Distributed design of product oriented manufacturing systems

Manufacturing leanness and agility are requirements of today’s manufacturing systems. Leanness call for a best fit of the manufacturing systems to products, therefore requiring product oriented manufacturing systems (POMS). Manufacturing agility can be achieved through easy systems reconfiguration to fit changing manufacturing requirements, which may mean dynamically configuring POMS. For this a suitable design system is required. Due to complexity of this design, and to the need for using suitable design methods, which may not be available locally, distributed sources of design services can be used. This paper presents and describes a prototype of a Distributed Design system for POMS based on a POMS design methodology and distributed suppliers of design services

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

<p>Abstract</p> <p>Background</p> <p>Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites.</p> <p>Results</p> <p>We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information.</p> <p>Conclusion</p> <p>While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at <url>http://phos3d.mpimp-golm.mpg.de</url>.</p

The Mass Distribution and Rotation Curve in the Galaxy

The mass distribution in the Galaxy is determined by dynamical and photometric methods. Rotation curves are the major tool for determining the dynamical mass distribution in the Milky Way and spiral galaxies. The photometric (statistical) method utilizes luminosity profiles from optical and infrared observations, and assumes empirical values of the mass-to-luminosity (M/L) ratio to convert the luminosity to mass. In this chapter the dynamical method is described in detail, and rotation curves and mass distribution in the Milky Way and nearby spiral galaxies are presented. The dynamical method is categorized into two methods: the decomposition method and direct method. The former fits the rotation curve by calculated curve assuming several mass components such as a bulge, disk and halo, and adjust the dynamical parameters of each component. Explanations are given of the mass profiles as the de Vaucouleurs law, exponential disk, and dark halo profiles inferred from numerical simulations. Another method is the direct method, with which the mass distribution can be directly calculated from the data of rotation velocities without employing any mass models. Some results from both methods are presented, and the Galactic structure is discussed in terms of the mass. Rotation curves and mass distributions in external galaxies are also discussed, and the fundamental mass structures are shown to be universal.Comment: 54 pages, 25 figures, in 'Planets, Stars and Stellar Systems', Springer, Vol. 5, ed. G. Gilmore, Chap. 19. Note: Preprint with full figures is available from http://www.ioa.s.u-tokyo.ac.jp/~sofue/htdocs/2013psss

Gravitational-wave research as an emerging field in the Max Planck Society. The long roots of GEO600 and of the Albert Einstein Institute

On the occasion of the 50th anniversary since the beginning of the search for gravitational waves at the Max Planck Society, and in coincidence with the 25th anniversary of the foundation of the Albert Einstein Institute, we explore the interplay between the renaissance of general relativity and the advent of relativistic astrophysics following the German early involvement in gravitational-wave research, to the point when gravitational-wave detection became established by the appearance of full-scale detectors and international collaborations. On the background of the spectacular astrophysical discoveries of the 1960s and the growing role of relativistic astrophysics, Ludwig Biermann and his collaborators at the Max Planck Institute for Astrophysics in Munich became deeply involved in research related to such new horizons. At the end of the 1960s, Joseph Weber's announcements claiming detection of gravitational waves sparked the decisive entry of this group into the field, in parallel with the appointment of the renowned relativist Juergen Ehlers. The Munich area group of Max Planck institutes provided the fertile ground for acquiring a leading position in the 1970s, facilitating the experimental transition from resonant bars towards laser interferometry and its innovation at increasingly large scales, eventually moving to a dedicated site in Hannover in the early 1990s. The Hannover group emphasized perfecting experimental systems at pilot scales, and never developed a full-sized detector, rather joining the LIGO Scientific Collaboration at the end of the century. In parallel, the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) had been founded in Potsdam, and both sites, in Hannover and Potsdam, became a unified entity in the early 2000s and were central contributors to the first detection of gravitational waves in 2015.Comment: 94 pages. Enlarged version including new results from further archival research. A previous version appears as a chapter in the volume The Renaissance of General Relativity in Context, edited by A. Blum, R. Lalli and J. Renn (Boston: Birkhauser, 2020

Flexible Manufacturing Systems: background examples and models

In this paper, we discuss recent innovations in manufacturing technology and their implications on the design and control of manufacturing systems. Recognizing the need to respond properly to rapidly changing market demands, we discuss several types of flexibility that can be incorporated in our production organisation to achieve this goal. We show how the concept of a Flexible Manufacturing System (FMS) naturally arises as an attempt to combine the advantages of traditional Job Shops and dedicated production lines.The main body of the paper is devoted to a classification of FMS problem areas and a review of models developed to understand and solve these problems. For each problem area, a number of important contributions in the literature is indicated. The reader, interested in the applications of Operations Research models but not familiar with the technical background of FMS’s, will find the descriptions of some essential FMS elements useful. Some final remarks and directions for future research conclude the paper.<br/