Concurrent object based modeling of fuzzy strategies

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.

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

Deadlock/livelock problems can cause catastrophic results in flexible manufacturing systems (FMS) by forcing them to stop production processes at an unpredictable stage of production. Therefore, they must be handled properly in order to obtain flawless production in FMS. Petri net (PN) based deadlock/livelock studies for FMS have been widely carried out to obtain live PN models. When a PN model is live, this ensures that the modelled FMS is deadlock-free. Firstly, an uncontrolled (plant) PN model is constructed for the FMS suffering from deadlocks/livelocks. Then reachability graph (RG) analysis of this PN model is carried out to provide all possible reachable states of the modelled system. An RG of a PN model of an FMS suffering from deadlock/livelock problems can be split into the live zone (LZ) and the deadlock zone (DZ). The former is the set of system states considered to be legal (good), while the latter is the set of system states regarded to be illegal (bad). The LZ represents the optimal (maximally permissive) system behavior that must be provided by an optimal control policy. Generally, in PN based liveness studies, a liveness enforcing supervisor (LES) consisting of a set of control places (CP) is computed. Then the controlled (closed-loop) PN model is obtained by merging the plant PN model and the LES. If the number of reachable live states of the controlled PN model is the same as the ones that exist in the LZ, then the controlled model is optimal. Otherwise, it is suboptimal. The greater the number of live reachable states of the RG, the more products to be produced within the FMS. Therefore, the number of reachable live states of the controlled PN model is considered as a quality measure. It defines the behavioral permissiveness of the controlled model. In the literature, to verify the behavioral permissiveness of the PN models, the PN tool called INA (Integrated Net Analyzer) has been widely used. Recently, by means of INA, a method was proposed to compute the number of states within the LZ and the DZ of a given PN model suffering from deadlocks/livelocks. Unfortunately, INA cannot compute RGs of large PNs having a few millions of states. Therefore, in this paper by means of TINA (TIme petri Net Analyzer), an alternative faster and much more efficient method is proposed for the computation of the number of states within the LZ and the DZ for PN models with large RGs. In addition, in order to enable the development of new PN based deadlock prevention methods, further computations are also proposed. These include the computation of the set of states in the DZ, LZ and first met bad markings (FBMs) for a given PN model suffering from deadlocks/livelocks. The applicability and the effectiveness of the proposed methods are demonstrated by considering several well-known examples of FMS from the relevant literature.INDEX TERMS Flexible manufacturing systems (FMS), deadlock, deadlock prevention, Petri Nets (PN), liveness enforcing supervisor (LES), PN computation tools.

Flexibility of flexible manufacturing systems (FMSs) has been considered as an effective tool to compete in the present manufacturing environment. Enormous research efforts have been made to harness the benefits of flexibility through superior control strategies. While modeling flexibility and control strategies, researchers have mostly assumed an information system that can provide real-time control. Literature qualitatively reports that the real-time control can be highly capital intensive and difficult to achieve. This paper focuses on FMS operating under review-period (RP)-based control and presents a combined study of routing flexibility (RF), control strategies, and information system under Taguchi's method using simulation. RP-based control for FMS has been compared with real-time control. This paper contributes an approach for the decision maker to study the performance of an FMS operating under RP control and to identify the periodicity (time interval) of RP that will not deteriorate its performance in comparison to real-time control. It also helps the decision maker to reach a tradeoff between RP-based control and real-time control. The results show that RP-based control can be effectively implemented on an FMS having lower RF level. RP-based control can outperform real-time control with a superior control strategy and smaller RP size. The results under Taguchi's method suggest that the RF and control strategy should have maximum relative percentage contributions in FMS performance, whereas contribution of the RP (information system) should be minimum. Increasing the relative percentage contribution of the information system may deteriorate the performance of FMS. The information system is needed as a catalyst to facilitate the contributions of other factors in improving the FMS performance and not its own contribution. © 2007 IEEE.

Some Managerial Issues Concerning Implementation and Maintenance of Flexible Manufacturing Systems- An Indian Perspective

In this study, a new and simple alternate routing heuristics, which would be superior to the conventional routing strategies in terms of various system performance measures and easier to apply practically, was presented. Because of the high investment costs of FMSs, it is also definitely worth choosing the best operating policy and system configuration by analyzing the system model, and adapting to changes over time. In future research, the heuristic rule base will be extended to include other supplementary constraints such as dynamic tool allocation and sequence dependent setup times. For practical implementation of the proposed decision support system, additional research in the area of human interfaces could be useful to develop more user friendly system which automatically constructs simulation model of the system from the knowledge base of a production system.

A KNOWLEDGE BASED SIMULATION APPROACH FOR REAL-TIME MODEL VALIDATION

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.

An FMS is a typical real-time concurrent system composed of a number of computer-controlled machine tools, automated material handling and storage systems that operate as an integrated system under the control of host computer(s). The growing demand for higher performance and flexibility in these systems and the interlocking factors of concurrency, deadline-driven activities, and real-time decision making pose a significant challenge to FMS design, especially in terms of control and scheduling. A formal engineering approach that helps handle the complexity and dynamics of FMS modeling, design and analysis is needed. A real-time architectural specification (RAS) model and its application in the modeling of flexible manufacturing system (FMS) are presented. RAS combines mature operational and descriptive formal methods, in particular time Petri nets (TPN) and real-time computational tree logic (RTCTL), to form an integrated system model for architectural specification and analysis of real-time concurrent systems such as FMS. The contribution of RAS is twofold: First, it provides a formal system to systematically maintain a strong correlation between (real-time) requirements and design and to verify the conformance of the design to the requirements, which helps enhance traceability and thus to help us to achieve high assurance in design. Second, it offers better scalability in modeling and analysis, which provides an effective way to deal with complexity in the application of formal methods. These two features together make RAS a suitable model for the design of FMS.

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).

Discrete event simulation (DES) is a well-recognized technique in evaluating the performance of flexible manufacturing systems (FMS). FMSs lend themselves to such a method because of the inherent complex element interactions, the queueing principles involved and the changes of state that occur within them. In particular, to attempt to rely on intuition, experience or static optimization alone can lead only to a limited FMS design solution. DES allows the analyst to recognize the dynamics of FMS while also allowing him to interact with the system model in such a way that changes in, say, layout, system design and operation strategies (scheduling, routing, etc.) may be assessed. Hence, “what if?” scenarios are orchestrated [1]. The analyst not only is able to make changes to the simulation rules but also is capable of altering data records and displays.

A real-time interactive model of a flexible manufacturing system (FMS) is described, with emphasis given to the system's structure and to the model's interactive component. An attempt is made to illustrate how the model can be used to extract knowledge concerning human strategies at supervisory control of an FMS, knowledge that would otherwise be largely inaccessible. This knowledge is considered essential for the development of expert systems that would serve as supervisory controllers of FMSs.

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts’ sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

PurposeThe generic design environment for a flexible printed‐circuit board assemblies (PCBA) remanufacturing cell contains four interrelated complex design domains. Mechanical design domains are really complex and the use of well‐proven mechanical product design methodologies does not help the designer. Hence, this paper aims to develop a generic systematic design methodology for a flexible PCBA remanufacturing cell.Design/methodology/approachThe study investigates the use of conventional mechanical product design techniques for the design of a flexible PCBA rework (remanufacturing) cell. It indicates problems and the weaknesses when conventional product design techniques are used for the development of flexible manufacturing systems (FMS). It then provides a new systematic mechanical design methodology for designing a flexible PCBA rework (remanufacturing) cell. The design methodology is intended to be generic in order to apply successfully to any FMS design.FindingsConventional product design methodology cannot be used directly for the design of a flexible PCBA remanufacturing cell. Hence, two design methodologies were developed: the generic FMS mechanical design methodology and a specific FMS design methodology for a PCBA rework cell. The first one was developed based on the tasks of the conventional product design process integrated with new design tools. The generic design methodology was then extended to obtain the second methodology for a PCBA rework cell design. Both of the methodologies were applied to a flexible PCBA rework cell design problem. Both design methodologies eliminated unusable design solutions at the early design stages of the conceptual design process and made the design process easier.Practical implicationsThe generic and specific design methodologies provide a better design environment, even for less specialized FMS designers.Originality/valueThe design methodologies may help for the commercialization of a flexible PCBA remanufacturing cell that may be used for SM rework and assembly.

Designing products for easy assembly and disassembly during their entire life cycles for purposes including product assembly, product upgrade, product servicing and repair, and product disposal is a process that involves many disciplines. In addition, finding the best solution often involves considering the design as a whole and by considering its intended life cycle. Different goals and manufacturing plan selection criteria, as compared to initial assembly, require re-visiting significant fundamental assumptions and methods that underlie current assembly planning techniques. Previous work in this area has been limited to either academic studies of issues in assembly planning or to applied studies of life cycle assembly processes that give no attention to automatic planning. It is believed that merging these two areas will result in a much greater ability to design for, optimize, and analyze the cycle assembly processes. The study of assembly planning is at the very heart of manufacturing research facilities and academic engineering institutions; and, in recent years a number of significant advances in the field of assembly planning have been made. These advances have ranged from the development of automated assembly planning systems, such as Sandia's Automated Assembly Analysis System Archimedes 3.0{copyright}, to the startling revolution in microprocessors and computer-controlled production tools such as computer-aided design (CAD), computer-aided manufacturing (CAM), flexible manufacturing systems (EMS), and computer-integrated manufacturing (CIM). These results have kindled considerable interest in the study of algorithms for life cycle related assembly processes and have blossomed into a field of intense interest. The intent of this manuscript is to bring together the fundamental results in this area, so that the unifying principles and underlying concepts of algorithm design may more easily be implemented in practice.