Requirement Analysis of an OWL Based Disassembly Planning Information Model

Bicheng Zhu, R. Utpal
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J Robotics Autom 2020, 4(1):131-142 Open Access | Page 132 | They can be considered as an abstraction of the reality. Graph theory has been used as a powerful tool to solve the problems of disassembly planning, and representation models like connection diagram and AND/OR graph are usually utilized in such methods. The characteristics and functions of a disassembly system are explicitly expressed in the graph, and different searching algorithms are applied to find all the feasible disassembly sequences according to the topological, geometrical and technical constraints. Different strategies are further applied to locate the optimal sequence with consideration of the plan effectiveness and cost-effectiveness. Several outstanding graph-based approaches are briefly discussed below. Penev, et al. [6] used AND/OR graph theory and methods of dynamic programming for the generation and evaluation of the feasible disassembly plans. A new economic model is introduced to determine the optimal disassembly depth. Zhang, et al. [7] developed a graph based heuristic approach for the generation of disassembly sequences from CAD system directly. They proposed a Component-Fastener Graph to analyze the product assembly relationship and a searching for cut-vertex and decomposition of the EOL product into several subassemblies is further applied on the graph to simplify the disassembly analyzing process. Murayma, et al. [8] described the disassembly sequence generation using the idea of information entropy and heuristics to replace components at maintenance stages. The advantage of this method is primarily in the reduction of searching time and searching places for disassembly sequences. The author also developed a software tool integrated with a CAD system and carried out an experiment for an electric drill using the tool. A graph-based information modelling system to represent the process for disassembly and recycle planning of consumer products was proposed by Kanai, et al. [9]. Four kinds of graph have been presented: (1) A configuration graph of sub-assemblies or fragments; (2) A connection graph between parts and materials; (3) A process graph of disassembly, shredding, and sorting activities; (4) A retrieval condition graph. Rules and procedures for transforming the models of these activities are uniformly formulated. A vacuum cleaner is used as an example to demonstrate the proposed graph-based method. Lambert [10] proposed a Linear Programming (LP) model, based again on the AND/OR graph, to the disassembly planning problems. The LP model tries to find the optimal disassembly sequence based on maximizing the total value of the retrieved parts/ subassembly and minimizing the total disassembly operation cost associated with them. Petri net-based approach: Besides the traditional graphbased disassembly analysis approach, Petri-Net (PN), as a graphical and mathematical tool, provides a uniform environment for modelling and analyzing both static and dynamic discrete events. They provide a very promising method for disassembly sequence generation. Zussman, et al. [11] proposed a complete and mathematically sound Disassembly Petri Net (DPN) approach to model the disassembly processes. In their work, the detailed construction and advantages of the proposed DPN have been discussed, and a DPN based searching algorithm has been Things (IoT) and Life Cycle Units (LCU), have already been discussed in the disassembly research community for ideas like future cloud-based remanufacturing [4] and semantic recovery information service [5]. Briefly, IoT provides a network to connect different physical objects, which allows them to be sensed and controlled remotely across existing network infrastructure, creating opportunities for more direct integrations of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit. LCU, on the other hand, is developed specifically for the product disassembly process. As mentioned before, in a disassembly factory, different products arrive continuously for disassembly, and individual decisions regarding optimal disassembly sequences have to be made for every product. It is difficult to predict any pre-defined disassembly process sequences a priori, so the detailed information on how to disassemble each arriving product is needed. LCU is proposed for decentralizing that information by integrating a physical device named Life Cycle Units (LCU) into every product. The LCU stores information needed for disassembly. Once enough disassembly information about a product is present, the optimal disassembly sequence can be generated based on the actual physical status of the EOL product. Combining the LCU and IoT technologies together, individualized EOL product information could be sensed and collected by LCU and transferred to the central Product Lifecycle Management (PLM) system through the IoT network. This could be used to tackle the problem of disassembly information bottleneck. In this reported work, we develop a Disassembly Information Model (DIM) that can be integrated into the future sustainable and smart manufacturing environment, for efficient disassembly planning activities. As the first part of this work, detailed requirements regarding the DIM are identified and analyzed in this paper, which looks into both of the disassembly domain aspect and information modelling aspect. An overview of the developed DIM is also briefly presented. A layered Information Model (IM) development methodology is proposed to address the reusability-usability trade-off problem. The developed DIM is further implemented into the Web Ontology Language (OWL), through which relevant information can be computationally analyzed and utilized.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36959/673/364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Disassembly, a process of separating the End of Life (EOL) product into discrete components for re-utilizing their associated residual values, is an important part for the sustainable manufacturing. This work focuses on the modeling of the disassembly planning related information, and develops a Disassembly Information Model (DIM) based on an extensive investigation of various informational aspects of the disassembly planning. In this paper, the requirement analysis for the development of the DIM has been carried out and two categories of the requirements relating to the disassembly domain aspect and the information model aspect are thoroughly discussed. Citation: Zhu B, Roy U (2020) Requirement Analysis of an OWL Based Disassembly Planning Information Model. J Robotics Autom 4(1):131142 Zhu and Roy. J Robotics Autom 2020, 4(1):131-142 Open Access | Page 132 | They can be considered as an abstraction of the reality. Graph theory has been used as a powerful tool to solve the problems of disassembly planning, and representation models like connection diagram and AND/OR graph are usually utilized in such methods. The characteristics and functions of a disassembly system are explicitly expressed in the graph, and different searching algorithms are applied to find all the feasible disassembly sequences according to the topological, geometrical and technical constraints. Different strategies are further applied to locate the optimal sequence with consideration of the plan effectiveness and cost-effectiveness. Several outstanding graph-based approaches are briefly discussed below. Penev, et al. [6] used AND/OR graph theory and methods of dynamic programming for the generation and evaluation of the feasible disassembly plans. A new economic model is introduced to determine the optimal disassembly depth. Zhang, et al. [7] developed a graph based heuristic approach for the generation of disassembly sequences from CAD system directly. They proposed a Component-Fastener Graph to analyze the product assembly relationship and a searching for cut-vertex and decomposition of the EOL product into several subassemblies is further applied on the graph to simplify the disassembly analyzing process. Murayma, et al. [8] described the disassembly sequence generation using the idea of information entropy and heuristics to replace components at maintenance stages. The advantage of this method is primarily in the reduction of searching time and searching places for disassembly sequences. The author also developed a software tool integrated with a CAD system and carried out an experiment for an electric drill using the tool. A graph-based information modelling system to represent the process for disassembly and recycle planning of consumer products was proposed by Kanai, et al. [9]. Four kinds of graph have been presented: (1) A configuration graph of sub-assemblies or fragments; (2) A connection graph between parts and materials; (3) A process graph of disassembly, shredding, and sorting activities; (4) A retrieval condition graph. Rules and procedures for transforming the models of these activities are uniformly formulated. A vacuum cleaner is used as an example to demonstrate the proposed graph-based method. Lambert [10] proposed a Linear Programming (LP) model, based again on the AND/OR graph, to the disassembly planning problems. The LP model tries to find the optimal disassembly sequence based on maximizing the total value of the retrieved parts/ subassembly and minimizing the total disassembly operation cost associated with them. Petri net-based approach: Besides the traditional graphbased disassembly analysis approach, Petri-Net (PN), as a graphical and mathematical tool, provides a uniform environment for modelling and analyzing both static and dynamic discrete events. They provide a very promising method for disassembly sequence generation. Zussman, et al. [11] proposed a complete and mathematically sound Disassembly Petri Net (DPN) approach to model the disassembly processes. In their work, the detailed construction and advantages of the proposed DPN have been discussed, and a DPN based searching algorithm has been Things (IoT) and Life Cycle Units (LCU), have already been discussed in the disassembly research community for ideas like future cloud-based remanufacturing [4] and semantic recovery information service [5]. Briefly, IoT provides a network to connect different physical objects, which allows them to be sensed and controlled remotely across existing network infrastructure, creating opportunities for more direct integrations of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit. LCU, on the other hand, is developed specifically for the product disassembly process. As mentioned before, in a disassembly factory, different products arrive continuously for disassembly, and individual decisions regarding optimal disassembly sequences have to be made for every product. It is difficult to predict any pre-defined disassembly process sequences a priori, so the detailed information on how to disassemble each arriving product is needed. LCU is proposed for decentralizing that information by integrating a physical device named Life Cycle Units (LCU) into every product. The LCU stores information needed for disassembly. Once enough disassembly information about a product is present, the optimal disassembly sequence can be generated based on the actual physical status of the EOL product. Combining the LCU and IoT technologies together, individualized EOL product information could be sensed and collected by LCU and transferred to the central Product Lifecycle Management (PLM) system through the IoT network. This could be used to tackle the problem of disassembly information bottleneck. In this reported work, we develop a Disassembly Information Model (DIM) that can be integrated into the future sustainable and smart manufacturing environment, for efficient disassembly planning activities. As the first part of this work, detailed requirements regarding the DIM are identified and analyzed in this paper, which looks into both of the disassembly domain aspect and information modelling aspect. An overview of the developed DIM is also briefly presented. A layered Information Model (IM) development methodology is proposed to address the reusability-usability trade-off problem. The developed DIM is further implemented into the Web Ontology Language (OWL), through which relevant information can be computationally analyzed and utilized.
基于OWL的拆卸规划信息模型需求分析
拆卸是将寿命终止(EOL)产品分离为离散部件以重新利用其相关残值的过程,是可持续制造的重要组成部分。本工作侧重于拆卸计划相关信息的建模,并在对拆卸计划的各个信息方面进行广泛调查的基础上开发了拆卸信息模型(DIM)。本文对DIM的开发进行了需求分析,深入讨论了与拆卸领域方面和信息模型方面有关的两类需求。引文:朱B,罗伊U(2020)基于OWL的拆卸规划信息模型的需求分析。机器人学学报4(1):131142朱和罗伊。J Robotics Autom 2020,4(1):131-142开放访问|第132页|它们可以被认为是对现实的抽象。图论已被用作解决拆卸计划问题的强大工具,在这些方法中通常使用连接图和and/OR图等表示模型。图中明确表示了拆卸系统的特征和功能,并根据拓扑、几何和技术约束,应用不同的搜索算法来找到所有可行的拆卸序列。考虑到计划的有效性和成本效益,进一步应用不同的策略来定位最优序列。下面简要讨论了几种杰出的基于图的方法。Penev等人[6]使用AND/OR图论和动态规划方法来生成和评估可行的拆卸计划。引入了一种新的经济模型来确定最佳拆卸深度。张等人[7]开发了一种基于图的启发式方法,用于直接从CAD系统生成拆卸序列。他们提出了一个组件-紧固件图来分析产品-装配关系,并在图上进一步应用了对切割顶点的搜索和EOL产品分解为几个子组件,以简化拆卸分析过程。Murayma等人[8]描述了使用信息熵和启发式思想在维护阶段替换组件的拆卸序列生成。这种方法的优点主要在于减少了反汇编序列的搜索时间和搜索位置。作者还开发了一个与CAD系统集成的软件工具,并用该工具对电钻进行了实验。Kanai等人提出了一种基于图形的信息建模系统,用于表示消费品的拆卸和回收计划过程。[9]。给出了四种图:(1)子组件或碎片的构型图;(2) 零件和材料之间的连接图;(3) 拆卸、切碎和分拣活动的流程图;(4) 检索条件图。统一制定了转换这些活动模式的规则和程序。以真空吸尘器为例说明了所提出的基于图的方法。Lambert[10]再次基于AND/OR图,提出了一种线性规划(LP)模型来解决拆卸规划问题。LP模型试图在最大化取回的零件/子组件的总价值和最小化与它们相关的总拆卸操作成本的基础上找到最优拆卸顺序。基于Petri网的方法:除了传统的基于图的拆卸分析方法外,Petri网(PN)作为一种图形和数学工具,为静态和动态离散事件的建模和分析提供了一个统一的环境。它们为反汇编序列的生成提供了一种非常有前途的方法。Zussman等人[11]提出了一种完整且数学上合理的拆卸Petri网(DPN)方法来对拆卸过程进行建模。在他们的工作中,已经讨论了所提出的DPN的详细结构和优势,并且基于DPN的搜索算法物联网和生命周期单元已经在拆解研究社区中进行了讨论,以获得未来基于云的再制造[4]和语义恢复信息服务[5]等想法。简言之,物联网提供了一个连接不同物理对象的网络,这使它们能够在现有的网络基础设施中被远程感知和控制,为将物理世界更直接地集成到基于计算机的系统中创造了机会,并提高了效率、准确性和经济效益。另一方面,LCU是专门为产品拆卸过程开发的。 如前所述,在拆卸工厂中,不同的产品不断到达进行拆卸,并且必须为每个产品做出关于最佳拆卸顺序的单独决定。很难先验地预测任何预定义的拆卸过程序列,因此需要关于如何拆卸每个到达的产品的详细信息。LCU被提议通过将名为生命周期单元(LCU)的物理设备集成到每个产品中来分散信息。LCU存储拆卸所需的信息。一旦存在足够的关于产品的拆卸信息,就可以基于EOL产品的实际物理状态生成最佳拆卸序列。将LCU和物联网技术结合在一起,LCU可以感知和收集个性化EOL产品信息,并通过物联网网络将其传输到中央产品生命周期管理(PLM)系统。这可以用来解决反汇编信息瓶颈的问题。在这项报告的工作中,我们开发了一个可集成到未来可持续和智能制造环境中的拆卸信息模型(DIM),以进行高效的拆卸规划活动。作为本工作的第一部分,本文从拆卸领域和信息建模两个方面对DIM的详细需求进行了识别和分析。还简要介绍了所开发的DIM的概况。提出了一种分层信息模型(IM)开发方法来解决可重用性和可用性的权衡问题。将开发的DIM进一步实现为Web本体语言(OWL),通过该语言可以对相关信息进行计算分析和利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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