Simulation of intelligent hierarchical flexible manufacturing:batch job routing in operation overlapping

We present an approach to embedding expert systems within an object-oriented simulation environment that facilitates the creation of classes of expert system model elements that can be interfaced with other model components. Previous work has shown how distributed expert systems can be defined as modular components of simulations models. This article illustrates their usefulness in fractal architectures for flexible manufacturing, as proposed in the literature. Alternate structures (reconfigured structures) of a proposed hierarchical factory architecture can be generated through the recursive pruning process. Such rapid prototyping should greatly enhance the ability to investigate alternative architectural solutions to manufacturing problems in a timely manner     

Enabling multi-use, multi-tool models of manufacturing systems through an experimental frame expert system

A significant shortcoming of traditional modeling methodologies is the limited access they provide for decision-makers who are not modeling specialists. This paper presents an expert system approach to address this shortcoming. An expert system called the experimental frame expert system (EFES) was developed for this purpose within an advanced modeling environment for manufacturing systems. EFES reduces the dependence upon modeling specialists, and thus, makes models, both analytical and simulation, more accessible to decision-makers. This is accomplished by using two knowledge bases, one related to the manufacturing system specific symptoms and problems, and the other to system analysis and optimization tools. This paper presents the dissertation research effort that led to development of these two knowledge bases as well as the EFES framework within the advanced modeling environment.     

Knowledge-based environment for investigating multicomputer architectures

Multicomputers for massively parallel processing will eventually employ billions of processing elements, each of which will be capable of communicating with every other processing element. A knowledge-based modelling and simulation environment (KBMSE) for investigating such multicomputer architecture at a discrete-event system level is described. The KBMSE implements the discrete-event system specification (DEVS) formalism in an object-oriented programming system of Scheme (a dialect), which supports building models in a hierarchical, modular manner, a systems-oriented approach not possible in conventional simulation languages. The paper presents a framework for knowledge-based modelling and simulation by exemplifying modelling a hypercube multicomputer architecture in the KBMSE. The KBMSE has been tested on a variety of domains characterized by complex, hierarchical structures such as advanced multicomputer architectures, local area computer networks, intelligent multi-robot organizations, and biologically based life-support systems.     

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     

Expert systems: An application in flexible manufacturing

Flexible manufacturing systems (FMS) are needed to provide manufacturing operations with the capability to adjust, in real time, to changes in the manufacturing environment. Realization of the goals of flexible manufacturing is governed by the ability of the FMS to maintain adequate information on the factory to assist in generating scenarios from product planning to operations and performance. This leads to a view where the factory is represented as an integrated information system. To facilitate the analysis of information requirements and the design of information systems for flexible manufacturing, an expert support system (ESS) which can be used to model and study the various structures is described. This ESS uses the information cell model to build these information structures. Petri net representations of these structures and their interactions are then constructed. The ESS may now be used to exercise these models and study their performance using time and cost measures.     

A data-driven generic simulation model for logistics-embedded assembly manufacturing lines

Simulation has been used to evaluate various aspects of manufacturing systems. However, building a simulation model of a manufacturing system is time-consuming and error-prone because of the complexity of the systems. This paper introduces a generic simulation modeling framework to reduce the simulation model build time. The framework consists of layout modeling software and a data-driven generic simulation model. The generic simulation model was developed considering the processing as well as the logistics aspects of assembly manufacturing systems. The framework can be used to quickly develop an integrated simulation model of the production schedule, operation processes and logistics of a system. The framework was validated by developing simulation models of cellular and conveyor manufacturing systems.     

An environment for DEVS-based multiformalism simulation in Common Lisp/CLOS

The paper presents the realization of an object-oriented kernel of a new modeling and simulation environment. The kernel system stands out as it is based on systems theoretical concepts and facilitates combined discrete-continuous, modular, hierarchical modeling. Its implementation language is the AI language Common Lisp and its object-oriented superset CLOS. The kernel system serves as the basis for a knowledge-based modeling and simulation environment supporting interactive modeling and simulation and automatic model construction. This research was supported in part by SIEMENS Munich, ZFE, ST.     

Integrated knowledge-based Petri net intelligent flexible assembly planning

Automatic assembly planning is recognized as an important tool for reducing manufacturing costs in concurrent product and process development. A novel knowledge-based Petri net (KBPN) is defined, based on the incorporation of expert systems into the usual Petri nets, and used for a unified assembly knowledge representation scheme. A KBPN-approach integrated with a sequence generation algorithm is proposed for the modeling, planning, simulation, analysis and evaluation of the flexible assembly system (FAS). The developed KBPN-based assembly planning system (KAPS) can automatically adjust the deviations between the theoretical planning parameters and the process parameters of real assembly operations to guarantee the best strategies and plans (sequences) for flexible assembly. The research findings are exemplified with a simple assembly to show the effectiveness of the method.     

RASES: A database supported framework for structured model base management

Structured management of model base has placed demands on some kind of computer based frameworks with highly structured formalisms. This paper proposes a new framework, called the relational algebraic system entity structure (RASES), which is based on the system entity structure (SES) formalism and the relational algebra (RA) formalism. These formalisms provide a conceptual basis for the structured model base management. Within the framework, structural knowledge of a system is represented in a hierarchical structure and saved in a database. Furthermore, several operations can be formulated in terms of relational algebra which can be coded in a standard query language such as the SQL. The framework can be easily implemented on, and fully utilize the functionality of, relational database management system (RDBMS). With the help of the implemented framework, simulation models can be systematically synthesized from the models in the model base through the following processes. First, a family of hierarchical structures of a system is organized in the form of entity structure by the entity structuring process. Then, candidate models of the system which meet design objectives are synthesized from the entity structure through the pruning process. Finally, designers can conduct appropriate experiment with the models for design verification and performance measure.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

Using online simulation in Holonic manufacturing systems

This paper deals with the use of online simulation on Holonic manufacturing systems. Concepts needed for the use of online simulation in a classical hierarchical system were already defined, the observer being the central one. The behavior's differences between both classes of systems are studied to determine the best way to adapt these concepts to this new environment. In the product resource order staff approach (PROSA) reference architecture, staff holons were chosen to welcome the simulation models and the observer. An application on an industrial sized Holonic manufacturing system is described to demonstrate the validity of the approach.     

Using knowledge-based technology to integrate CIM databases

The authors propose a framework for using knowledge-based systems to integrate the heterogeneous multidatabases of computer integrated manufacturing (CIM). For each database, a corresponding knowledge-based system is designed for directing knowledge-processing of shared information. This one-to-one method reduces the complexity of the problem. Specifically, the structure, features, and knowledge representation for a knowledge-based system are presented. Then, a prototype of an interface between manufacturing planning and computer-aided design is described. Due to the potential for rapid changes in the manufacturing environment, the linkages among CIM databases are designed to be dynamic, flexible, and adaptive to a wide variety of situations     

Implementation of real-time distributed control for discrete event robotic systems using Petri nets

This article presents a systematic method of modeling and implementing real-time control for discrete-event robotic systems using Petri nets. Because, in complex robotic systems such as flexible manufacturing systems, the controllers are distributed according to their physical structure, it is desirable to realize real-time distributed control. In this article, the task specification of robotic processes is represented as a system control-level net. Then, based on the hierarchical approach, it is transformed into detailed subnets, which are decomposed and distributed into the local machine controllers. The implementation of real-time distributed control through communication between the system controller and the machine controllers on a microcomputer network is described for a sample robotic system. The proposed implementation method is sufficiently general, and can be used as an effective prototyping tool for consistent modeling, simulation, and real-time control of large and complex robotic systems.     

Manufacturing system application of a knowledge based simulation

The flexibility in a modern manufacturing facility introduces complexity to the decision making. The requirement for a real time control mechanism results in a need for an on-line simulation system that can simulate the complicated scheduling, routing and similar decisions required by the system.

This paper describes a knowledge-based simulation and control system written in PROLOG. This system is composed of four parts: a static data base, a dynamic database, a modeling knowledge part, and a simulation driver. The simulator contains the actual control mechanism of the physical system and can be removed from the system in order to simulate it.

The manufacturing system under investigation is a combination of flexible manufacturing cells that feed an automated assembly station. The knowledge-based simulation helps to develp and understand control mechanisms for that system, which can later be implemented in the physical system as the controller.     

Qualitative representation of behavior in the medical domain

In medical knowledge-based systems, there is a need for models of the human body which can predict and explain behavior based on qualitative information about the structure and behavior of the body. We present a framework for representing the structure and behavior of physical systems and apply it to the human cardiovascular system. Our framework allows for hierarchical representation of physical systems and facilitates two kinds of reasoning processes: composition of behaviors and qualitative simulation.     

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.     

Composition of image analysis processes through object-centeredhierarchical planning

This paper presents a new approach to the knowledge-based composition of processes for image interpretation and analysis. Its computer implementation in the VISIPLAN (Vision Planner) system provides a way of modeling the composition of image analysis processes within a unified, object-centered hierarchical planning framework. The approach has been tested and shown to be flexible in handling a reasonably broad class of multi-modality biomedical image analysis and interpretation problems. It provides a relatively general design or planning framework, within which problem specific image analysis and recognition processes can be generated more efficiently and effectively. In this way, generality is gained at the design and planning stages, even though the final implementation stage of interpretation processes is almost invariably problem- and domain-specific     

Generation of an adaptive simulation driven by product trajectories

The tracking of products trajectories involves major challenges in simulation generation and adaptation. Positioning techniques and technologies have become available and affordable to incorporate more deeply into workshop operations. We present our 2-year effort into developing a general framework in location and manufacturing applications. We demonstrate the features of the proposed applications using a case study, a synthetic flexible manufacturing environment, with product-driven policy, which enables the generation of a location data stream of product trajectories over the whole plant. These location data are mined and processed to reproduce the manufacturing system dynamics in an adaptive simulation scheme. This article proposes an original method for the generation of simulation models in discrete event systems. This method uses the product location data in the running system. The data stream of points (product ID, location, and time) is the starting point for the algorithm to generate a queuing network simulation model.     

Expert systems for manufacturing cell simulation and design

Computer Integrated Manufacturing (CIM) is approached by means of the application of Computer Aided Design (CAD), Computer Aided Manufacturing (CAM) and other CA techniques, methods and programs/program systems. These programs are often implemented as knowledge-based, or expert systems and in this way they became typical examples of engineering application of artificial intelligence. The production task of CIM systems is solved by using flexible manufacturing systems (FMSs). FMSs built up from smaller, complex units, i.e. from flexible manufacturing cells (FMCs) have several advantages. The design and the operation of manufacturing systems need new, sophisticated methods to utilize all the embedded benefits of the sophisticated and expensive elements installed for production purposes. New methods like knowledge processing technology, cooperative problem-solving techniques, etc., offer wide possibilities to design more reasonable systems. This paper describes prototype expert systems that make use of different knowledge-based tools and techniques to design (configure, reconfigure) and simulate manufacturing cells, taking into consideration technological plans and other relevant information.     

Computer programs that know: A tutorial

Computational process models have emerged as complements to more traditional statistical and mathematical models. Knowledge-based models and expert systems are particularly well suited for modeling within ill-structured and complex domains. In this tutorial, we discuss the feasibility, building, and application of knowledge-based models in some detail, emphasizing knowledge acquisition, knowledge representation, and system control issues. We conclude the essay with a more practical look at some of the intrigue and challenges associated with building knowledge-based models.