Knowledge-based approach and system for assembly-oriented design,Part II: the system implementation

Assembly is one of the most important stages for product development. Assembly-oriented design (AOD) is a new approach to designing assemblies, which uses a number of design and analysis tools to help the designer plan out and analyze candidate assembly schemes prior to having detailed knowledge of the geometry of the parts. Using this approach, many assembly schemes can be inexpensively evaluated for their ability to deliver the important characteristics of the final product. This research proposes a knowledge-based approach and develops an expert design system to support top-down design for assembled products. The presentation of research report is divided into two parts: the knowledge-based approach (Part I) and the knowledge-based expert design system (Part II). This paper is the second part of the report (Part II). It will focus on the development of knowledge-based expert design system for assembly oriented design. The knowledge-based assembly oriented design system, i.e., the assembly oriented design expert system (AODES) is constructed to integrate assembly modeling and design, assembly planning, assemblability analysis and evaluation within a concurrent engineering environment. This intelligent system is implemented by integrating object-oriented representation, constraint-based modeling, rule-based reasoning, truth maintenance, and interfacing to database management system and CAD module, in which fuzzy logic based knowledge representation and inference technique are also applied to deal with uncertain data and knowledge in the design process. The developed system differs from the existing systems adopting part-first bottom-up modeling technique, in which a comprehensive intelligent framework is used for assembly modeling and design in a top-down manner from the conceptual level to the detailed level. It is able to help obtain better design ideas, provide users with suggestions so as to create and improve a design, and therefore give users the possibility to assess and reduce the total production cost at an early stage during the design process. Through the use of the system, the concurrent engineering knowledge can be effectively incorporated into the assembly design process in an integrated manner. A case assembly design shows that the intelligent modeling and design system is feasible.     

A knowledge intensive multi-agent framework for cooperative/collaborative design modeling and decision support of assemblies

Multi-agent modeling has emerged as a promising discipline for dealing with decision making process in distributed information system applications. One of such applications is the modeling of distributed design or manufacturing processes which can link up various designs or manufacturing processes to form a virtual consortium on a global basis. This paper proposes a novel knowledge intensive multi-agent cooperative/collaborative framework for concurrent intelligent design and assembly planning, which integrates product design, design for assembly, assembly planning, assembly system design, and assembly simulation subjected to econo-technical evaluations. An AI protocol based method is proposed to facilitate the integration of intelligent agents for assembly design, planning, evaluation and simulation process. A unified class of knowledge intensive Petri nets is defined using the O-O knowledge-based Petri net approach and used as an AI protocol for handling both the integration and the negotiation problems among multi-agents. The detailed cooperative/collaborative mechanism and algorithms are given based on the knowledge objects cooperation formalisms. As such, the assembly-oriented design system can easily be implemented under the multi-agent-based knowledge-intensive Petri net framework with concurrent integration of multiple cooperative knowledge sources and software. Thus, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system.     

A knowledge-based simulation environment for hierarchical flexiblemanufacturing

This article presents an approach to embedding expert systems within an object oriented simulation environment. The basic idea is to create classes of expert system models that can be interfaced with other model classes. An expert system shell is developed within a knowledge-based design and simulation environment which combines artificial intelligence and systems modeling concepts. In the given framework, interruptible and distributed expert systems can be defined as components of simulations models. This facilitates simulation modeling of knowledge-based controls for flexible manufacturing and many other autonomous intelligent systems. Moreover, the structure of a system can be specified using a recursive system entity structure (SES) and unfolded to generate a family of hierarchical structures using an extension of SES pruning called recursive pruning. This recursive generation of hierarchical structures is especially appropriate for design of multilevel flexible factories. The article illustrates the utility of the proposed framework within the flexible manufacturing context     

Web-based modular interface geometries with constraints in assembly models

The use of a modular technique in modeling for assembly can improve design efficiency and reduce the cost of product development. This paper presents an approach to an assembly model that was built using modular interface geometries. This paper proposes a novel, hybrid modular design strategy instead of the traditional, top-down design process. The curve-joint method is used as a simplified process for converting a 3D solid model to a skeleton model with interface geometries in modeling for assembly. This research builds assembly interface geometries with their constraints in the assembly model instead of using information about individual assembly parts for the product. These interface geometries are easy to share, and they deliver the design requirements properly. They also ensure that minimal efforts will be required in the design change process. By implementing this method, the constraints of the features in modular assembly parts can be transferred to interface geometries. Designers can easily add, replace, and delete design parts in the modular product. Module interaction for application programmed interface (MIAPI) is developed using HTML and JavaScript. The module structure of products can be verified via the web-based Internet in VRML format. These simplified assembly models that have fewer constraints allow design project managers to simulate the functioning of the product in the modularized design before the prototype is built. By using the assembly models, customers can easily choose various modules to assemble the exact products they are seeking via the Internet process. A desk lamp model is used as the example for implementation to validate the feasibility of this research.     

Integration of the STEP-based assembly model and XML schema with the fuzzy analytic hierarchy process (FAHP) for muti-agent based assembly evaluation

Assemblability analysis and evaluation plays a key role in assembly design, operation analysis and planning. In this paper, we propose an integrated intelligent approach and framework for evaluation of assemblability and assembly sequence for electro-mechanical assemblies (EMAs). The approach integrates the STEP (STandard for the Exchange of Product model data, officially ISO 10303)-based assembly model and XML schema with the fuzzy analytic hierarchy process for assembly evaluation. The evaluation structure covers not only the geometric and physical characteristics of the assembly parts but also the assembly operation data necessary to assemble the parts. The realization of the integration system is implemented through a multi-agent framework. Through integration with the STEP-based product modeling agent system, CAD agent system and assembly planning agent system, the developed assembly evaluation agent system can effectively incorporate, exchange, and share concurrent engineering knowledge into the preliminary design process so as to provide users with suggestions for improving a design and also helping obtain better design ideas. The applications show that the proposed approach and system are feasible. Received: July 2004 / Accepted: January 2006     

Digital twin-based smart assembly process design and application framework for complex products and its case study

With rapid advances in new generation information technologies, digital twin (DT), and cyber-physical system, smart assembly has become a core focus for intelligent manufacturing in the fourth industrial evolution. Deep integration between information and physical worlds is a key phase to develop smart assembly process design that bridge the gap between product assembly design and manufacturing. This paper presents a digital twin reference model for smart assembly process design, and proposes an application framework for DT-based smart assembly with three layers. Product assembly station components are detailed in the physical space layer; two main modules, communication connection and data processing, are introduced in the interaction layer; and we discuss working mechanisms of assembly process planning, simulation, predication, and control management in the virtual space layer in detail. A case study shows the proposed approach application for an experimental simplified satellite assembly case using the DT-based assembly application system (DT-AAS) to verify the proposed application framework and method effectiveness.     

An integrated case-based reasoning approach for intelligent help desk fault management

As modern business functions become more complex and knowledge-intensive, with increasing demands for quality services, there is an emerging trend for organisations to develop and deploy intelligent knowledge-based systems for mission-critical operations. Some of the challenges in successfully implementing this breed of systems depend on how well the intelligent system is integrated with conventional existing information systems and workflow, and the quality of the intelligent system itself. Developing quality expert systems lies in the effective modelling of cognitive processes of human experts and representation of various forms of related knowledge in a domain. An integrated intelligent system called the Intelligent Help Desk Facilitator (IHDF), has been developed for computer and network fault management. The system, which comprises various modules including an expert system, is successfully deployed in a problem response help desk environment of a local bank. This paper describes a cognitive-driven approach to the development of the expert system based on a hybrid knowledge representation and reasoning strategy. The approach incorporates a hybrid case-based reasoning (CBR) framework of techniques which include case memory organisation structures (discrimination networks and shared-featured networks), case indexing and retrieval schemes (fuzzy character-matching, nearest-neighbour similarity matching and knowledge-guided indexing); and an interactive and incremental style of reasoning. The paper discusses the design and implementation of the expert system component of IHDF and illustrates the appropriateness of the hybrid architecture for problem resolution and diagnostic types of applications.     

Product modeling framework based on interaction feature pair

Designing products effectively and efficiently is of great significance. However, currently part models are usually created without knowing how they will interact with other parts, leading to gaps between part modeling and assembly modeling and between other applications, and to tedious and redundant labor. This paper proposes a novel product modeling framework to address the problems. The framework is different from current product modeling systems from two aspects. On the architecture level, a new module based on a concept of interaction feature pair (IFP) is developed. An IFP incorporates information of interaction type, related feature pairs and behavioral information that fulfill the interactions. The new module can model the structure of IFPs mathematically through operators and functions defined in a space spanned from six basic IFPs. It can also utilize the constituent elements of an IFP as state variables to form behavior models for the IFP. On the process level, the IFP-based framework can support both bottom-up and top-down approaches, and integrate part modeling and assembly modeling together by changing the workflows. Concretely, IFPs will be embedded into part models at part modeling stage to make them pre-interact with each other, and at assembly modeling stage, parts will be assembled by instantiating the embedded IFPs instead of specifying mating constraints, thus reducing the tedious and redundant labor. Incorporating knowledge of different domains, IFPs can also be developed to integrate more applications together. The implementation of the framework is demonstrated through a prototype system.     

EFDEX: A Knowledge-Based Expert System for Functional Design of Engineering Systems

This paper presents a knowledge-based system, ‘EFDEX’, the Engineering Functional Design Expert, which was developed using an expert system shell, CLIPS 6.1, to perform intelligent functional design of engineering systems. On the basis of a flexible, causal and hierarchical functional modeling framework, we propose a knowledge-based functional reasoning methodology. By using this intelligent functional reasoning strategy, physical behavior can be reasoned out from a desired function or desired behavior, and inter-connection of these behaviors is possible when there is compatibility between the functional output of one and the corresponding functional requirement (e.g. driving input) of the next one. In addition, a complicated, desired function which cannot be matched with the functional output of any behavior after searching the object-oriented behavior base, will be automatically decomposed into less complex sub-functions by means of relevant function decomposition rules. An intelligent system for the functional design of an automatic assembly system provides an application of this intelligent design environment, and a demonstration of its methodology. In this paper, a knowledge-based functional representation scheme which integrates two popular AI representation techniques (object-oriented representation and rule-based representation) is also proposed as a prelude to a knowledge-based functional design system     

A framework for collaborative top-down assembly design

This paper presents a new system framework for collaborative top-down assembly design. Different from current computer-aided design (CAD) systems, the framework allows a group of designers to collaboratively conduct product design in a top-down manner. In our framework, a multi-level and distributed assembly model is adopted to effectively support collaborative top-down assembly design. Meanwhile, fine-granularity collaborative design functionalities are provided. First, the coupled structural parameters involved in the distributed skeleton models of the product can be collaboratively determined by the correlative designers based on fuzzy and utility theory. Second, agent based design variation propagation is achieved to ensure the consistency of the multi-level and distributed assembly model during the whole design process. Third, collaborative design of assembly interfaces between the components assigned to different designers is supported. The prototype implementation shows that our framework works well for supporting practical collaborative top-down assembly design.     

Intelligent approaches for generating assembly drawings from 3-D computer models of mechanical products

In order to reduce the time of mechanical product design and ensure the high quality of their assembly drawings, this paper develops an intelligent approach for generating assembly drawings automatically from three-dimensional (3-D) computer assembly models of mechanical products by simulating the experienced human designer's thinking mode with the aid of computer graphics and knowledge-based expert system. The key issues include the strategies and methods for selecting the necessary views in an assembly drawing, determining necessary sectional views in each view, eliminating the unreasonable projective overlap of the components in each view, and minimizing the numbers of both the views in an assembly drawing and the sectional views in each view. Based on the approach, corresponding software prototype was developed. Finally, it is demonstrated, from an example of the fixture in a modularized drilling machine, that its assembly drawing was generated successfully using this intelligent software prototype.     

Multi-level assembly model for top-down design of mechanical products

To enable next generation CAD tools to effectively support top-down design of products, a top-down assembly design process is refined from the traditional product design process to better exhibit the recursive-execution and structure-evolvement characteristics of product design. Based on the top-down assembly design process, a multi-level assembly model is put forward to capture the abstract information, skeleton information and detailed information involved. The multi-level assembly model is a meta-level implementation and is easy to be extended. Moreover, the inheritance mechanisms are explored to ensure the feasibility of information transferring and conversion between different design phases in the top-down assembly design process. A top-down assembly design sample is analyzed at length to show the application effects of the multi-level assembly model and the relevant inheritance mechanisms. In addition, a practical topic about the model adaptation of existing CAD systems is also discussed for a broader application of the top-down assembly design. Finally, the conclusion of the work and the future directions for further exploration are given.     

An object-oriented knowledge based Petri net approach to intelligent integration of design and assembly planning

Artificial intelligence can play an important role in the reduction of manufacturing costs and the enhancement of production efficiency and product quality. In order to assist designers in the early stages of a product development this paper develops an intelligent methodology for integration of design and assembly planning processes, including product design, assembly evaluation and redesign, assembly process planning, design of assembly system and assembly simulation, subjected to both econo-technical and ergonomic evaluations. A new unified class of object-oriented knowledge based Petri nets called OOKPNs, incorporating knowledge based expert systems and fuzzy logic into ordinary place–transition Petri nets, is defined and used for the representation and modeling of the distributed design processes. A prototype intelligent integrated design and assembly planning system (IIDAP) is implemented through distributed blackboard structure with concurrent integration of multiple cooperative knowledge sources and software. It consists essentially of the networked agents and the meta-system, each of which is a knowledge Petri net system with the capabilities of problem solving, learning and conflict resolution, and can be obtained through the inheritance, polymorphism and dynamic binding of instances of OOKPNs. In IIDAP system, both C/C++ language and COOL (CLIPS object-oriented language) are used to incorporate a Petri net tool, a geometric modeling and design tool, a planner and simulator and an evaluation tool. By use of this system, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system. The design of manufacturable, cost-effective, usable products can therefore be achieved rapidly and flexibly. The developed methodology and system have been successfully applied to assembly design and planning of a micro switch.     

Internet驱动的产品协同装配理论和技术研究

介绍了Internet驱动的分布式产品协同装配中的关键技术问题,协同装配设计平台的构建、产品模型呈现方法、冲突处理、协同装配信息建模和协同装配设计优化,并分析总结了目前存在的问题。最后构建了一个全面的产品协同装配系统框架。     

Knowledge intensive Petri net framework for concurrent intelligent design of automatic assembly systems

The integration of design and planning of flexible assembly system has been recognized as a tool for achieving efficient assembly in a production environment that demands assembly with a high degree of flexibility. This paper proposes a concurrent intelligent approach and framework for the design of robotic flexible assembly systems. The principle of the proposed approach is based on the knowledge Petri net formalisms, incorporating Petri nets with more general problem-solving strategies in AI using knowledge-based system techniques. The complex assembly systems are modeled and analyzed by adopting a formal representation of the system dynamic behaviors through knowledge Petri net modeling from the specifications and the analysis of those models. A template is first defined for a knowledge Petri net model, and then the models for assembly system individuals are established in the form of instances of the template. The design of assembly systems is implemented through a knowledge Petri net-based function–behavior–structure model. The research results show that the proposed knowledge Petri net approach is applicable for design, simulation, analysis and evaluation, and even layout optimization of the flexible assembly system in an integrated intelligent environment. The integration of assembly design and planning process can help reduce the development time of assembly systems.     

A bio-inspired approach for self-correcting compliant assembly systems

Statistical process monitoring and control has been popularized in manufacturing as well as various other industries interested in improving product quality and reducing costs. Advances in this field have focused primarily on more efficient ways for diagnosing faults, reducing variation, developing robust design techniques, and increasing sensor capabilities. However, statistical process monitoring cannot address the need for instant variation reduction during assembly operations. This paper presents a unique dimensional error-compensation approach for compliant sheet metal assembly processes. The resulting autonomous self-correction system integrates rapidly advancing data mining methods, physical models, assembly modeling techniques, sensor capabilities, and actuator networks to implement part-by-part dimensional error compensation. Inspired by biological systems, the proposed quality control approach utilizes immunological principles as a means of developing the required mathematical framework behind the self-correcting methodology. The resulting assembly system obtained through this bio-mimicking approach will be used for autonomous monitoring, detection, diagnosis, and control of station and system level faults, contrary to traditional systems that largely rely on final product measurements and expert analysis to eliminate process faults.     

A knowledge-based master model approach exemplified with jet engine structural design

Successful product development requires the consideration of multiple engineering disciplines and the quantification of tradeoffs among conflicting objectives from the very early design phases. The single-largest challenge to do so is the lack of detailed design information. A possible remedy of this issue is knowledge-based engineering. This paper presents a knowledge-based master model approach that enables the management of concurrent design and analysis models within different engineering disciplines in relation to the same governing product definition. The approach is exemplified on an early phase structural design of a turbo-fan jet engine. The model allows geometric-, structural mechanics- and rotor-dynamic- models to be concurrently integrated into a multi-disciplinary design and optimization loop.     

Decision support systems: An expert systems approach

This paper provides a conceptual framework for designing decision support systems (DSS) using an expert systems approach. Currently there is a significant trend towards the use of knowledge-based systems techniques in DSS design, but a comprehensive framework is yet to be proposed. Our paper addresses this problem and presents such a framework. Efforts are currently underway to design, implement and test a system based on this framework.     

A rule-based expert system approach to process selection for cast components

A knowledge-based expert system at the discretion of casting product designers can be employed as a real-time expert advisor to assist product designers to achieve the correct casting design and select the most appropriate casting process for a given component. This paper proposes a rule-based expert system approach for casting process selection, and describes an ongoing rule prototype development. The system in its present development state consists of five interconnected levels each concerning a particular process selection parameter or group of parameters including alloy to be cast, casting geometric features, casting accuracy, production quantity and overall comparative costs. The system progressively evaluates the user's specifications against the capabilities of various casting processes and in each level selects the processes that satisfy the design parameters specified. The final comparative cost level compares the processes that have satisfied all the criteria in the previous levels and recommends the most economical option.     

Analysis of assembly operations’ difficulty using enhanced expert high-level colored fuzzy Petri net model

Majority of the products can be assembled in several ways that means the same final product can be realized by different sequences of assembly operations. Different degree of difficulty is associated with each sequence of assembly operation and such difficulties are caused by the different mechanical constraints forced by the different sequences of operations. In the past, few notable attempts have been made to represent and enumerate the degree of difficulty associated with an assembly sequence (in the form of triangular fuzzy number) by using the concept of assembly graph. However, such representation schemes do not possess the capabilities to model the user's reasoning and preferences. In this research, an intelligent Petri net model that combines the abilities of modelling, planning and performance evaluation for assembly operation is presented. This modelling tool can represent the issues concerning degree of difficulty associated with assembly sequences. The proposed mechanism is enhanced expert high-level colored fuzzy Petri net (EEHLCFPN) that is a hybrid of knowledge-based system and colored Petri net. An example encompassing assembly of subassemblies is considered to efficiently delineate the modelling capabilities of proposed hybrid petri net model.