Mass customization design of engineer-to-order products using Benders’ decomposition and bi-level stochastic programming

Leveraging product differentiation and mass production efficiency in mass customization basically entails a configure-to-order paradigm. In the engineer-to-order (ETO) business, however, companies build unique products in response to ‘foreseeable’ customer specifications. The key challenge of ETO mass customization lies in the complexity of accommodating future design changes when customers are involved in customizing design specifications. This paper proposes a two-stage, bi-level stochastic programming framework to tackle ETO mass customization. At the first stage, product platform configuration is integrated with production reconfiguration, which is formulated as a shortest path problem with resource constraints (SPPRC) to optimize production delays within the capabilities of the process platform. Benders’ decomposition algorithm is applied to solve this optimal configuration problem owing to its high computational efficiency. The second stage scrutinizes the optimal configuration resulting from the first stage for scaling optimization of design parameters (DPs) for each module. All DPs are differentiated by standard or customizable DPs. A bi-level stochastic program is implemented to leverage conflicting goals between the producer (leader) and consumer (follower) surpluses. As a result, ETO customization design is anchored with optimal values of standard DPs and optimal value ranges of customizable DPs. A case study of ship engine and power generator ETO design is presented, demonstrating the feasibility and potential of the ETO mass customization framework.     

Adaptive generic product structure modelling for design reuse in engineer-to-order products

In product lifecycle management, the efficiency of information reuse relies on the definition and management of equivalence information between various product data and structure representations. Equivalence information ensures the consistency and traceability of product information throughout the product lifecycle. The sales-delivery process of engineer-to-order (ETO) products presents a great potential for design reuse, i.e. the reuse of previously validated design solutions in the design of new product variants according to customer-specific requirements. A product family data model that focuses on the interdependencies of viewpoints on information will therefore improve the setup of design reuse mechanisms such as modularity. This paper describes the Adaptive Generic Product Structure (AGPS), a dynamic structure-based product family modelling approach that enables the systematic aggregation of product variants and their distinctive components. The purpose of the approach is to capitalize on the expanding component variety developed within previous product variants as early as the sales lead phase of the sales-delivery process, in order to reduce customer-driven design costs and shorten lead-times. An illustrative example based on the aerospace industry is presented.     

面向重用的产品设计过程知识建模与检索

针对传统的产品设计过程知识模型与知识检索方法在提高产品设计过程知识重用性上的不足,提出了多层次多粒度的知识模型以及基于语义的智能检索算法。首先通过分析产品设计过程知识重用的需求,将产品设计过程知识分为项目管理知识、领域知识、产品设计对象知识三类,并建立对应的多层次知识模型。然后在运用本体技术建立产品设计过程知识本体库的基础上,提出了一种基于语义的智能检索算法。最后给出了产品设计过程知识重用模型,并以柴油发动机方案设计为例,证明了该模型的有效性。     

Design reuse oriented partial retrieval of CAD models

As a huge number of 3D CAD models is generated each year, retrieval of 3D CAD models is becoming more and more important for achieving design reuse. However, the existing methods for partial retrieval of 3D CAD models are very few and far from the requirements of design reuse. In this paper, we present an approach to partial retrieval of 3D CAD models for design reuse. The criteria for determining whether a subpart of 3D CAD models is reusable for design is defined first. Based on the criteria defined, all the design reusable subparts involved in the 3D CAD models in the library are automatically extracted and stored in the library as reference models. Moreover, each design reusable subpart in the library is represented by all its local matching regions in a hierarchical way so as to support multi-mode partial retrieval. In our approach, three partial retrieval modes including normal retrieval, exact retrieval and relaxed retrieval are defined to meet various partial retrieval requirements of design reuse such as the incomplete and vague queries during the early design stage. And the multi-mode partial retrieval is achieved by performing multi-mode matching and similarity assessment between the query and the design reusable subparts in the library indexed by bitmap. Experimental results are presented to demonstrate the effectiveness of the approach.     

A RFBSE model for capturing engineers’ useful knowledge and experience during the design process

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.     

A collaborative system for capturing and reusing in-context design knowledge with an integrated representation model

Current research on design knowledge capture and reuse has predominantly focused on either the codification view of knowledge or the personalisation view of knowledge, resulting in a failure to address designers’ knowledge needs caused by a lack of context of information and insufficient computational support. Precisely motivated by this gap, this work aims to address the integration of these two views into a complete, contextual and trustworthy knowledge management scheme enabled by the emerging collaborative technologies. Specifically, a knowledge model is developed to represent an integrated knowledge space, which can combine geometric model, knowledge-based analysis codes and problem-solving strategies and processes. On this basis, a smart collaborative system is also designed and developed to streamline the design process as well as to facilitate knowledge capture, retrieval and reuse as users with different roles are working on various tasks within this process. An engineering case study is undertaken to demonstrate the idea of collaborative knowledge creation and sharing and evaluate the effectiveness of the knowledge representation model and the collaborative technologies employed. As evidenced in the development and evaluation, the methods proposed are effective for capturing an integrated knowledge space and the collaborative knowledge management system not only facilitates problem-solving using knowledge-based analysis but also supplies in-context tacit knowledge captured from the communications between users throughout the design process.     

A study on the collaborative management method of product design cycle knowledge

Because of the ever-increasing market competition and rapidly changing of customers’ requirements, the innovation quality and design efficiency of knowledge-intensive product has become the key factors in business success. The traditional knowledge management method which is based on design reuse and the single categories of design knowledge cannot satisfy these demands any more. Therefore, in order to effectively support the innovative design process of enterprises, a design knowledge collaborative management method based on multi-knowledge migration is proposed. According to the characteristics and functions during the product design process, the design knowledge is divided into three categories, design principle knowledge, design domain knowledge and design object knowledge. By extracting the operation attributes, relation attributes and physical attributes of the design knowledge, a unified knowledge representation model is established for different design participants. The ontology concept and knowledge matrix are used to establish the association between various categories of design knowledge. Multifarious knowledge search methods include keyword, function, principle and natural semantics are proposed for different design participants in different design stages. They can not only realize the knowledge reuse in the same domain but also support the cross-domain knowledge migration among different domain. Finally, based on the system analysis modelling, a design knowledge collaborative platform is established for the design process of mechanical products. A case study is also presented to illustrate the implementation of the platform.     

Customized products recommendation based on probabilistic relevance model

Product customization is attracting more attentions in industry as a viable strategy to better meet customer requirements and gain more profit. However the vast number of product variants in product customization process often makes it difficult for consumers to make purchase decisions, a phenomenon referred to as information overload. In this paper we take a two-prong approach to tackle the issue of information overload in customized products recommendation. Basically, the method answers two questions, namely, which products to recommend and in what order to present the recommendations. Firstly, a probability relevance model is deployed to calculate the probability of relevance for each end product. Then a probability ranking principle is exploited to present the recommendations. The approach also takes customer flexibility into consideration and thus mitigates the effect of inconsistent specifications from customers. It does not require any prior knowledge about an active customer’s preference and can accommodate the new customers challenge facing by recommendation approaches. Analytical results show that the method is optimal in terms of customer’s utility and product recommendation efficiency. Numerical experiments are also conducted to test the presented approach.     

Developing a multi-layer reference design retrieval technology for knowledge management in engineering design

Engineering design is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various areas of knowledge and experience. The sharing of such knowledge and experience is critical to increasing the capacity for developing products and to increasing their quality. It is also critical to reducing the duration and cost of the development cycle. Accordingly, offering engineering designers various methods for retrieving engineering knowledge is one of the most important tasks in managing engineering knowledge.

This study develops a multi-layer reference design retrieval technology for engineering knowledge management to provide engineering designers with easy access to relevant design and related knowledge. The tasks performed in this research include (i) designing a multi-layer reference design retrieval process, (ii) developing techniques associated with multi-layer reference design retrieval technology, and (iii) implementing a multi-layer reference design retrieval mechanism. The retrieval process contains three main phases—‘customer requirement-based reference design retrieval’, ‘functional requirement-based reference design retrieval’ and ‘functional feature-based reference design retrieval’. This technology involves (1) customer requirement-based reference design retrieval, which involves a structured query model for customer requirements, a case-based representation of designed entities, a customer requirement-based index structure for historical design cases, and customer requirement-based case searching, matching and ranking mechanisms, (2) functional requirement-based reference design retrieval, which includes a structured query model for functional requirements, a functional requirement-based index structure for historical design cases, and functional requirement-based case searching, matching and ranking mechanisms, and (3) functional feature-based reference design retrieval, which is a binary code-based representation for functional features, an ART1 neural network for functional feature-based case clustering and functional feature-based case ranking.     

Systematic modeling and reusing of process knowledge for rapid process configuration

Rapid product development relies heavily on quick and reliable process planning and knowledge reuse. Process configuration borrows the principles of product configuration and applies them to process planning. It allows the reuse of hierarchical, historical and case-based manufacturing process knowledge to generate process plans efficiently and effectively. This paper presents a systematic knowledge model for manufacturing process cases. The model represents process knowledge at different levels of granularity and to facilitate process configuration. With this knowledge model the process knowledge is categorized into 6 levels: (i) core process skeletons, (ii) process networks, (iii) process routes, (iv) process segments, (v) processes/workplan, and (vi) operations/working step. Based on the systematic knowledge model, this paper also proposes an approach to achieve rapid process configuration by reusing the process knowledge and by performing the involved configuration rules so as to create an appropriate, reliable and effective process plan. The prototype for a graphical process planner based on this knowledge model is developed and an aerospace example is used to validate the proposed process knowledge model and process configuration.     

On technology for functional requirement-based reference design retrieval in engineering knowledge management

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various aspects of technical knowledge and experience. Whether this technical knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Consequently, providing engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management.The study develops a technology for functional requirement-based reference design retrieval as a decision support mechanism, which can assist engineering designers to retrieve relevant design and associated knowledge for reference in conducting functional requirements of a product. This study involves the following tasks: (i) designing a functional requirement-based reference design retrieval process, (ii) developing techniques related to the technology for functional requirement-based reference design retrieval, and (iii) implementing a functional requirement-based reference design retrieval mechanism. The retrieval process includes the steps of functional requirement-based query, case searching and matching, and case ranking. The technology involves (i) a structured query model for functional requirements, (ii) an index structures for historical design cases, (iii) functional requirement-based case searching and matching mechanisms, (iv) a functional requirement-based case ranking mechanism, and (v) a case-based representation of designed entities. Finally, the experimental example with indexing and retrieving similar designed entities is conducted to demonstrate the proposed techniques worked efficiently.     

基于Topic Map的知识管理系统研究

为提高企事业知识的共享、重用以及有效检索,提出了一个基于主题图的知识管理系统模型,采用本体描述语言TopicMaps对企事业中的知识类型进行描述,分析了主题图的特点,研究了知识管理系统中知识主题图和知识表示、检索之间的关系,并由一个实例分析说明了该模型框架的应用。     

支持大批量定制的产品配置设计系统的研究

针对大批量定制生产的特点，提出基于产品功能结构单元的产品配置模板来完成对客户配置需求的快速响应，给出了产品配置模板的信息模型和配置求解策略．由于机械产品结构的复杂性，引入配置设计知识的混合表达方法以适应不同产品设计类型的要求．最后给出基于产品配置模板信息模型的配置设计系统的实例．     

Developing a multi-layer reference design retrieval technology for knowledge management in engineering design

Engineering design is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various areas of knowledge and experience. The sharing of such knowledge and experience is critical to increasing the capacity for developing products and to increasing their quality. It is also critical to reducing the duration and cost of the development cycle. Accordingly, offering engineering designers various methods for retrieving engineering knowledge is one of the most important tasks in managing engineering knowledge.This study develops a multi-layer reference design retrieval technology for engineering knowledge management to provide engineering designers with easy access to relevant design and related knowledge. The tasks performed in this research include (i) designing a multi-layer reference design retrieval process, (ii) developing techniques associated with multi-layer reference design retrieval technology, and (iii) implementing a multi-layer reference design retrieval mechanism. The retrieval process contains three main phases—‘customer requirement-based reference design retrieval’, ‘functional requirement-based reference design retrieval’ and ‘functional feature-based reference design retrieval’. This technology involves (1) customer requirement-based reference design retrieval, which involves a structured query model for customer requirements, a case-based representation of designed entities, a customer requirement-based index structure for historical design cases, and customer requirement-based case searching, matching and ranking mechanisms, (2) functional requirement-based reference design retrieval, which includes a structured query model for functional requirements, a functional requirement-based index structure for historical design cases, and functional requirement-based case searching, matching and ranking mechanisms, and (3) functional feature-based reference design retrieval, which is a binary code-based representation for functional features, an ART1 neural network for functional feature-based case clustering and functional feature-based case ranking.     

A part affordance-based approach for capturing detailed design knowledge

Design knowledge reuse is widely accepted as an effective strategy for designers to develop robust artifacts with less time and lower cost. However, there has been very little research on how to help designers capture detailed design knowledge for reuse. As a result, most detailed design knowledge still has to remain in designers’ memories as tacit knowledge, which can easily get lost due to oblivion or the mobility of designers. Therefore, this paper attempts to develop a part affordance-based approach for externalizing and capturing detailed design knowledge for effective reuse. It first introduces a part model for representing the detailed design-related information. Based on the relational theory for design, the concept, part affordance, is then employed to help designers externalize and capture various lifecycle factors that are implicit in a detailed design. Based on the affordance constraint axiom, a systematic approach is then proposed for deriving tacit design knowledge from captured part affordances through the analysis of extreme working situations. The proposed approach has been implemented as the Design Knowledge-Capturing System (DKCS). A fixture design case has been employed to illustrate the proposed approach.     

An approach to user knowledge acquisition in product design

As the world increasingly moves towards a knowledge-based economy, user requirements become an important factor for enterprises to drive product collaborative design evolution. To map user requirements to the product model, user requirements are generally extracted into knowledge that can be used for design decisions. However, because users are interest-driven participants and not professional design engineers, the effect of user knowledge acquisition is not ideal. There are significant challenges for rapid knowledge acquisition with dynamic user requirements. This paper presents an approach to user knowledge acquisition in the product design process, which obtains the tangible requirements of users under the premise that users are adequate for participation. In this approach, the typical information flow is divided into four stages: submission, interaction, knowledge discovery, and model evolution. In the submission stage, natural language processing technology is used to transform text form solutions into data, so that computer technology can be applied to manage large-scale user requirements. In the interaction stage, users are helped to improve their solutions by the iterative recommendation process. In the knowledge discovery stage, after less concerned partial solutions are removed and vacant items are predicted to be supplemented, the final collection of user design information is obtained. Finally, based on rough set theory, design knowledge can be extracted to support the decision of the product model. The washing machine design project is used as a case study to explain the implementation of the proposed approach.     

An automatic text generation algorithm of technical disclosure for catenary construction based on knowledge element model

Preparing technical disclosure documents has always been a labor-intensive task in the site management practice of current OCS (Overhead Contact System) project construction, and the overall information level of construction management is not high. As a result, the technical disclosure documents are of poor quality, which significantly affects the effective play of technical documents in guiding construction activities. In view of the above limitations, this paper proposes a text-generation method for OCS engineering technical disclosure based on a knowledge element model. By investigating the characteristics of OCS engineering technical knowledge, a representation model is established to model the technical knowledge from multiple sources, such as case data, standard specifications, and design data. As OCS engineering is highly standardized, we propose a case-rule hybrid reasoning model for the reuse of OCS engineering case knowledge. The mining and utilization of earlier engineering technical knowledge are made possible by similar retrieval of precedent situations and adaptive rules modification. Finally, we suggest an automatic text-generating technique based on a configuration template for new building projects. The knowledge element model is converted into a technical disclosure document expressed in natural language using a two-level mapping process. The cantilever installation project is used as an illustration for empirical research, and relevant practitioners are invited to carry out a manual review by questionnaire from the perspectives of topic relevance, topic integrity, topic word implication, sentence smoothness, sentence continuity, and information volume. At the same time, standard assessment metrics such as BLEU and ROUGE are employed to compare with the neural network-based text generation approach. The outcomes demonstrate that the strategy suggested in this paper can generate technical disclosure text that performs well. Overall, its text integrity and readability may satisfy on-site management's demands and help on-site management lessen the workload of technical management staff.     

Reuse of knowledge assets from repositories: A mixed methods study

Reuse of information retrieved from an electronic knowledge repository and how this complements person-to-person interactions are poorly understood. I developed a research model that examined factors influencing how individuals benefit from reuse of knowledge assets. Using a mixed method approach, two empirical studies were conducted to test the model. The results showed that two key factors helped users to overcome difficulties in reusing knowledge assets: seeking assistance from and sharing a common perspective with the author of the asset. The study explains when and how individuals receive benefits from knowledge reuse. When individuals reuse complex knowledge assets in domains with which they are unfamiliar, they apparently gain more benefit by contacting the author; sharing a common perspective with the author also facilitates asset reuse. Thus both electronic repositories and person-to-person interaction mechanisms complement one another in facilitating knowledge sharing.     

An ontology-based support for product conceptual design

The research presented in this paper is a follow-up of our prior work involving the development of a graphical modeling tool to support designers at the conceptual design stage. To close the loop for supporting designers in generating design concepts flexibly, fast, and easily, an ontology-based approach for knowledge management that works along with the graphical modeling tool is discussed. Ontology and databases for the tool are developed to promote the systematic capture of design knowledge and efficient reuse of the design knowledge selection. In order to locate the proper information and query the data from the databases, the relationship between the ontology and databases, the data analysis process, ontology enrichment, and the ontology-based query engine are built to offer users multiple design results according to users’ requirements. A tire design example is presented to demonstrate the proposed approach. The ontology-based method described in this paper can help retrieve and save the complex relations, support the reasoning, integrate heterogeneous data resources and offer users more accurate, proper and comprehensive data.