Process Knowledge Reuse Research Articles

An effective process design intent inference method of process data via integrating deep learning and grammar parsing

With the constantly generation of process data in industries, process knowledge reuse and learning from process dataset has shown promising potential in machining process planning. However, existing methods cannot effectively extract different granularity process intents, and thus the process data cannot be effectively utilized. In this paper, an effective process design intent inference method of process data via integrating deep learning and grammar parsing is proposed. First, based on the projection of cutter location segments, an association approach between machining operations and machining features is proposed to extract the process intent of each machining operation. Then, a deep learning based working step process intent sequence decision-making model is proposed to estimate the probability distributions of alternative working step process intents at each time. Moreover, according to the working step process intent sequences of existing parts in an industry, the process knowledge And-Or graph (PK-AOG) is constructed by introducing the probabilistic grammar graph model. Finally, the optimal process intents of each working step are jointly obtained based on grammar parsing by taking the PK-AOG as a guide. In the experiments, the effectiveness of our approach is validated by developing a prototype system, and the results show that our approach is practical in process intents extraction.

Solution of Spatial Transformation Relationship of Similar Ruled Surfaces Based on Registration of Divided Regions

Since the geometric transformation relationship of similar surfaces with complex features, such as local deformation and curvature changes, is hard to be solved through global registration, this paper proposes a method for solving the spatial transformation relationship of similar ruled surfaces based on registration of divided regions. First, an adaptive region division algorithm is proposed to divide similar surfaces, and then, an improved registration algorithm is proposed by adding two constraints which are the curvature feature and differential geometric features of point clouds. Through this improved registration algorithm, the geometric transformation relationship of each sub-region can be solved, and then the spatial geometric transformation relationship of the overall similar surface can be established. Moreover, the improved registration algorithm can ensure that the differential geometric properties of corresponding points are similar after registration, which may provide a basis for mapping and reuse of process knowledge between corresponding points on similar surfaces. Finally, two similar ruled surface blades are taken as examples for simulation verification, the results show that the maximum registration error of each sub-region is 0.025 mm, which is within the allowable error range, and the registration speed of the proposed algorithm is better than the S-ICP algorithm. This proves that the method in this paper is feasible and effective.

Assembly process case matching based on a multilevel assembly ontology method

PurposeThe purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.Design/methodology/approachBy integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.FindingsBy fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.Originality/valueThe process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.

The design culture: actions and narratives between archives and exhibitions

The article is focused on the value of design archives as resources to be enhanced through exhibitions, and as heritage for innovation based on process of knowledge re-use, especially for creative industries. Starting from the background of the debate on the new dimension of the archive (especially the one focused on the relation between art and design practices and the archive), the article will focus on a specific context as the one of design archives which have been in recent years particularly vivid realities. Focusing on designer’s archive (in between the broader system of design documentation), and through a case study such as CSAC of University of Parma, we will examine how these archives are not merely repositories of drawings and how they can be connectors for creative industries, through exhibitions and other programs. In the second part of the article, we will focus on three exhibitions devoted to design which are expressions of a huge patrimony organized in structured archives, analysing different curatorial practices and narratives paradigms. In these cases, design exhibitions are ‘active’ representation of design archives.

Knowledge recommender system for complex product development using ontology and vector space model

Knowledge recommendation has become a trend to improve the efficiency of acquiring knowledge during product development. As such, coping with the challenge of constantly discovering new knowledge is critical for knowledge reuse. This article proposes a knowledge recommendation framework based on design tasks, to facilitate the capturing and sharing of knowledge in manufacturing firms. An ontology-based knowledge representation model is designed and developed to organize the knowledge resources and a vector space model-based knowledge recommendation model is built to hasten the knowledge reuse process. A case study demonstrates the effectiveness of the proposed method.

Process Knowledge Graph Construction Method for Process Reuse

Aiming at the problems of process knowledge reuse and sharing led by the difficulty of unified representation of complex and diverse process knowledge, a process knowledge graph construction method for process reuse is proposed. Firstly, to ensure the accuracy and universality of data schema for process knowledge, the basic schema of process knowledge graph is constructed based on step-nc. Secondly, to improve process knowledge graph basic schema, the process knowledge graph extensive schema is established through process knowledge analysis and process knowledge combination. Meanwhile, to construct the process knowledge graph schema, the existing rules of experience are represented by SWRL language. Moreover, to instantiate the process knowledge graph schema, the process cases are analyzed under the guidance of process knowledge graph schema and the similarity between process cases is computed by latent semantic analysis technology. And then, process cases are transformed into the structured process knowledge graph representation, and process knowledge graph data is obtained. Finally, the process knowledge graph construction application platform is developed to verify the feasibility of the proposed method.

A reliable process planning approach based on fuzzy comprehensive evaluation method incorporating historical machining data

The quality of process planning could directly affect product quality, machining efficiency and cost. In small batch production such as machining aircraft structural parts, human experience is dominant in the process planning of those parts with great variability. Inferior planning of the machining process directly leads to low efficiency and quality, which has serious impact on the lead time of aircraft structural parts. To address these problems, different from the existing process knowledge reuse method by estimating the geometric similarity, a more reliable process planning method based on fuzzy comprehensive evaluation via historical machining data is proposed in this article. As long as machining resources are determined, a feature-based historical machining data model can be built, and the similarities between new machining features and the features in the database are estimated accordingly. Machining strategy, which contains tool path strategy and machining parameters, can then be identified according to the evaluation results of the similar features based on entropy weight method. A prototype system is developed and successfully applied to the typical aircraft structural parts.

Deep learning-enabled intelligent process planning for digital twin manufacturing cell

The transition to intelligent manufacturing provides a fulcrum for the revolution of product lifecycle like design, manufacturing and maintenance, so does it for process planning. Specifically, digital twin manufacturing cell (DTMC) is regarded as a new means of and also a basic unit for implementing intelligent manufacturing. Incorporating process planning in DTMC could improve the integrity of DTMC and enhance the feasibility of process planning. Consequently, this paper proposes a deep learning-enabled framework for intelligent process planning towards DTMC. Firstly, a process knowledge reuse network (PKR-Net) that takes deep residual networks as base architecture is embedding into the framework, which could understand design intents expressed in a drawing or a 3D computer-aided design (CAD) model via its views and automatically retrieve relevant knowledge for the quick generation of theorical processes. Then, an evaluation twin is constructed to transform the theorical processes into practical operations and produce an optimal process plan. Finally, a test bed of the framework is constructed and the experimental results demonstrate the feasibility and effectiveness of the approach.

Semantic Representation of Design Process Knowledge Reuse

Semantic Representation of Design Process Knowledge Reuse

A machining feature definition approach by using two-times unsupervised clustering based on historical data for process knowledge reuse

Machining features have been deemed as an effective way to accumulate and reuse machining process knowledge. The research gap for machining feature based method is how to define machining features, as the geometric shapes and machining processes of the same kind of machining features are only similar but not seriously unique. In order to address the issue mentioned above, a machining feature definition approach based on historical data for process knowledge reuse via two-times unsupervised clustering is proposed in this paper. Machining feature definition is realized based on learning machining feature patterns using unsupervised clustering by taking advantage of historical data. The feasibility of the proposed approach is validated by some aircraft structural parts, which provides an important theoretical reference for process planning and process reuse.

Managing time-awareness in modularized processes

Managing temporal process constraints in a suitable way is crucial for long-running business processes in many application domains. However, proper support of time-aware processes is still missing in contemporary information systems. This paper tackles a particular challenge existing in this context, namely the handling of temporal constraints for modularized processes (i.e., processes comprising subprocesses), which shall enable both the reuse of process knowledge and the modular design of complex processes. In detail, this paper focuses on the representation and support of time-aware modularized processes in process-aware information systems. To this end, we present a sound and complete method to derive the duration restrictions of a time-aware (sub-)process in such a way that its temporal properties are completely specified. We then show how this characterization of a process can be utilized when reusing it as a subprocess within a modularized process. As a motivating example, we consider a compound process from healthcare. Altogether the proper handling of temporal constraints for modularized processes is crucial for the enhancement of time- and process-aware information systems.

Innovating by Combining: A Process Model

Innovation studies receive more and more attention recently. Recombining previous workable solutions to generate new solutions is considered to be a generally useful strategy to innovate. However, there are few studies aiming at developing operational process model for innovating by combining except for the model proposed by Majchrzak, et al. Majchrzak, et al used grounded theory to build a model of knowledge reuse process for innovation. But this model is not operational enough for industry people to use. We extend this model by (1) providing a theoretical foundation for it, (2) providing two search criteria, surface similarity and structural similarity for the scan step, and (3) providing a tool called insight matrix for the in-depth analysis step.

Research on FE Modeling Common Method and Integration System for Nuclear Power Valve

Because of the high security, shape complexity of valve cavity and the nonlinear of joint surface at sealing position, establishing the finite element model quickly and accurately that could meet engineering accuracy and calculation condition is the problem that need urgently solved. A new method on knowledge reuse process of finite element analysis among valve similar model is presented based on modular thought, which could effectively improve the simulation accuracy and efficiency. Evaluation index system would be constructed according to the characteristics of nuclear power valves in order to perfect the technical standard and the norm of nuclear power valve design in our country. And on these bases above, the integrated platform as practical engineering tools could be constructed, which integrates design, simulation, and optimization of nuclear power valves together supporting heterogeneous model transfer. It is expected to give theoretical development and practical application to improve the design ability and the product performance of nuclear power valves.

Building a knowledge map model situated in product design

In product design, the complication of knowledge presentation and the scattered distribution of knowledge resources make knowledge sharing and reuse difficult. As an important knowledge management tool, knowledge map provides the knowledge sharing platform of knowledge assets. This paper proposes a knowledge map model and its building approaches. We present the knowledge map based on knowledge reuse process and its support to product design, also build a framework of knowledge map system. And then we analyse the key techniques: knowledge indexing, knowledge operation on the knowledge map, and the implementation of the knowledge map. By XML description method and scalable vector graphics (SVG) format map, concept knowledge map and process knowledge map can be used to reduce the islands of knowledge. These methods and technologies are verified in the automotive interior design process.

Collaborative case-based reasoning for knowledge discovery of elders health assessment system.

The existing Elders Health Assessment (EHA) system based on single-case-library reasoning has low intelligence level, poor coordination, and limited capabilities of assessment decision support. To effectively support knowledge reuse of EHA system, this paper proposes collaborative case reasoning and applies it to the whole knowledge reuse process of EHA system. It proposes a multi-case library reasoning application framework of EHA knowledge reuse system, and studies key techniques such as case representation, case retrieval algorithm, case optimization and correction, and reuse etc.. In the aspect of case representation, XML-based multi-case representation for case organization and storage is applied to facilitate case retrieval and management. In the aspect of retrieval method, Knowledge-Guided Approach with Nearest-Neighbor is proposed. Given the complexity of EHA, Gray Relational Analysis with weighted Euclidean Distance is used to measure the similarity so as to improve case retrieval accuracy.

An Ontological and Semantic Approach for the Construction Risk Inferring and Application

Construction risk and safety management is a knowledge-intensive task. In addition to the construction risk knowledge itself, construction process knowledge is also important to the construction safety, since the different construction objects and processes selection often imply different potential risks may occur. However, most of construction risk management systems only focused on the construction risk knowledge itself. The process management and risk management usually are handled separately. In this paper, we explore to combine the construction process knowledge reuse methodology with the ontological modeling and semantic inferring approach to facilitate considering the risk issue during construction process reuse to directly improve the construction risk and safety management level. A meta ontology model is proposed to integrate risk knowledge domain with the risk monitor object domain. The meta model can be instantiated with the domain specific terms and relations and finally results into the specific domain model for specific application. The domain risk model for the deep foundation pit excavation using support systemcontiguous bored pile retaining wall system is shown as an illustrative example, in which the construction risk path knowledge is extracted via Fault Tree Analysis (FTA). In order to represent the construction risk knowledge in a computer-interpretable and semantically inferable way, the semantic web technique is used to represent the knowledge into OWL axioms and SWRL rules. Finally, based on the ontological model, the semantic inferring and application mechanism of construction risk knowledge are discussed and illustrated in the Protg platform. The proposed approach enables the construction risk knowledge to be presented in a computer-interpretable and semantically inferable way. The risk-oriented ontology model can be used as the basic structure of knowledge-based risk management system.

A Rapid Design System Integrated CBR with Variant Design

In the machine tool manufacturing industry, most of the design is based on previous experience and cases. However, some parts in the machine are complex and hard to modify for reuse. In this paper, CBR integrated with variant design is proposed to accelerate the knowledge reuse process. The experience and the cases are saved in the case base, and the similarity of the cases includes the parameters and structure. The revise process is using the proposed variant design to modify the case, and we mainly talking about the process on the construction of the functional relationship, which is the key steps of the variant design. Finally, we build a rapid design system for milling machine. The application indicate that the approach for complex parts design are useful and promising in intelligent design process in terms of shorter design time and more intelligent process.

Reusing knowledge based on Ontology and Organizational Model

The work presented in this paper is related to knowledge management during the design process of mechanical products. More exactly, we are concentrating on the knowledge reuse process. We propose a knowledge reuse system (KRS) based on two approaches. Namely, an organizational approach and a modeling user approach. Both are ontology-based models. Our system takes into account, the actors’ roles (by the organizational approach), their preferences (by the model user approach), and their collaboration throughout the product design process in order to help designers to get knowledge that is considered the most relevant in all the phases of the product design process.

Balancing codification and personalization for knowledge reuse: a Markov decision process approach

Purpose – This paper aims to provide a systematic framework for organizations to analyze their knowledge reuse processes, and balance codification and personalization within their knowledge strategy according to cost/benefit analysis. Design/methodology/approach – This paper divides knowledge reuse process into a sequence of five stages, and accordingly analyzes costs/benefits under codification and personalization strategies. Markov decision process, a mathematical framework for multi-stage decision-making, is employed to optimize a mixed strategy for knowledge reuse processes within an organization. Findings – Organizations need to consider factors such as the number of reusable knowledge items, reuse patterns, and intra-organizational interest alignment which are critical to determine their optimal mix between codification and personalization. Companies should determine a knowledge strategy based on their knowledge reuse contexts instead of following success cases blindly. Research limitations/implications – This paper presents an illustrative example to show how this framework might be applied by an organization. However, the validity and reliability of strategic decision-making also depends on the accuracy of the model's parameter values. Firms can adopt many methods as surveys, Delphi method, to determine the parameter values. Practical implications – The proposed framework offers an opportunity for firms to gain insights by setting the model's parameters to their own reuse contexts/characteristics and conducting what-if analysis. Originality/value – This paper proposes a formal framework for analyzing knowledge reuse processes and offers organizations guidelines about decision-making of knowledge strategies.

Construction of Design Process Ontology Database Based on Process Ontology

Based on product design process knowledge reuse, according to the characteristics of ontology knowledge representation, process ontology knowledge representation method is offered. The paper extracts the category of design process, defines and describes the attribute and relationship of these categories. Then, the design process ontology database based on process ontology is constructed. As a result, it supports to achieve the sharing and reusing of design process knowledge.