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dc.contributor.advisorGeorgia Perakis and Daniel Whitney.en_US
dc.contributor.authorBalwani, Siddharth (Siddharth Vashdev)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2013-04-12T19:29:12Z
dc.date.available2013-04-12T19:29:12Z
dc.date.copyright2012en_US
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/78490
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; 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. 84-85).en_US
dc.description.abstractThis thesis covers work done at National Grid to improve resource planning and the execution of pipeline construction and maintenance work carried out at the yards. Resource Planning, the art of picking the right jobs for the right days and assigning the right crews to them while meeting constraints of regulation, customer service, and safety at the minimum cost is an extremely difficult problem. This is exacerbated by the fact that there needs to be enough slack in the system to deal with one or more pipeline leaks that may be called in. At the execution stage, when the jobs are carried out by crews, the lack of standardization in work processes dealing with granting and approval of overtime, productivity tracking, data collection, and imperfect alignment of incentives make it difficult to get the best work from the crews. These issues lead to high levels of overtime at yards, which are the major source of costs for gas operations for the company. We propose the Resource Allocation and Planning Tool (RAPT) accompanied by yard level process management to improve operations performance. To automate short term planning, RAPT includes a two stage stochastic optimization model to perform job scheduling and crew assignment in the presence of a variable number of emergency leaks, thus creating optimal daily and weekly plans with minimal overtime costs. The tool also serves as a business intelligence platform, providing a companywide view of gas operations efficiency and as a decision aid, enabling management to predict the impact of management policies on field operations. The execution of work was improved by the creation of new processes for scheduling, crew data entry, overtime approval, incorporating accountability and oversight at multiple levels. This work has enabled more consistent processes, better overtime and productivity management, and the ability to understand and track deviations. These changes are currently being piloted at yards across the company and the initial results are very encouraging. As a direct result of this work, National Grid has the potential to achieve up to 65% reduction in overtime, saving the company a substantial amount of money.en_US
dc.description.statementofresponsibilityby Siddharth Balwani.en_US
dc.format.extent85 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.subjectEngineering Systems Division.en_US
dc.subjectSloan School of Management.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleOperational efficiency through resource planning optimization and work process improvementen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.contributor.departmentSloan School of Management.en_US
dc.contributor.departmentLeaders for Global Operations Program.en_US
dc.identifier.oclc836759994en_US


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