An integrated multidimensional process improvement methodology for manufacturing systems

In this paper, an integrated multidimensional process improvement methodology (IMPIM) is formulated to address the yield management, process control and cost management problems of a manufacturing system. Simulation is used as a platform to implement the integrated multidimensional process methodology by incorporating the productivity, quality and cost dimension in a unified, systematic and holistic manner. Total Quality Management (TQM) addresses the quality parameters and Activity-Based Costing is used to manage the cost dimension of the system. Discrete event simulation is then used as a platform to perform process reengineering (Business Process Reengineering) and process improvement (TQM). The general implementation framework of the IMPIM is given with a step-by-step explanation. A conceptual discussion is also provided for the integrated methodology. The generic IMPIM is then formulated and the detailed implementation procedures for two case studies are compared with the generic methodology.     

A methodology for evaluating computer integrated manufacturing technologies

The decision to invest in advanced manufacturing technology is often made at the strategic level. The technique to be used to justify these decisions should have the ability to incorporate the non-quantifiable, intangible benefits associated with implementing these technologies. Among the methods introduced recently, the linear additive models have received considerable attention. This paper reviews a linear additive method which can be used to evaluate long-term and short-term automation manufacturing investment alternatives. The paper also concentrates on those cases in which some common characteristics of available alternatives are assumed to be independent.     

Evaluation and optimisation of integrated manufacturing system operations using Taguch's experiment design in computer simulation

The application of computer simulation have been proposed and implemented to solve the problems of variation in integrated manufacturing systems. However, a simulation model only acts as a tool in examining performance. It is essentially a trial and error methodology, and does not directly provide explanations for observed system behaviours. Therefore, in this paper the use of Taguchi's Experiment Design in simulation is studied to solve decision-making problems in integrated manufacturing systems. In particular, we use the case of a steel soaking-pit/rolling-mill plant to demonstrate how the approach works. The results reveal that this approach can take into account the evaluation and optimisation of operating conditions in complex systems simultaneously.     

A methodology for the evaluation of integrated manufacturing systems

The evaluation and selection of equipment for today's integrated manufacturing systems presents management with a complex multiattribute decision problems. This paper presents a spreadsheet based methodology that permits the incorporation of both monetary and non-monetary factors into the decision making process.     

An integrated methodology for fixture design

In this paper, a methodology to perform fixture design as an integrated aspect of process planning is proposed. A three-phase methodology for the fixture design activity has been developed. The three phases include predesign analysis (phase I), functional analysis (phase II), and productivity improvement (phase III). In phase I, the product design information is studied, and initial fixture design aspects are developed. In phase II, the clamping and location aspects of fixture design are addressed for the given initial process sequence and product design information. Phase III involves studying ways to increase the productivity including using simultaneous machining approaches, multiclustering, use of specialized jigs, etc.     

An integrated system for computer aided design and analysis of multibody systems

An integrated system for design and analysis of multibody systems has been developed and is described in this paper. The use of the system is demonstrated through the example provided. The system consists of a commercially available CAD program and a multibody system analysis code developed at the Royal Institute of Technology in Stockholm, These tools are integrated using a relational database, the structure of which was developed at Luleå University of Technology, in order to get a complete system for design and analysis of multibody systems. The main gains from the integrated system are the possibilities of using calculated component data like mass and moment of inertia from the CAD program in the simulation models, the automatic formulation of input files for the analysis code, and finally the visualization of simulation results using the surface data of the solid models. The interactive structured query language (ISQL) of the database management system provides the possibility of examining the components of the multibody system during the design work and before any simulation is performed.     

An integrated form-feature-based design system for manufacturing

Much of the knowledge that is applied in or communicated between design and manufacturing activities is primarily shape based or shape indexed. Previous attempts to acquire and organize shape knowledge have been mostly concentrated on feature recognition from solid models, group technology (GT) coding schemes, and feature-based modeling. This paper presents the development of an efficient form-feature-based modeling system, and addresses the important issue of utilizing feature information for manufacturing, which has not been extensively discussed by previous work. In this paper we first present a Euler operator-based approach for efficient and effective form-feature encoding and manipulation in a feature-based design environment. Subsequently, a hybrid representation scheme called enhanced CSG tree of feature (ECTOF), which integrates feature model with solid model in a tree structure, is discussed. A feature interference resolution methodology to maintain the correct and consistent feature information in an ECTOF is also deliberated. Finally, we present a machinability-checking module, which employs global accessibility criteria to analyze a feature's machinability on a three-axis machining center. By developing feature interference resolving and machinability testing techniques and integrating with an efficient feature-based design system, this research makes the development of an integrated feature-based design and manufacturing system possible.     

Expert systems for manufacturing cell simulation and design

Computer Integrated Manufacturing (CIM) is approached by means of the application of Computer Aided Design (CAD), Computer Aided Manufacturing (CAM) and other CA techniques, methods and programs/program systems. These programs are often implemented as knowledge-based, or expert systems and in this way they became typical examples of engineering application of artificial intelligence. The production task of CIM systems is solved by using flexible manufacturing systems (FMSs). FMSs built up from smaller, complex units, i.e. from flexible manufacturing cells (FMCs) have several advantages. The design and the operation of manufacturing systems need new, sophisticated methods to utilize all the embedded benefits of the sophisticated and expensive elements installed for production purposes. New methods like knowledge processing technology, cooperative problem-solving techniques, etc., offer wide possibilities to design more reasonable systems. This paper describes prototype expert systems that make use of different knowledge-based tools and techniques to design (configure, reconfigure) and simulate manufacturing cells, taking into consideration technological plans and other relevant information.     

The methodology for design of effective computer-integrated manufacturing systems

This paper the combines group technology and the simulation approach to the design of an effective material flow system in production processes of a discrete nature. The GT method shows how to find operational groups using a classification system, and how to design GT cells to achieve their maximal effectiveness. Dynamic modelling and simulation of the designed system are emphasized as the tools for checking the behavior of the designed structure and measuring its effectiveness. An example of an application of the suggested approach in the case of a textile machine factory is discussed.     

Organizing for computer integrated manufacturing

Good organizational structure design is increasingly important in Computer Integrated Manufacturing (CIM) environments. It can reduce problems due to the changing roles of organizational units and information technologies. This paper presents observations about organizational structures for CIM and discusses the basic approaches. An initial framework for evaluating CIM organizational structures is proposed and is used to evaluate the basic structures.     

Modelling and simulation of dynamically integrated manufacturing systems

Fluctuations in demand patterns and products?? mixes, driven by continuous changes in customer requirements, are inducing significant changes on the operations of manufacturing organisations. How to respond to such changes rapidly and at minimum cost constitutes a major challenge for manufacturers. The DIMS project (Dynamically Integrated Manufacturing Systems) has developed an agent-based approach that enables manufacturing systems to be modelled using multi-agent systems such that optimal and timely responses to changes are generated from the interactions taking place within the multi-agents systems. This approach also incorporates a distributed discrete event simulation mechanism that enables ??what-if?? system configurations that have been generated through agent interactions to be evaluated dynamically for system restructure. This paper presents the approach with particular focus on the distributed simulation mechanism.     

Using computer controlled physical models to analyze computer integrated manufacturing systems

It is usually difficult to design and install complex computer integrated manufacturing (CIM) systems without a large amount of time spent on debugging. In many cases miniature computer controlled physical models can provide information that reduces the time spent in the design and installation of larger systems. This paper describes how miniature physical models can be used to help industrial engineers design and install CIM systems.     

Controller area network (CAN) for computer integrated manufacturing systems

Communication acts a central role in computer-integrated manufacturing (CIM). The choice of communication system widely determines the capability and productivity of a factory as a whole. Moreover, in the implementation of CIM systems, the costs associated with the interconnection of the individual CIM components are very important. In CIM, communication is largely used to control programmable manufacturing equipment. Here, the time requirements are high, and error-free data transmission is a necessity. Fieldbuses are special form of local area network dedicated to applications in the field of data acquisition and the control of sensors and actuators in machines or on the factory floor. Many fieldbus standards exist in the market today. Each of them has been invented at different periods by different companies and for different purposes. Controller area network (CAN) is one of the most popular fieldbuses. The highest advantages of CAN are its low cost, abundance of silicon technology, and reliability in networking multiple real-time systems. CAN is a multimaster bus topology and has shown to be very efficient medium for error detection and fault tolerance. CAN's technical specifications are defined in the ISO/OSI network layer spans just two layer of the model. CAN specifies, in many innovative ways, the physical signaling over the media, data formats, timing, error recovery, protocols and arbitration. It does not define the media itself and its connectors, and also the upper layers (usually software) of the model.     

An intelligent simulation environment for manufacturing systems

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor. Despite the fact that there are a great number of simulation tools, most of them do not take into account the specific requirements of the “new manufacturing era” such as distributed organization, interoperability, cooperation, scalability, fault tolerance and agility. On the other hand, Multiagent System technology has demonstrated its utility in manufacturing system modeling and implementation. Agenthood features such as proactivity, reactivity, and sociability may also be useful for associating them with the specific simulation needs of the new changing requirements for manufacturing systems. In this paper, an Agent-supported Simulation Environment for intelligent manufacturing systems is presented. The different roles that are played by the agents of the simulation environment are defined taking into account the specific dynamic features in manufacturing simulation and the requirements of the new manufacturing era. Moreover, the interaction and cooperation scenarios among these agents are specified to facilitate manufacturing simulation in an appropriate and flexible way. A detailed evaluation study, with regards to the new manufacturing era requirements, demonstrates the advantages of the proposed approach over current state-of-the-art proposals.     

Implementation of a dynamic scheduler for apparel computer integrated manufacturing systems

A major problem faced by the typical apparel manufacturer in day-to-day operations is the need for an effective scheduler to determine actions required because of operator and/or machine non-performance. The dynamic resource allocation system (DRAS) scheduler described in this paper is the natural outgrowth of previously funded research related to the design, development, technology transfer and installation of a CIM system in an apparel plant. The already developed CIM system provides a way for the DRAS scheduler (described in this paper) to change a production process dynamically. The implementation and modeling approach of the scheduler is described. The underlying system model is based on Petri nets and object-oriented databases. Petri nets provide a dynamic model of the CIM system, while object-oriented databases provide necessary information about system components and overall system activity. The data from the CIM system is used by the scheduler in the simulation mode. The daily production plan is used as a guideline to determine how to react to and correct production problems.     

A methodology to design virtual cellular manufacturing systems

Virtual Cellular Manufacturing System is a new type of cellular system that emerged as a promising alternative for designing cells in real time. The problem is complex and time consuming NP-hard problem in its nature. This study was conducted to design virtual cells that maximizes similarity index and minimizes lead time. A mathematical model and an effective solution procedure were proposed. Several randomly generated data sets were used along a case study to test the performance of the proposed approach. The effects of inherent parameters of virtual systems were investigated and compared by using particular performance measures.     

A methodology of forming manufacturing cells using manufacturing and design attributes

This study develops a methodology for forming machine cells using part's design and manufacturing dissimilarities. The proposed methodology is divided into two sequential phases. In phase I parts are grouped into families based upon their design and manufacturing attributes. In phase II, the machines are grouped into manufacturing cells based on relevant operational costs and the various cells are assigned part families using an optimization technique.