机床产品制造系统能效的最优控制

本文结合机床产品制造系统的能量流特性,研究机床产品制造系统能效的最优控制.首先,利用无线传感器网络,构建制造系统能效感知网络,并设计了网络能量高效的通信协议,实时获取制造系统的能效数据.进而,利用能效感知数据,分别从单机设备局部优化与综合资源全局优化两方面,设计能效优化控制算法.根据单机设备任意两工步间空载能耗特性,给出单机设备空载能效最优控制模型.同时,建立以缩短生产周期、减少机器空转时间、提高产品合格率为优化目标的综合生产资源能效多目标优化方案.考虑到所论综合资源能效优化问题是离散组合优化问题,本文提出了文化基因支配排序粒子群算法进行求解,并采用层次分析(analysis hierarchy process,AHP)决策方法从Pareto解集中选取最优综合能效的优化策略.最后,利用实例与仿真相结合的方法,验证了文中所提方法的有效性.     

Development of an Internet-enabled interactive fixture design system

Fixture design is a complex and an intuitive process. An efficient fixture design system is essential to cut costs and reduce the product lead-time. In today's manufacturing landscape, various computer-aided systems exist to aid the various stages of manufacturing. A fixture design system should be able to transfer information with the various other systems to bring about a seamless product design and manufacturing environment. A fixture design system should also be portable on different operating platforms. This paper addresses the development of an Internet-enabled interactive fixture design system. The Internet and the use of XML as a file format provide a means for the transfer of information and knowledge between the various computer-aided manufacturing systems. The system has been implemented using Java and is based on a three-tier Thin Client-Fat Server architecture. This ensures the platform independent performance of the system. A locating scheme independent interactive fixture design method has also been developed in this work for detailed fixture design.     

Combinatorial scheme for management of life cycle: Example for concrete macrotechnology

The paper describes a combinatorial scheme for the analysis and synthesis of product life cycle on the basis of a typical compressed structure: design of materials and manufacturing process. In addition, the following problems are studied: system refinement, series-parallel production process, and multistage design (design of product trajectories). Hierarchical combinatorial morphological approach is proposed. The solving process is based on ordinal expert knowledge. The following phases are examined: design of a basic system morphology, generation of local design alternatives, knowledge acquisition as ordinal estimates for local design alternatives and their compatibility, and synthesis of the best compositions.A realistic numerical example for concrete-macrotechnology (composing of concrete from constituents and selection of manufacturing alternatives) illustrates the approach.     

Supervisory control of a rapid thermal multiprocessor

An application of supervisory control theory to a piece of semiconductor manufacturing equipment is presented. The approach allows the flexible design and reliable update of processing recipes to accommodate frequently changing manufacturing requirements. An input-output interpretation of supervisory control theory is given. This interpretation leads to a generic implementation scheme for manufacturing systems. A synthesis fixpoint algorithm implementation using binary decision diagrams enables the design of supervisors of realistic size. A sample synthesis for an oxide growth recipe is performed on a state space of the order of 10⁶ states. The actual implementation of the logic sequencing control software for the application under investigation is described     

Customer-driven product design and evaluation method for collaborative design environments

Product concept generation and evaluation in a product development environment has been identified as the two major activities needed for obtaining an optimal design scheme. Product conceptual design is of critical importance in design through customer involvement for the systematic and simultaneous consideration on the impact of design decisions on manufacturing and assembly leads to repeated and excessive changes in design and processes. This paper introduces a novel knowledge support approach for the organization and ranking of design feature knowledge towards an integrated product model that incorporates a feature-based representation scheme targeted to evaluate the impact of design on subsequent activities in the conceptual design phase, taking into account the presence of design information and user preferences. An uncertain linguistic multi-attribute decision-making evaluation model is proposed and discussed for obtaining an optimal design scheme during the evaluation and selection of product design alternatives in conceptual design. The focus of this paper is on the development of a knowledge-intensive support design scheme and a comprehensive systematic fuzzy evaluation methodology for product conceptual design generation, evaluation, and selection. A case study and the corresponding scenario of knowledge support for design alternatives generation, evaluation and selection are provided for illustration.     

Applications of group technology in distributed manufacturing

This paper discusses the systematic use of group technology (GT) to support important activities of distributed manufacturing including design indexing and retrieval, variant design, variant process planning, and design critiquing. We introduce an Object-Oriented Group Technology (OOGT) scheme, which captures design data critical to the product's manufacture. Our approach uses a STEP-based product information model to generate the OOGT data automatically. The latter are then used to conduct an efficient search for similar products manufactured by selected companies and to retrieve and use information about the manufacturing processes and performance of these similar products.     

基于多智能体的数字孪生及其在工业中应用的综述

数字孪生是一种将物理实体数字化的技术,通过建立虚拟的数字孪生模型模拟实际的物理过程,以便进行模拟仿真、数据分析和优化设计等操作.鉴于此,分析数字孪生技术在复杂工业生产中的发展历程和研究现状,并重点讨论其概念、国家相关重点研究的政策,以及数字孪生使能技术在各行业的应用.主要途径是分析和综述基于多智能体的数字孪生、基于数字孪生的设计、制造和运维、数字孪生的集成在智能制造中的应用相关的研究成果.此外,提出高炉连续生产数字孪生方案和大飞机多智能体离散制造方案,高炉模型包括成分场大模型和增量学习小模型,该模型可以为数字孪生在复杂流程工业中的应用提供带有增量补偿的机理与计算机视觉相结合的解决方案.在复杂工业制造中,数字孪生和多智能体技术可以提高生产效率和质量,减少能源消耗和废品产生,同时也能够降低复杂度、安全风险和成本.     

A comparative study of nonlinear optimization and Taguchi methods applied to the intelligent control of manufacturing processes

current investigation focused on neural-network-based control of manufacturing processes utilizing an optimization scheme. In an earlier study, Demirci and Coulter introduced the utilization of neural networks for the intelligent control of molding processes. In that study, a forward model neural network, employed with a search strategy based on the factorial design of experiments method, was shown to successfully control the flow progression during injection molding processes. Recently, Demirciet al. showed that the search mechanism based on the factorial design of experiments method can be intolerable in time during on-line control of manufacturing processes, and suggested an inverse model neural network. This inverse model neural network was shown to be beneficial as it totally eliminated time-consuming parameter searches, but it required a harder mapping than the forward model neural network and thus its performance was inferior. In the present study, the authors investigated two different optimization methods that were utilized in making the search method of the forward control scheme more efficient. The first method was Taguchi's method of parameter design, and the second method was a nonlinear optimization method known as Nelder and Mead's downhill simplex method. These two methods were separately utilized in creating an efficient search method to be used with the forward model neural network. The performance of the resulting two control methods was compared with each other as well as with that of the forward control scheme utilizing a search strategy based on the factorial design of experiments method. Although the applications in this study were on molding processes, the method can be applied to any manufacturing process for which a process model and anin-situ sensing scheme exists.     

A process knowledge representation approach for decision support in design of complex engineered systems

Process knowledge is of considerable significance to the digitalization and intelligentization of the manufacturing industry. Current research on the process knowledge representation of decision-making in engineering design has predominantly focused on either mathematical models of individual decisions at the micro-level or organizational models of group decision consensus at the macro-level. However, the management of complexity and uncertainty in the model-based realization of engineered systems is critical to achieving rational, comprehensive, and robust decisions, especially in terms of knowledge-intensive design. The efficiency and effectiveness of decisions in system design are intrinsically linked to the process, knowledge, and system concepts involved, necessitating a more flexible and systematic decision process representation scheme that supports both the management of complexity and uncertainty. Hence, in this paper, we propose a decision-centric design process representation scheme named the Phase-Event-Information X (PEI-X) diagram and its corresponding systematic design guidance method for designing decision workflows. Using the proposed method, designers have the ability to (1) model hierarchical decision processes that cover vertical and horizontal interaction patterns, and (2) exploit the synthesis of the “Formulating-Identifying-Reusing-Exploring” iterative process to extend the understanding and prediction of decision process behaviors in design. We achieve the aforesaid abilities through the implementation of a knowledge-based design guidance system for collaborative decision support and we demonstrate the efficacy by adopting a specific multi-stage manufacturing process design problem, hot rod rolling system design, and carry out an integrated design of materials, products, and related manufacturing processes.     

Multiobjective layout optimization of robotic cellular manufacturing systems

This paper proposes a multiobjective layout optimization method for the conceptual design of robot cellular manufacturing systems. Robot cellular manufacturing systems utilize one or more flexible robots which can carry out a large number of operations, and can conduct flexible assemble processes. The layout design stage of such manufacturing systems is especially important since fundamental performances of the manufacturing system under consideration are determined at this stage. In this paper, the design criteria for robot cellular manufacturing system layout designs are clarified, and objective functions are formulated. Next, layout design candidates are represented using a sequence-pair scheme to avoid interference between assembly system components, and the use of dummy components is proposed to represent layout areas where components are sparse. A multiobjective genetic algorithm is then used to obtain Pareto optimal solutions for the layout optimization problems. Finally, several numerical examples are provided to illustrate the effectiveness and usefulness of the proposed method.     

基于多层C/S结构的饲料行业MRP系统

为适应饲料行业生产管理自动化的需要,设计并实现了基于多层C/S结构即客户机/应用服务器/数据库服务器体系结构的饲料生产行业制造资源计划(MRP)系统,对饲料生产MRP进行了系统分析,介绍了系统的设计方案与体系结构,重点介绍了生产管理模块的设计与实现,对生产管理的主要模块如物料清单(BOM)管理和MRP计算等进行了详细分析.     

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Present manufacturing systems are facing significant challenges concerning their adaptability. Holonic manufacturing systems are among the technologies that can provide solutions to such requests, if certain conditions are met. As being included in the class of semi-heterarchical control architectures, holonic systems need appropriate coordination and planning schemes, together with validation tools to increase the beneficiaries’ trust. This paper proposes a coordination scheme for holonic systems, based on a mix between contract net protocol and distributed constraint satisfaction problems. The distinct phases of this method are explained, with details referring to the adaptation of contract net protocol. About the constraint satisfaction mechanism, a guide is provided on how a manufacturing problem can be expressed according to this formalism. To validate the introduced coordination scheme, a coloured Petri net model was developed. This allowed several simulation experiments for scenarios regarding a manufacturing system with four robots to be carried out. The obtained solutions showed that the proposed method can determine both the right holarchy related to the manufacturing goal, and optimal plans for robots. Moreover, as proven by the reachability graphs obtained for different goals, the proposed method reached correct results for all goals and diverse constraints, and it determined all possible solutions. An advantage is about how knowledge possessed by different types of holons is efficiently used, without producing an increased communication load. In conclusion, our method can ensure the right trade-off between complexity and optimality, and the attached model can constitute the required link between design and implementation, thus contributing to an easier deployment of holonic systems.     

Petri网精细化操作及其在系统设计中的应用

针对柔性制造系统的设计问题,提出了用Petri网精细化操作解决问题的方案.给出了两种精细化操作.研究了Petri网精细化操作的动态性质保持问题,给出了精细化操作保持活性、有界性、可回复性的充分必要条件;对一个柔性制造系统进行了设计和验证.其结果可为Petri网系统静态和动态性质的考察提供有效途径,为Petri网复杂大系统的分析提供重要手段,并特别适合于柔性制造系统的设计,具有一定的实用价值.     

Petri网共享子网合成及其在系统设计中的应用

针对柔性制造系统的设计和分析,提出了经由Petri网共享子网构成合成网的解决方案;研究了Petri网共享子网合成的动态性质保持问题,给出了合成网保持活性、有界性的一组充分条件;对一个柔性制造系统进行了设计和分析。本文的结果可为Petri网系统静态和动态性质的考察提供有效途径,为Petri网复杂大系统的分析提供重要手段,并特别适合于柔性制造系统的设计,具有一定的实用价值。     

一种传感器虚拟检测系统的开放实验研究

介绍了一种基于虚拟仪器技术的角度传感器检测系统开发的开放实验设计方案,分析了线性角度传感器的电器特性,阐述了实验的详细设计方法。该开放实验可由学生根据企业需求来设计开发,并已经应用于角度传感器的工业生产及应用检测中,该虚拟系统具有运行稳定、价格低廉和使用便捷等特点。     

Design of parts for cellular manufacturing using neural network-based approach

A neural network approach is applied to the problem of integrating design and manufacturing engineering. The self organising map (SOM) neural network recognizes products and parts which are modeled as boundary representation (B-rep) solids using a modified face complexity code scheme adopted, and forms the necessary feature families. Based on the part features, machines, tools and fixtures are selected. These information are then fed into a four layer feed-forward neural network that provides a designer with the desired features that meet the current manufacturing constraints for design of a new product or part. The proposed methodology does not involve training of the neural networks used and is seen to be a significant potential for application in concurrent engineering where design and manufacturing are integrated.     

Automotive engineering curriculum development: case study for Clemson University

The automotive manufacturing industry has transitioned in the past 20 years from a central technical focus to an integrated and globally distributed supply chain. As car makers outsource not only a greater portion of their manufacturing, but also their technical design responsibility, a more thorough understanding of both design and manufacturing changes’ effect on total vehicle and total production system performance and cost is critical. The distribution of technical responsibility in automotive manufacturing has motivated the development of a specific curriculum in Automotive Engineering at Clemson University in South Carolina, USA, with core focus on the interaction between systems, both in design and manufacturing. In this development, a detailed survey of automotive Original Equipment Manufacturers and major suppliers was carried out. The differences in perceived need between these organization types is explored, and the incorporation of these perceived needs to a new Automotive Engineering curriculum is presented.     

Multiple platforms design and product family process planning for combined additive and subtractive manufacturing

Industry 4.0 promotes the utilization of new exponential technologies such as additive manufacturing in responding to different manufacturing challenges. Among these, the integration of additive and subtractive manufacturing technologies can play an important role and be a game changer in manufacturing products. In addition, using product platforms improves the efficiency and responsiveness of manufacturing systems and is considered an enabler of mass customization. In this paper, a model to design multiple platforms that can be customized using additive and subtractive manufacturing to manufacture a product family cost-effectively is proposed. The developed model is used to determine the optimal number of product platforms, each platform design (i.e. its features set), the assignment of each platform to various product variants, and the macro process plans for customizing the platforms while minimizing the overall product family manufacturing cost.The multiple additive/subtractive platforms and their process plans are determined by considering not only the commonality between the product variants but also their various manufacturing cost elements and the customer demand of each variant. The design of multiple product family platforms and their process plans is NP-hard problem. A genetic algorithm-based model is developed to reduce the computational complexity and find optimal or near optimal solution. Two case studies are used to illustrate the developed multiple platform model. The model results were compared with a single platform model in literature and the results demonstrate the multiple platform model superiority in manufacturing product families in lower cost. The use of the developed model enables manufacturing product families cost efficiently and allows manufacturers to manage diversity in products and market demands.     

基于ASP技术的计算机辅助工业设计系统的设计与研究

随着计算机网络技术的迅猛发展,全球经济面临着深刻的变革。计算机技术的发展使得制造业发生了很大变化。为了更好地将计算机技术应用到工业上去,本文提出了一种基于服务提供商模式的解决方案,用于解决计算机辅助工业设计中网络化制造的问题。本文设计并开发的系统由四个工具集构成,每个工具都是利用可重用组件技术进行开发,动态加载到计算机辅助工业设计平台中。本文重点研究了工具集中的形态布局、色彩方案、人机设计等技术,开发出的系统可以为企业提供一些基本的计算机辅助工业设计应用服务。实验表明,该系统能够提高企业的工作效率,提高企业的设计能力,对网络化制造业具有重要意义。