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dc.contributor.advisorRoy E. Welsch and Randolph E. Kirchain, Jr.en_US
dc.contributor.authorStoddard, Steven Jen_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2012-09-27T15:30:57Z
dc.date.available2012-09-27T15:30:57Z
dc.date.copyright2012en_US
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/73418
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2012.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 46-48).en_US
dc.description.abstractCompany X uses large amounts of electricity in its manufacturing operations. Electricity prices at selected plants in the company's Region 1 territory rose by over 350% between 2000 and 2011, in part due to increasing reliance on high-cost fossil fuels. A focus on reducing these costs has identified numerous energy-saving projects in recent years, but with mixed implementation and performance results between the different plants in the region. Consequently, there is both a need to reduce exposure to high electricity prices and an opportunity to better share best-use practices between plants. This paper has two focuses: identifying and quantifying energy cost-reduction opportunities, and mapping the value-streams for the decision-making and implementation process for energy savings projects. From this Value Stream Map, recommendations are made for a new process that can be standardized and rolled out to other sites in the region. During the first phase of the project, data gathered from utility bills, power meters, and production records are used to identify the best opportunities for energy reduction within the plants. Using this technique, 7 GWh/year of potential energy cost savings are identified via reduced downtime, lighting motion detectors, high-efficiency lighting, and negotiable changes to energy contracts. For the benchmarking phase, the historical record of identified energy projects is compared with the number of projects actually implemented. An observational study of the local LEAN team from one plant is combined with interviews of engineers, managers, and financial analysts to build a process map of both the current and former processes for energy project identification, evaluation, and implementation. The results show a reduction in process steps and a step-change increase in the number of energy projects implemented. A key feature of the new approach is the creation of a dedicated energy team within the existing LEAN program. It is believed that emulating this integration of energy and LEAN at other sites will yield cost reductions as well. To follow up this work, a pilot study modeling this program at another site is recommended before further expansion to the rest of the region.en_US
dc.description.statementofresponsibilityby Steven J. Stoddard.en_US
dc.format.extent58 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleProject process mapping : evaluation, selection, implementation, and assessment of energy cost reduction opportunities in Manufacturingen_US
dc.title.alternativeEnergy cost reduction opportunitiesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeM.B.A.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc810338551en_US


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