A Feature-Based Automatic Dimension Marking Method for In-Process Models

2014 ◽  
Vol 556-562 ◽  
pp. 6089-6093
Author(s):  
Li Shao ◽  
Shu Sheng Zhang ◽  
Chao Zhou ◽  
Xiao Liang Bai
Keyword(s):  
Process Model ◽  
Process Models ◽  
Feature Location ◽  
Process Data ◽  
Design Data ◽  
Experimental Section ◽  
Feature Based ◽  
Feature Dimension ◽  
Process Dimension ◽  
Manufacturing Features

To reduce the workload for marking the dimensions of in-process models, a method of dimension marking based on manufacturing features for in-process model is proposed. Firstly, the dimension information is extracted from model based definition (MBD) models; secondly, the feature dimension chains are constructed according to the feature location dimension and the process data, when the process data and design data are not coincided with each other; thirdly, the process dimension tolerances are calculated by using the increasing links and the decreasing links of the MBD. In experimental section, an example was given to illustrate the validity and effectiveness of the proposed method.

Research on the Algorithm of Technological Dimension Chain Based on 3D Process Models

2011 ◽  
Vol 58-60 ◽  
pp. 1421-1428
Author(s):  
Zhi Yong Chang ◽  
Jian Xin Yang ◽  
Neng Wan ◽  
Jie Zhao
Keyword(s):  
Process Parameters ◽  
Process Model ◽  
Three Dimensional ◽  
Process Models ◽  
Two Dimensional ◽  
Technological Design ◽  
Process Route ◽  
Process Dimension

Aiming at the wide application of technological design in three-dimensional CAD software, while the technological dimension chain’s calculation is completed in the two-dimensional process sketch still. A sort of method of calculating technological dimension chain was put forward, which is based on three-dimensional process model. Three-dimensional process model is created through the process of technological design by introducing the concept of three-dimensional process model, and then, the information of process dimension is extracted from the three-dimensional process model and a tree oriented process dimension structure is established. On the basis of the above, we can proceed with technological dimension chain’s integrated calculation and analysis, redistributing the process dimension and its corresponding allowance dimension and tolerance. It will offer more reasonable and reliable process parameters to the technologists in the design of process route, and also effectively solve the problems of the technological dimension chain’s calculation involving to CAPP system in the environment of three-dimensional CAD software.

scholarly journals Data-Driven Adaptive Observer for Fault Diagnosis

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Shen Yin ◽  
Xuebo Yang ◽  
Hamid Reza Karimi
Keyword(s):  
Fault Diagnosis ◽  
Process Model ◽  
Large Scale ◽  
Process Models ◽  
Physical Models ◽  
Adaptive Observer ◽  
Data Driven ◽  
Process Data ◽  
Tank System ◽  
Residual Generator

This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are directly identified from the process data without identification of complete process model. To deal with normal variations in the process, the parameters of residual generator are online updated by standard adaptive technique to achieve reliable fault detection performance. After a fault is successfully detected, the isolation scheme will be activated, in which each isolation observer serves as an indicator corresponding to occurrence of a particular type of fault in the process. The thresholds can be determined analytically or through estimating the probability density function of related variables. To illustrate the performance of proposed fault diagnosis approach, a laboratory-scale three-tank system is finally utilized. It shows that the proposed data-driven scheme is efficient to deal with applications, whose analytical process models are unavailable. Especially, for the large-scale plants, whose physical models are generally difficult to be established, the proposed approach may offer an effective alternative solution for process monitoring.

An Approach to Recognize Machining Features for In-Process Models by Using a Hybrid Graph and Rule-Based Method

2014 ◽  
Vol 607 ◽  
pp. 333-337 ◽  
Author(s):  
Li Shao ◽  
Xiao Liang Bai ◽  
Shu Sheng Zhang ◽  
Liang Li
Keyword(s):  
Process Model ◽  
Matrix Form ◽  
Process Models ◽  
Model Construction ◽  
Machining Features ◽  
Rule Based ◽  
Adjacency Graph ◽  
Experimental Section ◽  
Volumetric Features ◽  
Feature Template

A hybrid graph and rule-based method for recognizing machining features is proposed in this paper, which aims to get the machining feature in 3D in-process model construction system. Initially, the attributed adjacency graph (AAG) of the input MBD models is constructed and represented in matrix form. After that, by deleting the convex edges of the AAG, the concave sub-graphs are generated. For obtaining the volumetric features, their concave sub-graphs are matched with the feature template graphs in a pre-defined library; for those which can be generated by sweeping the edge loops, such as open pocket, closed pocket, through pocket and slot, their features are recognized by using rules. In experimental section, an example is given to illustrate the validity and effectiveness of the proposed method.

Politikvermittlung an der Schnittstelle von Unterhaltung und Information : Political communication at the interface of entertainment and information

SPIEL ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 121-145
Author(s):  
Larissa Leonhard ◽  
Anne Bartsch ◽  
Frank M. Schneider
Keyword(s):  
Information Processing ◽  
Political Participation ◽  
Knowledge Acquisition ◽  
Political Communication ◽  
Information Seeking ◽  
Process Model ◽  
Political Information ◽  
Process Models ◽  
Dual Process ◽  
Dual Process Model

This article presents an extended dual-process model of entertainment effects on political information processing and engagement. We suggest that entertainment consumption can either be driven by hedonic, escapist motivations that are associated with a superficial mode of information processing, or by eudaimonic, truth-seeking motivations that prompt more elaborate forms of information processing. This framework offers substantial extensions to existing dual-process models of entertainment by conceptualizing the effects of entertainment on active and reflective forms of information seeking, knowledge acquisition and political participation.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

Geometrical Modeling Method of Process Driven by Typical Process Model

2013 ◽  
Vol 770 ◽  
pp. 361-365
Author(s):  
Yu Peng Xin ◽  
Xi Tian Tian ◽  
Li Jiang Huang ◽  
Jun Hao Geng
Keyword(s):  
Process Model ◽  
Modeling Method ◽  
Process Models ◽  
Machining Process ◽  
Process Ontology ◽  
Geometrical Modeling ◽  
Mapping Rules ◽  
Model Mapping ◽  
Generate Process ◽  
Typical Process

In order to improve the efficiency of NC machining programming, and realize the rapid establishment of blank model or middle blank model, a geometrical modeling method of process driven by typical process model was put forward. This method is based on the typical process for the establishment of typical process model, to establish a mapping between modeling operation and machining process ontology, and format model mapping rules. In the process geometrical modeling of the high similarity parts, by calling the typical process model mapping rules, can generate process models automatically. A enterprise disc type parts typical process as an example is used to verify the proposed method.

scholarly journals Business processes exceptions in relation to operational performance

2019 ◽  
Vol 25 (5) ◽  
pp. 908-922 ◽  
Author(s):  
Remco Dijkman ◽  
Oktay Turetken ◽  
Geoffrey Robert van IJzendoorn ◽  
Meint de Vries
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Operational Performance ◽  
Normal Flow ◽  
Throughput Time ◽  
Content Type ◽  
Business Process Models ◽  
Practical Implications

Purpose Business process models describe the way of working in an organization. Typically, business process models distinguish between the normal flow of work and exceptions to that normal flow. However, they often present an idealized view. This means that unexpected exceptions – exceptions that are not modeled in the business process model – can also occur in practice. This has an effect on the efficiency of the organization, because information systems are not developed to handle unexpected exceptions. The purpose of this paper is to study the relation between the occurrence of exceptions and operational performance. Design/methodology/approach The paper does this by analyzing the execution logs of business processes from five organizations, classifying execution paths as normal or exceptional. Subsequently, it analyzes the differences between normal and exceptional paths. Findings The results show that exceptions are related to worse operational performance in terms of a longer throughput time and that unexpected exceptions relate to a stronger increase in throughput time than expected exceptions. Practical implications These findings lead to practical implications on policies that can be followed with respect to exceptions. Most importantly, unexpected exceptions should be avoided by incorporating them into the process – and thus transforming them into expected exceptions – as much as possible. Also, as not all exceptions lead to longer throughput times, continuous improvement should be employed to continuously monitor the occurrence of exceptions and make decisions on their desirability in the process. Originality/value While work exists on analyzing the occurrence of exceptions in business processes, especially in the context of process conformance analysis, to the best of the authors’ knowledge this is the first work that analyzes the possible consequences of such exceptions.

scholarly journals Pengujian Unit Plugin Pemberian Anotasi Efek Secara Semantik pada Proses Bisnis BPMN

2021 ◽  
Vol 6 (3) ◽  
pp. 170
Author(s):  
Hilman Nuril Hadi
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Unit Testing ◽  
Business Process Model ◽  
Testing Technique ◽  
Modeling Tools ◽  
Path Testing ◽  
Future Business

Business process model was created to make it easier for business process stakeholders to communicate and discuss the structure of the process more effectively and efficiently. Business process models can also be business artifacts and media that can be analyzed further to improve and maintain organizational competitiveness. To analyze business processes in a structured manner, the effect/results of the execution of business processes will be one of the important information. The effect/result of the execution of certain activities or a business process as a whole are useful for managing business processes, including for improvements related to future business processes. This effect annotation approach needs to be supported by business process modeling tools to assist business analysts in managing business processes properly. In previous research, the author has developed a plugin that supports business analysts to describe the effects semantically attached to activities in the Business Process Model and Notation (BPMN) business process model. In this paper, the author describes the unit testing process and its results on the plugin of semantic effect annotation that have been developed. Unit testing was carried out using the basic path testing technique and has obtained three test paths. The results of unit test for plugin are also described in this paper.

scholarly journals Improving the performance of process discovery algorithms by instance selection

2020 ◽  
Vol 17 (3) ◽  
pp. 927-958
Author(s):  
Mohammadreza Sani ◽  
Sebastiaan van Zelst ◽  
Aalst van der
Keyword(s):  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Instance Selection ◽  
Event Data ◽  
Process Discovery ◽  
Selection Strategies ◽  
Speed Up ◽  
The Right ◽  
Discovery Algorithms

Process discovery algorithms automatically discover process models based on event data that is captured during the execution of business processes. These algorithms tend to use all of the event data to discover a process model. When dealing with large event logs, it is no longer feasible using standard hardware in limited time. A straightforward approach to overcome this problem is to down-size the event data by means of sampling. However, little research has been conducted on selecting the right sample, given the available time and characteristics of event data. This paper evaluates various subset selection methods and evaluates their performance on real event data. The proposed methods have been implemented in both the ProM and the RapidProM platforms. Our experiments show that it is possible to considerably speed up discovery using instance selection strategies. Furthermore, results show that applying biased selection of the process instances compared to random sampling will result in simpler process models with higher quality.

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