Coping with large design spaces: design problem solving in fluidic engineering

This paper is about tool support for knowledge-intensive engineering tasks. In particular, it introduces software technology to assist the design of complex technical systems. There is a long tradition in automated design problem solving in the field of artificial intelligence, where, especially in the early stages, the search paradigm dictated many approaches. Later, in the so-called modern period, a better problem understanding led to the development of more adequate problem solving techniques. However, search still constitutes an indispensable part in computer-based design problem solving—albeit many human problem solvers get by without (almost). We tried to learn lessons from this observation, and one is presented in this paper. We introduce design problem solving by functional abstraction which follows the motto: construct a poor solution with little search, which then must be repaired. For the domain of fluidic engineering we have operationalized the paradigm by the combination of several high-level techniques. The red thread of this paper is design automation, but the presented technology does also contribute in the following respects: (a) productivity enhancement by relieving experts from auxiliary and routine tasks; (b) formulation, exchange, and documentation of knowledge about design; (c) requirements engineering, feasibility analysis, and validation. This research was supported by DFG grants Schw 120/56-3, KL 529/10-3, KL 529/7-3, and KL 529/10-1.     

供需链管理系统基于CORBA的实现

本文基于分布对象技术CORBA、代理及Web技术提出了一敏捷供需链管理系统的实施方案,在分布、异构环境下实现应用系统集成。     

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.     

基于强化学习的机器人多接触交互任务控制

作为自动化和智能化时代的代表,机器人技术的发展成为智能控制领域研究的焦点,各种基于机器人的智能控制技术应运而生,机器人被越来越多地应用于实现与环境之间的复杂多接触交互任务.本文以机器人复杂多接触交互任务为核心问题展开讨论,结合基于强化学习的机器人智能体训练相关研究,对基于强化学习方法实现机器人多接触交互任务展开综述.概述了强化学习在机器人多接触任务研究中的代表性研究,当前研究中存在的问题以及改进多接触交互任务实验效果的优化方法,结合当前研究成果和各优化方法特点对未来机器人多接触交互任务的智能控制方法进行了展望.     

Knowledge engineering

Summary Several new and emerging computational paradigms for engineering problem solving automation and processing of various types of knowledge are reviewed. They are artificial intelligence/sybmolic processing, object-oriented programming paradigm, machine learning, evolutionary computing/genetic algorithms, and neurocomputing. Examples of recent research efforts in each area are briefly described.     

A decision support system for product design in concurrent engineering

Compared with the traditional sequential design method, concurrent engineering is a systematic approach to integrate concurrent design of products and their related processes. One of the key factors to successfully implement concurrent engineering is information technology. In order to design a product and its manufacturing process simultaneously, information on product features, manufacturing requirements, and customer demands must be processed while the design is concurrently going on. There is an increased understanding of the importance of the correct decisions being made at the conceptual design and development stages that involve many complex evaluation and decision-making tasks. In order to promote the efficiency in concurrent product development, appropriate evaluation and decision tools need to be provided. In this paper, the characteristics of fuzzy, multi-stage evaluation and decision making in concurrent product development process are analyzed and a decision support system for product design in concurrent engineering is presented. An example is given to illustrate the application of the system.     

Development of technology for customer requirement-based reference design retrieval

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each task involves various aspects of knowledge and experience. Whether this 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. Therefore, offering 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 customer requirement-based reference design retrieval to provide engineering designers with easy access to relevant design and associated knowledge. The tasks involved in this research include (i) designing a customer requirement-based reference design retrieval process, (ii) developing techniques related to the technology for customer requirement-based reference design retrieval, and (iii) implementing a customer requirement-based reference design retrieval mechanism. The retrieval process comprises the steps of customer requirement-based query, case searching and matching, and case ranking. The technology involves (1) a structured query model for customer requirement, (2) an index structure for historical design cases, (3) customer requirement-based case searching and matching mechanisms, (4) a customer requirement-based case ranking mechanism, and (5) a case-based representation of designed entities.     

自动化学科面临的挑战

本文分析了控制理论与应用、模式识别与智能系统、导航制导与控制、系统科学与工程、人工智能与自动化交叉等领域的发展现状. 结合科技发展、国内国际研究前沿和新兴领域对自动化科学技术的需求, 提出重点发展智能控制理论和方法、高性能作业机器人、信息物理系统、导航与控制技术、重大装备自动化技术、自主智能系统和人工智能驱动的自动化技术优先领域, 加强数据驱动控制理论、人工智能基础理论研究, 进一步发展人机协同、跨域融合的智能自动化, 为实现国家社会的全面信息化智能化提供理论和技术保障.     

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.     

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 systematic literature review on intelligent automation: Aligning concepts from theory,practice, and future perspectives

With the recent developments in robotic process automation (RPA) and artificial intelligence (AI), academics and industrial practitioners are now pursuing robust and adaptive decision making (DM) in real-life engineering applications and automated business workflows and processes to accommodate context awareness, adaptation to environment and customisation. The emerging research via RPA, AI and soft computing offers sophisticated decision analysis methods, data-driven DM and scenario analysis with regard to the consideration of decision choices and provides benefits in numerous engineering applications. The emerging intelligent automation (IA) – the combination of RPA, AI and soft computing – can further transcend traditional DM to achieve unprecedented levels of operational efficiency, decision quality and system reliability. RPA allows an intelligent agent to eliminate operational errors and mimic manual routine decisions, including rule-based, well-structured and repetitive decisions involving enormous data, in a digital system, while AI has the cognitive capabilities to emulate the actions of human behaviour and process unstructured data via machine learning, natural language processing and image processing. Insights from IA drive new opportunities in providing automated DM processes, fault diagnosis, knowledge elicitation and solutions under complex decision environments with the presence of context-aware data, uncertainty and customer preferences. This sophisticated review attempts to deliver the relevant research directions and applications from the selected literature to the readers and address the key contributions of the selected literature, IA’s benefits, implementation considerations, challenges and potential IA applications to foster the relevant research development in the domain.     

不精确推理在储粮安全预警专家系统的研究

为了提高我国粮食储藏技术水平,利用粮食仓储知识及经验、计算机和人工智能技术,研究开发储粮安全预警专家系统。将数据库、人工智能、管理信息系统、决策支持系统、计算机技术以及信息集成技术应用到粮食储藏领域。使用系统有助于粮库仓储管理的智能化及自动化,能够最大限度的降低粮食在仓储过程中的损失率,确保国家粮食安全。     

Vector optimization vs vectorization

This paper differentiates between vectorization and concurrentization and vector optimization. Vectorization (concurrentization) is the process of translating serial DO loops into vector code for a vector computer (concurrent code for a multiprocessor computer). Vector optimization uses vectorization (concurrentization) but adds some intelligence to decide which loop (s) to run in parallel. Vector optimization tools, such as loop interchanging and generation of multiple versions of a loop, are introduced and some decision mechanisms are discussed.     

基于开放式标准化思想的CIMS信息集成方法

论述CIMS的基于集成、开放、标准化和并行工程思想的信息集成方法.即应用STEP、 EXPRESS、SGML、HyTime、X Windows、UNIX等国际标准或主流工业标准,依托面向对 象工程数据库,开发一个开放式的由软件工具和超媒体界面组成的支持环境,实现CIMS信息 的数字化交换、共享、集成,支持并行工程思想.     

平行区块链:概念、方法与内涵解析

本文提出了平行区块链的概念框架、基础理论和研究方法体系,并探讨了平行区块链的内涵.平行区块链技术是平行智能理论方法与区块链技术的有机结合,致力于通过实际区块链系统与人工区块链系统的平行互动与协同演化,为目前的区块链技术增加计算实验与平行决策功能,实现描述、预测、引导相结合的区块链系统管理与决策.平行区块链这一新型研究范式可望为下一步区块链研究和未来产业应用提供有益的启发与借鉴.     

A decision support system for the selection of computer-integrated manufacturing technologies

The adoption of computer-integrated manufacturing (CIM) offers manufacturing organizations many tangible and intangible benefits which enable them to produce products of high quality at low costs. However, the selection and evaluation of CIM is a complex process as it involves the consideration of many parameters to ensure that the selected technology meets the requirements of individual companies. This paper describes the development of a quantitative/qualitative decision support system for the evaluation of CIM which takes into consideration the objectives and operating characteristics of a company, thus ensuring that the selected technology matches the individual needs of that company. The methodology used in the decision support system is based on a combination of the analytical hierarchy process (AHP) and database technology. The AHP provides a means to consider both the tangible and the intangible benefits of CIM while databases are used to store the knowledge about the various benefits that CIM may offer. The system has been implemented in EXCEL, which fully automates the evaluation process. A case study is also presented to illustrate the capability of the proposed decision support system.     

工业人工智能发展方向

本文结合工业自动化和信息技术在工业革命中的作用以及制造与生产全流程决策、控制以及运行管理的现状和智能化发展方向的分析, 提出了发展工业人工智能的必要性. 通过对人工智能技术的涵义、发展简史和发展方向的分析以及自动化与人工智能研究与应用的核心目标、实现方式、研究对象与研究方法等方面的对比分析, 提出了工业人工智能技术的涵义. 通过对工业人工智能和工业自动化的研究对象与研究目标对比分析, 提出了工业人工智能的研究方向和研究思路与方法.     

Artificial intelligence and expert systems applications in new product development—a survey

The authors review and categorize the research in applications of artificial intelligence (AI) and expert systems (ES) in new product development (NPD) activities. A brief overview of NPD process and AI is presented. This is followed by a literature survey in regard to AI and ES applications in NPD, which revealed twenty four articles (twenty two applications) in the 1990–1997 period. The applications are categorized into five areas: expert decision support systems for NPD project evaluation, knowledge-based systems (KBS) for product and process design, KBS for QFD, AI support for conceptual design and AI support for group decision making in concurrent engineering. Brief review of each application is provided. The articles are also grouped by NPD stages and seven NPD core elements (competencies and abilities). Further research areas are pointed out.     

装配序列规划研究综述

装配序列规划是机器人智能装配中的一项重要研究课题，也是ＣＡＤ／ＣＡＭ以及ＣＩＭＳ研究的一个重要组成部分，涉及计算机，人工智能，自动化，机器人和机械工程等领域，本文对机械装配序列规划研究的历史和技术现状进行了综述。     

Development of a computer-aided concurrent net shape product and process development environment

This paper presents a systematic approach to developing a collaborative environment for computer-aided concurrent net shape product and process development. This approach includes the steps of (1) conventional development process analysis, (2) development process re-engineering, (3) computer-based system functional requirements analysis, (4) system framework design, and (5) system modeling, integration and implementation. This environment can support concurrent net shape product and process development by providing and integrating functions of product data management, process management and development advisory tools. The results of this research will facilitate the rationalization and automation of net shape product and process development and thus improve the efficiency and quality, and reduce the cost of net shape product development.

IDEF structural analysis methodology was employed to capture the characteristics of net shape product and process development process. The concept of concurrent engineering was used to re-engineer the development process. The technology of system engineering was used to design the computer-aided system framework. Object-oriented analysis, modeling and design methodology, knowledge engineering and data engineering techniques were employed for system modeling and implementation.