A Representational Framework for Scenarios of System Use

Scenarios are becoming widely used in three areas of system development: software engineering, human–computer interaction (HCI), and organisational process design. There are many reasons to use scenarios during system design. The one usually advanced in support of the practice is to aid the processes of validating the developers’ understanding of the customers’ or users’ work practices, organisational goals and structures, and system requirements. All three areas identified above deal with these processes, and not surprisingly this has given rise to a profusion of scenario-based practices and representations. Yet there has been little analysis of why scenarios should be useful, let alone whether they are. Only by having such a framework for understanding what scenarios are, and what they are for, can we begin to evaluate different scenario approaches in specific development contexts. This paper is a contribution toward such a framework. We lay out a space of representational possibilities for scenarios and enumerate a set of values or criteria that are important for different uses of scenarios. We then summarise several salient representations drawn from the software engineering, HCI, and organisational process design communities to clarify how these representational choices contribute to or detract from the goals of the respective practices. Finally, we discuss how scenario representations from one area of design may be useful in others, and we discuss the relationship between these representations and other significant early-design and requirements engineering practices.     

An intelligent system for automatic layout routing in aerospace design

This paper discusses the development of an intelligent routing system for automating design of electrical wiring harnesses and pipes in aircraft. The system employs knowledge based engineering (KBE) methods and technologies for capturing and implementing rules and engineering knowledge relating to the routing process. The system reads a mesh of three dimensional structure and obstacles falling within a given search space and connects source and target terminals satisfying a knowledge base of design rules and best practices. Routed paths are output as computer aided design (CAD) readable geometry, and a finite element (FE) mesh consisting of geometry, routed paths and a knowledge layer providing detail of the rules and knowledge implemented in the process. Use of this intelligent routing system provides structure to the routing design process and has potential to deliver significant savings in time and cost.     

巨型计算机工程设计描述模型

巨型机并行设计环境是巨型机工程设计自动化的发展趋势,它能有机地集成多领域ＣＡＤ工具,统一管理数据,统筹安排设计人员协同完成巨型机工程设计任务。本文介绍的设计描述模型建立此类设计环境的基础。     

Knowledge representation framework for interactive capture and management of reflection process in product concepts development

A design process can be characterized by reflection-in-action; that is, the process consists of a series of problem solving activities and each is embodied with a problem and a solution. In this process, a designer represents a hypothetical concept on each design alternative, deploys and verifies the concept from multiple viewpoints considering other alternatives, and modifies it. An advanced integrated design environment should be based on a representation framework that embodies this process of reflection in concept development, which usually remains in the realm of the designer’s tacit knowledge. This paper proposes a knowledge representation framework for an integrated design environment, named DRIFT (Design Representation Integration Framework of Three layers), which interactively captures and manages reflection processes of generating and verifying design concepts. The core of DRIFT is a three-layered design process model of actions, operations, and argumentation. This model integrates various design tools and captures performed design activities. The action level captures the sequence of design operations. The model operation level captures the transition of design states, recording a design snapshot over design tools, which are integrated through ontology-based representation of design concepts. The argumentation level captures the process of defining problems and corresponding alternative solutions. Integration of three levels with a template of design operation extracted from Design-For-X approaches enables a proposed system to interactively and efficiently capture and manage the process of design concept development through operations over design tools. A design operation template works to limit the number of links between the three levels remaining easy to manage its semantics. This paper also demonstrates a prototype implementation of DRIFT and its application to conceptual design of a small mechatronic system with a system modeling method. The paper concludes with a discussion of some future issues.     

A generic model for building design

The design of building structures has benefited considerably through computer automation, but further developments in this field are still required. This paper presenis a generic approach to computer automation of the detailed design of building structures. Because of its high level of abstraction, the resulting model is applicable to a wide range of structure types. Other advantages include the use of a consistent data model for software design and implementation, abstract data types for the representation of engineering data, the ability to represent heuristic knowledge, and the ability to evaluate design results in an intelligent manner.     

The smooth (tractor) operator: insights of knowledge engineering

The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training.     

A collaborative Design for Usability approach supported by Virtual Reality and a Multi-Agent System embedded in a PLM environment

This paper details a collaborative workstation design approach integrating knowledge based on engineering process, using a Multi-Agent System (MAS) on a Virtual Reality (VR) platform. The MAS supports R&D teams to extract and re-use engineering knowledge so as to improve their efficiency in developing new products. Our research targets the development of a knowledge engineering system integrated into a PLM-Product Life cycle Management-environment linked with virtual reality tools. A PLM is a strategic business approach with a consistent set of methodologies and software solutions. It is meant to promote collaborative creation, management, delivery and proper use of this life cycle definition and information product in multinational companies. This system is used by engineers to carry out projects in a collective way while conveying a defined process. The MAS allows capitalization, and to annotate knowledge according to the actions of the designers inside a PLM environment. Then, this knowledge is used by VR tools to analyze various aspects of the virtual prototype such as manufacturing, maintenance, reliability or ergonomics. Consequently, we use expert knowledge to pilot the design process of a virtual prototype inside a three-dimensional immersive virtual reality platform. In this context, our paper describes our knowledge management approach applied to improve ergonomics and collaborative design in industrial areas.     

Distributed representation learning and intelligent retrieval of knowledge concepts for conceptual design

Data-driven conceptual design is rapidly emerging as a powerful approach to generate novel and meaningful ideas by leveraging external knowledge especially in the early design phase. Currently, most existing studies focus on the identification and exploration of design knowledge by either using common-sense or building specific-domain ontology databases and semantic networks. However, the overwhelming majority of engineering knowledge is published as highly unstructured and heterogeneous texts, which presents two main challenges for modern conceptual design: (a) how to capture the highly contextual and complex knowledge relationships, (b) how to efficiently retrieve of meaningful and valuable implicit knowledge associations. To this end, in this work, we propose a new data-driven conceptual design approach to represent and retrieve cross-domain knowledge concepts for enhancing design ideation. Specifically, this methodology is divided into three parts. Firstly, engineering design knowledge from the massive body of scientific literature is efficiently learned as information-dense word embeddings, which can encode complex and diverse engineering knowledge concepts into a common distributed vector space. Secondly, we develop a novel semantic association metric to effectively quantify the strength of both explicit and implicit knowledge associations, which further guides the construction of a novel large-scale design knowledge semantic network (DKSN). The resulting DKSN can structure cross-domain engineering knowledge concepts into a weighted directed graph with interconnected nodes. Thirdly, to automatically explore both explicit and implicit knowledge associations of design queries, we further establish an intelligent retrieval framework by applying pathfinding algorithms on the DKSN. Next, the validation results on three benchmarks MTURK-771, TTR and MDEH demonstrate that our constructed DKSN can represent and associate engineering knowledge concepts better than existing state-of-the-art semantic networks. Eventually, two case studies show the effectiveness and practicality of our proposed approach in the real-world engineering conceptual design.     

A process knowledge representation approach for decision support in design of complex engineered systems

Process knowledge is of considerable significance to the digitalization and intelligentization of the manufacturing industry. Current research on the process knowledge representation of decision-making in engineering design has predominantly focused on either mathematical models of individual decisions at the micro-level or organizational models of group decision consensus at the macro-level. However, the management of complexity and uncertainty in the model-based realization of engineered systems is critical to achieving rational, comprehensive, and robust decisions, especially in terms of knowledge-intensive design. The efficiency and effectiveness of decisions in system design are intrinsically linked to the process, knowledge, and system concepts involved, necessitating a more flexible and systematic decision process representation scheme that supports both the management of complexity and uncertainty. Hence, in this paper, we propose a decision-centric design process representation scheme named the Phase-Event-Information X (PEI-X) diagram and its corresponding systematic design guidance method for designing decision workflows. Using the proposed method, designers have the ability to (1) model hierarchical decision processes that cover vertical and horizontal interaction patterns, and (2) exploit the synthesis of the “Formulating-Identifying-Reusing-Exploring” iterative process to extend the understanding and prediction of decision process behaviors in design. We achieve the aforesaid abilities through the implementation of a knowledge-based design guidance system for collaborative decision support and we demonstrate the efficacy by adopting a specific multi-stage manufacturing process design problem, hot rod rolling system design, and carry out an integrated design of materials, products, and related manufacturing processes.