Forecasting for intermittent spare parts in single-echelon multi-location and multi-item logistics network: Case KONE Global Spares Supply

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Oguji, Nnamdi 2016-02-25T11:08:17Z 2016-02-25T11:08:17Z 2013
dc.description.abstract The objective of this thesis is to test existing forecasting models for intermittence demand SKU's and implement the best forecast model that suits the inventory control policy of the case company. The optimal forecasting model was selected based on the model that produces optimal performance in terms of customer service levels, inventory total cost and inventory value. Intermittence demand type was categorized based on degree of lumpiness, erratic, smooth-intermittence and intermittent types. The quantitative data set comprised of historical demand information from 2010-2012 (36 months period) for sixteen thousand stock keeping units (SKU) in the three central distribution centers of the case company. Algorithms for the different forecasting models was developed using VBA programming in Excel 2007 and simulated against the demand data. Explorative approach was used to gather information regarding new material introduction process, forecasting parameters used in the software package (Servigistics) and how the results of the research can be implemented in the case organization. The result of the analysis shows that traditional forecast accuracy measure is inadequate for selecting best forecast model. Nevertheless, our result shows that no forecast method (Simple Exponential Smoothening (SES), Croston and Modified Croston (SBA) explicitly showed superior performance in all the traditional measures utilized. When stock control measure was utilized Croston showed superior customer service levels of 1% to SES and 1.4% to SBA. The superior customer service levels come with a 1% increase in total cost. The findings of the thesis also suggest the need for amending the outlier management settings in the software system and to customized tracking signal in the forecast review board to enable the prioritization of review reasons in degree of descending order of stock value and tracking signal estimates en
dc.format.extent 87
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Forecasting for intermittent spare parts in single-echelon multi-location and multi-item logistics network: Case KONE Global Spares Supply en
dc.type G2 Pro gradu, diplomityö fi Kauppakorkeakoulu fi School of Business en
dc.contributor.department Tieto- ja palvelutalouden laitos fi
dc.contributor.department Department of Information and Service Economy en
dc.subject.keyword Forecasting Performance
dc.subject.keyword Intermittence
dc.subject.keyword Croston
dc.subject.keyword Continuous Review System
dc.identifier.urn URN:NBN:fi:aalto-201602261432
dc.type.dcmitype text en
dc.programme.major Logistics en
dc.programme.major Logistiikka fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Pro gradu tutkielma fi
dc.subject.helecon logistiikka
dc.subject.helecon logistics
dc.subject.helecon ennusteet
dc.subject.helecon forecasts
dc.subject.helecon mallit
dc.subject.helecon models
dc.subject.helecon asiakashallinta
dc.subject.helecon customer relationship management
dc.subject.helecon inventointi
dc.subject.helecon inventory
dc.ethesisid 14276 2013-04-18
dc.location P1 I

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