Towards resilient supply chain networks

In the past decade, events like 9/11 terror attacks, the recent financial crisis and other major crisis has proved that there is strong interaction and interdependency of a supply chain network with its external environments in various channels and thus a need to focus on building resiliency (in short, the ability of the system to recover from damage or disruption) of the entire network system. Although literature has discussed some way of improving resiliency of an individual firm which is a member of the network system, it lacked to capture a holistic view of the supply chain network. Pertaining to this observation, this work proposes to improve resiliency of a supply chain network from a system’s perspective rather concentrate on an individual firm. For this purpose, this thesis proposes a conceptual framework to promote early identification and timely information of the disruptions arising in a supply chain network and timely sharing of this information among all the members of the network. The key principle emphasized in this thesis is that recovery from an inevitable disruption has a better possibility if a member of the supply chain network has an early indication or knowledge of the upcoming disruption. A discrete event dynamic system simulation tool called Petri nets is utilized to realize the proposed conceptual framework. Furthermore, the practical benefits and implications of the proposed model and tool are demonstrated with help of two case studies. This thesis has several contributions to the field of operation management and supply chain. First, a new paradigm for supply chain management to avoid large scale failures such as financial crisis is available to the field, which may be applied by governments or regulatory bodies. Second, a new framework which allows for a quantitative analysis of failures of an entire supply chain network is available to the field, which is easy to be used. Third, a novel application of Petri nets to this new problem in supply chain management is available

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Petri Nets Models for Analysis and Control of Public Bicycle-Sharing Systems

International audienc

On two-echelon inventory systems with Poisson demand and lost sales

We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

Performance modelling of fuel cell systems through Petri nets

This paper introduces a model based on the Petri net method for the performance evaluation of fuel cell systems during operation. The model simulates the operation of the fuel cell stack and its supporting systems by taking into account the causal relationships between the operation of the balance of plant and the fuel cell stack performance. Failures of the supporting system affect the operating parameters such as the stack temperature and humidity, the reactants’ flow and pressure, and, in turn, the stack performance in terms of output voltage. Voltage degradation rates are needed in order to evaluate the system lifetime. The voltage degradation is related to the important operating parameters by means of empirical relationships. In order to demonstrate the capability of the model, numerical simulations are performed using data for voltage degradation rates collected from the literature. The voltage decay rate is modelled as a random variable within the aforementioned ranges. Time to failure and time to repair of components are generated from stochastic distributions. The use of a stochastic approach allows taking into account data uncertainty and variability. The modelling process produces distributions of the output parameters rather than point estimates delivered by alternative methods. This enables an appreciation of the best and worst possible output lifetime as well as the expected system performance. The model can be used to support the design, operation and maintenance of fuel cell systems

An effective tool for supply chain decision support during new product development process

The global marketplace has transformed supply chain design into a discipline which requires business sense supported by mathematical expertise. Several methods have been introduced to support supply chain design, most notably mixed integer programming. The current methods are tailor-made for situations where a product's bill-of-material is fixed. However, this assumption does not hold during product development where several competing product designs exist. Therefore this research investigates the question of what is an effective way to support supply chain decisions during new product development. The study is divided into four research questions, corresponding to the articles from which the dissertation is compiled: (1) Does a product structure-driven method exist for modeling and analyzing supply chains? (2) If such a method is discovered, what is its mathematical formulation? (3) Is there evidence to support the theoretical and practical usability of such a method? (4) How can strategic supply chain decisions be validated? Regarding question (1) the research finds that there is a shortage of methods that fulfill supply chain modeling and analysis requirements imposed by new product development process. During the research a Petri-net based method was constructed which satisfies these requirements. For question (2), the formal definitions of the constructed Petri net class are provided. Regarding question (3), the research finds that the created method and associated tool are useful aids when solving the question of the effect of demand variation and the number of product variants on the optimal supply chain. Furthermore, interviews with end users of the tool implementation provide evidence of the Petri net method's practical usefulness. Regarding question (4), the research finds that the validation of strategic supply chain decisions from companies' reporting systems is important, but it has not become a common practice due to the challenges in integrating various IT systems

Application of artificial neural networks and colored petri nets on earthquake resilient water distribution systems

Water distribution systems are important lifelines and a critical and complex infrastructure of a country. The performance of this system during unexpected rare events is important as it is one of the lifelines that people directly depend on and other factors indirectly impact the economy of a nation. In this thesis a couple of methods that can be used to predict damage and simulate the restoration process of a water distribution system are presented. Contributing to the effort of applying computational tools to infrastructure systems, Artificial Neural Network (ANN) is used to predict the rate of damage in the pipe network during seismic events. Prediction done in this thesis is based on earthquake intensity, peak ground velocity, and pipe size and material type. Further, restoration process of water distribution network in a seismic event is modeled and restoration curves are simulated using colored Petri nets. This dynamic simulation will aid decision makers to adopt the best strategies during disaster management. Prediction of damages, modeling and simulation in conjunction with other disaster reduction methodologies and strategies is expected to be helpful to be more resilient and better prepared for disasters --Abstract, page iv

Measurements, Models, Systems and Design

531 s.