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This 2 page Class Notes was uploaded by Merle Hoeger on Saturday September 26, 2015. The Class Notes belongs to MGT 390 at Clemson University taught by Gregg Thomas in Fall. Since its upload, it has received 12 views. For similar materials see /class/214293/mgt-390-clemson-university in Business, management at Clemson University.
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Date Created: 09/26/15
Projects on time operations designed to accomplish a set of objectives Project manager must manage work human resources communications quality time costs Project life cycle de nition planning execution delivery Program evaluation and review technique PERT and Critical Path Method CPM are used to manage large scale projects Slack LS ES Critical path the path with the longest duration Optimistic time to time under optimal conditionsPessimistic Time tp under worst conditionsMost I 4quot 1 If 7 likely time tm most probable time Expected time te 6 Path mean Z of expected times of activities on the path V 39 39 quot r 6 Standard DevumomoDam 1 Z nances 0t acmmes on p llh Speci ed lime Path mean Path Variance Project Completion Probability Palh Standard ammo Project Crashing using additional funds or support to shorten the time of a project Error Potential incomplete network relationships not correctly expressed time inaccuracies major risks not included too focused on critical path Good Risk Management identify as many risks as possible analyze risks work to minimize occurrence establish contingency plans LITTLE S LAW I R x T I inventory R throughput T Flow time Stable Process one in which in the long run average in ow rate average out ow Average Flow time average time needed to convert input to output Average Inventory number of ow units present within process boundaries Inventory Turnover Ratio R I R RxT 1 flquot Forecast a statement about the future value of a variable of interest Common Forecast Features Assume past trends will continue not perfect group forecasts are more accurate than individual forecasts accuracy decreases as forecasting horizon increases Good Forecasts Timely accurate reliable in meaningful units in writing simple to use amp understand cost effective Judgmental Forecasts relies on opinions amp Uses executive opinions sales force opinions consumer surveys Delphi Method TimeSeries Forecasts forecasts project patterns by using a sequence of observations taken at regular time interv s TimeSeries Behaviors trend seasonality cycles irregular variations random variation Trend longterm upward or downward movement in data Seasonality shortterm variations usually related to calendar or time of day Cycle wave like variations lasting more than a year Random variation residual variation that remains a er other behaviors have been accounted for Irregular Variation due to unusual circumstances that do not re ect typical behavior Nai39ve Method the forecast for a time period is equal to the previous time period s value Can only be used when timeseries is stable a trend and is seasonality V 7 MA u here A 7 Fnyucml rm limtllcnndf MA 7 npnnod mmillg nvcmgc E E E 5 7a 4 7 A VIIquotth ur minds in lhe mm mg mtmgc E w rlrquot7ll39l4hr ll lAb Moving Average where w 7 vciglu for period I w t 7 wrighl fur period 7 r an die actual value for period 1 7L etc Weighted Moving Average A 7 the actualvalue for period I 11 F 4 am 11 when I El 40mm or the previous period a Smoorhing constant mer rnr period Q fl J I Forecasting Error Actual Forecast Actuall Foreczhl z r x100 ems h ZlAcmall 7Furet mlr 7 2Acmal7 Forecnsll MAPE 7 n 1171 17 Linear Trend F a bt a value at F att 0 b slope ofline F speci ed number ofthe periods Least Squares Line y a bxy predicted depend variable F predicted indep variable b slope of line a value of y When X Regression assumptions variations are random deviations are normal distrib predictions are Within range 0 v ABC Approach classi es inventory according to measure of importance a most important amp usually 1020 of inv But 6070 of annual 3 value l noderately cleast important amp 5060 of inv but 1015 of annual 3 value Cycle counting physical count of items in inventory accuracy needed A items Within 2 B items Within 1 C items Within 5 Tnml ml 7 Annunl Holding Gm 7 Annunl om ing am 7 11 7 170 s where Q 7014 quantity in units II 7 lloldiug carrying cost per unit D 7 Demand usually u unit per em39 0 F 1annual demandorder cost Total Annual Cost 30rdcringcusl Qf 11 J almualpcrunitlmldingcosl EOQ Assumptions Only one product annual demand is known demand is even thru the year lead time does not change each order is received in a single delivery no quantity discounts lolal CM 7 rawymg 30517 Ordering 39ml 7 Pulclmsmg m 725397PD Q vlme Quantity Discount Model Iquot 5quot mi
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