Remote Supervision of CIM-Systems using Hybrid Simulation (Control Software Technology) Armando Walter Colombo Grupo de Sistemas Robóticos e CIM, DEE - FCT - UNL Quinta da Torre, 2825-114 Monte de Caparica telef.:2948519 / fax: 2941253 / e-mail:
[email protected]
ABSTRACT Computers have long been applied to support many areas of production. However, the data has not yet been combined in an “integrated model” which is understood and used by all subsystems. A tool that has been used for design and analysis for many years and in different fields of computer-integrated-manufacturing is the simulation. Nevertheless, few work has been made to integrate it as part of an implemented system. This is only possible when supervisory control aspects of the production environment, i.e., control-, monitoring-, decision-making functionality, etc. can be performed by the simulation component itself. The principal goal is then to consider the simulation model of the system and its supervisory control itself as a new component of the CIM-structure.
system in order to analyse the influence of some effects such as (Fig. 1): 1) Changes of the product families; 2) Changes of the product design; 3) Changes of raw materials to be used for the production; 4) Changes of production methods; 5) Changes of the product quality and final cost of a product; 6) Etc. The more complex manufacturing systems become, the more important it is to test and validate them (their specifications) before they are built in reality. Moreover, the use of simulation tools allows to compare variants and alternatives and to evaluate the results of changes with little technical effort and without high costs. This is an efficient way to maintain development time and costs within reasonable bounds [6].
INTRODUCTION The resources and the operations of a manufacturing system can be seen as a set where each of them are closely related with each other and not isolated. The operation of these kind of systems is characterised by concurrency, competition and other type of relationships among resources. All these characteristics generate a lot of problems during the development process of the systems, that is, during the modelling, validation and implementation phases [1], [4]. A manufacturing system has to achieve some objectives related with its productivity, which can be defined by means of an optimal utilisation of resources, raw materials, energy, financial variables, work and technology. Moreover, the factor of the system defined by the necessary operators/hours has to be maximised. A manufacturing system can be classified as a discrete-event dynamic system. The control, monitoring and other supervisory functions of this kind of systems has to consider them within a CIM (Computer Integrated Manufacturing) concept. That is, from real-time control at the machine level to decision-making processes at the planning level, the supervisory system must cover all characteristics related with the structure and layout, mutual exclusion relationships between resources, errordetection, -diagnosis and -recovery processes, etc. This all depends on having the right tools available to help design-implementation process of the manufacturing system and its supervisory control system itself quickly and effectively [2], [3]. “Simulation-based methods” have been used to support the design and optimisation of a manufacturing
Traditional roles of simulation
C Simulation-model1
Management Simulation-model 2
Planning
I
Simulation-model3
System - Level Simulation-model4
Cell - Level Simulation-model5
M
Level of coordination control Level of maschine-control (local) Level of process interface Level of hardware-components (actuators)
New role of simulation
C I Simulation-model
M
Fig. 1: Traditional and new roles of simulation in relation with CIM-architectures Not only that. Later on, simulation models can become components of the real manufacturing environment in order to perform supervisory control functions and also to help maintenance of the system [7].
As a part of the implemented system, simulation is used in this case to process collected data, to provide analysis of the data into performance measures, and to generate and optimise supervisory control strategies under current or selected decision structures (Fig. 2). AN APPROACH FOR THE SUPERVISION OF CIMSTRUCTURES USING SIMULATION A new solution is the application of 3D-kinematic simulation with discrete-event simulation as a unique design-validation-implementation tool (hybrid simulation). The application of such a hybrid-simulationbased technology allows to cover:
1) Design of the structure of a production system within a CIM architecture; 2) Optimisation of layout, resource utilisation and material flow specifications (Fig. 2); 3) Design and validation of the supervisory control component of the system as an integrated part of the production environment; 4) Implementation of the system by means of the “hardware-in-the-loop” principle; 5) Use of different technologies to communicate the real production environment with a virtual (digital) production world represented by the hybrid simulation model running on a PC (Fig. 3) [5].
Simulation Material-Flow
Process
Movement of pallets Determination of control
Movements & task evolution Determination of control programs
Generation of production orders Movement of tools
Determination of possible tasks Evolution of process parameters
Determination of control strategies Generation of tool distributions
Determination of desviations Generation of process parameters
SUMMARY This paper proposes an expanded role for simulation in the computer-integrated-manufacturing field. The role is not a new one for systems engineers but is a new one for control software engineers and simulationists who are involved in discrete-event and 3D-kinematic simulation modelling. The extension -from a formal point of view- of simulation models developed for planning, scheduling and policy evaluation to the new supervisory control role is an exciting aspect of simulation that has been shown in the work developed by the authors.
Fig. 2: Simulation used as a CIM-component REFERENCES Discrete-event Simulation
3D-kinematic Simulation
Di sc ret
M Ori o e tni te
Virtual Production Environment
Remote Supervision
Real Production Environment
Fig. 3: Simulation used as supervisory control component of a CIM-system
[1] Colombo, A. W. & Carelli, R.: “Petri nets for designing manufacturing systems”. In: Computer-Assisted Management and Control of Manufacturing Systems, cap. 11. (S. G. Tzafestas (Ed.)). Springer Verlag, London, 1996. [2] Colombo, A. W.: “Development and implementation of hierarchical control structures of flexible production systems using high-level Petri nets”. In: Serie Fertigungstechnik Erlangen, vol. 82. (K. Feldmann (Ed.)). Meisenbach Verlag Bamberg. Germany, 1998. [3] Desrochers, A. & Silva, M.: “Introduction to the Special Issue on Computer Integrated Manufacturing”. In: IEEE Trans. On Rob. and Aut., 10 (2): pp 85-87, 1994. [4] Fanti, M.; Maione, B.; Piscitelli, G.; Turchiano, B.: “System approach to design generic software for real-time control of flexible manufacturing systems”. In: IEEE Trans. on Syst. Man, Cybern., 26 (2): pp 190-202, 1996. [5] Fishwick, P.: “Simulation model design and execution / building digital worlds”. Series in Industrial and Systems Engineering, Prentice Hall International, USA, 1995. [6] Monsef, Y.: “Modelling and simulation of complex systems / concepts, methods and tool”. In: Kerckhoffs E, Lehmann H, Pierreval H, Zobel R (eds.) Frontiers in Simulation Series. SCS Press, Erlangen/Ghent, 1997. [7] Pegden, C.: “Simulation: a look to the future”. In: Proc. of the 11th European Simulation Multiconference (ESM´97). Erlangen/Ghent. SCS Press, pp k/17-k/21, 1997.
