157 research outputs found

    Understanding the Emergent Structure of Competency Centers in Post-implementation Enterprise Systems

    Get PDF
    Part 3: Structures and NetworksInternational audiencePrior research provides conflicting insights about the link between investment in enterprise systems and firm value and in the ES governance mechanisms. The literature generally suggests that management should cultivate its technical and organizational expertise to derive value from currently deployed Enterprise Systems (ES) [8]. In the realm of practice, ERP vendors and configuration/integration partners strongly recommend the creation of an organizational structure to govern the ERP implementation and post-implementation process to improve project success and extract greater value from the ES investment. The ES literature, while unclear on the formation, and functioning of ES governance units, suggests the need for formal and fixed governance structures. This research utilizes Deleuze’s assemblage theory and emergence theory to explain the genesis and evolution of the governing ‘structure’ known as the Competency Center (CC). Our results illustrate the business needs driving the structuring processes behind the CC, are also those that lead to unintended and destabilizing outcomes. Whether the CC ‘assemblage’ survives to provide value depends on how the emergent issues are handled and how the assemblages are “positioned”. This research suggests effective ES governance is not derived from a prescribed step-wise process yielding formal structures, but rather form an organic process of assemblage

    Viscoelastic gels of guar and xanthan gum mixtures provide long-term stabilization of iron micro- and nanoparticles

    Get PDF
    Iron micro- and nanoparticles used for groundwater remediation and medical applications are prone to fast aggregation and sedimentation. Diluted single biopolymer water solutions of guar gum (GG) or xanthan gum (XG) can stabilize these particles for few hours providing steric repulsion and by increasing the viscosity of the suspension. The goal of the study is to demonstrate that amending GG solutions with small amounts of XG (XG/GG weight ratio 1:19; 3 g/L of total biopolymer concentration) can significantly improve the capability of the biopolymer to stabilize highly concentrated iron micro- and nanoparticle suspensions. The synergistic effect between GG and XG generates a viscoelastic gel that can maintain 20 g/L iron particles suspended for over 24 h. This is attributed to (i) an increase in the static viscosity, (ii) a combined polymer structure the yield stress of which contrasts the downward stress exerted by the iron particles, and (iii) the adsorption of the polymers to the iron surface having an anchoring effect on the particles. The XG/GG viscoelastic gel is characterized by a marked shear thinning behavior. This property, coupled with the low biopolymer concentration, determines small viscosity values at high shear rates, facilitating the injection in porous media. Furthermore, the thermosensitivity of the soft elastic polymeric network promotes higher stability and longer storage times at low temperatures and rapid decrease of viscosity at higher temperatures. This feature can be exploited in order to improve the flowability and the delivery of the suspensions to the target as well as to effectively tune and control the release of the iron particle

    Remediation of Uranium in the Hanford Vadose Zone Using Ammonia Gas: FY 2010 Laboratory-Scale Experiments

    Get PDF
    This investigation is focused on refining an in situ technology for vadose zone remediation of uranium by the addition of ammonia (NH3) gas. Objectives are to: a) refine the technique of ammonia gas treatment of low water content sediments to minimize uranium mobility by changing uranium surface phases (or coat surface phases), b) identify the geochemical changes in uranium surface phases during ammonia gas treatment, c) identify broader geochemical changes that occur in sediment during ammonia gas treatment, and d) predict and test injection of ammonia gas for intermediate-scale systems to identify process interactions that occur at a larger scale and could impact field scale implementation.Overall, NH3 gas treatment of low-water content sediments appears quite effective at decreasing aqueous, adsorbed uranium concentrations. The NH3 gas treatment is also fairly effective for decreasing the mobility of U-carbonate coprecipitates, but shows mixed success for U present in Na-boltwoodite. There are some changes in U-carbonate surface phases that were identified by surface phase analysis, but no changes observed for Na-boltwoodite. It is likely that dissolution of sediment minerals (predominantly montmorillonite, muscovite, kaolinite) under the alkaline conditions created and subsequent precipitation as the pH returns to natural conditions coat some of the uranium surface phases, although a greater understanding of these processes is needed to predict the long term impact on uranium mobility. Injection of NH3 gas into sediments at low water content (1% to 16% water content) can effectively treat a large area without water addition, so there is little uranium mobilization (i.e., transport over cm or larger scale) during the injection phase

    Responsive Production in Manufacturing: A Modular Architecture

    Full text link
    [EN] This paper proposes an architecture aiming at promoting the convergence of the physical and digital worlds, through CPS and IoT technologies, to accommodate more customized and higher quality products following Industry 4.0 concepts. The architecture combines concepts such as cyber-physical systems, decentralization, modularity and scalability aiming at responsive production. Combining these aspects with virtualization, contextualization, modeling and simulation capabilities it will enable self-adaptation, situational awareness and decentralized decision-making to answer dynamic market demands and support the design and reconfiguration of the manufacturing enterprise.The research leading to these results has received funding from the European Union H2020 project C2 NET (FoF-01-2014) nr 636909.Marques, M.; Agostinho, C.; Zacharewicz, G.; Poler, R.; Jardim-Goncalves, R. (2018). Responsive Production in Manufacturing: A Modular Architecture. Studies in Systems, Decision and Control. 140:231-254. https://doi.org/10.1007/978-3-319-78437-3_10S231254140European Commission: For a European Industrial Renaissance, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions (2014)Hartmann, B., King, W.P., Narayanan, S.: Digital manufacturing: the revolution will be virtualized. McKinsey & Company (2015)European Forum for Manufacture: Driving Innovation and Growth in European Manufacturing (2015)European Factories of the Future Research Association (EFFRA): Factories of the Future: Multi-annual Roadmap for the Contractual PPP under the Horizon 2020 (2013)European Commission: Horizon 2020—Work Programme 2016–2017: 17. Cross-cutting Activities (2016)Schlaepfer, R.C., Koch, M., Merkofer, P.: Industry 4.0 challenges and solutions for the digital transformation and use of exponential technologies. Deloitte AG (2015)7iD: Industry 4.0. https://www.7id.com/technology/industry-4-0/ (2016)European Commission: Horizon 2020—Work Program 2016-2017—Cross-cutting Activities, 25 July 2016EFFRA: Factories of the Future: Multi-annual Roadmap for the Contractual PPP under the Horizon 2020 (2013)FInES Research Roadmap Task Force (2012)Jacinto, J.: Smart manufacturing? Industry 4.0? What’s it all about? Siements Totally Integrated Automation, Automation World & Design World (2014)Monostori, L.: Cyber-physical production systems: roots, expectations and R&D challenges. Procedia CIRP 17, 9–13 (2014)Adolphs, P.: RAMI 4.0—An architectural Model for Industrie 4.0. Platform Industrie 4.0 (2015)Collins, M.: Why America has a shortage of skilled workers. Industry Week (2015)Forbes, J., Naujok, N., Geissbauer, R., Vedso, J., Schrauf, S.: Industry 4.0: building the digital enterprise. PWC (2016)World Economic Forum Industrial Internet Survey (2014)Chen, D., Vernadat, F.B.: Enterprise interoperability: a standardisation view. Enterprise Inter- and Intra-Organizational Integration, Volume 108 of the series IFIP—The International Federation for Information Processing, pp. 273–282 (2003)Yan, L., Li, Z., Yuan, X.: Study on method-of-robust-multidisciplinary-design-collaborative-decision for product design. Inf. Technol. J. 8(4), 441–452 (2009)Ruiz Dominguez, G. A.: CaractĂ©risation de l’activitĂ© de conception collaborative Ă  distance: Ă©tude des effets de synchronisation cognitive (2005)Jung, J.J.: Reusing ontology mappings for query routing in semantic peer-to-peer environment. Inf. Sci. (2010). https://doi.org/10.1016/j.ins.2010.04.018Ranjan, R., Zhao, L., Wu, X., Liu, A., Quiroz, A., Parashar, M.: Peer-to-Peer Cloud Provisioning: Service Discovery and Load-Balancing. https://doi.org/10.1007/978-1-84996-241-4_12Agostinho, C., Pinto, P., Jardim-goncalves, R.: Dynamic adaptors to support model-driven interoperability and enhance sensing enterprise networks. In: 19th World Congress of the International Federation of Automatic Control (IFAC’14), Cape Town, South Africa (2014)Chen, D., Doumeingts, G., Vernadat, F.: Architectures for enterprise integration and interoperability: past, present and future. Comput. Ind. 59, 647–659 (2008). https://doi.org/10.1016/j.compind.2007.12.016Ducq, Y., Chen, D., Alix, T.: Principles of servitization and definition of an architecture for model driven service system engineering. In: 4th International IFIP Working Conference on Enterprise Interoperability (IWEI 2012), Harbin, China, 2012. https://doi.org/10.1007/978-3-642-33068-17_12ElvesĂŠter, B., Hahn, A., Berre, A., Neple, T.: Towards an interoperability framework for model-driven development of software systems. In: 1st International Conference on Interoperability Enterprise Software and Applications. Springer. http://www.springerlink.com/index/L10NU4306N054T6G.pdf (2005)OMG: MDA Guide Version 1.0.1 (omg/2003-06-01), Object Management Group. http://www.omg.org/cgibin/doc?omg/03-06-01.pdf (2003)Agostinho, C., Ducq, Y., Zacharewicz, G., Sarraipa, J., Lampathaki, F., Poler, R., Jardim-Goncalves, R.: Towards a sustainable interoperability in networked enterprise information systems: trends of knowledge and model-driven technology. Comput. Ind. (2015). https://doi.org/10.1016/j.compind.2015.07.001Santucci, G., Martinez, C., Vlad-cĂąlcic, D.: The sensing enterprise. In: FInES Work. FIA 2012, Aalborg, Denmark. http://www.theinternetofthings.eu/sites/default/files/%5Buser-name%5D/Sensing-enterprise.pdf (2012)Sriram, R.: Smart networked systems and societies: what will the future look like? In: IEEE IT Professional Conference (IT Pro). IEEE Computer Society (2014)Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., et al.: Big data: the next frontier for innovation, competition, and productivity. http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation (2011)Zacharewicz, G., Diallo, S., Ducq, Y., Agostinho, C., Jardim-Goncalves, R., Bazoun, H., Wang, Z., Doumeingts, G.: Model-based approaches for interoperability of next generation enterprise information systems: state of the art and future challenges. Inf. Syst. e-Bus. Manag. (2016). https://doi.org/10.1007/s10257-016-0317-8Jardim-Goncalves, R., Agostinho, C., Steiger-Garcao, A.: A reference model for sustainable interoperability in networked enterprises: towards the foundation of EI science base. Int. J. Comput. Integr. Manuf. 25(10) (2012). (Special Issue on Collaborative Manufacturing and Supply Chains). https://doi.org/10.1080/0951192x.2011.653831Schatsky, D., Muraskin, C.: Blockchain is coming to disrupt your industry. Deloitte (2015)Shi, J., Wan, J., Yan, H., Suo, H.: A survey of cyber-physical systems. In: International Conference on Wireless Communications and Signal Processing, pp. 1–6 (2011)Rajkumar, R.: Workshop report on foundations for innovation in cyber-physical systems. NIST. http://www.nist.gov/el/upload/CPS-WorkshopReport-1-30-13-Final.pdf/ (2013)Lee, J., Lapira, E., Yang, S. Kao, H.-A.: Predictive manufacturing system trends of next generation production systems. In: 11th IFAC Workshop on Intelligent Manufacturing Systems, vol. 11, issue 1, pp. 150–156 (2013)IDC: The digital universe of opportunities: rich data and increasing value of the internet of things. EMC Digital Universe. emc.com/collateral/analyst-reports/idc-digital-universe-2014.pdf . (2014)Baheti, R., Gill, H.: Cyber-physical systems. Impact Control Technol. 1–6 (2011)Lee, J., Bagheri, B., Kao, H.-A.: A cyber physical systems architecture for Industry 4.0-based manufacturing system. Manuf. Lett. 2015, 3, 18–23 (2014). https://doi.org/10.1016/j.mfglet.2014.12.001Bagheri, B., Lee, J.: Big future for cyber-physical manufacturing systems. Design World. http://www.designworldonline.com/big-future-for-cyber-physical-manufacturing-systems/ (2015)Lucke, D., Constantinescu, C., WestkĂ€mper, E.: Smart factory-a step towards the next generation of manufacturing. Manufacturing Systems and Technologies for the New Frontier, pp. 115–118. Springer, London (2008)Weiser, M.: The Computer for the 21st Century. Scientific American, Special Issue on Communications. Comput. Netw. (1991)WestkĂ€mper, E., Jendoubi, L., Eissele, M., Ertl, T.: Smart factory—bridging the gap between digital planning and reality. Manuf. Syst. 35(4), 307–314 (2006)Goryachev, A., Kozhevnikov, S., Kolbova, E., Kuznetsov, O., Simonova, E., Skobelev, P., Tsarev, A., Shepilov, Y.: Smart factory: intelligent system for workshop resource allocation, scheduling, optimization and controlling in real time. Adv. Mater. Res. 630, 508–513 (2012)Agostinho, C., Marques-Lucena, C., Sesana, M., Felic, A., Fischer, K., Rubattino, C., Sarraipa, J.: Osmosis process development for innovative product design and validation. 2015 ASME IMECE, Houston, USA (2015)Ko, J., Lee, B., Lee, K., Hong, S.G., Kim, N., Paek, J.: Sensor virtualization module: virtualizing IoT devices on mobile smartphones for effective sensor data management. Int. J. Distrib. Sens. Netw. (2015). https://doi.org/10.1155/2015/730762Guo, T., Papaioannou, T.G., Aberer, K.: Efficient indexing and query processing of model-view sensor data in the cloud. J. Big Data Res. 1, 52–65 (2014)Kumra, S., Sharma, L., Khanna, Y., Chattri, A.: Analysing an industrial automation pyramid and providing service oriented architecture. Int. J. Eng. Trends Technol. 3(5), 586–594 (2012)Endsley, M.: Design and evaluation for situational awareness enhancement. In: Proceedings of the Human Factors Society 32nd Annual Meeting. HFES, Santa Monica, pp. 97–10 (1988)Stanton, N.A., Chambers, P.R., Piggott, J.: Situational awareness and safety. Saf. Sci. 39(3), 189–204 (2001)Endsley, M.: Toward a theory of situation awareness in dynamic systems. Hum. Factors (The Journal of the Human Factors and Ergonomics Society) 37, 32–64 (1995)Bedny, G., Meister, D.: Theory of activity and situation awareness. Int. J. Cogn. Ergon. 3(1), 63–72 (1999)Smith, K., Hancock, P.A.: Situation awareness is adaptive, externally directed consciousness. Hum. Factors (The Journal of the Human Factors and Ergonomics Society) 37(1), 137–148 (1995)Ranganathan, A., Campbell, R.H.: An infrastructure for context-awareness based on first order logic. Pers. Ubiquit. Comput. 7(6), 353–364 (2003)Ning, K., Scholze, S., Marques, M., Campos, A, Neves-Silva, R. O’Sullivan, D.: A service oriented platform for context aware knowledge enhancing. In: 5th IFAC Conference on Management and Control of Production and Logistics (2010)Marques, M., Sucic, B., Vuk, T.: Context-based decision support for sustainable optimization of energy consumption. KES Trans. Sustain. Des. Manuf. 1(1), 899–910 (2014)Schneeweiss, C.: Distributed decision making in supply chain management. Int. J. Product. Econ. 84, 71–83 (2003)Alemany, M.M.E., AlarcĂłn, F., Lario, F.C., Boj, J.J.: An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Comput. Ind. 62(5), 519–540 (2011). https://doi.org/10.1016/j.compind.2011.02.002Hong, I.H., Ammons, J.C., Realff, M.J.: Centralized versus decentralized decision-making for recycled material flows. Environ. Sci. Technol. 42(4), 1172–1177 (2008)Pibernik, R., Sucky, E.: An approach to inter-domain master planning in supply chains. Int. J. Product. Econ. 108, 200–212 (2007). https://doi.org/10.1016/j.ijpe.2006.12.010Lee, H., Whang, S.: Decentralized multi-echelon supply chains: incentives and information. Manag. Sci. 45(5), 633–640 (1999)Jung, H., Chen, F., Jeong, B.: Decentralized supply chain planning framework for third party logistics partnership. Comput. Ind. Eng. 55(2), 348–364 (2008). https://doi.org/10.1016/j.cie.2007.12.017Wang, K.-J., Chen, M.-J.: Cooperative capacity planning and resource allocation by mutual outsourcing using ant algorithm in a decentralized supply chain. Expert Syst. Appl. 36(2), 2831–2842 (2009)Simon, H.A.: The Science of the Artificial, 1st edn. MIT Press, Cambridge, Mass, (1969). (3rd ed. in 1996, MIT Press)Mesarovic, M.D., Masko, D., Takahara, Y.: Theory of Hierarchical Multilevel Systems. Academic Press, New York and London (1970)Camarinha-Matos, L.M., Afsarmanesh, H.J.: Collaborative networks: a new scientific discipline. J. Intell. Manuf. 16(4), 439–452 (2005)Popplewell, K., Stojanovic, N., Abecker, A., Apostolou, D., Mentzas, G., Harding, J.: Supporting adaptive enterprise collaboration through semantic knowledge services. In: Enterprise Interoperability Iii: New Challenges and Industrial Approaches, pp. 381–393 (2008). http://doi.org/10.1007/978-1-84800-221-0_30Agostinho, C., Ducq, Y., Zacharewicz, G., Sarraipa, J., Lampathaki, F., Jardim-Goncalves, R., Poler, R.: Towards a sustainable interoperability in networked enterprise information systems: trends of knowledge and model-driven technology. Accepted for Publication at Computers in Industry. http://doi.org/10.1016/j.compind.2015.07.001Agostinho, C., Jardim-Gonçalves, R.: Sustaining interoperability of networked liquid-sensing enterprises: a complex systems perspective. Annu. Rev. Control 39, 128–143 (2015). https://doi.org/10.1016/j.arcontrol.2015.03.012Weichhart, G., Molina, A., Chen, D., Whitman, L. E., Vernadat, F.: Challenges and current developments for sensing, smart and sustainable enterprise systems. Computers in Industry (2015). http://doi.org/10.1016/j.compind.2015.07.002Weichhart, G.: Supporting Interoperability for Chaotic and Complex Adaptive Enterprise Systems. On the Move to Meaningful Internet Systems: OTM 2013 Workshops. Confederated International Workshops: OTM Academy, OTM Industry Case Studies Program, ACM, EI2N, ISDE, META4eS, ORM, SeDeS, SINCOM, SMS, and SOMOCO 2013. Proceedings: LNCS 8186, 86–92. (2013). http://doi.org/10.1007/978-3-642-41033-8_14Truex, D.P., Baskerville, R., Klein, H.: Growing systems in emergent organizations. Mag. Commun. ACM CACM Homepage Arch. 42(8), 117–123 (1999)Weiberg, S.: Facilitating collaborative decision-making in six steps. International Association of Facilitators Annual Meeting, pp. 14–15 (1999)Delbecq, A.L., VandeVen, A.H.: A group process model for problem identification and program planning. J. Appl. Behav. Sci. 7, 466–492 (1971). https://doi.org/10.1177/002188637100700404Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York, USA (1980

    High resolution 3-Dimensional imaging of the human cardiac conduction system from microanatomy to mathematical modeling

    Get PDF
    Cardiac arrhythmias and conduction disturbances are accompanied by structural remodelling of the specialised cardiomyocytes known collectively as the cardiac conduction system. Here, using contrast enhanced micro-computed tomography, we present, in attitudinally appropriate fashion, the first 3-dimensional representations of the cardiac conduction system within the intact human heart. We show that cardiomyocyte orientation can be extracted from these datasets at spatial resolutions approaching the single cell. These data show that commonly accepted anatomical representations are oversimplified. We have incorporated the high-resolution anatomical data into mathematical simulations of cardiac electrical depolarisation. The data presented should have multidisciplinary impact. Since the rate of depolarisation is dictated by cardiac microstructure, and the precise orientation of the cardiomyocytes, our data should improve the fidelity of mathematical models. By showing the precise 3-dimensional relationships between the cardiac conduction system and surrounding structures, we provide new insights relevant to valvar replacement surgery and ablation therapies. We also offer a practical method for investigation of remodelling in disease, and thus, virtual pathology and archiving. Such data presented as 3D images or 3D printed models, will inform discussions between medical teams and their patients, and aid the education of medical and surgical trainees

    Nanoscale Metallic Iron for Environmental Remediation: Prospects and Limitations

    Get PDF
    The amendment of the subsurface with nanoscale metallic iron particles (nano-Fe0) has been discussed in the literature as an efficient in situ technology for groundwater remediation. However, the introduction of this technology was controversial and its efficiency has never been univocally established. This unsatisfying situation has motivated this communication whose objective was a comprehensive discussion of the intrinsic reactivity of nano-Fe0 based on the contemporary knowledge on the mechanism of contaminant removal by Fe0 and a mathematical model. It is showed that due to limitations of the mass transfer of nano-Fe0 to contaminants, available concepts cannot explain the success of nano-Fe0 injection for in situ groundwater remediation. It is recommended to test the possibility of introducing nano-Fe0 to initiate the formation of roll-fronts which propagation would induce the reductive transformation of both dissolved and adsorbed contaminants. Within a roll-front, FeII from nano-Fe0 is the reducing agent for contaminants. FeII is recycled by biotic or abiotic FeIII reduction. While the roll-front concept could explain the success of already implemented reaction zones, more research is needed for a science-based recommendation of nano- Fe0 for subsurface treatment by roll-front

    Lingual kinematic strategies used to increase speech rate: Comparisons between younger and older adults

    Get PDF
    The primary objective of this study was to assess the lingual kinematic strategies used by younger and older adults to increase rate of speech. It was hypothesised that the strategies used by the older adults would differ from the young adults either as a direct result of, or in response to a need to compensate for, age-related changes in the tongue. Electromagnetic articulography was used to examine the tongue movements of eight young (M526.7 years) and eight older (M567.1 years) females during repetitions of /ta/ and /ka/ at a controlled moderate rate and then as fast as possible. The younger and older adults were found to significantly reduce consonant durations and increase syllable repetition rate by similar proportions. To achieve these reduced durations both groups appeared to use the same strategy, that of reducing the distances travelled by the tongue. Further comparisons at each rate, however, suggested a speed-accuracy trade-off and increased speech monitoring in the older adults. The results may assist in differentiating articulatory changes associated with normal aging from pathological changes found in disorders that affect the older population

    Scientific Opportunities for Monitoring of Environmental Remediation Sites (SOMERS) - 12224

    Get PDF
    ABSTRACT The US Department of Energy (DOE) is responsible for risk reduction and cleanup of its nuclear weapons complex. DOE maintains the largest cleanup program in the world, currently spanning over a million acres in 13 states. The inventory of contaminated materials includes 90 million gallons of radioactive waste, 6.4 trillion liters of groundwater, and 40 million cubic meters of soil and debris. It is not feasible to completely restore many sites to predisposal conditions. Any contamination left in place will require monitoring, engineering controls and/or land use restrictions to protect human health and environment. Research and development efforts to date have focused on improving characterization and remediation. Yet, monitoring will result in the largest life-cycle costs and will be critical to improving performance and protection. Through an inter-disciplinary effort, DOE is addressing a need to advance monitoring approaches from sole reliance on cost-and labor-intensive point-source monitoring to integrated systems-based approaches such as flux-based approaches and the use of early indicator parameters. Key objectives include identifying current scientific, technical and implementation opportunities and challenges, prioritizing science and technology strategies to meet current needs within the DOE complex for the most challenging environments, and developing an integrated and risk-informed monitoring framework
    • 

    corecore