Reuse Of Design Knowledge Research Articles

Conceptual design of smart product-service system based on function-oriented search

Unlike traditional products, Smart Product-Service System design requires the broad design knowledge support. However, traditional knowledge representation does not consider the characteristic elements of Smart Product-Service System, which can lead to the loss of essential information when organising and reusing design knowledge. This limitation affects the application of cross-domain functional knowledge in the conceptual design of Smart Product-Service System. To address this issue, a process model for the conceptual design of Smart Product-Service System based on function-oriented search is proposed. An initial functional modelling is first constructed based on the characteristics of the Smart Product-Service System. The extended Function Behaviour Structure model is then used to construct a design knowledge model of the system. Based on Function-Oriented Search to search for patent knowledge with highly similar functions in the patent database, the knowledge fusion is used to solve the derived problems after pruning, so as to obtain high-quality system conceptual solutions. Finally, the effectiveness of the method is verified by taking the scheme construction of intelligent forklift product service system as an example.

Knowledge graph based multi-granularity tacit design knowledge reuse for product design

Abstract Decomposing product design into multiple granularities is an effective strategy to implement complex product design. Tacit design knowledge (TDK), adhering to designers’ experience and intuition, plays an essential role in the product design at various granularities, but it is difficult to acquire and reuse due to its implicity. Aiming at this issue, a knowledge graph-based multi-granularity TDK reuse framework for product design is presented. First, the design issue-solving oriented knowledge graph (DSKG) model is employed to indirectly capture TDK, where the design result data are represented as design solution nodes and the design issues that refine design solution are represented as relation edges. An improved ontological concept model is designed as the schema of the DSKG to represent the multi-granularity design knowledge on functions, behaviours, and structures of products. Afterwards, the framework supports two design modes, i.e. top-down design and bottom-up design, where the captured TDK is reused to create the design context and predict design solutions. DSKG embedding is employed for design solution prediction in both design modes, while the design context creation is achieved distinctively. In top-down design, the design issue-solving process starts from the design requirements and then gradually downward refines the design solutions at different granularities with breadth-first strategy, which naturally creates the continuous design context, until moving to the detailed design. In bottom-up design, the target design solution is commonly isolated at specific fine-grained granularity. This paper presents a novel approach to constructing design context based on path-ranking algorithm. Path-ranking algorithm can identify the design solution influence paths to build connections between the design requirements and the isolated design solution and thus construct the design context. Finally, a case study for stamping die design is implemented, which illustrates the feasibility and effectiveness of the framework. The comparisons with the state-of-the-art design methods are also made to demonstrate the merits of the presented framework.

Timed-SAS: Modeling and Analyzing the Time Behaviors of Self-Adaptive Software under Uncertainty

Self-adaptive software (SAS) is gaining in popularity as it can handle dynamic changes in the operational context or in itself. Time behaviors are of vital importance for SAS systems, as the self-adaptation loops bring in additional overhead time. However, early modeling and quantitative analysis of time behaviors for the SAS systems is challenging, especially under uncertainty environments. To tackle this problem, this paper proposed an approach called Timed-SAS to define, describe, analyze, and optimize the time behaviors within the SAS systems. Concretely, Timed-SAS: (1) provides a systematic definition on the deterministic time constraints, the uncertainty delay time constraints, and the time-based evaluation metrics for the SAS systems; (2) creates a set of formal modeling templates for the self-adaptation processes, the time behaviors and the uncertainty environment to consolidate design knowledge for reuse; and (3) provides a set of statistical model checking-based quantitative analysis templates to analyze and verify the self-adaptation properties and the time properties under uncertainty. To validate its effectiveness, we presented an example application and a subject-based experiment. The results demonstrated that the Timed-SAS approach can effectively reduce modeling and verification difficulties of the time behaviors, and can help to optimize the self-adaptation logic.

A unified representation and retrieval of 3D grain configuration based on signed distance field

In this article, the design and development of a 3D grain configuration representation method with small data and high accuracy are presented, by which a unified grain database is established. There are two vital components in our proposed method: the traditional signed distance field (SDF) method is used for the unified representation of the 3D grain configuration; the proper generalized decomposition is employed to decompose the original SDF function to compress the data. With the proposed method, the reconstruction of 3D grain configuration is realized with small data and high accuracy, based on which the similarity measurement of different grains is proposed and the reuse of the 3D grain configurations is realized. The efficacy and accuracy of the proposed method are validated by reconstructing 3D grain configurations and the burnback curves of two different grain models. The similarities of the eight grains are calculated, which are accurately consistent with the burning surface area calculations results. The experiment results demonstrate that the proposed methods are feasible and efficient, and are significant for design case data and knowledge reuse.

Assessing Design Repository Search Effectiveness

Reuse of design knowledge in systems engineering (SE) has been identified as a potential way to decrease design cycle times and development costs of engineering projects. Design repositories (DR) have been proposed and demonstrated as a way to store design knowledge in a reusable way. Yet little attention has been devoted specifically to the search methods used to identifying useful information within a DR, or how search method effectiveness can be measured or assessed. This paper demonstrates a method for assessing the effectiveness of search approaches within DR. The use of this method in assessing multiple search algorithms is demonstrated by example. The assessment method presented herein can also be used to identify the characteristics of repository data or intended reuse applications that affect the performance of search methods. These results can be used by engineers to inform selection of search methods based on anticipated future DR use cases.

Time identification of design knowledge push based on cognitive load measurement

The reuse of multidisciplinary design knowledge is pivotal in product development because of the increasingly fierce market competition. It can assist designers, particularly those who lack sufficient experience, in making correct decisions and achieving rapid design. Traditionally, designers primarily acquire design knowledge through information retrieval, which is typically time-consuming and inefficient. A solution that is widely considered to overcome the deficiencies of traditional knowledge retrieval approaches and actively provide designers with necessary knowledge is knowledge push. However, achieving the timely push of required knowledge to designers during the design process remains a challenging task. Accordingly, this paper presents a time identification method based on cognitive load measurement to identify the suitable time for design knowledge push. First, behavioral indicators related to the changes in cognitive load are identified by investigating the influence of the load on three types of behaviors: mouse dynamics, keystroke dynamics, and emotional states. Second, the possibility and efficacy of inferring the cognitive load by simultaneously and unobtrusively tracking the three aforementioned behaviors are considered through behavioral observations. Finally, predicting the knowledge push time based on the cognitive load using classification algorithms is investigated. The experimental results indicate that the accuracy of the proposed method in inferring the cognitive load is 55%, and that of push time is 83%.

Extension Design Pattern of Requirement Analysis for Complex Mechanical Products Scheme Design

Due to the configuration process of a complex product scheme, a design structure often has the characteristics of multi-level, multi-attribute, creativity, and complexity; in order to improve the efficiency and quality of product scheme design, it has important research value to reasonably organize, reason, and reuse design knowledge. In this paper, the extension modeling problem under the extension design mode of complex product scheme is studied, the multitype design knowledge element modeling expression model of complex product scheme design is given, and the extension process model and the implication process model of requirement analysis of complex product scheme design is established. A new demand element weight assignment method based on extension distance is proposed to obtain accurate demand analysis index weight from the perspective of combined qualitative and quantitative analysis. On the basis of constructing the extension correlation degree of demand primitives, this paper puts forward the implementation method of the extension design pattern for the demand analysis of a complex product scheme design and gives the specific implementation algorithm. Finally, an example of product design is given to illustrate the method, and the results show the effectiveness and operability of the method.

Case representation and retrieval for complex product design based on case-based reasoning

Reusing design knowledge of products is a useful way to solve the efficiency issue of complex product design. The design knowledge is tacit, empirical, and unstructured and there exists insufficient case matching and inefficient design reuse in complex products design process. Aiming at these problems, this paper presents an improved case-based reasoning methodology combining ontology with two-stage retrieval. Firstly, a knowledge domain ontology model of complex product design is constructed, and the technology of ontology-based data access is introduced to automatically generate a case knowledge base with semantic information. Then, a new two-stage case retrieval method integrated semantic query with similarity calculation is proposed. The case subset is selected by query statements. It has the characteristic of isomorphism with design problem. The retrieval mechanism is applied to compress the traversal space, reduce the redundancy of semantic similarity calculation, improve the retrieval efficiency, and fulfill the target of case reuse. Finally, a variant design of the chiller unit as an example is executed to illustrate the use of the proposed method, and experiments are organized to evaluate its performance. The result shows that the proposed approach has an average precision of 92% and high stability, outperforming existing methods.

Process knowledge graph modeling techniques and application methods for ship heterogeneous models

In the process design and reuse of marine component products, there are a lot of heterogeneous models, causing the problem that the process knowledge and process design experience contained in them are difficult to express and reuse. Therefore, a process knowledge representation model for ship heterogeneous model is proposed in this paper. Firstly, the multi-element process knowledge graph is constructed, and the heterogeneous ship model is described in a unified way. Then, the multi-strategy ontology mapping method is applied, and the semantic expression between the process knowledge graph and the entity model is realized. Finally, by obtaining implicit semantics based on case-based reasoning and checking the similarity of the matching results, the case knowledge reuse is achieved, to achieve rapid design of the process. This method provides reliable technical support for the design of ship component assembly and welding process, greatly shortens the design cycle, and improves the working efficiency. In addition, taking the double-deck bottom segment of a ship as an example, the process knowledge map of the heterogeneous model is constructed to realize the rapid design of ship process, which shows that the method can effectively acquire the process knowledge in the design case and improve the efficiency and intelligence of knowledge reuse in the process design of the heterogeneous model of a ship.

Identifying profitable reference architectures in an engineer-to-order context

Companies operating with an engineer-to-order (ETO) strategy are often challenged with generating the desired profit as a consequence of product volumes and high levels of product customisation. Profit margins are seen to vary greatly from project to project, which may partly be explained by a lack of references to guide design decisions. Specifically, new product offerings are often based on reuse of design knowledge, which is often not efficiently utilised, as the knowledge transfer and reuse across projects are unstructured, incomplete, or not providing a suitable reference for design specification. To address this issue, this paper presents a method for identifying reference architectures under the consideration of profitability. The method was developed by combining and extending known methods within the fields of product architecture and complexity cost estimation to cover part of the ETO domain. The method was tested in two companies, one producing industrial spray drying plants and the other providing solutions for the production of confectionary products. The findings suggest that a limited understanding of ‘preferred solutions' existed in the two case companies, and applying the suggested method to identifying reference architectures could potentially support a more profitable project execution.

Freehand-Sketched Part Recognition Using VGG-CapsNet

<p indent=0mm>To solve the problem that the existing CAD system is difficult to match the corresponding parts accurately through the freehand sketch in the conceptual design, a recognition model (VGG-CapsNet) for freehand sketch of part is proposed, which combining the pre-trained network (VGG) and capsule network (CapsNet). Five designers are recruited to sketch parts, and build 23 kinds of freehand sketch of parts including standard parts and non-standard parts. The between-group experiment and within-group experiment are designed, and then the recognition models of VGG-CapsNet are constructed respectively. The recognition results of the VGG-CapsNet models are compared with the rVGG-13 models and the rCNN-13 models. The experimental results show that the mean accuracy of VGG-CapsNet model is higher than the other two models, which provides technical support for the retrieval and reuse of part design knowledge.

Application of Computer Technology in Optimal Design of Overall Structure of Special Machinery

With the transformation and upgrading of my country’s industrial structure, the level of manufacturing automation has gradually improved. According to research, the design of mechanical products is mostly completed by improvement or innovation on the basis of existing design knowledge. Knowledge reuse is a technique to ensure the maximization of design resource utilization by reusing design knowledge. This article applies knowledge reuse technology to the development and design of mechanical products. By integrating the technical logic of the functional analysis system with the development of quality functions, the transformation of customer demand information and product function design is realized, and the task of the product design plan analysis phase is completed. This paper uses the finite element analysis software ANSYS to explore a new nonlinear finite element modeling method and conducts simulation experiments. At the same time, this paper improves the genetic algorithm, which effectively improves the optimization efficiency and completes the parameter optimization under multiobjective and multistructure conditions. From the experimental results, it takes 328.64 seconds for the basic genetic algorithm to search for the optimal solution of the complex problem. The improved time is shortened to 86.31 seconds, and the efficiency is increased by 73.74%. This shows that the improved genetic algorithm has better robustness and can find the optimal solution in a shorter calculation time. For complex problems such as the optimization of the overall structure of special machinery, the improved genetic algorithm obviously helps to improve the optimization efficiency and improves the effectiveness and pertinence of product design schemes.

A C-RFBS model for the efficient construction and reuse of interpretable design knowledge records across knowledge networks

Effective and efficient provision and reuse of knowledge across a knowledge network in the global value chain still faces two challenges, namely the interpretability of model and the efficacy of construction. This research aims to address these challenges by proposing a novel representation model for design knowledge. First, a knowledge representation model based on the integration of the cognitive process theory and the Requirement-Function-Behavior-Structure model (C-RFBS model) is proposed to incorporate key elements from the cognitive process of designers to capture the rationale of deliberation and the context of decision-making, which the knowledge records created become more interpretable. Second, knowledge graph is employed to improve the productivity of knowledge records creation, storage and exploration. On this basis, we describe the creation of knowledge records using the C-RFBS model as well as the computational framework and methods for storing knowledge using knowledge graph. The proposed model and methods are implemented in a knowledge retrieval system on which we have conducted a fork design case study to evaluate and demonstrate the models and methods. As shown in the evaluation, the proposed model can effectively support knowledge elicitation and achieved improved performance in terms of knowledge retrieval through incorporating knowledge graph.

Knowledge Deduction and Reuse Application to the Products’ Design Process

In this paper, we introduce a framework for knowledge reuse and deduction in mechanical products design and development. The proposed system effectively exploits the capitalized and inferred knowledge. To this end, we settled up an ontology dealing with the design process of mechanical products such as “the car”. The ontology-based framework is supported by a software tool that brings an automatic and personalized assistance to correspondent actors using the deduction process. Indeed, the systems provides the relevant knowledge to the suitable users in order to facilitate their professional tasks considering their roles and collaboration. Experimental results have demonstrated the effectiveness of reusing knowledge during product development lifecycle.

A new function-based patent knowledge retrieval tool for conceptual design of innovative products

Abstract The reuse of design knowledge within a specific domain is currently a major research focus in product design. However, the importance of support from cross-domain knowledge is steadily on the increase for product innovative design, which includes multi-domain knowledge recombination, transfer and transformation. As the biggest knowledge provider, patent information plays an irreplaceable role inspiring designers in the conceptual design stage. Nevertheless, it is of a great importance and also an issue to figure out how to efficiently retrieve cross-domain patents. In this paper, we propose a function-based patent knowledge retrieval tool for conceptual design of innovative products. In order to establish the underlying local database, function information, technical terms and International Patent Classification (IPC) information are respectively extracted from patents crawled on Websites to represent function, technology and domain properties, thereby generating a patent knowledge space. Particularly, by using a semi-supervised learning algorithm, function information is automatically classified and labeled by functional basis, into which the design problem is abstracted and interpreted forming a design problem space. By functional basis mapping from the design problem space to the patent knowledge space, we retrieve the required cross-domain patents, which are then clustered and evaluated in accordance with the extracted technology and domain properties. The selected patents are thus purposefully recommended to trigger designers’ creativity. Finally, a case study illustrates the conceptual design process based on the proposed retrieval tool. In addition to that, we conducted an experiment to verify our tool. It demonstrates that our proposed tool can assist designers to generate more ideas and the novelty of ideas is higher.

A Model-Based Approach to Identify Barriers in Design Knowledge Reuse

AbstractToday, information and knowledge as competitive factors influence the success of companies as much as traditional production factors like human resources or physical capital. However, the reuse of design knowledge still represents a major challenge for engineering organizations. That is, because barriers exist hindering a successful knowledge reuse. On the basis of a literature review, the research depicted in this paper analyses the relation between single information conveying design knowledge and barriers hindering a successful knowledge reuse. Developing a model-based approach, we propose a micro logic containing three steps and underlying methods enabling practitioners to identify situation-specific barriers within their organization. We illustrate the industrial application of the approach in a case study at a mining machinery OEM.

Repressive coping as a confounding factor for sleep measurement

Reuse of designers’ knowledge and experience of solving problems during the engineering design process holds the key to increase efficiency of decision making in future projects. An important part of this useful knowledge and experience is the interpretation of data and information about design objects and processes as well as the generation of new information for decision-making. However, previous studies on knowledge representation models have mainly focused on developing a structure to describe the knowledge about design objects and design processes while a systematic method that can effectively integrate knowledge about design objects and knowledge about problem-solving strategies is still missing. To fill this gap, a RFBSE knowledge representation model for capturing useful design knowledge and experience for future reuse is developed and evaluated in this study. This paper describes the key elements of this model, explains the rationale of using particular elements, and discusses the evaluation of the model using an engineering design example.

An ontology-based product design framework for manufacturability verification and knowledge reuse

To achieve efficient development of high-quality product, manufacturing constraints must be fully taken into account at the early design stage. However, designers lack in-depth knowledge of manufacturing and production. Many time-consuming iterations of design changes are required between designers and manufacturing engineers. In order to minimize this knowledge gap, this paper presents an ontology-based product design framework for manufacturability verification and knowledge reuse to support the sharing and reuse of design and manufacturing knowledge. It aims at providing advices and feedback of restraints of manufacturing processes to the designers during the design process. The proposed framework consists of three major layers which include a foundation layer, a domain layer, and an instance layer. We use the Web Ontology Language (OWL), a standard of ontology representation language, to formalize the foundation layer. It contains the core product model and the standard ISO 10303 AP224 application protocol. The domain layer comprises extensional concepts and relationships for design and manufacturing integration and a rule base for manufacturability verification, which is represented in Semantic Web Rule Language (SWRL). In the instance layer, an inference engine is developed based on ontology and rule inference. It provides recommendations of manufacturability. Two case studies are provided as application examples to demonstrate the effectiveness of the framework.

Integrating multi-granularity model and similarity measurement for transforming process data into different granularity knowledge

Abstract The core of intelligent manufacturing is to incorporate the expert knowledge in manufacturing process, and knowledge transformation is the key to knowledge accumulation and application. In this paper, the research carried on transformation for different granularity knowledge from the cases of sheet metal parts in process planning. First of all, this paper analyzes the difference of organization structure between process data and knowledge in the base. The multi-granularity model of process knowledge is established in the form of tuple, which helps to clarify the hierarchy structure and internal relations. Thereafter, the concrete process is presented to transform single granularity process data into multi-granularity process knowledge, i.e., process data extraction, state determination and knowledge construction. With respect to state determination, similarity measure methods for different granularity knowledge are established to reduce the redundancy in the transformation process. As a novel approach, sequence alignment based on edit distance is proposed to calculate similarity exactly between two process flows. Finally, the knowledge transformation tool for different granularity knowledge is developed to enhance knowledge acquisition and improve the strength of knowledge reuse in fabrication order design for sheet metal parts through application of the above method. Also an example is given to illustrate the usefulness of the proposed method.

A qualitative investigation of design knowledge reuse in project-based mechanical design courses

ABSTRACTThe interpretation and reuse of previous design solutions, or precedents, is central to design. This paper describes qualitative research conducted over three years at two institutions, aimed at investigating the role of design knowledge re-use in project-based mechanical design courses. Research data were collected through participant observation, student interviews, anonymous questionnaires, and website analytics. The paper identifies challenges that must be addressed in order to support novice engineers in rehearsing the types of knowledge required to successfully reason about and engage with design precedents. Two categories of design precedents are identified: concept precedents and detail precedents. Providing students with access to the latter is identified as a particular challenge, as is providing students with access to engineering communities of practice. Approaches to addressing these challenges are discussed.