Flexible manufacturing systems

Flexible manufacturing is an important new technology. The article explains the concept of flexible manufacturing, outlines its worldwide use, and comments on development trends.     

Flexible manufacturing systems in Europe

Flexible manufacturing systems can be classified as lines, networks, and cells. Current research efforts are concentrated on tool flow systems, process monitoring, and system control. To minimize economical and technological risks already in an early stage of system planning software for simulation and economic evaluation has been realized. The economy of different types of manufacturing cells are compared.     

Structured intelligence for self-organizing manufacturing systems

This paper deals with fuzzy scheduling and path planning problems by genetic algorithms. We have proposed a self-organizing manufacturing system (SOMS) that is composed of a number of autonomous modules. Each module decides output through interaction with other modules, but the module does not share complete information concerning other modules in the SOMS. Therefore, we require structured intelligence as a whole system. In this paper, we consider a manufacturing line composed of machining centres and conveyor units. The manufacturing procedure can be divided into a sequence of three modules: (a) tool locating module, (b) scheduling module, and (c) path planning module. The tool locating problems have been already solved. In this paper, we first solve the scheduling problem as global preplanning. Here we assume that the processing time is not constant, because some delay may occur in the machining centres. We therefore apply fuzzy theory to represent incomplete information abou t the machining time. We solve the fuzzy scheduling problem with a genetic algorithm. After global preplanning, the path planning module transports materials and products. Next, the scheduling module acquires the actual processing time of each machining centre. Based on the processing time, the schedule module generates a fuzzy number for the processing time. We discuss the effectiveness of the proposed method through the computer simulation results.     

Emergence of intelligence in next-generation manufacturing systems

In the paper we propose a fundamental shift from the present manufacturing concepts and problem solving approaches towards new manufacturing paradigms involving phenomena such as emergence, intelligence, non-determinism, complexity, self-organization, bottom-up organization, and coexistence with the ecosystem. In the first part of the paper we study the characteristics of the past and the present manufacturing concepts and the problems they caused. According to the analogy with the terms in cognitive psychology four types of problems occurring in complex manufacturing systems are identified. Then, appropriateness of various intelligent systems for solving of these four types of problems is analyzed. In the second part of the paper, we study two completely different problems. These two problems are (1) identification of system in metal forming industry and (2) autonomous robot system in manufacturing environment. A genetic-based approach that imitates integration of living cells into tissues, organs, and organisms is used. The paper clearly shows how the state of the stable global order (i.e., the intelligence) of the overall system gradually emerges as a result of low-level interactions between entities of which the system consists and the environment.     

Flexible manufacturing systems—Manpower problems and policies

Flexible manufacturing systems can be seen as the latest stage in the automation of small batch production. The prevealing manpower approach to these systems is characterized by a hierarchical and highly specialized job structure. An alternative is to have a homogenous job structure on an advanced skill level. The latter approach increases problems and costs of implementation processes; however, it may ensure higher utilization times, more flexibility, and better quality in the long run. Trends in small batch and process manufacturing, the labor market, and union policies provide opportunities for the alternative approach.     

Flexible integrated computer-aided manufacturing systems increase productivity

In the field of metal cutting operations, the aircraft and helicopter division of MBB has closed the gap between theory and practical application in manufacturing by installing a flexible integrated CAM-system. This system covers the needs of a mid-volume, mid-variety production. Analysis of the problem leads to the conclusion that it is insufficient to aim towards stand-alone automated production solutions; rather an overall strategic concept of operational integration is required. It is also evident that such a concept must comprise the fields of engineering and production planning as well as that of manufacturing. This article examines the goals which were defined at the project's onset the preconditions which had to be considered and the solution which had been generated. It also illustrates the main system components and analyzes their economic efficiency.     

制造执行系统柔性应用框架研究

针对制造执行系统应用开发的复杂性,提出了一个制造执行系统的柔性应用框架。在多层服务体系结构的基础上,该应用框架通过运用面向过程的对象分析技术、基于规则的事件服务机制和业务工程分析技术,提供可重构的组织结构、可伸缩的业务流程和可定制的业务规则,使得系统开发和实施的柔性得以提高。同时,运用该柔性框架,对一个实例进行分析和实现。     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.     

Using computer controlled physical models to analyze computer integrated manufacturing systems

It is usually difficult to design and install complex computer integrated manufacturing (CIM) systems without a large amount of time spent on debugging. In many cases miniature computer controlled physical models can provide information that reduces the time spent in the design and installation of larger systems. This paper describes how miniature physical models can be used to help industrial engineers design and install CIM systems.     

Transaction language characteristics and user/computer interfaces in manufacturing systems

A problem-oriented language for manufacturing control and operator guidance within production systems is described. In-process control and the human/computer communication is combined and based on transactions. These are preplanned instruction sequences for a machine and an operator which are constructed logically. The commands of this language are everyday to reduce the error rate. Experimental characteristics of the language, of the dialogue types and of the system performance are presented. The usage of this professional language in local networks controlling production processes is demonstrated.     

Learning process in a class of computer integrated manufacturing systems with parametric uncertainties

The paper is concerned with a class of manufacturing processes described by a relational knowledge representation containing unknown parameters. Two kinds of the manufacturing processes with different structures of material and task flow are considered. For these kinds the algorithms of learning and control for the central decision support computer system integrating the manufacturing process are presented. The learning process consists in using the results of step by step knowledge validation and updating to the determination of the current control decisions. The idea of learning described in the paper may be considered as a generalization of the known concept of the adaptive control using the results of current identification. Simple illustrative examples, results of simulations for a simple case and additional remarks concerning related problems are included.