was surveyed using schema representation defined in various levels. Further, the hierarchical clustering technique structures the design space of alternatives into branches and organizes the essential parts, identified as building blocks, into a tree-shaped graph. Consequently, such a structure is crucial to revealing the leverage points in modularity and facilitates the exploration of product modularization. The proposed method was applied to an air-conditioner unit to demonstrate and ascertain its validity and effectiveness.

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Iteration is a major cause contributing to an increase in project duration and cost. By adopting the traditional models of design structure matrix and reward Markov chain, this paper proposes a hybrid algorithm for solving a task sequencing problem that aims for minimising the project duration. The proposed algorithm combines hierarchical clustering and genetic algorithms. This algorithmic strategy is intended to utilise the circuit concept to reduce the solution search space for GA. Our algorithm was compared to five other algorithms. Through numerical experiments, the proposed algorithm can solve large problems (number of tasks = 200), yield the same quality of solution results with shorter computational time, and deliver stable algorithmic performance. [ABSTRACT FROM AUTHOR]

Failure Mode and Effects Analysis (FMEA) is a systematic approach for evaluating the potential failure modes in a system, and is mainly employed in three distinct tasks labelled: (1) Functional FMEA – evaluating those failures associated with product functional definition, (2) Design FMEA – analysing those failures associated with design definition and (3) Process FMEA – assessing potential failures in manufacturing and assembly processes. The literature review has shown limited works on the field of synchronising these different tasks into a working model. To address this gap, this research developed a framework for integrating these tasks of FMEAs, and then qualitatively validating the proposed framework. This research adopted a semi-structured questionnaire to collect experts’ feedback and validate the proposed framework. The t-test was then employed to evaluate the collected feedback. The findings highlight that the proposed framework is applicable and could facilitate the synchronisation of the different tasks of FMEA. This research presents a methodological approach for executing and synchronising FMEAs. Therefore, the proposed framework is practically relevant as an aid for the practitioners in catching the cascading failures and reducing the relevant impact.

Lunar habitat design is a complex endeavor characterized by complicated task-composition, numerous internal iterations, and intense task-coupling. The design process of assembled building in terrestrial construction and the system composition of lunar habitats have been constructed. However, there is insufficient experience to fully understand lunar habitat design missions and likewise there is insufficient coordination between architects and various disciplines. The task flow for sequencing optimization can be determined using a design structure matrix (DSM), which is widely used in engineering. The DSM can reveal necessary interfaces within the lunar habitat system as per relevant interface variables and processes. By decomposing the lunar habitat design process, an initial activity-based DSM is established in the present study. Informational interactions between each design task and its respective intensity are statistically investigated to clarify them across the four dimensions of energy, space, materials, and information. A sequencing algorithm is applied to optimize the design process. Finally, 20 design tasks of lunar habitat design are clarified among four phases: Pre-planning, spatial design, environmental design, and optimization. Related disciplines should coordinate in the design process according to the optimization results, and use the optimized task coupling relationship to build the requirement model and design model in an orderly manner to improve the design efficiency.

Proper sequencing between activities has always been one of the major issues in project management. Sometimes it is needed to redo some activities especially in product development projects. It is assumed that one of the reasons for reworking some activities and backward can be due to the incompleteness of the information needed when doing them, and it is also assumed that having complete information requires cost. In this article, a network of activities is considered, which may require a duplication of the process due to the interdependence of information between them. In this paper, using the design structure matrix concept and interdependence between activities, a two purpose model for determining the proper sequence of activities has been provided to minimi7£ the length of feedback and reduce the cost of completing the information using matrix concept. To accurately solve this model, the combination of Lexicographic and Augmented Epsilon Constraints is used to obtsin the Pareto National Front, which shows an increase in the cost of reducing the degree of dependence between activities for reducing the feedback length between activities. From the Pareto front, the best answer was chosen in a way that, based on the economic justification of the project, the percentage of reduction in the feedback length would be higher than the percentage increase. [ABSTRACT FROM AUTHOR]

Satellite design process is an interdisciplinary subject in which the need for collaboration among various science and engineering disciplines is evident. Meanwhile, finding an optimal process for conceptual design of a satellite, which can optimize time and cost, is still an important issue. In this paper, based on system engineering approach, an optimal design process is proposed for LEO satellite constellations. In the proposed method, design process, design sequences, and data flow are established. In this regard, the conceptual design process is divided into two levels of mission (or constellation) and system (or satellite) as well as 15 main activities based on the mission profile, previous experiences of the authors, and existing literature. Then, the relationships between these activities have been determined by considering the importance of relationships according to their priority. Finally, these relations are optimized based on design structure matrix (DSM). By utilizing this approach, system design process of a telecommunication satellite constellation in LEO is formulated in conceptual design phase. Performance and capability of the proposed approach in optimal design process of the satellite constellation are investigated by comparing the outcome with existing results in the literature. [ABSTRACT FROM AUTHOR]

Determining a project delivery method that matches the characteristics of a construction project is a critical step that affects the success or failure of a project. The Project Delivery Method (PDM) should be adapted to the activities and processes of project implementation. However, the traditional selection method does not come from the internal process of the project which may lead to the delivery method not being able to meet the actual project requirements. This research proposes a DSM-based PDM selection framework model that regroups activities and identifies appropriate PDMs by revealing the dependencies and intensities between activities. The research uses a case to demonstrate the feasibility of the framework. After considering specific project requirements and goals, the framework model can be used as a basis for choosing specific project delivery methods, or as a visualization tool to help owners schedule activities. [ABSTRACT FROM AUTHOR]

Roadmap and especially technology roadmap is a management tool and technique to achieve future goals in order to link business to technology. With the increasing trend and the need to use different types of roadmaps, new tools are needed to analyze the complex relationships between layers and roadmap elements. The purpose of this study is to focus on a new tool for analyzing the relationships between roadmap layers with a combined method with a proposed framework. Previous research has addressed relationships between layers only with tools such as quality function deployment (QFD) and the linking grid. Although DSM and TRM have been extensively studied independently so far, this study, therefore, proposes an integrated six-step framework combining a multi-domain matrix and design structure matrix and fuzzy set theory in designing, creating, and developing technology roadmaps for Suggest systems to support decision making and case studies. In this study, multi-domain MDM matrix and fuzzy inference, and network theory were used in designing the technology roadmap. The advantage of using a multi-domain matrix is ​​the simultaneous analysis of each domain specifically in the DSM format as well as the entire domain in the MDM format. The results of the present study indicate the provision of detailed instructions for managers to prepare a suitable roadmap.

Crowdsourcing design for complex products has open objectives and requires collaboration among different fields. It is difficult to use a single approach to describe the process in which the number and interaction of tasks and steps of tasks are changed dynamically depending on the execution state. Motivated by modeling the collaborative business process of crowdsourcing design in complex products, a crowdsourcing hierarchical process modeling approach based on an object-oriented Petri net is proposed. From the perspective of organization and task, the crowdsourcing object interaction and design process are modeled separately. First, an organization layer modeling approach based on expert review is proposed to describe the information transfer relationship among crowdsourcing objects from the organization perspective. Then, the task layer modeling approach based on the component decomposition idea is proposed. From the perspective of the task, the task is decomposed by using a design structure matrix (DSM) and a product structure tree to model the interaction of the design process. The object-oriented Petri net-is used to realize the representation of the model. Finally, the method is verified by taking the model of the crowdsourcing design of an air cooler as an example. The model subnet is analyzed by means of an overlay tree and incidence matrix, and the reliability and robustness of the model are proven. This method provides a reference for the process modeling of the crowdsourcing design of complex products.

Since mechanical performances of the connecting part in the frame structure generally deteriorate, the mechanical performances may also deteriorate in the connecting part between the modules. If the design target is based on the existing parts, the boundaries divided into modules are naturally limited to the boundaries of the existing parts. In order to extract appropriate module boundaries, we propose a method using elements of finite element analysis which are smaller units than existing parts. In this study, we propose a modular design method of frame structure that suppresses the decrease of mechanical performances by using DSM (Design Structure Matrix) analysis. In DSM construction, not only the connection information of parts but also the von mises stress or strain energy indicating the mechanical state is added to the DSM, so that the module boundaries are not generated in that area with high mechanical loads. As a result, we showed that the mechanical performances of the modular structure extracted by adding the mechanical indicators are improved compared to the modular structure extracted only by the connection information of the parts.

To cope with an increasingly competitive market environment, manufacturers are utilizing modular technology to guide the production process, and a vital activity in the module partition is to determine the optimal granularity levels. A modular design methodology is developed for obtaining the optimal granularity of a modularized architecture in this paper. A relationship extraction solution is executed to automatically construct the design structure matrix (DSM) from the 3D CAD assembly model. Hierarchical clustering algorithm is implemented to form a hierarchical dendrogram with different granularity levels. An improved Elbow method is proposed to determine the optimum granularity level and corresponding modularity spectrum during the dendrogram process. The computational framework for hierarchical clustering and modularization with improved Elbow assessment operators is explained. Based on a existing literature example and a jaw crusher modular design case, comparative studies are carried out to verify the effectiveness and practicality of the proposed method. The methodology is characterized by running independently on the computer in data visualization format without human involvement, and the obtained result with optimized granularity favor further modular design work. [ABSTRACT FROM AUTHOR]

Modular system architectures are increasingly important to manufacturers as they seek to decrease system development lead time and as customers have come to expect systems that allow for frequent modular upgrades. There has been considerable research into how to design modules within a system architecture and how to assess the modularity of systems. However, with these established approaches, the modularity assessment is a stand-alone, post-architecting analysis. This research demonstrates how, using model-based systems engineering (MBSE), the assessment of the modularity of a system architecture can be incorporated into the architecting process. To facilitate this, a modularity ontology is developed to guide the semantics and syntax of extensions to the Systems Modeling Language (SysML). Model metadata from behavioural, structural, and state-based system elements is directly assessed using Design Structure Matrix (DSM) based analysis. Elements in the architecture are automatically assigned to modules and the system's modularity is assessed. The approach allows for the system architect to also consider non-functional characteristics in the formation of modules. The architecting and the modularity analysis of the system are completed in a single environment, using SysML parametric diagrams as the catalyst, allowing for a more holistic and complete understanding of the system and its modularity. [ABSTRACT FROM AUTHOR]

As the demands of customers in the modern industry increased, the number of products, and the variety of components has increased. These issues have led to difficulties in product development and production. Modularization of products has advantages such as cost reduction, product development time reduction, and production time reduction. Modular design of products has been studied in the design activities of the modern industry. In this study, a modular design method is proposed to design a modular product based on axiomatic design (AD) and design structure matrix (DSM). AD and DSM are efficiently integrated into the proposed method. Functional requirements and design parameters are defined based on the Independence Axiom of AD, and the zigzagging process of AD is employed for the decomposition of the functional requirements (FRs) and design parameters (DPs). The design sequence is established based on the design matrix. Coupled or functionally close DPs are grouped into a module (Module 1). These modules are efficiently used in the design sequence. DSM is used to modularize the design parameters of the lowest level of axiomatic design. DSM is constructed based on physical interfaces and numerical clustering algorithms are used to identify strongly related components. They are grouped into a module (Module 2). Module 2 is exploited for production and management. Therefore, these two modules for different purposes can be used to increase efficiency in the design and production process. The proposed method is applied to two automobile parts such as the suspension system and cooling system. The results are discussed from the viewpoint of usefulness. [ABSTRACT FROM AUTHOR]