{"74521":{"#nid":"74521","#data":{"type":"news","title":"Advanced Manufacturing at ISyE","body":[{"value":"\u003Cp\u003EWhen President Barack Obama named Georgia Tech\nPresident G. P. \u201cBud\u201d Peterson to the steering committee of the Advanced\nManufacturing Partnership (AMP) in June, he was acknowledging an established\nfact\u2014the Georgia Institute of Technology is a national leader in supporting\nAmerican industry.\u003C\/p\u003E\n\n\u003Cp\u003ETech joined other top universities\u2014the Massachusetts\nInstitute of Technology, Carnegie Mellon, Stanford, University of\nCalifornia-Berkeley, and University of Michigan\u2014in the $500 million AMP push to\nguide investment in emerging technologies and increase the supply of\nhigh-quality manufacturing jobs and overall U.S. global competitiveness.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cWe applaud this initiative, and Georgia Tech is\nhonored to collaborate to identify ways to strengthen the manufacturing sector\nto help create jobs in Georgia and across the United States,\u201d Peterson said.\n\u201cMany of our challenges can be solved through innovation and fostering an\nentrepreneurial environment, as well as collaboration between industry,\neducation, and government to create a healthy economic environment and an\neducated workforce.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EToday, the H. Milton Stewart School of Industrial and\nSystems Engineering (ISyE) leads the way in advanced manufacturing research and\ndevelopment at Georgia Tech. ISyE faculty specialize in many related\ndisciplines, including computer-integrated systems, controls for flexible\nautomation, manufacturing systems design, analysis and simulation, lean\nmanufacturing strategies, and performance measurements.\u003C\/p\u003E\n\n\u003Cp\u003EAdvanced manufacturing involves not only new ways to\nmanufacture existing products, but also new products emerging from advanced\ntechnologies, observes Stephen E. Cross, Georgia Tech\u2019s executive vice\npresident for research. Cross, who is also a professor in ISyE, is working with\nPresident Peterson to support the AMP.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cISyE\u2019s competencies in manufacturing, logistics,\nsupply chains, and methodological work in operations research, statistics,\nsimulation, and decision support provide the intellectual core for a\nrenaissance in advanced manufacturing,\u201d Cross said recently. \u201cISyE\u2019s track\nrecord of excellence, combined with equally stellar research throughout the\nrest of the Institute, has made Tech one of the leading research universities\nin the world.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EISyE Professor Leon McGinnis is supporting both\nPeterson and Cross in their work with the AMP Steering Committee. McGinnis is\nbeing joined by Ben Wang, who in January will assume the role of executive\ndirector of the Manufacturing Research Center (MaRC) at Georgia Tech and also\nbecome a professor in ISyE.\u003C\/p\u003E\n\n\u003Cp\u003EBoth educators will serve on a Georgia Tech working\ngroup that will focus on ways in which research and education can maximize the\nimpact of emerging technologies on the U.S. manufacturing sector.\u003C\/p\u003E\n\n\u003Cp\u003EOther ISyE faculty serving the advanced\nmanufacturing thrust includes Professor Chelsea (Chip) White III, Schneider\nNational Chair in Transportation and Logistics, and Harvey Donaldson, associate\nchair of Industry and International programs. Both are involved in a workshop\nfocusing on the Council on Competitiveness\u2019s U.S. manufacturing competitiveness\ninitiative. The meeting, planned for early 2012 at Georgia Tech, will focus on\nhow the supply chain and logistics industry can best support U.S. manufacturing\ncompetitiveness.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cAdvanced manufacturing can be viewed as a system of\nsystems that involves design, processes, equipment, information, energy,\nmaterials, and the entire supply chain,\u201d said Wang, who served as director of\nthe High-Performance Materials Institute at Florida State University before\ncoming to Georgia Tech. \u201cThis new kind of manufacturing relies on a highly\neducated workforce and on truly innovative research capable of furnishing the\nbasis for new companies as well as supporting existing industry\u2014and ISyE is\nuniquely positioned to supply both the skilled workforce and the innovative\nresearch.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EISyE faculty members conduct some $6.5 million in\nsponsored research annually, in areas that support all facets of manufacturing\nand industrial systems\u2013 optimization, stochastic systems, logistics,\nsimulation, statistics, natural systems, economic decision analysis, and\nhuman-integrated systems analysis. \u003C\/p\u003E\n\n\u003Cp\u003EBelow are instances (in alphabetical order) of the\ncutting-edge work being performed by ISyE faculty in areas related to advanced manufacturing.\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003EJane Ammons,\u003C\/strong\u003E who is the H. Milton and\nCarolyn J. Stewart School Chair and a professor in ISyE, collaborates on\nreverse production systems with Matthew Realff, a professor in the School of\nChemical \u0026amp; Biomolecular Engineering (ChBE) and David Wang Sr. Fellow. For\nmore than ten years, the team has focused on two important areas: the recovery and\nreuse of carpet wastes and ways to reduce electronic waste (e-waste).\u003C\/p\u003E\n\n\u003Cp\u003EAmmons, Realff, and their team have developed a\nmathematical framework to support the growth of used-carpet collection\nnetworks. Such networks could help to recycle much of the nation\u2019s annual\ncarpet waste total of 4.7 billion pounds. The successful reuse of that carpet\nhas a potential value of $2.8 billion, versus a cost of $100 million to send\nthe waste to landfills.\u003C\/p\u003E\n\n\u003Cp\u003EIn other work, the team is studying the problem of\ne-waste\u2014unwanted electronic components such as televisions, monitors, and\ncomputer boards and chips. The e-waste stream includes multiple hazardous\nmaterials containing lead and other toxins, yet effective management and reuse\nof e-components can be profitable. Ammons and Realff have devised mathematical\nmodels that address the complexities of e-waste processing, with the goal of\nhelping recycling companies stay economically viable.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cWorking with both, companies and government, our\ngoal is to eliminate as much product disposal in landfills as possible,\u201d Ammons\nsaid. \u201cBy extending our work to address new operational control and\ninfrastructure design problems, we can help to address uncertainty and\nvariability in closed-loop supply chain flows on a global scale.\u201d\u003C\/p\u003E\n\n\u003Cp\u003E\u0026nbsp;Associate\nProfessor \u003Cstrong\u003ENagi Gebraeel \u003C\/strong\u003Econducts\nresearch in the area of detecting and preventing failure in engineering systems\nas they degrade over time. The goal is to avoid both expensive downtime and\nunnecessary maintenance costs.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cWe could be talking about a fleet of airlines,\ntrucks, trains, ships\u2014or a manufacturing system,\u201d Gebraeel said. \u201cIn any of\nthese cases, it\u2019s extremely useful for a number of reasons to be able to\naccurately estimate the remaining useful lifetime of the system or its components.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EIn one project, Gebraeel and his team worked with\nRockwell Collins\u2014a Cedar Rapid, Iowa, maker of avionics and electronics\u2014to\nmonitor and diagnose the performance of circuit boards that control vital\naircraft communication systems.\u003C\/p\u003E\n\n\u003Cp\u003ESince the exact time of component failure is\nunknown, airlines are forced to anticipate when replacements are needed.\nScheduled maintenance can result in replacement of parts that still have usable\nlife. Using circuit boards until parts actually fail will result in unplanned\nand expensive downtime.\u003C\/p\u003E\n\n\u003Cp\u003EAs Gebraeel methodically exposes an avionics\ncomponent to heat and vibration, he employs a network of computers and sensors\nto record and analyze data on the degradation rate of the part he is testing.\nIf he can reliably predict the failure rate of a component, he can help\nairlines replace parts at the most cost-effective time.\u003C\/p\u003E\n\n\n\n\u003Cp\u003EIn another effort, Gebraeel has developed an\nadaptive prognostics system (APS), a custom research tool that allows him to\ninvestigate how quickly components degrade under vibration and other stresses.\nGebraeel and his team can use APS to test a complex system\u2014such as a gearbox\u2014by\nusing multiple sensors in a triangulated pattern to detect the frequency\nsignals coming from individual components.\u003C\/p\u003E\n\n\u003Cp\u003EGebraeel is currently in talks with a major airline\nto use APS to analyze critical engine components. The aim is to be able to\npredict engine wear rates in ways that will help optimize aircraft maintenance\nprocedures.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cThere\u2019s a real need for information about the remaining\nlife of components, so that users can find the economical middle ground between\nthe cost of scheduled replacements and the cost of failure,\u201d he said. \u201cThink of\nthe everyday problem of whether we really need to replace vehicle engine oil at\n3,000 miles. If we replace it early, we sacrifice some useful time, but if we\nreplace it later, we risk engine damage. It\u2019s very useful to have detailed\ninformation about degradation in a system over time.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EProfessor\n\u003Cstrong\u003ELeon McGinnis \u003C\/strong\u003Efocuses on model-based\nsystems engineering, an approach that uses cutting-edge computational methods\nto enable capture and reuse of systems knowledge among multiple stakeholders. McGinnis,\nhis team, and other faculty collaborators are pursuing several sponsored\nprojects in this area.\u003C\/p\u003E\n\n\u003Cp\u003EIn one notable project, McGinnis and his team are\nworking with Rockwell Collins, the Iowa-based maker of avionics and\nelectronics. The aim is to help the corporation speed transition of new\nproducts by automating the process that simulates physical manufacturing.\u003C\/p\u003E\n\n\u003Cp\u003EIn order to optimize the resources needed to make\nproducts at the required rate, McGinnis explains, Rockwell Collins creates a\ncomputerized simulation model of the manufacturing processes. Development of\nsimulation models has traditionally been the province of experts who are\nskilled in using initial system designs to simulate the demands of actual\nproduction.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cThis is not a trivial task\u2014producing a simulation\nmodel requires some 100 to 200 hours per product,\u201d said McGinnis, who holds the\nEugene C. Gwaltney Chair in Manufacturing Systems. \u201cDue to expert resource\nlimitations, the company was only able to generate a few production models at a\ntime, which created something of a bottleneck.\u201d\u003C\/p\u003E\n\n\u003Cp\u003ETo analyze the model-development process, an ISyE\nteam interviewed Rockwell Collins engineers on the methods they used to develop\na simulation model. The Georgia Tech investigators carefully analyzed the steps\nand methods that the engineers used to progress from an original system design\nto a simulation model.\u003C\/p\u003E\n\n\u003Cp\u003EThen the ISyE researchers turned to SysML, a\nlanguage that enables the computerized modeling of complex systems. SysML lets\ndesigners delineate a new product\u2014and multiple related factors such as people,\nmachinery, and product flows\u2014in a standardized way.\u003C\/p\u003E\n\n\u003Cp\u003EBy describing the evolution of a given product using\nSysML, McGinnis and his team were able to automate the movement of that product\nfrom design to simulation. Even more importantly, the ISyE team created a\ndomain-specific version of SysML that was customized to the Rockwell Collins\nenvironment. That achievement allowed any of the company\u2019s new products and\nsystems to be plugged into an SysML-based automation process.\u003C\/p\u003E\n\n\n\n\u003Cp\u003EThis new way to doing things appears to reduce the\ntime required to build simulation models by an order of magnitude McGinnis\nsaid. It also allows multiple products to be developed concurrently and\nencourages \u201cwhat-if\u201d studies that couldn\u2019t be performed before.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cEssentially, this technology lets the people who\nown a process validate it without the middleman\u2014the simulation expert,\u201d he\nsaid. \u201cThere\u2019s a two-part philosophy here\u2014one is to articulate the system in a\nway that all the stakeholders can agree on, and then to automate the bringing\nof information and knowledge to the stakeholders without requiring mediation by\nexperts.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EMcGinnis is also working on several other projects.\nIn one effort, he is collaborating with the School of Mechanical Engineering\nand the Manufacturing Research Center (MaRC) to develop semantics for\nmanufacturing processes under a DARPA contract. In another project, he is\ncollaborating with the Tennenbaum Institute to address the challenges of\nidentifying and mitigating risks in global manufacturing enterprise networks.\nIn other MaRC research, he is investigating the integration of product design\nand manufacturing management of flexibly automated production throughout an\nentire manufacturing system.\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003ESpiridon\nReveliotis\u003C\/strong\u003E, an ISyE professor, is currently involved in a\nproject that addresses a cutting-edge approach to automation in manufacturing.\nThis concept, known as flexible automation, involves variable-size batch\nproduction and the ability to reconfigure and rebalance the shop floor quickly\nto accommodate differing product mixes.\u003C\/p\u003E\n\n\u003Cp\u003ETo date, Reveliotis explains, flexible automation\nhas been most successful at the level of single manufacturing processes. To\naddress this limitation, he is developing the analytical capability and\ncomputational tools to enable effective deployment and in the methodological\nareas that define the technical bases for these works.\u003C\/p\u003E\n\n\u003Cp\u003EReveliotis is using the representation of a Resource\nAllocation System\u2014an enriched version of a queuing network model\u2014and also\nemploying modeling and analytical capabilities derived from modern control\ntheory, computer science, and operations research.\u003C\/p\u003E\n\n\u003Cp\u003EUsing these, he is seeking to build a framework and\nmethodology to enable rapid reconfiguration of automated production systems,\nwith control logic capable of managing the system operation in each new\nconfiguration. One challenge, he said, involves managing the trade-offs between\nthe quest for a high-fidelity model of the underlying shop floor dynamics and\nthe need to keep the control logic and its deployment manageable.\u003C\/p\u003E\n\n\u003Cp\u003EIn another project, Reveliotis is developing methods\nto help remanufacturing facilities approach component-disassembly tasks in the\nmost efficient ways. This work, sponsored by the National Science Foundation,\nuses a learning-based approach comprised of efficient sampling techniques and\nnovel machine-learning algorithms to determine the optimal disassembly plan for\neach product type.\u003C\/p\u003E\n\n\u003Cp\u003EBeyond addressing important practical problems in\nthe manufacturing and remanufacturing domains, both of the above lines of work\nare also contributing seminal analytical results enterprise development for the\naerospace industry. \u003C\/p\u003E\n\n\u003Cp\u003EProfessor\n\u003Cstrong\u003EJianjun (Jan) Shi\u2019s\u003C\/strong\u003E research\naddresses system informatics and control. He uses his training in both\nmechanical and electrical engineering to integrate system data\u2014comprised of\ndesign, manufacturing, automation, and performance information\u2014into models that\nseek to reduce process variability.\u003C\/p\u003E\n\n\u003Cp\u003EShi, who holds the Carolyn J. Stewart Chair in ISyE,\nis currently working on several sponsored projects. In one effort, Shi is\nworking with nGimat, a Norcross, Georgia-based company that was a 1997 graduate\nof the Advanced Technology Development Center startup-company incubator at\nGeorgia Tech.\u003C\/p\u003E\n\n\u003Cp\u003EnGimat is currently addressing the challenge of\nmass-producing a type of nanopowder for use in high-energy, high-density\nbatteries for electric cars. With sponsorship from the Department of Energy\n(DoE), Shi is supporting nGimat as it works to increase its output of this\nnanopowder by several orders of magnitude.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cThis nanopowder product has very good\ncharacteristics, and the task here is to scale-up production while maintaining\nthe quality,\u201d Shi said. \u201cWe must identify the parameters\u2014 what to monitor, what\nto control\u2014to reduce any variability and do so in an environmentally friendly\nway.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EIn work focusing on the steel industry, Shi is pursuing\nmultiple projects including investigating sensing technologies used to monitor\nvery high temperature environments used in steel manufacturing. With DoE\nsupport, he is working with OG technologies to develop methods that employ\noptical sensors capable of providing continuous high-speed images of very hot\nsurfaces\u2014in the area of 1,000 to 1,450 degrees Celsius.\u003C\/p\u003E\n\n\u003Cp\u003EIn steel manufacturing, Shi explains, continuous\ncasting and rolling lines can be miles long and production can take hours.\nVariations in the process temperature\u2014currently difficult to detect\u2014can lead to\ncostly quality problems, increased labor costs, and increased carbon dioxide\nemissions due to wasted energy.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cWe want to catch defect formation in the very early\nstage of manufacturing,\u201d Shi said. \u201cBy using imaging data of the product\neffectively with other process data to eliminate defects, we can help optimize\nthe casting process.\u201d\u003C\/p\u003E\n\n\u003Cp\u003EIn another representative project, Shi is\ninvestigating ways to use process measurements and online adjustments to\nimprove quality control in the manufacturing of the ubiquitous silicon wafers\nused in semiconductor electronics. In work sponsored by the National Science\nFoundation, he is working with several manufacturers to examine the root causes\nof undesirable geometric defects in wafer surfaces.\u003C\/p\u003E\n\n\u003Cp\u003EShi explains that the first step of his approach\ninvolves developing a software model capable of detecting and accurately\ncharacterizing surface characteristics on a silicon wafer. If waves are\npresent, the model must be able to capture both their mean profile as well as\ndetect and characterize particular types of waves.\u003C\/p\u003E\n\n\u003Cp\u003EThe second step requires using this model to judge\nwhether an actual wafer surface is of acceptable quality. If the surface is\nfaulty, the model returns data on what must be done to improve it.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cWafer manufacturing is another instance of a\ncontinuous process where, if you catch imperfections early, you can quickly and\ncost-effectively return to a previous step in the process and correct the\nproblem,\u201d Shi said.\u003C\/p\u003E\n\n\u003Cp\u003EAssociate\nProfessor \u003Cstrong\u003EJoel Sokol\u003C\/strong\u003E, A. Russell\nChandler III Chair and Professor \u003Cstrong\u003EGeorge\nNemhauser\u003C\/strong\u003E, and Professor \u003Cstrong\u003EShabbir\nAhmed\u003C\/strong\u003E recently completed a project supporting a major float glass\nmanufacturer. The company was automating a process where finished glass plates\nare removed from the production line and packed for shipment.\u003C\/p\u003E\n\n\u003Cp\u003EThe company was concerned that the new machines that\npick up and remove glass from the production line might fall behind, allowing\nvaluable plates to be heavily damaged. What was critically needed was the\ncapability to carefully schedule the sequence of production so the machines\ncould function at maximum capacity with as little waste as possible.\u003C\/p\u003E\n\n\n\n\u003Cp\u003EThe ISyE team tackled development of new software\nthat could minimize production scheduling problems. They devised algorithms\nthat allowed the machines to work at their maximum efficiency and enabled them\nto handle input data with more than 99 percent efficiency.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cThe algorithms we delivered can also be used\nstrategically to determine how many machines of each type should be installed\non a production line,\u201d Sokol said.\u003C\/p\u003E\n\n\u003Cp\u003EIn another project, Sokol,\u0026nbsp; Nemhauser, and Ahmed are collaborating on a\nproject for Korea-based Samsung. The aim is to support production throughput at\na Samsung semiconductor- manufacturing facility.\u003C\/p\u003E\n\n\u003Cp\u003EThe challenge involves the physical movement of\nsemiconductors from one processing station to another throughout the factory.\nBecause the routing of semiconductors between processing machines can differ\nfrom item to item, there\u2019s no linear assembly- line type of procedure; instead,\nhundreds of automated vehicles pick up an item from one processing point and\nmove it to its next step.\u003C\/p\u003E\n\n\u003Cp\u003EBecause of the facility\u2019s structure, these automated\nvehicles encounter congestion that can delay the production schedule, Nemhauser\nsaid. The ISyE team is developing ways to best route and schedule the vehicles\nto minimize congestion and move items between machines in ways that don\u2019t delay\nproduction.\u003C\/p\u003E\n\n\u003Cp\u003E\u201cThis is clearly a highly complex challenge that\nwill require development of an accurate system model,\u201d added Ahmed. \u201cBut it\u2019s\nexactly the type of problem that can be solved by devising effective software\nand hardware modifications.\u201d\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003EValerie Thomas\u003C\/strong\u003E, Anderson Interface\nassociate professor of Natural Systems in ISyE, is conducting research on the\nuse of information technology, mediated by bar codes or radio frequency (RFID)\ntags, to improve recycling and end-of-life management for electronics and other\nproducts.\u003C\/p\u003E\n\n\u003Cp\u003EThis work has been presented to the U.S.\nEnvironmental Protection Agency and the U.S. Congress and has been featured in\nthe New York Times and the Wall Street Journal.\u003C\/p\u003E\n\n\u003Cp\u003EIn another area, Thomas is collaborating with\nProfessors Matthew Realff and Ron Chance in the School of Chemical \u0026amp;\nBiomolecular Engineering (ChBE) and with ISyE PhD students Dexin Luo and Dong\nGu Choi on the design, energy efficiency, water management, and carbon\nfootprint for facilities to produce biofuels. This work is supported by Algenol\nBiofuels as part of their $25 million DoE-funded pilot plant for the production\nof ethanol from cyanobacteria.\u003C\/p\u003E\n\n\u003Cp\u003EAssociate\nProfessor \u003Cstrong\u003EChen Zhou\u003C\/strong\u003E, associate chair\nfor undergraduate studies, and Professor Leon McGinnis tackled sustainability\nissues for Ford Motor Company in a recent project.\u003C\/p\u003E\n\n\u003Cp\u003EThe issue involved shipping gearbox components from\nChina to the United States in ways that would minimize not only cost but\ngreenhouse gas emissions and waste.\u003C\/p\u003E\n\n\u003Cp\u003EIt turned out that packaging was at the heart of the\nissue. The researchers had to configure component packaging so that the maximum\nnumber of components could be placed in a cargo container yet also allow for\noptimal recycling of the packing materials to avoid waste and unnecessary cost.\u003C\/p\u003E\n\n\n\n\u003Cp\u003E\u201cThis was definitely a complex problem,\u201d Zhou said.\n\u201cYou must track every piece of packaging from its source to its final resting\nplace, when it either goes into another product or into a landfill.\u201d \u003C\/p\u003E\u003Cp\u003E\n\nThe team created a\nmodel\u2014a globally sourced auto parts packaging system\u2014 that optimized cargo\ncontainer space. The model also enabled the use of packing materials that were\nfully reusable; some materials were sent back to China for use in future\nshipments, while the rest was recycled into plastics that became part of new\nvehicles.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EISyE leads the way in advanced manufacturing research and\ndevelopment at Georgia Tech, specializing in many related\ndisciplines.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":"","uid":"27511","created_gmt":"2011-12-16 14:35:15","changed_gmt":"2016-10-08 03:10:53","author":"Ashley Daniel","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2012-01-03T00:00:00-05:00","iso_date":"2012-01-03T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"74531":{"id":"74531","type":"image","title":"(Clockwise) Leon McGinnis, professor, Jane Ammons, H. Milton and Carolyn J. Stewart School Chair, Nagi Gebraeel, associate professor, and Ben Wang, executive director of Manufacturing Research Center","body":null,"created":"1449178046","gmt_created":"2015-12-03 21:27:26","changed":"1475894688","gmt_changed":"2016-10-08 02:44:48","alt":"(Clockwise) Leon McGinnis, professor, Jane Ammons, H. Milton and Carolyn J. Stewart School Chair, Nagi Gebraeel, associate professor, and Ben Wang, executive director of Manufacturing Research Center","file":{"fid":"193786","name":"manufacturinggroup.jpg","image_path":"\/sites\/default\/files\/images\/manufacturinggroup_0.jpg","image_full_path":"http:\/\/tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/manufacturinggroup_0.jpg","mime":"image\/jpeg","size":355911,"path_740":"http:\/\/tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/manufacturinggroup_0.jpg?itok=N9OUkSgU"}}},"media_ids":["74531"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[{"id":"132","name":"Institute Leadership"}],"keywords":[{"id":"7903","name":"Chen Zhou"},{"id":"4742","name":"George Nemhauser"},{"id":"1202","name":"H. Milton Stewart School of Industrial and Systems Engineering"},{"id":"6991","name":"jan shi"},{"id":"7987","name":"Jane Ammons"},{"id":"1200","name":"joel sokol"},{"id":"577","name":"leon mcginnis"},{"id":"215","name":"manufacturing"},{"id":"6992","name":"nagi gebraeel"},{"id":"169661","name":"Shabbir Ahmed"},{"id":"169689","name":"spiridon reveliotis"},{"id":"1135","name":"valerie thomas"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:barbara.christopher@isye.gatech.edu\u0022\u003E\u003Cstrong\u003EBarbara Christopher\u003C\/strong\u003E\u003C\/a\u003E\u003Cbr \/\u003EIndustrial and Systems Engineering\u003Cbr \/\u003E\u003Cstrong\u003E404.385.3102\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}