What is Human-Intelligence-Based Manufacturing?

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.

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.

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...

Flexible manufacturing systems: Present development and trends

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.

High quality and low-cost factors are among the main components of manufacturing. Nowadays, businesses need to keep up with technological innovations in order to meet these factors and survive in a competitive environment. These require the use of high-performance computer integrated manufacturing (CIM) technologies in order to manufacture products faster, inexpensively, flexibly and more efficiently. These technologies generally include computer-aided design (CAD) and computer-aided manufacturing (CAM), industrial robotics, automated material handling systems, group technology, flexible manufacturing systems (FMS), rapid prototyping (RP) operations and computer numerical controlled (CNC) machines. The main purpose of these advancements is to provide higher labour efficiency and flexibility, lower production time and a reduction of direct labour requirements. In this chapter, the effects of CIM technologies on manufacturing processes as well as product quality will be comparatively analysed. The effect of the internet of things (IoT), cyber-physical service (CPS) and cloud computing (CC) on smart manufacturing systems, which can be operated and integrated with CIM and contribute to increasing manufacturing efficiency by using information, will be revealed in detail.

A flexible manufacturing cell with vision has been provided with a modular control system based on microcomputers and local area network. The development tool, the shop floor control software, with its basic architecture is overviewed. The control system implementation is presented including the corresponding control modules. An expert routine and scheduling system using rule based simulation is presented. The pilot system described is used to demonstrate flexible manufacturing systems (FMS) technology. It can also be used as a test bed when developing different control methods and algorithms to reach an optimal behaviour of FMS. The current development efforts are concentrated on refining the knowledge based methods to increase the system flexibility and to respond better to various disturbances in the production. >

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.

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.

SUMMARYIn the context of computer-integrated manufacture (CIM), the paper describes the need for flexible “intelligent” machinery and the need for integrated and distributed software. Methodologies in obtaining appropriate solutions are discussed and related to two major SERC sponsored research programmes at Loughborough University, which concern (i) the design of a family of mechanical and control system modules to allow robots to be configured with user defined kinematic and dynamic properties, and (ii) the design of distributed hardware and software structures, based on internationally accepted communication protocols, to allow FAS's to be produced.In batch manufacture today's increased demand for product variety, requiring reduced lead times and work in progress, the need arises for computer-integrated manufacture (CIM). Similarly, in many conventional continuous flow manufacturing processes dramatic improvements in plant efficiency can be achieved by linking shop floor computer systems with computers performing management and design functions.Considerable research and development work has centred on flexible manufacturing systems (FMSs)3−1 which conventionally relate to metal cutting environments. Similarly the labour intensive nature of assembly operations has led to considerable interest in the design of flexible assembly systems.3.4 The principles embodied in FMS and FAS are translatable, being applicable to most manufacturing environments.To achieve flexible integrated manufacturing two major requirements can be identified, viz. (i) the need for flexible “intelligent” machinery, and (ii) the need for integrated but distributed software systems. This paper will consider future trends in (i) and (ii).

Integrating manufacturing resources planning (MRP II) with flexible manufacturing systems (FMS)

Rapid prototyping of complex systems and their control strategies is an important approach in system modeling, especially in early design stages. Naturally, these systems can be seen as a network of concurrently running communicating objects. A practical application field are flexible manufacturing systems (FMS) used in computer integrated manufacturing (CIM). An FMS consists of concurrently working machines which are connected by a computerized material handling system. This leads to well-known problems like scheduling and resource allocation where the usefulness of the fuzzy logic approach has been shown. Concurrent objects as a modeling paradigm enable the designer to describe the system's structure and behavior naturally on a high abstraction level. In this paper we argue that the control strategies based on complex hierarchical fuzzy rule bases fit nicely in the concurrent object based modeling view and, consequently, in a consistent design approach. Moreover, we introduce a suitable programming language (DFKI Oz), extended by a fuzzy library, which supports the described modeling approach. Validation of our approach is described by modeling a complex FMS in the field of car production.

One of the main problems in the manufacturing of goods is the necessity of flexibility due to the increase of the diversification of products which causes smaller lot sizes. The solution usually adopted is flexible automation through the utilization of CNC machine tools, flexible manufacturing cells and systems.

Developing computer integrated manufacturing: Major issues and problem areas