Exception management on a shop floor using online simulation

Abstract

A framework for a supervisory controller to manage hard and soft exceptions on a shop floor is discussed. Various tasks involved in managing exceptions, the times at which these tasks are to be performed, and their impact on the performance of a supervisory controller are studied. Online simulation methodology is utilized to detect, classify, and handle exceptions.A synchronization procedure, an essential step to perform on-line control using a discreteevent simulation language, is developed. Its main purpose is to resolve discrepancies between the behavior of entities and resources in the simulation model and shop floor. The framework is restricted to manufacturing cells; however, it can easily be extended to manage exceptions in logistics and distribution systems. A simulation model of a flexible manufacturing cell is used to illustrate exception detection and synchronization concepts.

Grand Challenges in Modeling and Simulation of Complex Manufacturing Systems

“…Simulation models for this purpose are possible today due to the increased amount of data and information that is collected and maintained by current shop-floor information systems. The literature on real-time applications of simulation in manufacturing is sparse, but there are papers about simulation-based scheduling [20][21][22], order release [23], forecasting [10], and exception management [24]. In Peters et al [21], the focus is on the requirements for an online simulation tool, whereas Rogers and Gordon [22] provide an overview of the principal problems of simulation-based scheduling.…”

A model of exceptions in sales-order-processing workflows

“…1. During the application of robot systems, exceptions typically arise in the form of errors or deviations from normal operating conditions, such as hardware failure and incorrect locations of fixtures and workpieces [60][61][62][63]. Recovery from such errors (i.e.…”

Selective rerouting using simulated steady state system data

“…Simulation combined with a knowledge base has been presented by several authors (Katz and Manivannan 1993, Manivannan and Banks 1991and 1992. Using simulation to evaluate several alternatives when a disruption occurs has been discussed for real-time decision making (Harmonosky and Robohn 1995, Kim and Kim 1994, Harmonosky 1990).…”