Synthesis of control implementation for discrete manufacturing systems

The paper presents the concepts and steps required to synthesize a correct control implementation for discrete manufacturing systems, starting from Grafcet specifications. A formal framework implementing the synthesis steps is also presented and illustrated with an example of a drilling system.     

Object-oriented simulation to support research in manufacturing systems

Simulation is a popular tool for modelling and analysing modern manufacturing systems. Choosing an appropriate simulation approach for a long-term research activity is not an easy task. This report discusses the issues involved in selecting a simulation approach to support research in real-time resource allocation decisions in manufacturing. A review of current directions in simulation software is presented. Specialized simulation needs of university-based research are described. After evaluating our needs with respect to the available options, we found that an object-oriented programming paradigm suits our needs best.     

An overview of discrete event simulation methodologies and implementation

Discrete event simulation has been widely used to model and evaluate computer and engineering systems and has been an on-going area of research and development. This paper presents an overview of the field. It covers specifications of discrete event systems, simulation methodology, simulation languages, data structures for event management, and front and backend support in simulation packages including random number generation and resource management. The emphasis of the survey is on simulation methodology and event scheduling, which forms the core of any simulation package or environment.     

Quantifying benefits of conversion to lean manufacturing with discrete event simulation: A case study

Simulation is used to assist in the decision to implement lean manufacturing principles at an existing assembly operation. Models are developed for the existing assembly system, as well as for a new system (of similar capacity), that employ these principles. In addition to the manufacturing processes, the associated warehousing, inventory management, transportation, and production control/scheduling systems are included in the model to enable the quantification of lean manufacturing's impact on the total system. Simulation experiments measure each system's resource requirements and performance, thereby quantifying benefits to be derived from applying the shop-floor principles of lean manufacturing.     

Easing the implementation and change of manufacturing software systems

The software systems that underpin contemporary manufacturing enterprises can become the single most inflexible part of an enterprise, constraining a business that has to evolve. This paper describes an approach to manufacturing software system creation which supports system evolution. It is based on the notion that raising the level of the computing infrastructure through the use of a domain machine, can remove the need to transform the clear abstractions and decomposition identified during design into the incomprehensible maze of programming language constructs which prove difficult to maintain.

The paper provides a comparison between two implementations of a system to control a printed circuit board manufacturing line, one based on a conventional approach and the other based on the authors manufacturing domain machine. Ease of change enabled by the domain machine is illustrated through measuring the degree of modification required to each system when incorporating a new solder paste print machine in the production line.     

Online modeling refinement for discrete event systems

Abstract

Machine identification of discrete event systems (DES) addresses the issue of identifying an unknown system based on an externally observed sample path from the unknown system. Online Modeling Refinement studies the continuing machine identification process when the observed sample path is updated incrementally. The notion of information embedded in a sample path is defined. By taking advantage of the structural similarity between successive observed sample paths, the computational requirement for the proposed online modeling refinement algorithm is kept minimal. An example is provided to show how identification results converge as the incrementally observed sequence is accumulated over time.     

Logical models of discrete event systems: A comparative exposition

The increasing complexity of man-made systems calls for new tools and techniques to model them efficiently and at the desired level of abstraction. Well-established modelling paradigms, such as finite state machines, petri nets, communicating sequential processes etc., which are borrowed from the fields of computer science and operations research, often lack certain essential features for capturing discrete event dynamics. New tools such as state charts, timed transition models, finitely recursive processes etc., are evolving to take into account some of these requirements. In this paper we first characterize such systems as well as typical problems related to them. We then discuss and critically evaluate several modelling frameworks through examples. At the end we provide a comparison among the frameworks and directions for future research.     

Guidelines for selection of manufacturing simulation software

Manufacturing systems have become progressively complex and costly. Simulation is increasingly being used as an analysis and evaluation method in the design and operation of these systems. The practical use of simulation in the manufacturing environment has resulted in an increase in the number of available software tools for manufacturing simulation. This paper provides guidelines for selecting manufacturing simulation software according to the intended purpose of software use. The basic criteria to be examined in the software evaluation process are listed together with the level of their importance for particular types of users.     

A computational control implementation environment for automated manufacturing systems

This paper presents a computational environment as a tool for supporting the implementation of control coding of an automated manufacturing system. The proposed environment considers a cyclic three-stage control development – modelling, synthesis and implementation – until the real system accomplishes the required specification, resulting in the automated and integrated manufacturing system. The research details the three stages and describes the steps executed for each one. The mathematical formalism used in this work is also presented, as a basis for control implementation. The implementation environment is proposed in order to validate the control structure of this formalism and to allow a progressive integration of control hardware and software. To submit to a test and validate the proposal environment, two experiments are performed, in two different manufacturing systems. Thus, it is demanded that the control system can be reconfigurable in a fast and reliable way.     

A progressive damage simulation algorithm for GFRP composites under cyclic loading. Part II: FE implementation and model validation

The FE implementation of FADAS, a material constitutive model capable of simulating the mechanical behaviour of GFRP composites under variable amplitude multiaxial cyclic loading, was presented. The discretization of the problem domain by means of FE is necessary for predicting the damage progression in real structures, as failure initiates at the vicinity of a stress concentrator, causing stress redistribution and the gradual spread of damage until the global failure of the structure. The implementation of the stiffness and strength degradation models in the principal material directions of the unidirectional ply was thoroughly discussed. Details were also presented on the FE models developed, the computational effort needed and the definition of final failure considered. Numerical predictions were corroborated satisfactorily by experimental data from constant amplitude uniaxial fatigue of multidirectional glass/epoxy laminates under various stress ratios. The validation of predictions included fatigue strength, stiffness degradation and residual static strength after cyclic loading.     

Value network modelling and simulation for strategic analysis: a discrete event simulation approach

The survival of a company nowadays depends on answering to a customer-driven economy, and therefore relies on the performance of its entire network of partners. Competition is no longer among companies nor among supply chains, but rather between networks of companies which form a value network. Thus, the need has arisen to analyse the performance of a network of companies, and include the customer-perceived value in the strategic decision-making process. This paper proposes a framework and a tool to model, simulate and analyse a value network as a decision support system. The method extends the SimulValor approach and language. The discrete event simulation tool relies on a developed value network simulation library. This paper presents a case study in the shoemaking industry to validate the proposed approach.     

The discrete null space method for the energy consistent integration of constrained mechanical systems. Part II: multibody dynamics

In the present work, rigid bodies and multibody systems are regarded as constrained mechanical systems at the outset. The constraints may be divided into two classes: (i) internal constraints which are intimately connected with the assumption of rigidity of the bodies, and (ii) external constraints related to the presence of joints in a multibody framework. Concerning external constraints lower kinematic pairs such as revolute and prismatic pairs are treated in detail. Both internal and external constraints are dealt with on an equal footing. The present approach thus circumvents the use of rotational variables throughout the whole time discretization. After the discretization has been completed a size‐reduction of the discrete system is performed by eliminating the constraint forces. In the wake of the size‐reduction potential conditioning problems are eliminated. The newly proposed methodology facilitates the design of energy–momentum methods for multibody dynamics. The numerical examples deal with a gyro top, cylindrical and planar pairs and a six‐body linkage. Copyright © 2006 John Wiley & Sons, Ltd.     

State estimation of discrete event systems for RUL prediction issue

This paper concerns Remaining Useful Life (RUL) estimation of discrete event systems. For that purpose, physics-based models with partially observed stochastic Petri nets are used to represent the system and its sensors. The advantage of the proposed modelling approach is to provide a realistic representation of the system, including the interaction between the normal behaviours and the failure processes. From the proposed modelling and collected measurements, timed trajectories, which are consistent with the observations, are obtained. Based on the event dates, our approach consists in evaluating the probabilities of the consistent behaviours using probabilistic models. State estimation is obtained as a consequence. The most probable future degradations, from the current state, are then considered and a method for fault prognosis is presented. Finally, the prognosis result is used to estimate the RUL as a time interval. A case study is proposed to show the applicability of the proposed method.     

Optical implementation of fuzzy-logic controllers. Part II

In part I of a previous study [Appl. Opt. 37, 6937 (1998)] we introduced what is believed to be a novel two-dimensional (2-D) fuzzy-logic optical controller. The complexity of such a setup when we deal with an N-dimensional control procedure leads to a more compact version both in planning demands and in space. Viewing the pros and cons of the 2-D setup, we seek a simpler model and find it in a one- dimensional (1-D) multilayer setup. Here we explain the process of finding the optimal 1-D setup and support the concept with true optical results. The new 1-D optical controller is modular and easy to build, and the results that it yields are quite satisfactory.     

Quality and exposure control in semiconductor manufacturing. Part II: Evaluation

The purpose of this article is to test the performance of a heuristic algorithm that computes a quality control plan. The objective of the tests reported in this paper is twofold: (1) to compare the proposed heuristic algorithm (HA) to an optimal allocation (OA) method; and (2) to analyse the behaviour and limitations of the proposed HA on a scale-1 test with a before/after test. The method employed to evaluate this algorithm is based on comparisons: 1. The first test illustrates the method and its sensitivity to internal parameters. It is based on a simplified case study of a product from the semiconductor industry. The product is made up of 1000, 800 and 1200 wafers incorporating three different technologies. The production duration is 1 week, and three tools were involved in this test. The behaviour of the proposed algorithm is checked throughout the evolution of the model parameters: risk exposure limit (R_L ) and measurement capacity (P). The quality control plan for each tool and product are analysed and compared to those from a one stage allocation process (named C ⁰) that does not take into account risk exposure considerations. A comparison is also performed with OA.

2. The second scale-1 test is based on three scenarios of several months of regular semiconductor production. Data were obtained from 23 etching and 12 photolithographical tools. The outputs provided by the HA are used in the sampling scheduler implemented at this plant. The resulting samples are compared against three indicators.

The results of these comparisons show that, for small instances, OA is more relevant than the HA method. The HA provides realistic limits that are suitable for daily operations. Even though the HA may provide far from optimal results, it demonstrates major MAR improvement. In terms of the maximum inhibit limit, the HA achieves better performances than C ⁰, and they are strongly correlated to R_L and to the control capacity. The article concludes that the proposed algorithm can be used to plan controls and to guide their scheduling. It can also improve the insurance design for several levels of acceptance of risk.     

A study of scheduling rules of flexible manufacturing systems: A simulation approach

This study examines the effects of scheduling rules on the performance of flexible manufacturing systems (FMSs). Several machine and AGV scheduling rules are tested against the mean flowtime criterion. In general, scheduling rules are widely used in practice ranging from direct applications as a stand-alone scheduling scheme to indirect application as a part of complicated scheduling systems. In this paper, we compare the rules under various experimental conditions by using an FMS simulation model. Our objective is to measure sensitivity of the rules to changes in processing time distributions, various levels of breakdown rates, and types of AGV priority schemes. A comprehensive bibliography is also presented in the paper.     

SmartSim: An object oriented simulation program generator for manufacturing systems

SmartSim is a simulation environment that can be used by manufacturing engineers as a computer aided design tool for designing manufacturing systems. SmartSim has been found to increase the ease with which simulation models can be constructed and modified. It is able to accomplish this due to the synergy of an icon-based user interface, availability of interactive animation, support for an object-oriented simulation world view, inheritance, a built-in taxonomy of simulation objects, and facilities for subsystem construction, archiving and reuse.     

A new directional simulation method for system reliability. Part II: application of neural networks

A challenge in directional importance sampling is in identifying the location and the shape of the importance sampling density function when a realistic limit state for a structural system is considered in a finite element-supported reliability analysis. Deterministic point refinement schemes, previously studied in place of directional importance sampling, can be improved by prior knowledge of the limit state. This paper introduces two types of neural networks that identify the location and shape of the limit state quickly and thus facilitate directional simulation-based reliability assessment using the deterministic Fekete point sets introduced in the companion paper. A set of limit states composed of linear functions are used to test the efficiency and possible directional preference of the networks. These networks are shown in the tests and examples to reduce the simulation effort in finite element-based reliability assessment.