M-Ontomat-Annotizer A tool for Semantic Annotation of Images and Videos for Multimedia Anal
M-Ontomat-Annotizer:
A tool for Semantic Annotation of Images and Videos
for Multimedia Analysis and Retrieval
Kosmas Petridis1, Kai Kuehn2, Siegfried Handschuh2, Stephan Bloehdorn2, Carsten Saathoff3, Yannis Avrithis4, Yiannis Kompatsiaris1 and Steffen Staab3
1 Informatics and Telematics Institute, GR-57001 Thermi-Thessaloniki, Greece, {kosmas, ikom}@iti.gr
2 University of Karlsruhe, Institute AIFB, D-76128 Karlsruhe, Germany, {sha, sbl}@aifb.uni-karlsruhe.de
3 University of Koblenz-Landau, Institute for Computer Science, D-56016 Koblenz, Germany, {saathoff, staab}@uni-koblenz.de
4 National Technical University of Athens, School of Electrical and Computer Engineering, GR-15773 Zographou, Athens, Greece, iavr@image.ntua.gr
ABSTRACT
Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low-level descriptors, such as dominant color, or they have focused on the content dimension and corresponding annotations, such as person or vehicle. In this paper, we present a software environment to bridge between the two directions. M-OntoMat-Annotizer allows for linking low-level MPEG-7 visual descriptions to conventional Semantic Web ontologies and annotations. We use M-OntoMat-Annotizer in order to construct ontologies that include prototypical instances of high-level domain concepts together with a formal specification of corresponding visual descriptors. Thus, we formalize the interrelationship of high and low-level multimedia concept descriptions allowing for new kinds of multimedia content analysis.
Keywords
Multimedia Ontologies, Semantic Annotation, Semantic Multimedia Analysis
1. INTRODUCTION
Although today new multimedia standards, such as MPEG-7 [1], provide important functionalities for manipulation and transmission of objects and associated metadata, the extraction of semantic descriptions and annotation of the content with the corresponding metadata is out of the scope of these standards and is still left to the content manager. The consequent performance limitations have resulted towards an inclination to integrate semantics with audiovisual features into a unified framework, thus moving from low-level to high-level features allowing them to benefit from each other. This is exactly one of the main objectives of aceMedia IST FP6 project [2]; to use ontologies and Semantic Web technologies in order to achieve a knowledge-based semantic analysis and annotation of multimedia content. This includes appropriate existing languages extension to include multimedia descriptors, new knowledge-based content processing tools and reasoning with multimedia features. 2. KNOWLEDGE INFRASTRUCTURE
FOR ANALYSIS
MPEG-7 provides various color, texture, shape and motion standardized descriptors that extract visual, low-level, non-semantic information from images and videos and use it to create structural and detailed descriptions of audio-visual information. For example, the dominant color descriptor specifies among others, the number and value of dominant colors that are present in a region of interest and the percentage of pixels that each associated color value has. In order to handle the so called semantic gap in multimedia content interpretation, aceMedia proposed and implemented a comprehensive ontology infrastructure and a tool for the multimedia annotation of domain ontologies [3]. In this way, an a-priori knowledge base is formed and used as a basis for its further exploitation within semantic multimedia analysis, assisting the detection of high-level objects and events in multimedia content.
Structure and semantics in the developed multimedia knowledge structure have been carefully modelled to be largely consistent with the existing MPEG-7 standard. A Visual Descriptor Ontology(VDO) was developed, containing the expression of visual descriptors in RDFS, tightly coupled with the specification of the MPEG-7 Visual Part [4]. The necessary part of the MPEG-
7 Multimedia Description Scheme (MDS) [5] was modelled in the Multimedia Structure Ontology (MSO). Both ontologies enable an integrated representation of multimedia information in domain ontologies, as well as reasoning with such information. Spatial and temporal relations were also defined on a core upper ontology, in order to support visual information and harmonize and align multimedia and domain ontologies. In our framework, we have used and extended the DOLCE [6] core ontology. Using this infrastructure, domain ontologies for aceMedia showcases were constructed for selected personal and commercial domains. Concept definitions in these ontologies are enhanced with multimedia descriptors and spatiotemporal relations to enable the identification of objects and event in raw content, and subsequent automatic annotation.
3. THE M-ONTOMAT-ANNOTIZER TOOL While using and referencing the described knowledge representation infrastructure, the CREAM (CREAting Metadata
for the Semantic Web) framework and its reference implementation, OntoMat-Annotizer [7] were extended, in order to allow low-level multimedia feature annotation in a user-friendly way. The implemented framework is called M-OntoMat-Annotizer (M stands for Multimedia). For this reason, the Visual Descriptor Extraction Tool (VDE) tool was developed as a plug-in to OntoMat-Annotizer and is the core component for extending its capabilities and supporting the initialization and linking of RDF(S) domain ontologies with low-level multimedia features. The VDE plug-in manages the overall low-level feature extraction and linking process by communicating with the other
components.
Figure 1. The M-OntoMat-Annotizer user interface The VDE Visual Editor and Media Viewer presents a graphical interface for loading and processing of visual content (images and videos), visual feature extraction and linking with domain ontology concepts. The interface, as shown in Figure 1, seamlessly integrates with the common OntoMat-Annotizer interfaces. Usually, the user needs to extract the features (visual descriptors included in the VDO) of a specific object inside the image/frame. In order to achieve this, M-OntoMat-Annotizer lets the user draw a region of interest in the image/frame and apply the multimedia descriptors extraction procedure only to the specific selected region. By selecting a specific concept or instance in M-OntoMat-Annotizer’s ontology browser and selecting a region of interest the user can extract and link appropriate visual descriptors with corresponding domain concepts. In our framework, we propose to enrich the knowledge base with instances of domain concepts that serve as prototypes for these concepts.
Triggered by the users extraction command, M-OntoMat-Annotizer extracts the requested MPEG-7 Descriptors, through calls to a Feature Extraction Toolbox developed inside aceMedia that saves the extracted MPEG-7 Descriptors in XML format. M-OntoMat-Annotizer supports the transformation of the extracted XML multimedia resources into instances of the visual descriptors defined in the VDO, by means of an XSL transformation specification that creates a corresponding descriptor instance for each extraction, which is handed to the knowledge base on the annotation server. Then, M-OntoMat-Annotizer automatically links the newly created visual descriptor instance with the selected domain concept prototype instance on the annotation server. These prototype instances are not only instances of the domain concept in question but are also stated to be instances of a
separate Prototype concept. The created statements are added to the knowledge base and can be retrieved in a flexible way during analysis. The necessary conceptualizations can be seen as extensions to the VDO in a separate Visual Annotation Ontology (VDO-EXT ) that link to the core ontology and are implemented in RDF.
All the prototype instances can be saved in an RDFS file. M-OntoMat-Annotizer saves the domain concept prototype instances together with the corresponding extracted descriptors, separately from the ontology file, thus leaving the original domain ontology unmodified. This extracted knowledge is playing a central role in automatic semantic analysis, through tools currently being developed in aceMedia that automatically analyse content, generate metadata and annotation, and support intelligent content search and retrieval services. Despite the early stage in these developments and the limited domains handled so far, this approach has given promising results in the direction of handling the semantic gap in multimedia content interpretation.
M-OntoMat-Annotizer is already evaluated and used inside aceMedia, supporting the multimedia annotation of domain ontologies. Apart from that, the tool is publicly available as free software through the aceMedia web site.
4. ACKNOWLEDGMENTS
This research was partially supported by the European Commission under contract FP6-001765 aceMedia. The expressed content is the view of the authors but not necessarily the view of the aceMedia project as a whole.
5. REFERENCES
[1] S.-F. Chang, T. Sikora, and A. Puri. Overview of the MPEG-7 standard. IEEE Trans. On Circuits and Systems for Video Technology , 11(6):688–695, June 2001. [2] The aceMedia project : https://www.wendangku.net/doc/c93088666.html,/
[3] S. Bloehdorn, K. Petridis, C. Saathoff, N. Simou, V.
Tzouvaras, Y. Avrithis, S. Handschuh, I. Kompatsiaris, S. Staab and M.G. Strintzis: “Semantic Annotation of Images and Videos for Multimedia Analysis”, 2nd European
Semantic Web Conference (ESWC 2005), Heraklion, Greece, May 2005. [4] ISO/IEC 15938-3 FCD Information Technology -
Multimedia Content Description Interface - Part 3: Visual, March 2001, Singapore. [5] ISO/IEC 15938-5 FCD Information Technology -
Multimedia Content Description Interface - Part 5:
Multimedia Description Scemes, March 2001, Singapore. [6] A. Gangemi, N. Guarino, C. Masolo, A. Oltramari, and L.
Schneider. Sweetening Ontologies with DOLCE. In Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web, Proceedings of the 13th International Conference on Knowledge Acquisition, Modeling and Management, EKAW. [7] S. Handschuh and Steffen Staab, CREAM – CREAting
Metadata for the Semantic Web. Computer Networks, 42(5): 579-598, Elsevier 2003. Tool at:
https://www.wendangku.net/doc/c93088666.html,/ontomat
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高中英语选修 6 Unit 1 A SHORT HISTORY OF WESTERN PAINTING Art is influenced by the customs and faith of a people. Styles in Western art have changed many times. As there are so many different styles of Western art, it would be impossible to describe all of them in such a short text. Consequently, this text will describe only the most important ones. Starting from the sixth century AD. The Middle Ages(5th to the 15th century AD) During the Middle Ages, the main aim of painters was to represent religious themes. A conventional artistof this period was not interested in showing nature and people as they really were. A typical picture at this time was full of religious symbols, which created a feeling of respect and love for God. But it was evident that ideas were changing in the 13th century when painters like Giotto di Bondone began to paint religious scenes in a more realistic way. The Renaissance(15th to 16th century) During the Renaissance, new ideas and values gradually replaced those held in the Middle Ages. People began to concentrate less on
高效的刀具管理软件解决方案ToolExpert
高效的刀具管理软件解决方案ToolExpert 现代的制造车间以数控机床为主，配置各种CAD/CAM、PDM和ERP系统，由于各系统之间相互独立，导致数据无法交换，形成信息孤岛，数据需要重复输入现象严重，信息沟通多通过纸质文件进行，效率低下，而且制造文件的版本控制难以实现。据统计，制造车间NC机床的利用率只有30%。如果能通过一个数据平台，把制造相关的各种信息统一起来，数据能够无缝地进行交换，数控设备的利用率可以提高到70%～80%。 一、概述 现代的制造车间以数控机床为主，配置各种CAD/CAM、PDM和ERP系统，由于各系统之间相互独立，导致数据无法交换，形成信息孤岛，数据需要重复输入现象严重，信息沟通多通过纸质文件进行，效率低下，而且制造文件的版本控制难以实现。据统计，制造车间NC机床的利用率只有30%。如果能通过一个数据平台，把制造相关的各种信息统一起来，数据能够无缝地进行交换，数控设备的利用率可以提高到70%～80%。 针对以上问题，由Spring公司开发的数控刀具管理系统ToolExpert拥有一套成熟的解决方案。例如，用户企业可能拥有至少5台数控加工中心，在机械加工过程中存在下列问题：车间操作员将20%时间花在了切削刀具上;16%的生产计划因为缺少合适的刀具而停止;40%~80%的管理时间浪费在无效的刀具搜索;30%~60%的刀具库存没有被有效地管理等。而在生产车间，一切环节都围绕着机械加工流程展开，如何实现与机械加工各环节的信息化自动管理，成为缩短加工工时与提高生产能力的关键。ToolExpert作为一个数据平台，集成车间现有系统，从工艺编程开始，涉及了整个生产流程，包括计划排产、刀具库房管理、对刀仪数据接口、机床程序传输与监控、机床卸载刀具、刀具报废或修磨处理、刀具消耗统计以及刀具采购与订单接收管理。该系统采用C/S结构，客户端只需一次安装，后期的更新与维护在server端完成，维护简单方便。在sever安装有核心数据库，用于管理生产相关数据。 在数控车间内，通过基础核心数据库，对刀具相关部件、量具、夹具和程序等信息进行管理，集成CAD/CAM、PDM和ERP等系统，数据通过ToolExpert平台进行无缝传输，共享信息，提高及时性，避免了重复数据输入。ToolExpert负责管理以刀具为核心的整个生产过程，包括工艺编程、刀具查找、库房管理(刀具、夹具和量具)、理论装配与物理装配、计划排产、车间备刀、上传/卸载程序、刀具消耗分类统计、刀具使用预测以及采购申请与接收订单。 ToolExpert的设计理念是帮助用户实现生产工艺和生产线的全面自动化管理。优化工艺，监控和管理数字化车间的所有活动，基本功能模块包括：工艺;车间准备;CNC机床准备;库存管理/分析。ToolExpert负责管理所有与刀具相关的工作流程，ToolExpert的功能模块如图1所示。
高效的刀具管理软件解决方案ToolExpert
高效的刀具管理软件解决方案ToolExpert 现代的制造车间以数控机床为主，配置各种CAD/CAM、PDM和ERP系统，由于各系统之间相互独立，导致数据无法交换，形成信息孤岛，数据需要重复输入现象严重，信息沟通多通过纸质文件进行，效率低下，而且制造文件的版本控制难以实现。据统计，制造车间NC机床的利用率只有30%。如果能通过一个数据平台，把制造相关的各种信息统一起来，数据能够无缝地进行交换，数控设备的利用率可以提高到70%～80%。 一、概述 现代的制造车间以数控机床为主，配置各种CAD/CAM、PDM和ERP系统，由于各系统之间相互独立，导致数据无法交换，形成信息孤岛，数据需要重复输入现象严重，信息沟通多通过纸质文件进行，效率低下，而且制造文件的版本控制难以实现。据统计，制造车间NC机床的利用率只有30%。如果能通过一个数据平台，把制造相关的各种信息统一起来，数据能够无缝地进行交换，数控设备的利用率可以提高到70%～80%。 针对以上问题，由Spring公司开发的数控刀具管理系统ToolExpert拥有一套成熟的解决方案。例如，用户企业可能拥有至少5台数控加工中心，在机械加工过程中存在下列问题：车间操作员将20%时间花在了切削刀具上;16%的生产计划因为缺少合适的刀具而停止;40%~80%的管理时间浪费在无效的刀具搜索;30% ~60%的刀具库存没有被有效地管理等。而在生产车间，一切环节都围绕着机械加工流程展开，如何实现与机械加工各环节的信息化自动管理，成为缩短加工工时与提高生产能力的关键。ToolExpert作为一个数据平台，集成车间现有系统，从工艺编程开始，涉及了整个生产流程，包括计划排产、刀具库房管理、对刀仪数据接口、机床程序传输与监控、机床卸载刀具、刀具报废或修磨处理、刀具消耗统计以及刀具采购与订单接收管理。该系统采用C/S结构，客户端只需一次安装，后期的更新与维护在server端完成，维护简单方便。在sever安装有核心数据库，用于管理生产相关数据。 在数控车间内，通过基础核心数据库，对刀具相关部件、量具、夹具和程序等信息进行管理，集成C AD/CAM、PDM和ERP等系统，数据通过ToolExpert平台进行无缝传输，共享信息，提高及时性，避免了重复数据输入。ToolExpert负责管理以刀具为核心的整个生产过程，包括工艺编程、刀具查找、库房管理(刀具、夹具和量具)、理论装配与物理装配、计划排产、车间备刀、上传/卸载程序、刀具消耗分类统计、刀具使用预测以及采购申请与接收订单。 ToolExpert的设计理念是帮助用户实现生产工艺和生产线的全面自动化管理。优化工艺，监控和管理数字化车间的所有活动，基本功能模块包括：工艺;车间准备;CNC机床准备;库存管理/分析。ToolExpert 负责管理所有与刀具相关的工作流程，ToolExpert的功能模块如图1所示。
刀具管理系统的设计
机械工程师 MECHANICAL ENGINEER 2017年第12期网址：https://www.wendangku.net/doc/c93088666.html, 电邮：hrbengineer@https://www.wendangku.net/doc/c93088666.html, 刀具管理系统的设计 周洪燕，宿文玲，于海宏 （哈尔滨量具刃具集团有限责任公司， 哈尔滨150040）摘要：介绍了一套刀具管理系统，具有完善的刀具数据库管理功能， 能够灵活、高效地对不同生产厂家、不同类型的刀具进行库房管理，具有丰富的库存统计功能，可以满足用户对刀具管理的各种需求， 显著地提高机床的利用率，提高智能化管理水平。关键词：刀具；管理；智能化中图分类号：TP 311.52 文献标志码：A 文章编号：1002-2333（2017）12-0126-04Design of Tool Manager System ZHOU Hongyan ，杂哉Wenling, YU Haihong (Harbin Measuring &Cutting Tool Group Co.,Ltd.,Harbin 150040,China) Abstract 院This paper introduces a kind of tool manager system.It has perfect tool database manage function.It can manage different type of tools from different manufacturers.It has stock statistics function.It can satisfy user's any requirements for Tool manage,improve use ratio of machine and intelligent manage level. Keywords:tool;manager;intelligent 0引言 随着现代工业的发展，人工成本的急剧增加，精细化管理越来越引起人们的重视。 据统计，在众多的制造企业的生产过程中，间接的刀具费用占制造成本的30%。16%的计划作业停止是由于缺乏刀具造成的，30%~60%的刀具库存不在控制之中，20%的机械师时间花在查找刀具上，40%~80%的监督人员时间花费在寻找合适刀具上。由此可以看出，刀具管理在现代加工企业的生产现场管理工作中所占的比重非常大。刀具管理部分成了制约企业加工能力的瓶颈，那么刀具管理系统的开发势在必然。 近年来,刀具管理软件已经越来越引起众多大企业的重视,许多大企业也相继开发了自己的刀具管理软件,主要有英国CTMS 公司、 美国Cincinnati Milacron 公司、德国的Zoller 公司、瑞典的Sandvik 公司。国外的刀具管理软件功能都很完善，而且各有其优势，但是价格高昂，难以被大多数企业接受。目前，国内刀具管理系统的研究起步比较晚，现有的刀具管理软件产品，绝大多数由企业和科研院所根据企业的实际需求编制，主要目的是实现刀具信息的计算机管理，功能单一，大部分只是着眼于刀具管理系统的某一方面，主要解决刀具的库存管理以及借入、借出等简单的动态管理。 Kelch 公司是哈量的全资子公司，主要生产两大类产 品：刀柄和刀调仪，刀柄是用来装卡刀具的，刀调仪是用来测量刀具参数的， 应该说Kelch 公司的产品和刀具具有完全的相关性。在销售刀柄和刀调仪的过程中，客户也提出了购买刀具管理软件的需求，甚至于将订单和刀具管 理软件进行绑定，因此，开发具有我公司自主知识产权的刀具管理软件也是我公司的重要发展战略。 此套刀具管理系统是一款根据我公司对刀具管理的实际需求自主开发的专业的刀具管理系统，用智能的管 理系统来取代传统的落后的人工管理方式，显著提高刀具的管理水平。本系统着力于刀具的库存管理、刀具的2D/3D 模型管理、造型管理、加工方案制定等功能， 集合各家刀具管理软件的优点，其软件的起点是国际先进水平。此刀具管理软件系统发布版本目前已经完成，是一套比较成熟的刀具管理软件，对刀具的使用、存储进行管理，能够满足生产和使用厂家及经销商目前的迫切需求，打通目前企业中刀具管理制约加工能力的瓶颈，降低刀具管理成本及人工成本，大大增强企业的核心竞争力。1 刀具管理系统的主要功能模块 VS2012是微软公司推出的开发环境。是目前最流行 的Windows 应用程序开发环境。C#是微软为.NET Framework 量身订做的程序语言，C#拥有C/C++的强大功 能以及Visual Basic 简易使用的特性，并且面向对象的设计思想也是最强大的。是目前可视化和面向对象最强大的开发工具。 本软件采用VS2012作为开发平台，C#作为开发语言，Access 作为数据库开发工具，EDrawing2008插件作为TooIM 刀具管理系统工具管理制造管理 基础数据辅助功能工具管刀具管加工方使用记库存管用户管设备管供 应商管仓库管数据库联组件导打印输基金项目：国家重大科技专项 （2015ZX04005-008）126
英语选修六课文翻译第五单元word版本
英语选修六课文翻译 第五单元
英语选修六课文翻译第五单元 reading An exciting job I have the greatest job in the world. travel to unusual places and work alongside people from all over the world sometimes working outdoors sometimes in an office sometimes using scientific equipment and sometimes meeting local people and tourists I am never bored although my job is occasionally dangerous I don't mind because danger excites me and makes me feel alive However the most important thing about my job is that I heIp protect ordinary people from one of the most powerful forces on earth-the volcano. I was appointed as a volcanologist working for the Hawaiian Volcano Observatory (HVO) twenty years ago My job is collecting information for a database about Mount KiLauea which is one of the most active volcanoes in Hawaii Having collected and evaluated the information I help oyher scientists to predict where lava from the path of the lava can be warned to leave their houses Unfortunately we cannot move their homes out of the way and many houses have been covered with lava or burned to the ground. When boiling rock erupts from a volcano and crashes back to earth, it causes less damage than you might imagine. This is because no one lives near the top of Mount Kilauea, where the rocks fall. The lava that flows slowly like a wave down the mountain causes far more damage because it buries everything in its path under the molten rock. However, the eruption itself is really exciting to watch and I shall never forget my first sight of one. It was in the second week after I arrived in Hawaii. Having worked hard all day, I went to bed early. I was fast asleep when suddenly my bed began shaking and I heard a strange sound, like a railway train passing my window. Having experienced quite a few earthquakes in Hawaii already, I didn't take much notice. I was about to go back to sleep when suddenly my bedroom became as bright as day. I ran out of the house into the back garden where I could see Mount Kilauea in the distance. There had been an eruption from the side of the mountain and red hot lava was fountaining hundreds of metres into the air. It was an absolutely fantastic sight. The day after this eruption I was lucky enough to have a much closer look at it. Two other scientists and I were driven up the mountain and dropped as close as possible to the crater that had been formed duing the eruption. Having earlier collected special clothes from the observatory, we put them on before we went any closer. All three of us looked like spacemen. We had white protective suits that covered our whole body, helmets,big boots and special gloves. It was not easy to walk in these suits, but we slowly made our way to the edge of the crater and looked down into the red, boiling centre. The other two climbed down into the crater to collect some lava for later study, but this being my first experience, I stayed at the top and watched them.
刀具管理软件国内外现状
刀具销售管理软件国内外现状 据统计，在众多的制造业企业的生产过程中，间接的刀具费用占制造成本的30%。 而山特维克官方数据也很好地验证了这一点： 16%的计划作业停止是由于缺乏刀具造成的。 30%-60%的刀具库存不在控制之中。 20%的机械师时间花在查找刀具上。 40%-80%的监督人员时间花费在寻求刀具上。 由此可以看出，刀具在现代加工企业中所占的比重非常大，而目前的管理现状却使得刀具部分成了企业的加工能力瓶颈，限制了企业的核心竟争力。国内外很多研究者也早已注意到这个问题，为此撰写了大量的论文并开发了一些相应的刀具管理系统软件。尤其是最近几年来，刀具管理系统技术得到了长足的发展. 国外现有的刀具管理软件： 在国外，已经出现了不少商用的刀具管理软件，其中较具代表性的有： (1) 英国CTMS公司的计算机用刀具管理系统(CYMS) 它由一系统软件模块组成，可配置16个终端，分别设置在刀具房、刀具预调间、计量室和供应科室等处，各终端直接与中心数据库联网，整个系统的作用可以概括
为：改善刀具的发放时间及控制发放在外的刀具数量;不断更新刀具房的库存信息，直接用刀具预调数据以调定刀具;提供刀具购置信息;提供刀具用途分析报告。 (2) 美国Cincinnati Milacron 公司的刀具管理系统软件包括以下五个方面的职能： 为刀具库准备刀具;给各机床分派刀具;刀具的调度与搬运;刀具检测;刀具的信息处理。 (3) 德国的Delkel开发的Tool Manager 计算机辅助刀具管理系统： 适合于加工单元、柔性制造系统甚至整个部门的刀具监视、跟踪管理。其软件功能包括：刀具的储备;刀架配备的优化;刀具装配安排;各零件对刀具的需求;刀具寿命规划。 (4) 瑞典的Sandvik公司的成套商用刀具管理软件Coratas： 可使刀具管理实现自动化。该系统能监控刀具从有效地点进入刀具库，直到机加工车间机床上的全部去街过程。它能保证在开始一批新工件的加工时，预先对刀具作合理的准备，并对刀具的状态和工况进行监测。此系统能发现刀具的临界状态和确定刀具库存量的合理性，大大提高了生产的柔性和可靠性以及设备的利用率。该系统可在各加工阶段优化与刀具管理组织有关的各种因素，进而缩短准备、结束时间，减少车间刀具存放量，提高刀具的使用寿命。 国内现有的刀具管理软件: 目前，国内现有的刀具管理软件产品，绝大多数软件由企业和科研院所根据企业的实际需求编制，主要目的是实现刀具信息的计算机管理，功能单一，主要解决刀具的库存管理以及借入、借出等简单的动态管理。