Hyo Won Suh

On identifying and estimating the cycle time of product development process

A timely introduction of a new product has become invaluable to the firm since the competitors are capable of introducing new or similar products once the driving technology becomes available. In order to generate a high profit from a new product, managers in other departments, such as marketing and production, have to plan ahead of time so that a seamless series of operations can be executed from product development to mass production. Needless to say, a competitive edge is given to the firm with better knowledge on product development process. Such knowledge, nonetheless, is not easy to acquire since a typical product development process is a complex network of many relationships among activities, which we call patterns. In addition to its complex topology, the product development process is often uncertain, iterative, and evolving over time; therefore, even studying individual islands of relationships (patterns) is challenging. Although there were some existing models that shed lights on some of these patterns, very little has been done to systematically analyze the product development process as a whole. In this paper, we develop analytical models that capture essential properties, including uncertainty, iteration and evolution, and estimate the cycle time of each pattern. With our proposed models, the cycle time of a set of patterns (or the whole product development process) can be effectively estimated. As demonstrated in a case study, our model provides valuable insights on how product development process progresses over time, while the corresponding time estimate can help managers to set appropriate manufacturing and marketing strategies.

A personalized query expansion approach for engineering document retrieval

Engineers create engineering documents with their own terminologies, and want to search existing engineering documents quickly and accurately during a product development process. Keyword-based search methods have been widely used due to their ease of use, but their search accuracy has been often problematic because of the semantic ambiguity of terminologies in engineering documents and queries. The semantic ambiguity can be alleviated by using a domain ontology. Also, if queries are expanded to incorporate the engineer’s personalized information needs, the accuracy of the search result would be improved. Therefore, we propose a framework to search engineering documents with less semantic ambiguity and more focus on each engineer’s personalized information needs. The framework includes four processes: (1) developing a domain ontology, (2) indexing engineering documents, (3) learning user profiles, and (4) performing personalized query expansion and retrieval. A domain ontology is developed based on product structure information and engineering documents. Using the domain ontology, terminologies in documents are disambiguated and indexed. Also, a user profile is generated from the domain ontology. By user profile learning, user’s interests are captured from the relevant documents. During a personalized query expansion process, the learned user profile is used to reflect user’s interests. Simultaneously, user’s searching intent, which is implicitly inferred from the user’s task context, is also considered. To retrieve relevant documents, an expanded query in which both user’s interests and intents are reflected is then matched against the document collection. The experimental results show that the proposed approach can substantially outperform both the keyword-based approach and the existing query expansion method in retrieving engineering documents. Reflecting a user’s information needs precisely has been identified to be the most important factor underlying this notable improvement.

Automatic CAD model retrieval based on design documents using semantic processing and rule processing

Design documents that contain initial design information are used to retrieve relevant CAD models.Semantic gap between text in CAD models and text in design documents is resolved.Design information is converted to semantically structured information.Hidden design information in CAD models and design documents is extracted.The experimental results show that the proposed approach is better than keyword-based approach. Reuse of CAD model is important for manufacturing companies where similar products are produced. If existing CAD models have design information related to the design of a new product, their reuse saves costs and reduces time of product design. Since design documents generated in the early design stage contain product specifications and design directions for new product design, they can be used as input queries to retrieve existing CAD models. In this paper, we propose an approach to retrieving CAD models with design documents. A major challenge of the proposed approach was reduction of semantic gap between design documents and CAD models because design documents generated in the early design stage contain abstract design descriptions, while CAD models contain detailed design descriptions. In order to reduce the semantic gap between CAD models and design documents, we adopt semantic processing and rule processing. During the semantic processing, semantic representations are generated from the text in CAD models and text in design documents using a domain ontology and shallow natural language processing (NLP). Hidden design information is extracted from CAD models and design documents based on rule processing. The experimental results show that the proposed approach can outperform the keyword-based approach which does not overcome semantic gap.

Semantic relation based personalized ranking approach for engineering document retrieval

Since engineering design is heavily informational, engineers want to retrieve existing engineering documents accurately during the product development process. However, engineers have difficulties searching for documents because of low retrieval accuracy. One of the reasons for this is the limitation of existing document ranking approaches, in which relationships between terms in documents are not considered to assess the relevance of the retrieved documents. Therefore, we propose a new ranking approach that provides more correct evaluation of document relevance to a given query. Our approach exploits domain ontology to consider relationships among terms in the relevance scoring process. Based on domain ontology, the semantics of a document are represented by a graph (called Document Semantic Network) and, then, proposed relation-based weighting schemes are used to evaluate the graph to calculate the document relevance score. In our ranking approach, user interests and searching intent are also considered in order to provide personalized services. The experimental results show that the proposed approach outperforms existing ranking approaches. A precisely represented semantics of a document as a graph and multiple relation-based weighting schemes are important factors underlying the notable improvement.

Methodology to Support Environmentally Aware Product Design Using Axiomatic Design: eAD+

With the increasing environmental sophistication of consumers, there is a need to consider environmental factors and sustainability in the design process. This paper proposes a design methodology intended for software implementation called eAD+ to address the following four issues: 1) there are inherent couplings between eco-factors and product design parameters, 2) eco-factors are seldom structured for ready use within all phases of the design process, 3) there is a need for a formal feedback mechanism from the results of eco-analysis to the design process, and 4) it can be difficult to identify which design choice causes the most egregious environmental issue or functional coupling. eAD+ is based primarily on the Axiomatic Design (AD) methodology and addresses these issues as follows. First, AD directly identifies couplings between the functional requirements (FRs) in a design so that efforts, such as TRIZ, can be applied to address them. Second, as common eco-factors do not provide sufficient structure for inclusion in the AD framework, we develop structured eco-FRs and constraints. These are included alongside the product FRs throughout the design process. Third, the subset of the design matrix (DM) relating the eco-FRs to the design parameters explicitly incorporates feedback from eco-analysis into the design process. Here a database containing environmental (or sustainability) information is employed to evaluate the design. Fourth, we employ an augmented DM (drawing inspiration from the House of Quality of QFD) that provides weights highlighting which design parameter has the greatest influence on eco-factors and functional couplings.Copyright

Product modeling framework and language for behavior evaluation

Supporting different stakeholder viewpoints across the products entire lifecycle requires semantic richness for representing product related information. This paper proposes a multi-layered product-modeling framework that enables stakeholders to define their product-specific models and relate product-specific models to physical or simulated instances. The framework is defined within the Model-driven Architecture and adapted to the multi-layer approach of the architecture. The data layer represents real world products, the model layer includes models of those products, and the meta-model layer defines the product modeling language. The semantic-based product modeling language described in this paper is specialized from a web ontology language enabling product designers to express the semantics of their product models explicitly and logically in an engineering-friendly way. The interactions between these three layers are described to illustrate how each layer in the framework is used in a product engineering context.

Cooperative routing with video complexity for heterogeneous motion-level streaming

Abstract Cooperative relay is a promising technique that can improve network capacity in multi-hop wireless networks. However, conventional video streaming schemes on cooperative relay networks do not consider the video complexity of each video sequence. In this paper, we develop and experimentally evaluate a video streaming scheme that considers video complexity over a cooperative multi-hop relay network. We first develop a video distortion model taking into account the video complexity of the video sequences. Then, we propose a flow-routing algorithm for heterogeneous motion-level video streams in multi-hop cooperative networks. To evaluate the video routing performance for heterogeneous motion-level video sequences, we conduct experimental simulations with the proposed routing algorithm and a video distortion model. Numerical results show that network performance improves when video sequences are routed while considering heterogeneous motion levels to maximize the minimum peak signal-to-noise ratio (PSNR) value for the video sessions. The simulation results also show that the adoption of cooperative relays and a hop-count limitation can also improve the routing performance of video streams.