Intelligent knowledge based expert inventory control system for computer integrated manufacturing

The paper discusses the framework and development of an expert inventory management system for integrative manufacturing planning. The system developed with an artificial intelligent language provides a linkage between management and computer-integrated manufacturing(CIM), has the following major elements: data base to represent a hierarchical tree using recursive objects on different levels; knowledge base containing heuristic rules; goal oriented interaction; and backtracking interface procedures. Potential benefits of the system includes: better manufacturing planning, reduced inventory levels and production lead times, and consistent inventory control records.     

An integrated form-feature-based design system for manufacturing

Much of the knowledge that is applied in or communicated between design and manufacturing activities is primarily shape based or shape indexed. Previous attempts to acquire and organize shape knowledge have been mostly concentrated on feature recognition from solid models, group technology (GT) coding schemes, and feature-based modeling. This paper presents the development of an efficient form-feature-based modeling system, and addresses the important issue of utilizing feature information for manufacturing, which has not been extensively discussed by previous work. In this paper we first present a Euler operator-based approach for efficient and effective form-feature encoding and manipulation in a feature-based design environment. Subsequently, a hybrid representation scheme called enhanced CSG tree of feature (ECTOF), which integrates feature model with solid model in a tree structure, is discussed. A feature interference resolution methodology to maintain the correct and consistent feature information in an ECTOF is also deliberated. Finally, we present a machinability-checking module, which employs global accessibility criteria to analyze a feature's machinability on a three-axis machining center. By developing feature interference resolving and machinability testing techniques and integrating with an efficient feature-based design system, this research makes the development of an integrated feature-based design and manufacturing system possible.     

An architecture for an intelligent support system for design validation and manufacturing of aerospace components

This paper presents the architecture of a multi‐agent system that aims to support the design and manufacturing processes of composite material components for the aerospace, automobile, ship and other industries. The major goals are to accelerate the design process while minimising cost; support users in selecting the optimum material in terms of its properties, cost and environmental impact; and enhance the efficiency of the component manufacturing phase by extending the decision support capabilities of the existing real‐time monitoring software. An important requirement for achieving these objectives is to enable the more efficient utilisation of existing distributed information on composite materials. To this end, state‐of‐the‐art advances in metadata concepts were adopted and extended. By implementing metadata structures for each data category available, the searching and retrieval mechanisms are improved both in terms of speed and usage. In addition, large amounts of knowledge about the design and manufacturing processes themselves are incorporated into a multi‐agent environment in order to enhance the ability to support the user groups involved in the various stages of component design and manufacturing. In order to present the system architecture here, an example from the aerospace industry has been used.     

Knowledge-based integrated product design framework towards sustainable low-carbon manufacturing

With a global challenge on the serious ecological problems, low-carbon manufacturing aiming to reduce carbon emission and resource consumption is gaining the ever-increasing attention. Due to the significant impact on the product lifecycle, low-carbon product design is considered as an effective and attractive approach to improve the eco-market trade-off of electromechanical products. Existing low-carbon product design approaches focus on solving specific low-carbon problems, and how to explore and navigate the integrative design space considering low-carbon and knowledge in a holistic perspective is rarely discussed. In response, this paper proposes a knowledge-based integrated product design framework to support low-carbon product development. An ontology-based knowledge modelling approach is put forward to represent the multidisciplinary design knowledge to facilitate knowledge sharing and integration. Subsequently, a function–structure synthesis approach based on case-based reasoning is presented to narrow down the design space to generate suitable design solutions for achieving desired functions. A multi-objective mathematical model is established, and the multi-objective particle swarm optimization is adopted to solve the low-carbon product optimization. Furthermore, a decision-making ranking approach based on the closeness degree is employed to prioritize the potential solutions from Pareto set. Finally, a case study of low-carbon product design of hydraulic machine is demonstrated to show the effectiveness.     

A CORBA-based agent-driven design for distributed intelligent manufacturing systems

An agent-oriented methodology is presented for representation, acquisition, and processing of manufacturing knowledge along with analysis and modeling of an intelligent manufacturing system (IMS). An intelligent manufacturing system adopts heterarchical and collaborative control as its information system architecture. The behavior of the entire manufacturing system is collaboratively determined by many interacting subsystems that may have their own independent interests, values, and modes of operation. The subsystems are represented as agents. An agent's architecture and task decomposition method are presented. The agent-oriented methodology is used to analyze and model an intelligent machine cell. An intelligent machine center is considered as an autonomous, modular, reconfigurable and fault-tolerant machine tool with self-perception, decision making, and self-process planning, able to cooperate with other machines through communication. The common object request broker architecture (CORBA) distributed software control system was developed as a simple prototype. A case study illustrates an intelligent machine center.     

Computer aids to the design of integrated manufacturing systems

Building an Integrated Manufacturing System is a complicated and expensive task. There are very few companies anywhere that will deliver turn-key CAD/CAM systems, far less produce a full line of hardware and software products covering every function required. In designing such a system we are faced with the problem of the proper interfacing and coordination of several hundreds of functional sub-systems. It is, therefore, a natural endeavour to use CAD methods in the design of CAD/CAM systems. Brief outlines are given of a highly interactive system having formalized diagrams and alphanumeric information on the input side, and readable system documentation and analysis reports, on the output side - both interacting to widely accepted extant techniques. The structure of a more complex system affording further facilities is also presented.     

Exploring design space for an integrated intelligent system

Understanding the trade-offs available in the design space of intelligent systems is a major unaddressed element in the study of Artificial Intelligence. In this paper, we approach this problem in two ways. First, we discuss the development of our integrated robotic system in terms of its trajectory through design space. Second, we demonstrate the practical implications of architectural design decisions by using this system as an experimental platform for comparing behaviourally similar yet architecturally different systems. The results of this show that our system occupies a “sweet spot” in design space in terms of the cost of moving information between processing components.     

Stochastic cellular manufacturing system design subject to maximum acceptable risk level

In this study, a non-linear mathematical model is proposed to solve the stochastic cellular manufacturing system (CMS) design problem. The problem is observed in both machine and labor-intensive cells, where operation times are probabilistic in addition to uncertain customer demand. We assume that processing times and customer demand are normally distributed. The objective is to design a CMS with product families that are formed with most similar products and minimum number of cells and machines for a specified risk level. Various experiments are carried out to study the impact of risk level on CMS design. As the risk level increases, lower number of cells and product families are formed and average cell utilization increases. However, this leads to poor performance in cells, where standard deviations of capacity requirements are high. Later, the deterministic approach proposed by Suer, Huang, and Sripathi (2010) and the proposed stochastic model with various risk levels are compared. Both of the models’ results are simulated with Arena Simulation Software. Simulation is performed to validate models and assess the performance of designed CMSs with respect to following measures: cell utilization, WIP, total waiting time and total number waiting. Stochastic CMS design with 10% risk formed a better CMS in all of the performance measures according to the results obtained from simulation experiments.     

Analysis of tolerances and process inaccuracies in discrete part manufacturing

This paper discusses basic problems of tolerancing mechanical parts. The problem of part design analysis (determination of consistency, determinacy and stability) is reduced to the analysis of systems of linear inequalities. It is shown that the calculation of resulting tolerances between components of parts can be easily solved by linear programming. A method is provided for the construction of a system of inequalities which the working dimensions and inaccuracies of machining operations must satisfy if a given tolerance specification is to be met.     

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.     

Bi-level programming enabled design of an intelligent maritime search and rescue system

This paper studies an intelligent maritime search and rescue (SAR) system problem. According to historical accidents and available SAR equipment information, a bi-level mixed-integer programming (MIP) model is proposed to determine the type and number of SAR equipment allocated to activated stations. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) algorithm are applied to solve the proposed mathematical model. Computational experiments based on real instances in the East Sea China not only validate the effectiveness of the bi-level MIP model in balancing two objectives during decision process, but also indicate that PSO algorithm is better than GA algorithm to solve the proposed model and generate reasonable equipment allocation plans. Some managerial implications are also outlined on the basis of the numerical experiments.     

智能在线电导率分析仪的设计与实现

介绍了一个利用单片机技术的智能在线电导率分析仪的设计 ,给出了系统的硬件结构和软件设计的思路。本设计符合工厂应用的要求 ,可以由用户自己定义、自己设计 ,以满足不同的要求     

MetaMorph II: an agent-based architecture for distributed intelligent design and manufacturing

Agent technology derived from Distributed Artificial Intelligence is increasingly being considered for next generation computer-integrated manufacturing systems, to satisfy new requirements for increased integrability, configurability, adaptability, extendibility, agility, and reliability. This paper reviews our previous research on the application of the agent-based technology to intelligent design and manufacturing and describes the current research project MetaMorph II (an agent-based architecture for distributed intelligent design and manufacturing).     

An organism-oriented modeling approach to support the analysis and design of intelligent manufacturing systems

In this paper a generic macroscopic object, termed an organism, is introduced. An organism defines a high-level modeling object that has the capabilities for organizational networking, standardization or characteristics specifications, decoupling of editing and visualization as well as temporal management. Organism-oriented models inherit from their parent object-oriented and object/agent-oriented models a simplified representation of the manufacturing entities as well as a capacity for many levels of abstraction. Moreover, the organism-oriented modeling approach enriches these models by not only considering basic manufacturing objects and agents, but also the fact that each of these objects and agents may itself be an organization and also part of one or several organizations. The paper first surveys some of the current approaches used for modeling and analysing manufacturing systems: structured analysis, Petri nets, object and object/ agent models. The object model behind the organism-oriented modeling approach is then presented and its application to a manufacturing case is illustrated.     

Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm

This paper presents a mixed-integer programming model for a multi-floor layout design of cellular manufacturing systems (CMSs) in a dynamic environment. A novel aspect of this model is to concurrently determine the cell formation (CF) and group layout (GL) as the interrelated decisions involved in the design of a CMS in order to achieve an optimal (or near-optimal) design solution for a multi-floor factory in a multi-period planning horizon. Other design aspects are to design a multi-floor layout to form cells in different floors, a multi-rows layout of equal area facilities in each cell, flexible reconfigurations of cells during successive periods, distance-based material handling cost, and machine depot keeping idle machines. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. The objective is to minimize the total costs of intra-cell, inter-cell, and inter-floor material handling, purchasing machines, machine processing, machine overhead, and machine relocation. Two numerical examples are solved by the CPLEX software to verify the performance of the presented model and illustrate the model features. Since this model belongs to NP-hard class, an efficient genetic algorithm (GA) with a matrix-based chromosome structure is proposed to derive near-optimal solutions. To verify its computational efficiency in comparison to the CPLEX software, several test problems with different sizes and settings are implemented. The efficiency of the proposed GA in terms of the objective function value and computational time is proved by the obtained results.     

Generation of alternative process plans in integrated manufacturing systems

The availability of alternative process plans is a key factor for integration of design, process planning, and scheduling functions. The availability of alternative process plans can speed up the process of incremental process plan generation which can help in providing real time cost feed back to the designer after each design modification. Also alternative process plans relax the constraints in the optimization of production schedules, which in turn results in more efficient use of production resources and better delivery schedules. This paper describes a methodology for generation of alternative process plans in the integrated manufacturing environment. The procedure consists of: selection of alternative machining processes, clustering and sequencing of machining processes, and generation of a process plan network. Each of these steps is explained in detail. The result of the procedure is the process plan network that provides all alternative process plans for the given part. Methods for the selection of an optimal process plan are also described. Computational complexity of the procedure is discussed and experimental results on several realistic examples are shown.     

Preliminary design and manufacturing planning integration using web-based intelligent agents

Software agents have been increasingly used in the product and process development in industry over the past years due to the rapid evolvement of the Internet technology. This paper describes agents for the integration of conceptual design and process planning. Agents provide mechanisms to interact with each other. This mechanism is important since both of those processes involve negotiations for optimization. A set of design and planning software agents has been developed. These agents are used in a computer-based collaborative environment, called a multi-agent platform. The main purpose of developing such a platform is to support product preliminary design, optimize product form and structure, and reduce the manufacturing cost in the early design stage. The agents on the platform have access to a knowledge base that contains design and planning rules. These rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, production volume, and production rate. These rules are used by process planning agents to provide process planners with information regarding selecting preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. Additionally, the agents communicate with WEB servers, and they are accessible by users through Internet browsers. During performing design and planning tasks, agents access the data pertinent to design and manufacturing processes by the programming interfaces of existing computer-aided design (CAD) and manufacturing system. The agents are supported by a developed prototype agent platform. The agents and the platform enable the information exchange among agents, based on a previously developed integrated design and manufacturing process object model.     

Internet-based manufacturing: A review and a new infrastructure for distributed intelligent manufacturing

Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing enterprises. Traditional centralized manufacturing systems are not able to meet these requirements. In recent years, the internet has become the worldwide information platform for the sharing of information and data. Information processing is an important challenge in an internet-based manufacturing environment, and must facilitate distribution, heterogeneity, autonomy and cooperation. This paper reviews recent trends and major developments in internet-based manufacturing. Broad categories of distributed information management are identified, based upon the development of computer integrated manufacturing, and the possible direction of future research is indicated.     

Synchronization-oriented reconfiguration of FPAI under graduation intelligent manufacturing system in the COVID-19 pandemic and beyond

Companies with manufacturing systems that are more responsive and resilient will be able to survive or even gain market shares in the face of the unpredicted variable of an outbreak similar to the COVID-19 pandemic. Motivated by an industrial company restructuring its manufacturing system with the layout of fixed-position assembly islands (FPAI) during the COVID-19 pandemic, this paper introduces the synchronization-oriented reconfiguration of FPAI under Graduation Intelligent Manufacturing System (GiMS). Inspired by the graduation ceremony, a novel manufacturing mode-Graduation Manufacturing System (GMS) with ticket-based reconfigurable structures, is designed for organizing production operations with simplicity and resilience for the layout of FPAI. The IIoT and digital twin-enabled GiMS is developed for transforming real-time visibility in operations to support the reconfiguration of the manufacturing system. A synchronization-oriented reconfiguration mechanism is proposed to achieve the synchronous interaction among changing customer demand, island configuration, and production activities allocation rapidly and cost-effectively. Cloud services integrating the proposed reconfiguration mechanism are developed for managers and onsite operators for supporting the successful reconfiguration implementation with enhanced operational visibility. Through the case study of an industrial company, the effectiveness of the proposed concept and approach is verified.     

Advanced human–machine system for intelligent manufacturing

The use of ontologies has gained more and more interest above all for the knowledge management, e.g. the exchange of professional “know-how”, as reported in various previous papers. Under the pressure of a turbulent international market situation enterprises stress the importance of innovation in manufacturing areas. For instance, due to the drastic growing automation degree of manufacturing systems an intuitive interaction form is required, which enables the shop-floor personnel an active participation to the production without specific technical background, as well as to capture and retrieve systematically knowledge contents arising from the interaction process. The following contribution takes this topic into consideration and proposes an innovative ontology- based approach called ontological filtering system (OFS) based on methods and procedures to formalize natural language contents in a systematic way. By means of a so-called ontological network (ON) generic term forms used in the human–machine interaction (HMI) via natural language could be led back to a set of pre-defined terms. Thus, the ON consists, on the one hand, of a large number of generic natural language terms and, on the other hand, of a set of so-called key terms. The generic terms are defined, classified in semantic categories and chained together per semantic relations for a specific use in a particular domain of discourse. The key terms are used to build information on machine level and, therefore, have a formal definition. Through additional syntax roles and application-specific semantic constrains a systematic access and processing of natural language instructions is accomplished computationally. The proposed concepts have been set up and tested within an experimental testbed. The obtained results show a high system performance and encourage the research team to invest further efforts, in order to validate the system operational performances towards its industrial use at shop-floor level. Received: February 2005 / Accepted: January 2006