Modular control system with expert scheduling for flexible manufacturing

Modular control system with intelligent scheduling

Flexible manufacturing has been amazingly developed and now becomes one of the leading manufacturing facilities in all the industrial nations. Flexible manufacturing can be classified into several basic system configurations, and of these Flexible Manufacturing Cell (FMC) is dominant, and even the large-sized Flexible Manufacturing System (FMS) is to be in reality by integrating a group of FMCs, i.e. FMC-integrated system of modular type. In consequence, we need now the design methodology for flexible manufacturing, extremely the standardisation of basic FMCs. Within standardised FMC context, a facing engineering problem is to apply the graph theory to the description of FMC, so that the similarity evaluation for FMC can be carried out. On the strength of the similarity evaluation, it is possible to determine a group of standardised FMCs, which can facilitate the system design for flexible manufacturing as core modules to greater extent.

During the last decade (from the late 1970s to the beginning of the 1990s), manufacturing systems have significantly changed. Their function and performance have altered in a period of rapid development, mainly as a result of the application of the techniques of computer science. The new systems are termed either flexible manufacturing systems (FMS) or computer- integrated manufacturing (CIM). The advance of flexible manufacturing and its related technologies has been accompanied by a number of related developments, such as flexible manufacturing of a global network type, CIM incorporating personnel functions, skill-based manufacturing, and compact flexible manufacturing cells (FMC). These all have notable influences on the system configuration and operational technologies of flexible manufacturing: perhaps as a result, there is some confusion about their terminology. A number of differing nomenclatures are used (such as FMC, FMS, flexible or factory automation (FA), CIM and enterprise automation (EA), for the same fundamental technology.

Software developers often meet the problem of creating new components of an application that someone probably has already produced. Without having effective reuse tools usually it is more natural to create new components from scratch than to seek for useful elements in other programmes and/or systems.In the field of simulation of Flexible Manufacturing Systems (FMS) this issue often occurs, when different systems with some similar features have to be managed. FMSs are highly automated production systems with minimal human control. FMS usually consist Flexible Manufacturing Cells (FMCs). An FMC is considered as a group of one or more machine tools, robots, adjacent mechanical elements, tool and fixture supporting workstations and an internal transport system.The components of different FMSs and FMCs are the same type of machine tools, transfer equipment, etc. In the relevant aspects they usually differ from each other only in their amounts and working parameters. This fact itself breeds the idea of reuse of FMS and FMC simulation model elements.Simulation can be used for analysing the behaviour of an existing or would-be system. It is useful for calculating utilisation statistics, finding bottlenecks, pointing out scheduling errors, and even for creating manufacturing schedules. Simulation is a very effective technique for dynamic analysis, but it is short of optimising ability. A satisfactory solution can be obtained through modelling and simulating alternative approaches with iteration.There are many concepts, object classes, and lines of source code created, that could be reused in the new applications. Usage of reuse methodology and practice will reduce our efforts in developing new systems.In this paper the reuse of the components of simulation models in a hybrid simulation and scheduling system for new simulation applications will be introduced. This simulation-scheduler system has been implemented as a combination of a traditional simulation language (SIMAN/Cinema) and an intelligent expert environment (G2). The design methodology used for model development is based on the object-oriented Rational Rose CASE tool and on a use-case model.

Flexible manufacturing systems: Present development and trends

A flexible manufacturing cell (FMC) is part of a flexible manufacturing system (FMS). In general, a FMC consists of versatile workstations and storage buffers connected by a versatile material handling system. Owing to its versatile configurations and material routeing alternatives, effective modelling and control of the FMC is a complex and challenging problem. In order to resolve these difficulties, it is desired to establish a set of specifications for the FMC, then to develop a suitable model to analyse and control the performance of the FMC. Since the cell control is distributed in nature, the cell controller specifications are established in terms of cell functionality, software, hardware, and environment aspects. On the basis of the cell controller specification, a coloured timed Petri net (CTPN) is developed for modelling and control of the FMC. A cell controller including CNC controller, robot controller will be developed on the basis of the CTPN model. Finally, a FMC example is given to illustra...

Modern flexible manufacturing systems (FMS) are highly automated and flexible in which raw parts of various types are processed concurrently. Deadlock issue arises easily in these systems due to shared equipment usage and high production flexibility. It was indicated in Wysk et al . (Wysk, R., Yang, N. and Joshi, S., Detection of deadlocks in flexible manufacturing cells. IEEE Trans. Rob. Auto., 1991, 7, 853–859.) that when a manufacturing system is modelled by a digraph, existence of circuits in such a graph is a necessary condition for deadlock. Deadlock avoidance for systems with free choice in part routing has been well studied in the Petri net formalism, however, we have not found that it has been studied systematically in the digraph formalism. Because of choices introduced, part flow dynamics become much more complex. Based on our previous work Zhang et al . (Zhang, W., Judd, R.P. and Paul P., Evaluating order of circuits for deadlock avoidance in a flexible manufacturing system. Int. J. Prod. Res., 2006, 44, 5247–5259.), this paper presents a deadlock avoidance algorithm for FMS, which allows free choices in part routing by calculation of effective free space of circuits of the digraph model. The algorithm is highly permissive since the effective free space calculation captures more parts flow dynamics, especially when there exist multiple knots in the digraph model. And it runs in polynomial time once the set of circuits of the digraph is computed offline. Simulation results on selected examples are given. †This paper is an extended version of Zhang and Judd (2005) published in the Proceedings of 2005 American Control Conference, Portland, OR.

The possibilities of efficiency increse of working positions (WP) servicing by industrial robots (IR) in mechano-assembly Flexible Manufacturing Systems (FMS) by the workparts intermediate storage places (ISP) usage in Flexible Manufacturing Cells (FMC) are considered. The possible variants of WP service strategies in FMC with one-placed ISP usage are considered, the formal description of service strategies are given. The possible variant of classification of the WP service strategies by IR is proposed. The actuality of computer-aided search of optimal equipment service strategies in conditions of their multivariaty is determined.

GE Aircraft Engines, a major supplier of jet engines for commercial and military aircraft, has developed a fully integrated manufacturing facility to produce aircraft engine components in flexible manufacturing cells. This paper discusses many aspects of the implementation including process technologies, material handling, software control system architecture, socio-technical systems and lessons learned. Emphasis is placed on the appropriate use of automation in a flexible manufacturing system.

The current article introduces a solution to provide a decision support system (DSS) by combining artificial neural network (ANN) and fuzzy analytic network process (FANP) in order to select the flexible manufacturing system (FMS). In this context, a case study in factory of Tashgaz Company, specialists and MATLAB software are used. Given that today’s manufacturing systems are moving toward FMSs, and most of the similar pieces of research have used flexible manufacturing cells and AHP in definite mode, fuzzy numbers were used to compare criteria such as manufacturing rate, manufacturing accuracy, energy consumption, etc. for selecting manufacturing system, and a three-layered ANN was also used to create an expansion motor, and then, FANP was used for systemic selection instead of cell selection. And, the proposed model was implemented in a case study to explain more.

A flexible manufacturing system (FMS) is designed to achieve good productivity and low cost. The success of an FMS depends largely on effective production scheduling and control. However, it has been found that current manufacturing scheduling and control algorithms lack the flexibility to handle interruptions or resource breakdowns; hence, system performance drops dramatically and abruptly when interruptions occur. This research develops a computer-simulation-based framework of FMS scheduling and control system using the holonic concept. This framework can maintain stability and flexibility while accommodating system disturbance, increase throughput, reduce part flow-time and work-in-process inventory, and balance workload among identical workstations. The significance of this research is the investigation of an innovative approach to revolutionary advances of control technologies for advanced manufacturing systems, and to the revitalisation of control and scheduling algorithms used by existing FMSs. A case study has been provided to substantiate the effectiveness of this proposed framework.

In previous chapters we have, in the main, been concerned with a discussion about stand-alone turning and machining centre technology and related activities, such as tooling, workholding, and cutting fluids. This final chapter will consider how best to achieve a degree of automation using equipment and looking into the relative merits and drawbacks of such implementations. Prior to discussing the role of currently available FMC/S solutions, it is probably worth defining what we mean by “Flexible Manufacture” - whether one is describing either a cell, or a system. The definition favoured by the author is a modification to that proposed by an early investigation commissioned in America by the US Task Force Study: “Two or more machines coupled to either a robot, or an automatic transfer mechanism for the machining of parts”. This loosely describes, in the most basic terms, the requirements for a flexible manufacturing cell; in fact we must qualify this definition by saying that, according to an FMS builder, such systems must be “as rigidly flexible as possible!”. This means that either a cell or system should have a degree of flexibility within rigid constraints in order to perform in anything like a flexible manner.

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