An algorithm to determine the causes of inventory stock-outs in manufacturing firms

Thesis (M.Eng.)--Massachusetts Institute of Technology, Engineering Systems Division, 2000.Includes bibliographical references (leaf 52).The recent trends in manufacturing toward lower inventory levels, shorter cycle times, and more closely integrated production schedules have led to an extremely low tolerance for inventory stock-outs. In such an environment, any shortage is costly, and understanding why stock-outs occur and how to prevent them is an important issue. However, the answer to the question of why stock-outs occur is not always easy to determine. Investigations into the root causes of inventory stock-outs are often hindered by data collection problems, data overload, and the investigators' lack of a well-accepted, systematic framework with which to conduct the analysis, resulting in a cursory review of the problem and a subjective diagnosis. This thesis proposes an algorithm to determine objectively the causes of inventory stockouts in manufacturing firms. Instead of observing stock-outs through the lens of the classical inventory model that aggregates all variations in resupply time and demand during leadtime into one variable, this thesis attempts to view the problem with a broader supply chain perspective that considers multiple sources of variation. Given data that describe the transactions of materials and information between members of the supply chain, the algorithm identifies which causes among a prescribed set of causes lead to a given stock-out occurrence. The transaction data is analyzed using a simple supply chain model to determine how each possible stock-out cause could affect actual inventory performance compared to planned inventory performance. This approach to analyzing inventory stock-outs has many possible uses, including its use as a supply chain metric to evaluate efforts to minimize inventory stock-outs.by Matthew H. Burt.M.Eng

Visualization in cyber-geography: reconsidering cartography's concept of visualization in current usercentric cybergeographic cosmologies

This article discusses some epistemological problems of a semiotic and cybernetic character in two current scientific cosmologies in the study of geographic information systems (GIS) with special reference to the concept of visualization in modern cartography. Setting off from Michael Batty’s prolegomena for a virtual geography and Michael Goodchild’s “Human-Computer-Reality-Interaction” as the field of a new media convergence and networking of GIS-computation of geo-data, the paper outlines preliminarily a common field of study, namely that of cybernetic geography, or just “cyber-geography) owing to the principal similarities with second order cybernetics. Relating these geographical cosmologies to some of Science’s dominant, historical perceptions of the exploring and appropriating of Nature as an “inventory of knowledge”, the article seeks to identify some basic ontological and epistemological dimensions of cybernetic geography and visualization in modern cartography. The points made is that a generalized notion of visualization understood as the use of maps, or more precisely as cybergeographic GIS-thinking seems necessary as an epistemological as well as a methodological prerequisite to scientific knowledge in cybergeography. Moreover do these generalized concept seem to lead to a displacement of the positions traditionally held by the scientist and lay-man citizen, that is not only in respect of the perception of the matter studied, i.e. the field of geography, but also of the manner in which the scientist informs the lay-man citizen in the course of action in the public participation in decision making; a displacement that seems to lead to a more critical, or perhaps even quasi-scientific approach as concerns the lay-man user

Conservation science in NOAA’s National Marine Sanctuaries: description and recent accomplishments

This report describes cases relating to the management of national marine sanctuaries in which certain scientific information was required so managers could make decisions that effectively protected trust resources. The cases presented represent only a fraction of difficult issues that marine sanctuary managers deal with daily. They include, among others, problems related to wildlife disturbance, vessel routing, marine reserve placement, watershed management, oil spill response, and habitat restoration. Scientific approaches to address these problems vary significantly, and include literature surveys, data mining, field studies (monitoring, mapping, observations, and measurement), geospatial and biogeographic analysis, and modeling. In most cases there is also an element of expert consultation and collaboration among multiple partners, agencies with resource protection responsibilities, and other users and stakeholders. The resulting management responses may involve direct intervention (e.g., for spill response or habitat restoration issues), proposal of boundary alternatives for marine sanctuaries or reserves, changes in agency policy or regulations, making recommendations to other agencies with resource protection responsibilities, proposing changes to international or domestic shipping rules, or development of new education or outreach programs. (PDF contains 37 pages.

Observing bullying at school: The mental health implications of witness status

This study explores the impact of bullying on the mental health of students who witness it. A representative sample of 2,002 students aged 12 to 16 years attending 14 schools in the United Kingdom were surveyed using a questionnaire that included measures of bullying at school, substance abuse, and mental health risk. The results suggest that observing bullying at school predicted risks to mental health over and above that predicted for those students who were directly involved in bullying behavior as either a perpetrator or a victim. Observing others was also found to predict higher risk irrespective of whether students were or were not victims themselves. The results are discussed with reference to past research on bystander and witness behavior

Regression Monte Carlo for Microgrid Management

We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.Comment: CEMRACS 2017 Summer project - proceedings

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations)

Analiza diagnostic a subsitemelor sistemului de management Diagnosis Analysis of the Sub-Sistems of Management System

The management system represents all the elements having an organizational, decisional, informational, and methodological character through the agency of whom the process of management is achieved with a view of attaining a maximum level of performance. The managerial machinery of a modern company has a systemic structure within which the interdependencies among the component elements determine the functioning mechanism of the management at all levels. Irrespective of company’s characteristics (profile, size, market position, etc.) the following components of the management system should be noticed: the decisional sub-system, the organizational sub-system, the methodological and managerial sub-system, and the informational sub-system. The paper deals with a profound diagnosis analysis of these sub-systems considering the case of a company which activates within the Romanian energetic industry. The decisional sub-system gathers all the decisions adopted and implemented within the company according to the established goals and to the managerial hierarchical configuration. Integrated within the methodology of managerial analysis of the company, the diagnosis analysis of the decisional sub-system has as a goal the knowledge of its components, namely of the decisions established by managers during a certain period, of the manner the authority within the company is structured, of the decisional tools employed as well as of the part played by the organisms of participative management. Organizational sub-system represents all organizational elements that provide the frame, the division, the combination, and the functionality of labor processes with a view of achieving envisaged goals. The data displayed by the organizational scheme, the organizational and functioning regulations, jobs responsibilities at the level of a machines building company have emphasized several aspects that represent the starting point of analyzing the two components of this management sub-system, namely formal organization and informal organization. Informational sub-system comprises a series of data, items of information, informational fluxes and circuits, procedures and means of approaching information meant to contribute to the settlement and achievement of the company’s goals. The analysis of the informational sub-system has in view the fact that its part is to provide the company’s inner needs of information and its quality depends on the level of development of the technologies of transmitting information. The methodological sub-system designates the group of systems (complex methods), methods, and techniques employed in conceiving and exerting managerial functions and relations within a company. The important mutations that take place within the internal and external environment of the companies determine the managerial team to employ systems, methods, and techniques characteristic to managerial activity that are continually up-dated.diagnosis analysis; management system; decisional sub-system, organizational sub-system; informational sub-system; methodological sub-system

The Classroom Observation Schedule to Measure Intentional Communication (COSMIC): An observational measure of the intentional communication of children with autism in an unstructured classroom setting

The Classroom Observation Schedule to Measure Intentional Communication (COSMIC) was devised to provide ecologically valid outcome measures for a communication-focused intervention trial. Ninety-one children with autism spectrum disorder aged 6 years 10 months (SD 16 months) were videoed during their everyday snack, teaching and free play activities. Inter-rater reliability was high and relevant items showed significant associations with comparable items from concurrent Autism Diagnostic Observation Schedule – Generic (Lord et al., 2000) assessments. In a subsample of 28 children initial differences in rates of initiations, initiated speech/vocalisation and commenting were predictive of language and communication competence 15 months later. Results suggest that the use of observational measures of intentional communication in natural settings is a valuable assessment strategy for research and clinical practice