Donghun Kang

Parameterized activity cycle diagram and its application

The classical activity cycle diagram (ACD), which is a bipartite directed graph, is easy to learn and use for describing the dynamic behavior of a discrete-event system. However, the complexity of the classical ACD model increases rapidly as the system size increases. This article presents an enriched ACD called the parameterized ACD (P-ACD). In P-ACD, each node is allowed to have parameter variables, and parameter values are passed to the parameter variables through a directed arc. This article demonstrates how a single P-ACD model can be used to represent an entire class of very large-scale systems instead of requiring different ACD models for every instance. We also illustrate that the well-known activity scanning algorithm can be used to execute a P-ACD model. A prototype P-ACD simulator implemented in C# programming language is provided, and an illustrative example of a conveyor-driven serial production line with the prototype simulator is presented to illustrate construction and execution of a P-ACD model. In addition, it is demonstrated that the proposed P-ACD allows an effective and concise modeling of a job shop, which was not possible with the classical ACD.

The extended activity cycle diagram and its generality

Abstract The simplicity of the two-symbol activity cycle diagram (ACD) has made it easy to learn and use to describe discrete event systems in a natural way. But as the complexity of the model increases, the ability of the ACD to provide a full description of the system under consideration becomes more limited. This paper presents an extended ACD with arc attributes and its formal definition to increase the modeling power of the ACD. The validity of the proposed extensions is shown by proving the generality of the extended ACD, which has not yet been done on the ACD. In addition, this paper proposes a model specification for the simulation execution of the extended ACD models which we call the activity transition table (ATT). At last, the simulation software tool is presented to support model implementation, model execution, and experimentation for the extended ACD models.

Visual Modeling And Simulation Toolkit For Activity Cycle Diagram.

A direct use of activity cycle diagram (ACD) model into a simulation execution has a limitation that it does not maximize the power of the widely adopted three-phase rule in the simulation execution of ACD models. This paper presents a key model specification for the simulation execution of the ACD model, named, activity transition table (ATT). The proposed ATT reduces the gap between the ACD (the flow of state change) and the three-phase rule (activity transition) and maximizes the modularity of the three-phase rule. The presented ATT model and ACD model can be implemented and executed with the help of the visual modeling and simulation toolkit.

Parameterized ACD Modeling of Flexible Manufacturing Systems

Activity cycle diagram (ACD), which is essentially a timed Petri net, is one of the oldest formal modeling tools for discrete-event systems, and a flexible manufacturing system (FMS) is a highly automated job shop that is used widely in mechanical and electronics industries. Previous FMS modeling studies have indicated that formal modeling of real-life (or industrial) FMSs with classical ACDs (or Petri nets) is almost impossible. This paper presents an incremental modeling procedure for building a formal simulation model of a real-life FMS with parameterized ACD (P-ACD) that was proposed recently. The incremental modeling procedure consists of job flow modeling, job routing modeling, dispatching rule modeling, and refixture operation modeling. In this paper, a P-ACD model of a real-life FMS was constructed and an FMS simulator was implemented from the proposed P-ACD model. A simulation experiment was conducted in order to demonstrate the usefulness of the FMS simulator.

How to develop your own simulators for discrete-event systems

This tutorial explains how to develop dedicated simulators for executing event graph models and activity cycle diagram (ACD) models. An event-graph simulator template and an ACD simulator template are presented in pseudo code form, together with example C# implementations for a simple discrete-event system. A list of the simulation programs in C# codes is provided in a website. A brief description of a general-purpose simulator for executing ACD models is also presented.

Event graph modeling of a heterogeneous job shop with inline cells

In a flat panel display (FPD) production line, unlike a table-type machine that processes one glass at a time, an inline cell works simultaneously on several glasses unloaded from different cassettes in a serial manner and is divided into two types (uni-inline cell and bi-inline cell) according to the job loading and unloading behavior. In order to build a production simulator for this type of FPD production line, an object-oriented event graph modeling approach is proposed where the FPD production line is simplified into a job shop consisting of two types of inline cells, and the job shop is represented as an object-oriented event graph model. This type of job shop is referred to as a heterogeneous job shop. The resulting model is realized in a production simulator using an object-oriented event graph simulator and is illustrated with the experimental results from the production simulator.

Gantt Chart Simulation for FAB Scheduling

Capital-intensive facilities called electronic fabrications (“FABs” in short) are operated twenty-four hours a day to meet the massive orders on time. The main objectives of scheduling the complex manufacturing process are to meet the on time delivery and to maximize machine utilization. A discrete event simulation approach has brought good results to generate an efficient and practical schedule. However, the approach tends to make short-term decision, which loads any job rather than stays idle. When the setup time is long and the number of crews is limited, being idle could be a better decision than changing jobs. This paper proposes a method to compensate for the limitations of simulation-based schedulers. We propose a Gantt chart simulation approach that formulates WIP level with an incoming profile and a consuming profile with the number of loaded machines. With two profiles, we can determine when to add or release a machine for each job. The proposed method has been applied to a real factory and showed promising results.