Value Stream Analysis and Mapping for Product Development

This paper explores the concept of Value Stream Analysis and Mapping (VSA/M) as applied to Product Development (PD) efforts. Value Stream Analysis and Mapping is a method of business process improvement. The application of VSA/M began in the manufacturing community. PD efforts provide a different setting for the use of VSA/M. Site visits were made to nine major U.S. aerospace organizations. Interviews, discussions, and participatory events were used to gather data on (1) the sophistication of the tools used in PD process improvement efforts, (2) the lean context of the use of the tools, and (3) success of the efforts. It was found that all three factors were strongly correlated, suggesting success depends on both good tools and lean context. Finally, a general VSA/M method for PD activities is proposed. The method uses modified process mapping tools to analyze and improve process.

Value Stream Mapping in a Manufacturing Environment

Current Value Stream Map Future Value Stream Map Research Motivation Key Research Questions

Value Stream Analysis and Mapping for Product Development

This paper explores the concept of Value Stream Analysis and Mapping (VSA/M) as applied to Product Development (PD) efforts. Value Stream Analysis and Mapping is a method of business process improvement. The application of VSA/M began in the manufacturing community. PD efforts provide a different setting for the use of VSA/M. Site visits were made to nine major U.S. aerospace organizations. Interviews, discussions, and participatory events were used to gather data on (1) the sophistication of the tools used in PD process improvement efforts, (2) the lean context of the use of the tools, and (3) success of the efforts. It was found that all three factors were strongly correlated, suggesting success depends on both good tools and lean context. Finally, a general VSA/M method for PD activities is proposed. The method uses modified process mapping tools to analyze and improve process.

Convex linear combination processes for compositions

Aitchison and Bacon-Shone (1999) considered convex linear combinations of compositions. In other words, they investigated compositions of compositions, where the mixing composition follows a logistic Normal distribution (or a perturbation process) and the compositions being mixed follow a logistic Normal distribution. In this paper, I investigate the extension to situations where the mixing composition varies with a number of dimensions. Examples would be where the mixing proportions vary with time or distance or a combination of the two. Practical situations include a river where the mixing proportions vary along the river, or across a lake and possibly with a time trend. This is illustrated with a dataset similar to that used in the Aitchison and Bacon-Shone paper, which looked at how pollution in a loch depended on the pollution in the three rivers that feed the loch. Here, I explicitly model the variation in the linear combination across the loch, assuming that the mean of the logistic Normal distribution depends on the river flows and relative distance from the source origins

Refinement criteria for global illumination using convex funcions

In several computer graphics areas, a refinement criterion is often needed to decide whether to go on or to stop sampling a signal. When the sampled values are homogeneous enough, we assume that they represent the signal fairly well and we do not need further refinement, otherwise more samples are required, possibly with adaptive subdivision of the domain. For this purpose, a criterion which is very sensitive to variability is necessary. In this paper, we present a family of discrimination measures, the f-divergences, meeting this requirement. These convex functions have been well studied and successfully applied to image processing and several areas of engineering. Two applications to global illumination are shown: oracles for hierarchical radiosity and criteria for adaptive refinement in ray-tracing. We obtain significantly better results than with classic criteria, showing that f-divergences are worth further investigation in computer graphics. Also a discrimination measure based on entropy of the samples for refinement in ray-tracing is introduced. The recursive decomposition of entropy provides us with a natural method to deal with the adaptive subdivision of the sampling region

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing one or more parameters in their definition. Methods that can be linked in this way are correspondence analysis, unweighted or weighted logratio analysis (the latter also known as "spectral mapping"), nonsymmetric correspondence analysis, principal component analysis (with and without logarithmic transformation of the data) and multidimensional scaling. In this presentation I will show how several of these methods, which are frequently used in compositional data analysis, may be linked through parametrizations such as power transformations, linear transformations and convex linear combinations. Since the methods of interest here all lead to visual maps of data, a "movie" can be made where where the linking parameter is allowed to vary in small steps: the results are recalculated "frame by frame" and one can see the smooth change from one method to another. Several of these "movies" will be shown, giving a deeper insight into the similarities and differences between these methods

Ka-Map: an interactive web-mapping application

ka-Map ("ka" as in ka-boom!) is an open source project that is aimed at providing a javascript API for developing highly interactive web-mapping interfaces using features available in modern web browsers. ka-Map currently has a number of interesting features. It sports the usual array of user interface elements such as: interactive, continuous panning without reloading the page; keyboard navigation options (zooming, panning); zooming to pre-set scales; interactive scalebar, legend and keymap support; optional layer control on client side; server side tile caching

Online Robust 3D Mapping Using Structure from Motion Cues

This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

Mapping sub-flows to p2mp LSPs

In previous work we proposed a multi-objective traffic engineering scheme (MHDB-S model) using different distribution trees to multicast several flows. In this paper, we propose a heuristic algorithm to create multiple point-to-multipoint (p2mp) LSPs based on the optimum sub-flow values obtained with our MHDB-S model. Moreover, a general problem for supporting multicasting in MPLS networks is the lack of labels. To reduce the number of labels used, a label space reduction algorithm solution is also considered

Mapping the Web and Web Science

This tutorial material introduces an activity in which the students are asked to redraw Tim Berners-Lee's map of the Web to include Web Science.

Mapping the Web

Different attempts to 'map' different aspects of the web. How do you impose some sort of high level understanding onto the Web Graph?

Scalable real-time crisis mapping and analytics of social media streams for disaster management and breaking news

Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

mapping your journey

mapping your journey