A conceptual modeling approach for supply chain event management (SCEM)

The management of supply chains is a very comprehensive task. Predictability and response to incidents in process executions are challenging. With Supply Chain Event Management (SCEM), researchers propose an approach for overcoming these problems through proactive monitoring and notification of crucial process activities across the supply chain. The identification and definition of such crucial activities and information needs are necessary to handle possible abnormalities although they are challenging task which have not been solved in SCEM research so far. Hence, we propose a modeling approach which allows the conceptual specification of an adequate information exchange along the supply chain. With our approach we focus on the specification of relevant logistical objects, the definition of possible events, and the design of notifications for decision makers in the supply chain

Biomass supply chain event management

 D. K. Folinas1, D. D. Bochtis2, C. G. Sørensen2, P. Busato3(1. ATEI Thessaloniki, Department of Logistics, Greece; 2. Department of Biosystems Engineering, Faculty of Agricultural Sciences, Aarhus University, Blichers Alle´ 20, P.O. box 50;   3. DEIAFA Department,Faculty of Agriculture, University of Turin, Via Leonardo da Vinci 44, 10095, Grugliasco, Turin, Italy) Abstract: The biomass supply chain constitutes a system that is highly dynamic and stochastic.  The developed and proposed systems architectures for the management of the supply chains of typical industrial products do not directly apply to the case of the biomass supply chain

10. Interuniversitäres Doktorandenseminar Wirtschaftsinformatik Juli 2009

Begonnen im Jahr 2000, ist das Interuniversitäre Wirtschaftsinformatik-Doktorandenseminar mittlerweile zu einer schönen Tradition geworden. Zunächst unter Beteiligung der Universitäten Leipzig und Halle-Wittenberg gestartet. Seit 2003 wird das Seminar zusammen mit der Jenaer Universität durchgeführt, in diesem Jahr sind erstmals auch die Technische Universität Dresden und die TU Bergakademie Freiberg dabei. Ziel der Interuniversitären Doktorandenseminare ist der über die eigenen Institutsgrenzen hinausgehende Gedankenaustausch zu aktuellen, in Promotionsprojekten behandelten Forschungsthemen. Indem der Schwerpunkt der Vorträge auch auf das Forschungsdesign gelegt wird, bietet sich allen Doktoranden die Möglichkeit, bereits in einer frühen Phase ihrer Arbeit wichtige Hinweise und Anregungen aus einem breiten Hörerspektrum zu bekommen. In den vorliegenden Research Papers sind elf Beiträge zum diesjährigen Doktorandenseminar in Jena enthalten. Sie stecken ein weites Feld ab - vom Data Mining und Wissensmanagement über die Unterstützung von Prozessen in Unternehmen bis hin zur RFID-Technologie. Die Wirtschaftsinformatik als typische Bindestrich-Informatik hat den Ruf einer thematischen Breite. Die Dissertationsprojekte aus fünf Universitäten belegen dies eindrucksvoll.

Managing Supply Chain Events to Build Sense-and-Respond Capability

As supply chains become more dynamic, there is a need for a sense-and-respond capability to react to events in a real-time manner. In this paper, we propose Petri nets extended with time and color (for case data) as a formalism for doing so. Hence, we describe seven basic patterns that are used to capture modeling concepts that arise commonly in supply chains. These basic patterns may be used by themselves and also be combined to create new patterns. Next, we show how to use the patterns as building blocks to model a complete supply chain and analyze it using dependency graphs and simulation. Dependency graphs can be used to analyze the various events and their causes. Simulation was, in addition, used to analyze various performance indicators (e.g. fill rates, replenishment times, and lead times) under different supply chain strategies. We performed sensitivity analysis to study the effect of changing parameter values on the performance indicators. In the experiments, by cutting resolution time for production delays in half (strategy 1), we were able to increase order fill rate from 89% to 95%. Similarly, upon raising the probability of successful alternative sourcing (strategy 2) from 0.5 to 0.7 the order fill rate again increased from 89% to 95%. We show that by modeling timing and causality issues accurately, it is possible to improve supply chain performance

Advanced Bayesian framework for uncertainty estimation of sediment transport models

2018 Summer.Includes bibliographical references.Numerical sediment transport models are widely used to forecast the potential changes in rivers that might result from natural and/or human influences. Unfortunately, predictions from those models always possess uncertainty, so that engineers interpret the model results very conservatively, which can lead to expensive over-design of projects. The Bayesian inference paradigm provides a formal way to evaluate the uncertainty in model forecasts originating from uncertain model elements. However, existing Bayesian methods have rarely been used for sediment transport models because they often have large computational times. In addition, past research has not sufficiently addressed ways to treat the uncertainty associated with diverse sediment transport variables. To resolve those limitations, this study establishes a formal and efficient Bayesian framework to assess uncertainty in the predictions from sediment transport models. Throughout this dissertation, new methodologies are developed to represent each of three main uncertainty sources including poorly specified model parameter values, measurement errors contained in the model input data, and imperfect sediment transport equations used in the model structure. The new methods characterize how those uncertain elements affect the model predictions. First, a new algorithm is developed to estimate the parameter uncertainty and its contribution to prediction uncertainty using fewer model simulations. Second, the uncertainties of various input data are described using simple error equations and evaluated within the parameter estimation framework. Lastly, an existing method that can assess the uncertainty related to the selection and application of a transport equation is modified to enable consideration of multiple model output variables. The new methodologies are tested with a one-dimensional sediment transport model that simulates flume experiments and a natural river. Overall, the results show that the new approaches can reduce the computational time about 16% to 55% and produce more accurate estimates (e.g., prediction ranges can cover about 6% to 46% more of the available observations) compared to existing Bayesian methods. Thus, this research enhances the applicability of Bayesian inference for sediment transport modeling. In addition, this study provides several avenues to improve the reliability of the uncertainty estimates, which can help guide interpretation of model results and strategies to reduce prediction uncertainty

The Emergence of Enterprise Systems Management - A Challenge to the IS Curriculum

This paper proposes four cornerstones of a future Information Systems curriculum. It analyzes the challenges of the IS curriculum based on the development of enterprise systems, and further argues that the practice and the research into enterprise systems have progressed to a new stage resulting in the emergence of Enterprise Systems Management (ESM). Enterprise Systems Management calls for new competences and consequently represents new challenges to the IS curriculum. The paper outlines potential teaching issues and discusses the impact on the IS curriculum. Finally the paper suggests ways of approaching the challenges.No; keywords

Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: a systematic literature review

Purpose: The objective of this paper is to provide a systematic literature review of recent developments in methodological frameworks for the modelling and simulation of agent-based advanced supply chain planning systems. Design/methodology/approach: A systematic literature review is provided to identify, select and make an analysis and a critical summary of all suitable studies in the area. It is organized into two blocks: the first one covers agent-based supply chain planning systems in general terms, while the second one specializes the previous search to identify those works explicitly containing methodological aspects. Findings: Among sixty suitable manuscripts identified in the primary literature search, only seven explicitly considered the methodological aspects. In addition, we noted that, in general, the notion of advanced supply chain planning is not considered unambiguously, that the social and individual aspects of the agent society are not taken into account in a clear manner in several studies and that a significant part of the works are of a theoretical nature, with few real-scale industrial applications. An integrated framework covering all phases of the modelling and simulation process is still lacking in the literature visited. Research limitations/implications: The main research limitations are related to the period covered (last four years), the selected scientific databases, the selected language (i.e. English) and the use of only one assessment framework for the descriptive evaluation part. Practical implications: The identification of recent works in the domain and discussion concerning their limitations can help pave the way for new and innovative researches towards a complete methodological framework for agent-based advanced supply chain planning systems. Originality/value: As there are no recent state-of-the-art reviews in the domain of methodological frameworks for agent-based supply chain planning, this paper contributes to systematizing and consolidating what has been done in recent years and uncovers interesting research gaps for future studies in this emerging fieldPeer Reviewe

An information systems framework for event management in supply chain operations

As competition has shifted from the company to the Supply Chain level, gaining a competitive edge becomes an issue of efficient collaboration amongst SC partners. Within the e-business era the level of competitiveness is determined by the ability of an SC to react and adjust rapidly to market and industrial changes and to overcome burdens originating both from inside and outside the SC borders. These features create the framework for defining agility within supply chains. Managing turbulence in SCs, while maintaining customer satisfaction at a low operational cost requires proactive dynamics towards risk factors. An agile Supply Chain addresses direct and indirect sources of risk, which expand outside the SC boundaries. Supply risk is related to the potential occurrence of an incident such as inbound supplies failure that results in customer dissatisfaction. Sources of risk in the SC have various origins which due to their dynamic nature cannot always be predicted, such as turbulence in oil or currency prices, physical or manmade disasters, production failures, product recalls and so on. Organizations need to respond to events as certain unexpected events can cause chaos in the SC and form patterns with negative impact, such as the bullwhip effect, backlogs etc. Chaos in the SC originates from managerial and computer control decisions and actions but apart from the internal sources, chaotic spikes in the SC demand can also originate from external changes. This thesis proposes that Internet based Information Systems support is required for responsive Supply Chains, in order to address risk origins under a holistic perspective. An event driven architectural framework is proposed in the context of SC operations, which enables flexibility and agility in an e-business setting. The concept of events is explored within the Supply Chain domain and the information regarding patterns of occurring events is identified and disseminated. Initially the theoretical ground for event identification is set and unexpected events in a SC context are classified. Building on the events classification, a notation (EPN) to model event patterns is described. Finally an architecture (SCEDRA) which captures unexpected events and forms and disseminates event patterns is proposed