Transformation of semantic knowledge into simulation-based decision support

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated transformation of this conceptual model into an executable one. This novel modeling approach makes model development more efficient by reducing its complexity. It is validated in a use case implementation from semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate the impacts of the COVID-19 pandemic on a global supply chain network.     

基于多Agent的协同制造平台的研究与设计

随着企业间的集成与协作越来越紧密,知识也越来越高度密集,本文基于多Agent技术,提出一种支持以知识为基础的协同制造开发平台——基于多Agent的可伸缩的多智能协同制造平台。详细设计了多Agent协同开发平台的体系结构、协作框架,以及多agent系统基于本体的通信机制。该平台凭借包装服务和代理商提供的通信能力,通过有效地支持制造业知识的表示、获取、检索和重利用,不仅有利于多学科的个体和团队的组织和协作,而且提出的基于本体库的广义知识库能使设计人员有效地、不受限制地交换信息和知识。     

基于本体的数字卡通项目知识共享与维护

针对数字卡通项目开发过程中知识管理和共享所面临的难题,提出了一种基于本体的数字卡通项目知识共享和维护解决方案。探讨了如何构造面向数字卡通项目管理的本体COPMO,给出了一种基于本体的知识共享和推送框架CKSF,并且研究了COPMO本体的演化和维护问题。     

Capturing Expert Knowledge for Supporting Design and Manufacturing of Injection Molds

Knowledge based approach is effective for renovating design and manufacturing processes. The objective of this paper is to investigate roles and usages of expert engineering knowledge in high-quality manufacturing, and to study a practical knowledge capturing method for realizing engineering support tools. An engineer oriented interface for a capturing method is proposed, and a flexible representation framework is studied for various types of expert knowledge. An integrated knowledge-based system has been developed for mold design support. The results have been evaluated by design and manufacturing of molds for cellular phones, and have shown substantial reduction of lead time for mold production.     

机床故障诊断系统知识表示的研究

针对所研究的机床故障诊断专家系统，以故障树分析法为基础，采用面向对象的事件知识表示方法。并以面向对象编程技术给出了知识表示的示例。分析了这种知识表示方法的特点。实践证明，这种知识表示方法在故障诊断专家系统中是确实有效的，而且这种表示方法融合了多种传统知识表示方法的长处，是一种值得研究与应用的方法。     

CIM技术在塑性成型工程的应用

本文根据国外ＣＩＭ技术发展的概况，针对塑性成形工程的特点，提出了塑性成形工程中实施ＣＩＭＳ技术应用和研究的几个重要的方向，同时，从系统集成的角度，指出基于知识集成的智能制造系统应是ＣＩＭＳ进一步发展的重点，最后，对这类系统建模的基本技术与方法进行了讨论。     

Development of a Composite Knowledge Manipulation Tool: K-Expert

A goal of this study is to develop a Composite Knowledge Manipulation Tool (CKMT). Some of traditional medical activities are rely heavily on the oral transfer of knowledge, with the risk of losing important knowledge. Moreover, the activities differ according to the regions, traditions, experts’ experiences, etc. Therefore, it is necessary to develop an integrated and consistent knowledge manipulation tool. By using the tool, it will be possible to extract the tacit knowledge consistently, transform different types of knowledge into a composite knowledge base (KB), integrate disseminated and complex knowledge, and complement the lack of knowledge. For the reason above, I have developed the CKMT called as K-Expert and it has four advanced functionalities as follows. Firstly, it can extract/import logical rules from data mining (DM) with the minimum of effort. I expect that the function can complement the oral transfer of traditional knowledge. Secondly, it transforms the various types of logical rules into database (DB) tables after the syntax checking and/or transformation. In this situation, knowledge managers can refine, evaluate, and manage the huge-sized composite KB consistently with the support of the DB management systems (DBMS). Thirdly, it visualizes the transformed knowledge in the shape of decision tree (DT). With the function, the knowledge workers can evaluate the completeness of the KB and complement the lack of knowledge. Finally, it gives SQL-based backward chaining function to the knowledge users. It could reduce the inference time effectively since it is based on SQL query and searching not the sentence-by-sentence translation used in the traditional inference systems. The function will give the young researchers and their fellows in the field of knowledge management (KM) and expert systems (ES) more opportunities to follow up and validate their knowledge. Finally, I expect that the approach can present the advantages of mitigating knowledge loss and the burdens of knowledge transformation and complementation.     

A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers

The aim of this study is to identify and prioritize the solutions of Knowledge Management (KM) adoption in Supply Chain (SC) to overcome its barriers. It helps organizations to concentrate on high rank solutions and develop strategies to implement them on priority. This paper proposes a framework based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of KM adoption in SC and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and fuzzy TOPSIS method is used to obtain final ranking of the solutions of KM adoption in SC. The empirical case study analysis of an Indian hydraulic valve manufacturing organization is conducted to illustrate the use of the proposed framework for ranking the solutions of KM adoption in SC to overcome its barriers. This proposed framework provides a more accurate, effective and systematic decision support tool for stepwise implementation of the solutions of KM adoption in SC to increase its success rate.     

Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives.In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.     

Visualising a knowledge mapping of information systems investment evaluation

Information systems (IS) facilitate organisations to increase responsiveness and reduce the costs of their supply chain. This paper seeks to make a contribution through exploring and visualising knowledge mapping from the perspective of IS investment evaluation. The evaluation of IS is regarded as a challenging and complex process, which becomes even more difficult with the increased complexity of IS. The intricacy of IS evaluation, however, is due to numerous interrelated factors (e.g. costs, benefits and risks) that have human or organisational dimensions. With this in mind, there appears to be an increasing need to assess investment decision-making processes, to better understand the often far-reaching implications associated with technology adoption and interrelated knowledge components (KC). Through the identification and extrapolation of key learning issues from the literature and empirical findings, organisations can better improve their business processes and thereby their effectiveness and efficiency, while preventing others from making costly oversights that may not necessarily be only financial. In seeking to enlighten the often obscure evaluation of IS investments, this paper attempts to inductively emphasise the dissemination of knowledge and learning through the application of a fuzzy Expert System (ES) based knowledge mapping technique (i.e. Fuzzy Cognitive Map [FCM]). The rationale for exploring knowledge and IS investment evaluation is that a knowledge map will materialise for others to exploit during their specific technology evaluation. This is realised through conceptualising the explicit and tacit investment drivers. Among the several findings drawn from this research, the key resulting knowledge mapping through FCM demonstrated the complex, multifaceted and emergent behaviour of causal relationships within the knowledge area. The principal relationships and knowledge within IS investment evaluation are illustrated as being determined by a blend of managerial and user perspectives.