N. Viswanadham

Deadlock prevention and deadlock avoidance in flexible manufacturing systems using Petri net models

Deadlocks constitute an important issue to be addressed in the design and operation of FMSs. It is shown that prevention and avoidance of FMS deadlocks can be implemented using Petri net models. For deadlock prevention, the reachability graph of a Petri net model of the given FMS is used, whereas for deadlock avoidance, a Petri-net-based online controller is proposed. The modeling of the General Electric FMS at Erie, PA, is discussed. For such real-world systems, deadlock prevention using the reachability graph is not feasible. A generic, Petri-net-based online controller for implementing deadlock avoidance in such real-world FMSs is developed. >

Observers for linear systems with unknown inputs

This paper presents a constructive solution to the problem of designing a reduced-order Luenberger observer for linear systems subject to arbitrary unknown inputs.

Performance analysis and design of supply chains: a Petri net approach

In this paper, we investigated a dynamic modelling technique for analysing supply chain networks using generalised stochastic Petri nets (GSPNs). The customer order arrival process is assumed to be Poisson and the service processes at the various facilities of the supply chain are assumed to be exponential. Our model takes into account both the procurement process and delivery logistics that exist between any two members of the supply chain. We compare the performance of two production planning and control policies, the make-to-stock and the assemble-to-order systems in terms of total cost which is the sum of inventory carrying cost and cost incurred due to delayed deliveries. We formulate and solve the decoupling point location problem in supply chains as a total relevant cost (sum of inventory carrying cost and the delay costs) minimisation problem. We use the framework of integrated GSPN-queuing network modelling—with the GSPN at the higher level and a generalised queuing network at the lower level—to solve the decoupling point location problem.

Analytical Framework for the Management of Risk in Supply Chains

In this paper, we develop a framework to classify supply chain risk-management problems and approaches for the solution of these problems. We argue that risk-management problems need to be handled at three levels: 1) strategic, 2) operational, and 3) tactical. In addition, risk within the supply chain might manifest itself in the form of deviations, disruptions, and disasters. To handle unforeseen events in the supply chain, there are two obvious approaches: 1) to design chains with built-in risk tolerance and 2) to contain the damage once the undesirable event has occurred. Both of these approaches require a clear understanding of undesirable events that may take place in the supply chain and the associated consequences and impacts from these events. Having described these approaches, we then focus our efforts on mapping out the propagation of events in the supply chain due to supplier nonperformance, and employ our insight to develop two mathematical programming-based preventive models for strategic level deviation and disruption management. The first model, a simple integer quadratic optimization model, adapted from the Markowitz model, determines optimal partner selection with the objective of minimizing both the operational cost and the variability of total operational cost. The second model, a simple mixed integer programming optimization model, adapted from the credit risk minimization model, determines optimal partner selection such that the supply shortfall is minimized even in the face of supplier disruptions. Hence, both of these models offer possible approaches to robust supply chain design

A Methodology for Knowledge Acquisition and Reasoning in Failure Analysis of Systems

The problem of modeling knowledge about the fault behavior of a system and utilizing this model for reasoning about and diagnosing failures is addressed. A solution that merges graph and fault-tree-based failure analysis with rule-oriented reasoning is presented. Failure analysis is divided into two phases, a failure source location phase and a failure cause identification phase. Each phase consists of a failure model and a process that operates on it. The failure models for the first and second phases are based on lesel-structured fault propagation digraphs and augmented fault trees, respectively. The augmented fault tree (AFT) is a conceptual structure that encodes probabilistic, temporal, and heuristic information in addition to the causal aspects of failures modeled by conventional fault trees. The two models are combined to form a novel hierarchical failure knowledge representation scheme. Upper levels of this hierarchy are made up of the fault propagation digraphs. Each level represents a view of the system under a particular granularity, and the granularity increases with levels. This feature permits control over the resolution of fault diagnosis. The lowest level consists of a set of cause-consequence knowledge bases containing production rules. These production rules are derived from augmented fault trees and represent the cause-effect relations among failure events that lead to the corresponding subsystems failure. A knowledge acquisition procedure to generate these failure models and failure analysis processes that operate on them are described. The methodology proposed is inherently parallel as the processes may operate on different levels independently.

Partner selection and synchronized planning in dynamic manufacturing networks

In this paper, we develop a mixed-integer programming model for integrated partner selection and scheduling in an Internet-enabled dynamic manufacturing network environment. We assume that all stakeholders in the supply chain (SC) share information on their capacities, schedules, and cost structures. Based on this information, the model addresses the issue of partner selection and SC synchronization for profit maximization, while considering various manufacturing and logistics constraints. Furthermore, we study the dynamic configuration of the SC and its performance with respect to different buyer locations, different order patterns, and the utilization of transshipment hubs. The model is solved using optimization tools from ILOG, located in Paris, France, and Mountain View, CA.

Fault detection and diagnosis of automated manufacturing systems

The authors develop a controller methodology for fault detection and diagnosis using Petri nets and fault trees in automated manufacturing systems. The controller has two levels. At the first level there are dedicated diagnostic systems for each of the subsystems, such as machine centers, robots, conveyers, etc. At the second level there is an intelligent controller monitoring the part flow and coordinating the local diagnostic systems and controllers. The authors assume that local controller and diagnostic systems exist for subsystem-level fault detection and diagnosis, and they present a Petri-net-based intelligent controller for system-level fault detection and diagnosis. The authors also describe fault-free-based diagnostics.<<ETX>>

Collaboration and information sharing in global contract manufacturing networks

In the semiconductor and telecommunications industry original equipment manufacturers (OEMs) outsource manufacturing to contract manufacturers who are specialist electronic manufacturing service providers. There are a large number of such specialists in existence who collaborate with the original equipment manufacturers at one end and the component suppliers at another end and provide engineering, manufacturing and distribution services. But there do not exist good theoretical developments supporting these real world operations. We consider a global manufacturing system consisting of the contract manufacturer, logistics provider, and OEM and study the influence of sharing scheduling and demand information over the Internet. More specifically, we consider an OEM operating an Internet-based private exchange as a channel master with its contract manufacturers and their suppliers participating by sharing information. We develop a linear program based optimization model for this environment. Specifically, our LP model calculates the quantity of raw materials that is to be procured in each time period from each of the suppliers in order to meet the given demand. We compare these results with traditional make-to-stock linear supply chains with sequential order flow. Our numerical experiments show that information sharing results in cost and inventory reduction.

Transient analysis of manufacturing systems performance

We present several situations in manufacturing systems where transient analysis is very important. Manufacturing systems and models in which such situations arise include: systems with failure states and deadlocks, unstable queueing systems, and systems with fluctuating or nonstationary workloads. Even in systems where equilibrium exists, transient analysis is important in studying issues such as accumulated performance rewards over finite intervals, first passage times, sensitivity analysis, settling time computation, and deriving the behavior of queueing models as they approach equilibrium. In this paper, we focus on transient analysis of Markovian models of manufacturing systems. After presenting several illustrative manufacturing situations where transient analysis has significance, we discuss two problems for demonstrating the importance of transient analysis. The first problem is concerned with the computation of distribution of time to absorption in Markov models of manufacturing systems with deadlocks or failures, and the second problem shows the relevance of transient analysis to a multiclass manufacturing system with significant setup times. We also discuss briefly computational aspects of transient analysis. >

Coloured Petri net models for automated manufacturing systems

In this paper, we propose an approach, using Coloured Petri Nets (CPN) for modelling flexible manufacturing systems. We illustrate our methodology for a Flexible Manufacturing Cell (FMC) with three machines and three robots. We also consider the analysis of the FMC for deadlocks using the invariant analysis of CPNs.