Sven-Arne Andréasson

Towards a Truly Flexible Manufacturing System

Abstract This paper describes the concepts that must be considered in order to achieve a flexible manufacturing system that allows the introduction of new products and new resources without an extensive reprogramming of the control system. In contrast to most other approaches a bottom-up design is attempted. A control software structure based on generic resource models and the basic structure of a resource capability model are presented. A description of how to manufacture the products is also essential. Basic guidelines for a product model are given. Control algorithm aspects are discussed. Operator interface and system dependability are given consideration. Finally, a machining cell, used as a case study, is described.

Generic resource models and a message-passing structure in an FMS controller

This paper presents part of the results from a research project aimed at increasing flexibility and reusability of cell-control software. First to be discussed are the concept of flexibility and the advantages and disadvantages of various types of modular controllers. Then guidelines, generic models that describe the behavior of manufacturing resources, and a message-passing structure are given. The guidelines and the models should be used as the basis to support system developers when implementing modular control software for machining cells. The two main case studies examined to achieve the models are also briefly described.

Models for fault tolerance in manufacturing systems

The field of fault tolerance in computer science and engineering has been thoroughly investigated over a long period of time. A great number of different approaches have been presented on means for improving fault tolerance under certain error conditions in computerized systems. One important area that has introduced computers in order to enhance productivity, flexibility and economy, is manufacturing systems in order to acquire computer-integrated manufacturing (CIM). Using computers in a manufacturing system introduces new sources of difficulties, as well as providing new possibilities for overcoming erroneous situations that might disturb production. The aim of this paper, is to describe how the use of different configurations for a manufacturing system can improve fault tolerance. One specific erroneous situation which may occur in CIM is the partitioning of a network. This situation can be handled satisfactorily by using the suggested manufacturing system configurations. Additional improvements to fault tolerance can be achieved through the introduction of data buffers and material buffers, This approach is described in this paper.

Fault tolerance strategies in an existing FMS installation

This paper describes a case study of an FMS installation in which fault tolerance is modelled through the use of a description model called the General Recursive System (GRS). The GRS makes it possible to study different system configuration are described, called Hardware Configuration, Mission Configuration and Work Configuration. Fault tolerance, i.e. ways to overcome erroneous situations in the FMS installation, is obtained by choosing alternative system configurations. Alternative ways to describe different fault tolerance strategies within the FMS installation are illustrated through examples.

Fault tolerance in partitioned manufacturing networks

Fault tolerance is especially important for computer systems that require a high degree of confidence. Computer Integrated Manufacturing (CIM) is an area where computer systems must not be disturbed by uncontrolled failures. This article deals with two problems that are related to fault tolerance and network partitions in automated manufacturing systems.The first problem relates to the distribution of information in partitioned data networks in CIM systems. We indicate how to overcome this problem by using the material network as a redundant data network:The second problem relates to fault detection and diagnosis in manufacturing systems. The problem is whether the indication of a fault means that a production unit itself has actually broken down, or that the indication is instead due to disturbances in the transmission of material. That is, the production unit continues to operate propcrly despite indications to the contrary. We describe how the material network can be used for detection and diagnosis.

Achieving fault tolerance in factory automation systems by dynamic configuration

A model for automated manufacturing suited for achieving fault-tolerant production is presented. It is shown that the configuring of an automated manufacturing system can be viewed as three different kinds of configuration, namely, hardware configuration, work configuration, and mission configuration. These three configurations will serve as the basis for constructing algorithms for flexible manufacturing system control. Fault tolerance can be achieved through dynamic reconfiguration of the system. Together with a graphical editor based on the GRS (general recursive system) model, the dynamic configuration model will be a powerful and convenient tool.<<ETX>>

Failure semantics in intelligent manufacturing systems

The notion of failure semantics, or failure behavior, for computerized systems in general, and intelligent manufacturing systems in particular is discussed. Failure semantics is especially important when trying to ascertain the right type of fault tolerance. Failure semantics is a specification of the failure behavior that different parts demonstrate within a manufacturing system. New aspects of failure semantics that are relevant in intelligent manufacturing systems are reported.<<ETX>>

An Abstract Data Type for Fault Tolerant Control Algorithms in Manufacturing Systems

Abstract Fault tolerance will in the future become an important issue in manufacturing systems. This paper addresses the issues of supporting fault tolerance control in such systems. To achieve fault tolerance, there must be more than one way to configure the manufacturing system. We describe algorithms which dynamically distribute the work among the units. As a usable concept for the algorithms we introduce a data structure called a Mission Pool (MP). A manufacturing system can be viewed as a hierarchically structured system. We use a method which we call a General Recursive System (GRS), to model the manufacturing system. GRS gives a flexible and uniform way to model all the levels of the manufacturing system hierarchy.

Information Accessibility and Reliability Improvement in an Automated Kitting System

Abstract This paper describes information accessibility and its effects on the reliability of manufacturing systems. To do this a case study of an automated kitting system is used. Reliability in manufacturing systems is a measure on how well productivity goals have been met. An important aspect in the efforts to uphold reliability is the accessibility of production information. i.e., to have correct production information at the right place at the right time in spite of problems that might occur, e.g., data network partitions. If the information cannot be retrieved, or accessed, in a timely and correct manner, the reliability of the entire manufacturing system will decrease. The paper describes how information accessibility can be improved in two ways in a manufacturing system, either by using the material network as a redundant data network or by caching important data to a production unit.

Operator control activities in flexible manufacturing systems

Modern control systems often exhibit problems in switches between automatic and manual system control. One reason for this is the structure of the control system, which is usually not designed for this type of action. This article presents a method for splitting the control system into different control levels. By switching between these control levels, the operator can increase or decrease the number of manual control activities he wishes to perform while still enjoying the support of the control system. The structural advantages of the control levels are demonstrated for two types of operator activity; 1 control flow tracing; and 2 control flow alteration. These two types of operator activity can be used in such situations as when locating an error, introducing a new machine, changing the ordering of products or optimizing the production flow.