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# Operations Management MD 021

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This 195 page Class Notes was uploaded by Mr. Warren Lang on Saturday October 3, 2015. The Class Notes belongs to MD 021 at Boston College taught by Staff in Fall. Since its upload, it has received 112 views. For similar materials see /class/218048/md-021-boston-college in Operations,Information & Strategic Mgmt at Boston College.

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Date Created: 10/03/15

MD 021 Management and Operations SupplyChain Management Outline De nitions Developing the supply chain Strategic management of the supply chain De nitions Supply Chain The interconnected set of linkages between suppliers of materials and services that spans the transformation of raw materials into products and services and delivers them to a firm s customers Supply Chain Management Synchronizing a firm s functions and those of its suppliers to match the ow of materials services and information With customer demand Developing the Supply Chain Make vs Buy Pros Cons o Increased control over price o Capital costs quality etc o Reduced exibility to change Make o Economies of combined partners operations o Reduced volume exibility Proprietary products protected o Low capital costs Unfavorable allocation of o Specialization product Buy o Competition o Lack of control over price o Increased exibility quality etc o Transaction costs Developing the Supply Chain Supplier Relations Competitive Orientation The view that negotiations between buyer and seller is a zerosum game Often used When a rm represents a signi cant share of the supplier s sales or many substitutes are available Example WalMart Cooperative Orientation The view that the buyer and seller are partners Includes sole sourcing Often used With strategically important and or high valueadded components Example McDonald s Mixed strategy Seeks to combine the advantages of the competitive orientation e g low prices With the cooperative orientation e g few suppliers Example Dell Computer Strategic Management of the Supply Chain E lciem Supply Chains The purpose of ef cient supply chains is to coordinate the ow of materials and services so as to minimize inventories and maximize the ef ciency of the manufacturers and service providers in the chain Ef cient supply chains work best when demand is predictable and products services are stable Examples of competitive priorities low cost consistent quality ontime delivery Responsive Supply Chains The purpose of responsive supply chains is to react quickly to market demands by positioning inventories and capacities in order to hedge against uncertainties in demand Responsive supply chains work best when demand is unpredictable new product introduction is frequent and product variety is high Examples of competitive priorities development speed fast delivery customization volume exibility highperformance design quality MD 021 Management and Operations Forecasting Outline 0 Components of demand 0 Judgment methods 0 Linear regression 0 Time series methods 0 Forecast errors Judgment Methods Sales force estimates Executive opinion Market research Delphi method Linear Regression Y1 a 9amp Where Y dependent variable X independent variable a Yintercept of the line b slope of the line Measures of Forecast Accuracy in Linear Regression Coef cient of correlation Coef cient of determination Standard error of the estimate Regression Analysis Example The manager of Al s Diner is interested in forecasting the number of potato skin appetizers sold each week He believes that the number sold has a linear relationship to the price and uses linear regression to determine if this is the case X Y Week Price Appetizers 1 270 760 2 3 50 510 3 200 980 4 420 250 5 310 320 6 405 480 The Excel output is below Regression Statistics Multiple R 0843 R Square 071 1 Adjusted R Square 0639 Standard Error 165257 Observations 6 ANOVA df SS MS F Signi cance F Regression 1 269160 269160 9856 0035 Residual 4 109239 27309 Total 5 378400 Coef cients Standard tStat P Error value Intercept 1454604 295939 4915 0008 Price 277628 88434 3139 0035 Linear Regression Example A professor is interested in determining Whether average study hours per week is a good predictor of test scores The results of her study are Score 90 95 65 80 95 60 85 70 A student says quotProfessor What can I do to get a B on the next test The professor asks quotOn average how many hours do you spend studying for this course per weekquot The student responds quotAbout 2 hoursquot Use linear regression to forecast the student39s test score Regression Statistics Multiple R 0391 R Square 0153 Adjusted R Square 00121 Standard Error 13544 Observations 8 ANOVA df SS MS F Signi cance F Regression 1 199246 199246 10861 03375 Residual 6 1100753 183458 Total 7 1300 Coef cients Standard Error tStat Pvalue Intercept 97325 17301 5625 00013 Study hours 4331 4156 1042 03375 Time Series Methods Naive forecasts Moving averages Weighted moving averages Exponential smoothing Trendadjusted exponential smoothing Regression Method Multiplicative seasonal method Moving Average Method Customer Month arrivals 1 800 A F 2 MA 2 I 2 740 t 3 810 4 790 0 Use a 3month moving average to forecast customer arrivals for month 5 F5 o If the actual demand for month 5 is 805 customers what is the forecast for month 6 F6 Weighted Moving Average Method Customer Month arrivals l 800 E WHAT WHAHH wlAt1 2 740 3 810 4 790 o Let W1 2 050 W2 2 030 and W3 2 020 Calculate the forecast for month 5 FS If the actual demand for month 5 is 805 customers what is the forecast for month 6 F6 Exponential Smoothing Customer Month arrivals 1 800 Ft 1 00E1 ozAt1 2 740 3 810 4 790 0 Suppose F3 783 customers and a 020 What is the forecast for month 5 F4 FS 0 If D5 805 what is the forecast for month 6 F6 TrendAdjusted Exponential Smoothing st 2 TAE 05At TAE Month m E 2 TH 8TAE TAFH TH 3 TAEH S I 3 4 54 5 55 0 Using months 14 an initial estimate of the trend is 2 4243 2 The starting forecast for month 5 is 542 56 Using a 03 and 8 04 forecast the number of patients in month 6 S5 2 T5 TAF6 the forecast for month 7 If the actual number of patients in month 6 is 58 what is Regression Method Example Garcia Garage Month t Number of Number of Oil time periods Changes Y from t 0 Jan 1 41 Feb 2 46 Mar 3 57 Apr 4 52 May 5 59 Jun 6 51 Jul 7 60 Aug 8 62 1 Forecast the numbers of oil changes in September October and November 2 What is the average value of the trend Regression Statistics MultipleR RSquare 0668 AdjustedR Square 0613 Standard Error 4572 Observations 8000 ANOVA Signi cance df SS MS F F Regression 1000 252595 252595 12085 0013 Residual 6000 125405 20901 Total 7000 378000 Standard P Upper Coef cients Error tStat value Lower95 95 Intercept 42464 3562 11921 0000 33748 51181 XVariabIe1 2452 0705 3476 0013 0726 4179 Step 1 Step 2 Step 3 Step 4 Step 5 Step 4 Multiplicative Seasonal Method Calculate the trend line based on the available data using regression Calculate the centered moving average with the number of periods equal to the number of seasons Calculate the seasonal relative for a period by dividing the actual demand for the period by the corresponding centered moving average Calculate the overall estimated seasonal relative by averaging the seasonal relatives om the same periods over the cycle Calculate the trend values for each of the periods to be forecast based on the trend line determined in Step 1 To get a forecast for a given period in a future cycle multiply the seasonal factor by the trend values Multiplicative Seasonal Method Application Quarter Demand CMA 4 seasons MA 2 periods Seasonal Relatives Normalized SR 1 2 400 250 3 300 2615 1147227533 1171002862 273 4 200 274 0729927007 0745054133 275 5 192 2855 0672504378 0686441468 296 6 408 298 1369127517 1397501537 300 7 384 Total 3918786436 4 8 216 9 331 trend value 227 forecast 10 344 trend value 480 forecast 11 356 trend value 417 forecast 12 369 trend value 275 forecast Using regression the trend line is 21886 1248t Forecast Errors Bias systematic errors 0 Random Errors variability Example Day 1 Day 2 Day 3 Day 4 Actual 100 100 100 100 Demand Forecast 105 105 105 105 1 Forecast 50 150 50 150 2 Forecast Error Measures Bias Zet Average error i n Variability e Mean squared error MSE M71 11 Standard deviation s MSE Zletl Mean absolute error MAD L n n e ZAt100l Mean percent absolute error MAPE H t n Control Chart for Forecast Errors Upper Control Limit UCL 0 leMSE Lower Control Limit LCL 0 ZVMSE Z the number of standard deviations om the mean Where to find 2 given the percentage of the control chart 190 Where to find 2 given the probability for type I error 06 Normal Distribution Table page 850 Table B2 Look for z corresponds to the probability PZlt z kg 05 190 1 06 eg A 95 control chart has 05 195 5 which means its probability for type I error is 5 Thus probability in the table should be 0975 P 10025 or P 05 0475 which corresponds to z 196 Pe od 1 OOICDO ILOOI MAD MSE S MAPE Summarizing Forecast Accuracy Actual A1 Forecast F1 Error EA F Abs Error Error Sq Abs EVA X 100 113 95 18 18 324 1593 85 80 5 5 25 588 96 103 7 7 49 729 86 119 33 33 1089 3837 121 117 4 4 16 331 100 125 25 25 625 2500 142 67 75 75 5625 5282 92 96 4 4 16 435 72 116 44 44 1936 6141 Total 11 215 9705 21406 239 12134 348 23896 Tracking and Analyzing Forecast Errors Penod Actual A Forecast F Error EAF 102 130 28 107 102 5 1 12 89 23 1 18 97 21 89 1 15 26 142 82 60 100 130 30 94 137 43 1 1 1 89 22 Total 4 Average error periods 118 039 Standard deviation periods 19 348 2s control limits 0 2348 O 696 UCL696 llCll 696 Forecasting Summary Notes Choosing a Forecasting Method General considerations Method Pros Cons Judgment Can be used in the absence of Subjective estimates are subject to historical data eg new product the biases and motives of the Helpful in identifying turning estimators points and preparing medium and longterm forecasts Causal Most sophisticated method Must have historical data on Very good for predicting turning points and preparing medium and longterm forecasts independent and dependent variables Relationships can be difficult to specify Time series Easy to implement Work well when demand is relatively stable Rely exclusively on past demand data Only useful for shortterm estimates Specific considerations for time series methods Method Pros Cons Naive forecast errors are small Easiest method low cost Works well when random Results in highly variable forecasts if the random errors are large Simple moving average method for random error Easiest moving average To some extent controls Data must be retained for 7 periods Forecast lags changes in the underlying average of demand Weighted moving average Weights can be varied to Data must be retained for be responsive to demand 7 periods pattern To some extent controls for random error Forecast lags changes in the underlying average of demand Exponential smoothing Requires little data Forecast lags changes in a can be varied to be responsive to demand pattern To some extent controls for random error the underlying average of demand In general emphasize recent demand ie small n large weights for recent observations large a for dynamic ie uncertain demand patterns Emphasize historical experience for stable demand patterns If a trend is present simple moving average weighted moving average and exponential smoothing estimates will always lag actual demand 20 Forecasting Notes Choosing a Time Series Forecasting Method Evaluating forecast performance Forecast errors can be classi ed as either bias errors or random errors Bias errors are the results of systematic over or underestimation Random errors are unpredictable Ideally a forecast should minimize both bias and random errors Method Purpose Mean forecast Measures bias errors Mean squared error MSE Measures the dispersion of forecast errors large errors get more weiat than when using MAD Mean absolute deviation Measures the dispersion of forecast errors method is MAD intuitive Mean absolute percent Measures the dispersion of forecast errors relative to the error MAPE level of demand Forecast error control chart Determines whether the method of forecasting is accurately predicting actual changes in demand 21 MD 021 Management and Operations Operations Strategy De nitions of strategy and operations strategy Levels of strategy corporate business functions Evaluating an operations strategy Example McDonald39s De nition of Strategy Strategy is a deliberate search for a plan of action that Will develop a business39s distinctive competence and compound it De nition of Operations Strategy An operations strategy consists of a sequence of decisions that over time enables a business unit to achieve a desired operations structure infrastructure and set of speci c capabilities in support of the competitive priorities OrderQuali ers and OrderWinners Orderquali ers are those criteria that a company must meet for a customer to even consider it as a possible supplier Companies need only be as good as competitors OrderWinners are those criteria that Win the order Companies need to be better than their competitors Levels of Strategy What business 39 9 Corporate are we 1n How do we compete D1V1s10nal Busmess Role 9f each Prod functlon m Components of the Operations Strategy Structural decision Capacity categories Facilities Vertical integration Technology Infrastructural decision Workforce categories Organization Informationcontrol systems Capabilities Unique to each rm Competitive priorities Cost Quality Highperformance design Consistent quality Time Fast delivery time Ontime delivery Development speed Flexibility Customization Volume exibility Criteria for Evaluating an Operations Strategy Consistency internal and external Between the operations strategy and the overall business strategy Between the operations strategy and the other functional strategies within the business Among the decision categories that make up the operations strategy Between the operations strategy and the business environment resources available competitive behavior governmental restraints etc Contribution to competitive advantage Making tradeoffs explicit enabling operations to set priorities that enhance the competitive advantage Directing attention to opportunities that complement the business strategy Promoting clarity regarding the operations strategy throughout the business unit so its potential can be fully realized Providing the operations capabilities that will be required by the business in the future Statement of McDonald s Operations Strategy To provide unmatched consistency in operations in support of high product quality This must be accomplished with adequate speed low cost and process innovation to accommodate changes in consumer tastes From the statement of McDonald s operations strategy it is clear that both consistent and high performance quality are considered order Winners While speed cost and innovation are considered order quali ers McDonald s Operations Strategy Dimension Strategy Capacity 0 Growth as needed through additional stores but capacity added carefully o Wellutilized franchisee s wellbeing depends on it being used heavily Facilities 0 Distributed facilities each facility being very similar to the next all focused around the same menu although the uniformity is beginning to change Process 0 High degree of process understanding emphasis on Technology quotfoolproof processes 0 A leader in the technology of fastfood delivery Vertical o Partnership arrangement Integration 0 Longterm relationship with suppliers to promote innovation and quality improvement Workforce o Franchisees welltrained carefully selected entrepreneurs o Operators highturnover cheap Organization 0 Guidelines provided by corporation but franchisees push to locally optimize Control 0 Centralized buying Systems 0 Bulk contracts quotPushquot system for basic supplies quotpullquot system dayto day in the restaurants Evaluation of the operations strategy 0 Internal and external consistency Looking at the operations strategy along the seven dimensions they all support the operations mission and the business strategy from the previous page Contribution to competitive advantage Systemic strategy creates unmatched consistency in operations that has been difficult to imitate STATISTICAL PROCESS CONTROL DATA COLLECTION FORM Product Unit MampM s Bag1 Fun Size What are important dimensions of quality for this product What is important to the customer What is important to the manufacturer Number of MampMs in bag Number of green MampM s in bag Number of defective MampM s in bag Number of defects across whole unit bag and candy Control Chart for Variables Averages and Range X bar chart and R chart Measurement Number of MampMs in Bag Unit of Measurement One bag 1 2 3 4 5 6 R bar average of sample ranges 275 UCLR D4 55 LCLR D3 5 0 Grand Mean X average of sample means 2079 UCLXbar X AZR 2211 LCLXbar X A5 1947 Control Chart for Attributes Proportions p chart Measurement Green MampM Candy Pieces Unit of Measurement Bag of 20 Future F of green of samples of observations in each sample 01375 6 p1pn 5 0077 n 20 UCLp p z 6 03685 using 2 3 LCLp p z 6 negative thus 0 using 2 3 Control Chart for Attributes Counts c chart Measurement Defects Across Bag Unit of Measurement One Bag 7 22 a c0 5 148 UCLc 7 z 6 664 using 2 3 LCLCT z 6c0usingz3 Product Unit Skittles BagJ Fun Size What are important dimensions of quality for this product What is important to the customer What is important to the manufacturer To see each answer below change the font color in the blank spaces to red Number of Skittles in bag Number of defective printed Skittles S in bag Number of defects across whole unit bag and candy Control Chart for Variables Averages and Range X bar chart and R chart Measurement Number of Skittles in Bag Unit of Measurement One bag 1 2 3 4 5 Future R bar average of sample ranges UCLR D4 R LCLR D3R Grand Mean X average of sample means UCLXbar X AZE LCLXW X A2 Control Chart for Attributes Proportions p chart Measurement Defective Pieces Unit of Measurement 19 pieces Future 026 5 047 016 3 011 4 021 6 011 To see answer space to F of defectives of samples of observations in each sample op p1pn 5 UCLp p z 6p LCLpp z 6 Control Chart for Attributes Counts c chart Measurement Defects Across Bag Unit of Measurement One Bag 4 To see answer space to Chapter 15 Scheduling Application 1 Scheduling at One Operation Using FCFS Job Code Standard time in Order of Arrival Including Due Date Setup Shr shrs from now AZl 35 l4 l4 DM246 8 20 SX435 10 6 PC088 3 18 Given the above information about four jobs devise an FCFS schedule for an automatic routing machine Assume each job has equal amounts of inventory Processing Begin End Flow Scheduled Actual Hours Hours Order Work Work Time hr Customer Customer Early Past Pickup Time Pickup Time Due l 2 3 4 T otal Av erage Average workinprocess inventory Next devise a schedule based on the shortest processing time SPT rule Processing Begin End Flow Scheduled Actual Hours Hours Order Work Work Time hr Customer Customer Early Past Pickup Time Pickup Time Due l 2 3 4 T otal Av erage Average workinprocess inventory MD 021 Management and Operations Process Location and Layout 0 Process Choice 0 Factors affecting location decisions 0 Breakeven location problem 0 Layout types 0 Product layout Process Management and Major Process Decisions Process management is the selection of the inputs operations work ows and methods that transform inputs into outputs Major process decisions Process choice A process decision that determines whether resources are organized around products or processes Vertical integration The degree to which a firm s own production system or service facility handles the entire supply chain Resource exibili The ease with which employees and equipment can handle a wide variety of products output levels duties and functions Customer involvement The ways in which customers become part of the process and the extent of their participation Location Decisions Dominant Factors in Manufacturing Favorable labor climate Proximity to markets Quality of life Proximity to suppliers and resources Proximity to other parent companies Utilities taxes and real estate costs Dominant Factors in Services Proximity to customers Transportation costs and proximity to markets Location of competitors Sitespeci c factors Breakeven Location Problem By chance the Atlantic City Community Chest has to close temporarily for general repairs They are considering four temporary of ce locations Property Address Movein Costs Monthly Rent Boardwalk 400 50 Marvin Gardens 280 24 St Charles Place 350 10 Baltic Avenue 60 60 a Can any of these addresses be immediately eliminated from consideration if the goal is to minimize total costs b Use the graph on the next page to help determine for what length of lease each location would be favored Calculate the breakeven lease lengths between addresses Breakeven Location Problem 500 400 300 Total Cost 200 100 0 0 1 2 3 4 5 6 7 8 9 10 Months Breakeven calculations Layout Types Process Product Hybrid Fixedposition Product Layout Although product layouts often follow a straight line a straight line is not always the best and layouts may take an L O S or U shape Why MD 021 Management and Operations Resource Planning Outline Dependent demand Material Requirement Plan MRP Bill of Materials BOM Master Production Schedule MPS Inventory record Lot sizing Independent Demand vs Dependent Demand Dependent demand Demand for subassemblies or parts to be used in the production of finished goods It is calculated rather than forecasted Complexity comes from interdependencies between items Independent demand Market demand for finished products o Components may have independent demand as spareparts o Must be forecasted Material Requirements Planning MRP Information system that translates the finished product requirements of the master schedule into timephased requirements for subassemblies parts and raw material Inputs to the MRP 0 Bill of Materials BOM o The Master Production Schedule MPS 0 Inventory record Outputs from the MRP 0 Planned orders 0 Order releases 0 Secondary reports Bill of Materials A record of all the components of an item the parentcomponent relationships and usage quantities derived om engineering and process designs The Master Production Schedule MPS A detailed plan that states how many end items Will be produced Within speci ed periods of time Inventory record Records status of each item by time period time bucket With respect to gross requirements schedule receipts expected amount on hand lotsize policy lead time supplier etc 133 E4 BOM Example X l I I B2 E E2 C F2 Parents BOM of X Gross requirements For 10 Xs Onhand inventory of individual items Available Invent0 ry Net requirements FEMUOUU Lead time in weeks X 1 B1 C 2 D2 E 1 F2 One scheduled receipt of 50 units of Item E to arrive at the beginning of week 1 Net Requirements Gross Requirements Available Inventory Available Inventory Projected onhand inventory Safety stock Inventory allocated to other items Projected onhand inventory Onhand inventory Scheduled Receipt MRP Schedule Item Lot Size Description Lead time Safety Stock Week 3 l 32 33 3 4 3 5 3 6 3 7 3 8 39 40 Gross requirements Scheduled Receipts Projected onhand inventory Planned receipts Planned order Releases LotSizing Rules 0 Lot for Lot Ordering 0 Economic Order Quantity 0 Economic Production Quantity 0 Fixed period Ordering Manufacturing Resources Planning MRP II Extention of MRP which includes MRP as well as capacity requirements planning financial planning marketing planning etc Enterprise Resources Planning ERP Information system that integrates all functional areas including MRP II nance accounting HR marketing etc MD 021 Management and Operations Managing Project Processes Outline De nition of a project Network methods using deterministic estimates Probabilistic estimates Cost considerations De nition of a project A project is an interrelated set of activities that has a de nite starting and ending point and results in unique product or service Examples of projects include building construction introducing a new product and redesigning the layout of a plant or o ice PERT and CPM Network Methods De nitions Activity The smallest unit of work effort consuming both time and resources that the project manager can schedule and control Precedence relationship A sequencing constraint between interrelated activities by Which one activity cannot start until a preceding activity has been completed Schedule A plan that sets priorities determines start and nish times and allocates resources to accomplish the activities Project Management Using Network Models First two steps Describe the project a De ne project activities bDetermine precedence relationships Diagram the network a Nodes circles and arcs arrows bActiVityonnode AON network 0 Nodes are activities and arcs show precedence relationships 0 Activityoriented Project Management Example St Adolph s Hospital Immediate Activit Description Predecessors y A Select administrative and medical staif B Select site and do site survey C Select equipment A D Prepare nal construction plans and layout B E Bring utilities to the site B F Interview applicants and ll positions in nursing A support staff maintenance and security G Purchase and take delivery of equipment C H Construct the hospital D I Develop an information system A Install the equipment Train nurses and support staff Network Time Calculations Earliest nish time EF for an activity EFESI Earliest start time ES for an activity ES Max EF times of all immediately preceding activities Latest start time LS for an activity LS LF t Latest nish time LF for an activity LF MinLS times for all immediately following activities Calculating Time Estimates a Optimistic time a Shortest time during which an activity can be completed bMost liker time m Best estimate of average time c Pessimistic time b Longest time an activity can take dActivity s time re and variance 0392 With beta distribution a4mb te 6 Calculating Probabilistic Estimates St Adolph s Hospital Example Time estimates weeks Optimistic Most likely Pessimistic Expected Variance Activity to rm tp time re 02 A 11 12 13 B 7 8 15 C 5 10 15 10 278 D 8 9 16 10 178 E 14 25 3O 24 711 F 6 9 18 10 400 G 25 36 41 35 711 H 36 4O 45 40 278 I 10 13 28 15 900 J 1 2 15 4 544 K 5 6 7 6 011 Analyzing Probabilities Probabilities can be assessed using the ztransformation formula Z Z T TE 6 T speci c time TE expected time path mean 0 standard deviation of path mean Assuming the activity times are independent the path standard deviation 0 is the square root of the sum of the activity time variances To determine the probability of completing a project in a speci ed amount of time o Calculate the probability of each of the paths being completed in that amount of time based on the value of Z For any value of Z that is greater than 3 the probability that the corresponding path will be completed in that amount of time can be considered to be 100 If all paths are independent then the probability of completing a project in the speci ed amount of time is the product of the individual path probabilities Hospital Project Completion Probabilities How likely is it that the hospital project Will be completed in 72 weeks 72 Expected path duration Probability of m Path standard deviation completion in 72 weeks AFK 72 28205 215 100 AI K 72 33304 128 100 ACGJK 72 67394 127 90 BDHJK 72 69345 087 81 BEJ K 72 43380 76 100 Analyzing Costs in a Project 1Direct costs and times 0 normal time 0 normal cost 0 crash time 0 crash cost 2 Cost assumptions linear costs per unit of time 3 Indirect costs and penalty costs Determining the MinimumCost Schedule Step 1 Determine the project s critical paths Step 2 Find the cheapest activity or activities on the critical paths to crash Step 3 Reduce the time for this activity until the rst of a it cannot be further reduced b another path becomes critical or c the increase in direct costs exceeds the savings that result from shortening the project If more than one path is critical the time for an activity on each path may have to be reduced simultaneously Step 4 Repeat this procedure until the increase in direct costs is less than the savings generated by shortening the project Direct Cost and Time Data for the Hospital Pro ect Normal Normal Crash Crash Max time Cost of time cost time cost reduction crashing per Activit wks K wks 10 wks week y A 12 12 11 13 1 1000 B 9 50 7 64 2 7000 C 10 4 5 7 5 600 D 10 16 8 20 2 2000 E 24 120 14 200 10 8000 F 10 10 6 16 4 1500 G 35 500 25 530 10 3000 H 40 1200 35 1260 5 12000 I 15 40 10 525 5 2500 J 4 10 1 13 3 1000 K 6 30 5 34 1 4000 Totals 1992 22095 Assume Hospital Project MinimumCost Schedule Indirect cost 8000Week Penalty cost 20000Week after Week 65 Crash Project Indirect Penalty Total Critical path activitV duration Crash cost cost change cost change cost change BDHJK 69 weeks MD 021 Management and Operations Capacity Planning and Decision Theory Measures of capacity Bottlenecks Capacity strategies A systematic approach to capacity decisions Make or Buy Problem Decision Making Under Uncertainty and Risk Decision Trees Capacity Planning Capacity is the maximum rate of output for a facility Capacity planning considers questions such as Should we have one large facility or several small ones Should we expand capacity before the demand is there or wait until demand is more certain Measuring Capacity Measurement Type 0 Output measure for product focus 0 Input measure for process focus W Utilization Design Capacity Actual Output Ef ciency E ectz ve Capacity Effective Capacity Design Capacity maximum output rate Allowances eg personal time maintenance and scrap Sizing Capacity Cushion Cushion the amount of the reserved capacity that a rm maintains to handle sudden increase in demand or temporary losses of production capacity Capacity cushion l Utilization Pressures for Large Cushion Uneven demand Uncertain demand Changing product mix Capacity comes in large increments Uncertain supply Pressure for Small Cushion Capital costs Links with Other Areas Other Choice Faster delivery times Smaller yield losses Higher capital intensity Less worker exibility Lower inventories More stable schedules Cushion 0 Larger o Smaller o Smaller 0 Larger 0 Larger o Smaller A Systematic Approach to Capacity Decisions 1 Estimate capacity requirements 2 Identify gaps 3 Develop alternatives 4 Evaluate the alternatives Estimate Capacity Requirements 1 One type of product Numbers of machines required Processing hours required for year39s demand hours available from one machine per year after the desired cushion deducted M Dp N1 C Where D number of units customers forecast per year p processing time in hours per unit or customer N total number of hours per year during Which the process operates C desired capacity cushion rate 2 More than one type of product n types of products Numbers of machines required 2 Processing and setup hours required for year39s demand sumed over all products hours available from one machine per year after the desired cushion deducted M D19 DQspmdm1 D19 D Qspmdm2 D19 D Qspmdm N1 C Q number of units in each lot s setup time in hours per lot Note Always round up the fractional part for the number of machines required Capacity Planning Problem You have been asked to put together a capacity plan for a critical bottleneck operation at the Surefoot Sandal Company Your capacity measure is number of machines Three products men s women s and kid s sandals are manufactured The time standards processing and setup lot sizes and demand forecasts are given in the following table The rm operates two 8hour shifts 5 days per week 50 weeks per year Experience shows that a capacity cushion of 5 percent is suf cient Time Standards Demand Processing Setup Lot Size Forecast Product hrpair hrlot pairslot pairsyr Men s sandals 005 05 240 80000 Women s 010 22 180 60000 sandals Kid s sandals 002 38 360 120000 a How many machines are needed at the bottleneck b If the operation currently has two machines what is the capacity gap c If the operation can not buy any more machines which products can be made d If the operation currently has ve machines what is the utilization Capacity Planning Problem Solution Total time available per machine per year 2 shiftsday8 hoursshift5 daysweek50 weeksyear 4000 hoursmachineyear With a 5 capacity cushion the hoursmachineyear that are available are 40001005 3800 hoursmachineyear Total time to produce the yearly demand of each product This is equal to the processing time plus the setup time Men s 005800008000024005 4167 hrs Women s 010600006000018022 6733 hrs Kid s 00212000012000036038 3667 hrs Total time for all products 416767333667 14567 hrs a Machines needed 145673800 383 4 machines CT Capacity gap is 4 2 2 machines c With two machines we have 3 8002 7600 hours of machine capacity We can make all of the women s sandals 6733 hours and some of the men s sandals for example 9 With five machines 54000 20000 machinehoursyr are available The total number of machinehoursyr needed for production are 14567 Utilization 1456720000100 73 Thus the capacity cushion is 100 73 27 Vertical Integration Problem Make or Buy Hahn Manufacturing has been purchasing a key component of one of its products from a local supplier The current purchase price is 1500 per unit Efforts to standardize parts have succeeded to the point that this same component can now be used in ve different products Annual component usage should increase from 150 to 750 units Management wonders whether it is time to make the component inhouse rather than to continue buying it from the supplier Fixed costs would increase by about 40000 per year for the new equipment and tooling needed The cost of raw materials and variable overhead would be about 1100 per unit and labor costs would go up by another 300 per unit produced a Should Hahn make rather than buy b What is the breakeven quantity c What other considerations might be important Decision Making Under Uncertainty Decision Rules Maximin Choose the alternative that is the best of the worst Maximax Choose the alternative that is the best of the best Laplace Choose the alternative with the best weighted payoff Minimax regret Choose the alternative with the best worst regret ie opportunity losses Decision Making Under Uncertainty Pro ts Event 1 Low demand Event 2 High demand Alternative 1 Small facility 300 200 Alternative 2 Large facility 50 400 Decision rules Maximin Maximax Laplace Minimax regret Decision Making Under Risk Pro ts Event 1 Low demand Event 2 High demand Probability 03 Probability 07 Alternative 1 Small facility 300 200 Alternative 2 Large facility 50 400 Use the expected value decision rule CHAPTER 5 EXAMPLES OF CAPACITY PLANNING Example 1 Eagles Cash Money Bank has the following processes a A loan processing operation that processes an average of 77 loans per day The operation has a design capacity of 100 loans per day and an effective capacity of 83 loans per day b EaglesCashMoneyBankcom a website that provides online banking services The website can process an average of 15000 transactionshour The website has a design capacity of 30000 transactionshour and an effective capacity of 23000 transactions per hour Calculate the efficiency and the utilization for each of these processes Loan Processing Operation Efficiency Utilization EaglesCashMoneyBank com Efficiency Utilization Example 2 PizzaTime Restaurants is building a new pizza place and needs to determine how big to make the various parts of its facility It wants to be able to accommodate a maximum of 500 customers per hour at its peak times PizzaTime has collected the following information the average time to place and receive an order is 11 minutes the average time spent in the restroom is 04 minutes 50 of the customers are men and 50 are women 20 of the customers have cars and require parking spots and the average length of time at the restaurant is 20 minutes per customer Assuming that PizzaTime wants to maintain a 20 capacity cushion for each area determine The number of cash registers required The number of toilets sinks needed for the restrooms The number of parking spaces needed The number of seatstables needed Are any of these operations bottlenecks What do you think an appropriate capacity cushion is for each of the operations listed in ad hQQOU N M7Dp N1 C Cash Registers ToiletsSinks Parking Spaces SeatsTables Are any of these Bottlenecks Example 3 Bob s Bicycles manufactures three different types of bikes the Tiny Tike the Adult Aero and the Mountain Monger Given the production schedule below including setup and processing times and lot sizes calculate the required capacity for this year s production Note that the times are given for indiVidual production lines so capacity calculations should be in terms of the number of lines necessary Assume that Bob s operates two shifts each with 2000 hours per year and wishes to maintain a 15 capacity cushion ZDP DQSlpmm M 1 N1 C N of hours during which the process operates C capacity cushion M Example 4 Eagleman s Donuts produces two varieties of pastry which are sold to a national grocery chain Muffin Tops and Doughnuts Assuming that Doog s operates a single shift for 1800 hours per year calculate the required capacity The processing time per unit setup time per lot the annual demand and lot size are given below Assume that the times given are for a production cell of four workers each so required capacity should be in terms of the number of production cells needed Eagleman s would like to maintain a 10 capacity cushion Zle DQSpmdu tx 2 N1 C N of hours during which the process operates C capacity cushion M Example 5 Surefoot Sandal Company operates two 8hour shifts five days per week 50 weeks per year A capacity cushion of 5 percent is used for all products Management is trying to determine if they should make a new line of sandals Time standards lot sizes and demand forecasts are Time Standards Processing Setup Lot Size Demand Forecast Product hrpair hrlot pairslot pairsyr Men s sandals 005 05 240 80000 Women s sandals 010 22 180 60000 Children s sandals 002 38 360 120000 a What are the capacity requirements for the three types of sandals b One manager threw out the idea that they should buy 5 machines Assuming managers choose to use 5 machines in the factory what is their utilization What is their capacity cushion c How many machines are needed at the bottleneck assuming a 5 capacity cushion d If the operation currently has two machines what is the capacity gap e If the operation can not buy any more machines which products can be made Example 6 Vertical Integration Problem Make or Buy Hahn Manufacturing has been purchasing a key component of one of its products from a local supplier The current purchase price is 1500 per unit Efforts to standardize parts have succeeded to the point that this same component can now be used in five different products Annual component usage should increase from 150 to 750 units Management wonders whether it is time to make the component in house rather than to continue buying it from the supplier Fixed costs would increase by about 40000 per year for the new equipment and tooling needed The cost of raw materials and variable overhead would be about 1100 per unit and labor costs would go up by another 300 per unit produced a Should Hahn make rather than buy b What is the breakeven quantity c What other considerations might be important MD 021 Management and Operations Aggregate Planning Outline Aggregate planning de nitions and strategies Linear programming LP Aggregate planning LP problem Chase and level strategy problems De nitions of Aggregate Planning Aggregate planning is the big picture approach to planning for the intermediate term 1 year The goal of aggregate planning is to achieve a production plan that will effectively utilize the organization s resources to satisfy expected demand Planners must make decisions on o Output rates Employment levels and changes Inventory levels and changes Backorders o Subcontractingoutsourcmg In a manufacturing firm the aggregate plan links the strategic goals with plans for the individual products ie the master production schedule In a service firm the aggregate plan links the strategic goals with detailed work force schedules Aggregation Reason for aggregation A planner can devise a course of action consistent With strategic goals and objectives Without having to deal With a lot of detail Three dimensions of aggregation Product families Based on similar demand requirements and common processing labor and materials requirements Labor Considerations include workforce exibility physical and geographic locations Timing The planning horizon is the length of time covered by the aggregate plan Planning Strategies Chase strategy Matching capacity to demand the planned output for a period is set at the expected demand of the period Level strategy Maintaining a steady rate of regular time output while meeting the variations in demand by a combination of inventories overtime parttime workers subcontracting and backorders Pros Cons 0 Low inventory investment and backlogs Chase strategy Expense of adjusting output rates and or workforce Alienation of workforce Loss of productivity Lower quality 0 Level output rates 0 Stable workforce Level strategy Increased inventory investment Increased undertime and overtime expense Increased backlogs Issues to Consider in Aggregate Planning Production Capacity Demand Material cost Labor cost Overhead cost Service level Workforce Minimum level Maximum level Overtime Subcontracting Hiring cost Firinglayoff costs Inventog Minimum level Maximum level Holding cost The Speci c Motors Company SMC which manufactures only one model of car wants to plan its production and inventory levels for the next 4 months The following table provides the relevant data for each month where the inventory levels in the last two columns refer to the levels at the end of the month Maximum Minimum Maximum Minimum Production production production inventory inventory Month Demand costunit level level level level 1 10000 10800 25000 3000 15000 2000 2 15000 11000 35000 3000 15000 2000 3 25000 11000 30000 3000 15000 2000 4 20000 11300 10000 3000 15000 2000 SMC estimates that the cost to hold one car in inventory for one month is 150 To estimate a month39s inventory costs SMC multiplies the average of the month39s starting and ending inventory levels by 150 SMC currently has an inventory level of 3000 cars SMC wants to meet its demand with no backlogging that is all demand must be met in the month it occurs Formulate an LP model for SMC Let X1 Number of cars to be produced in month 1 X2 Number of cars to be produced in month 2 X3 Number of cars to be produced in month 3 X4 Number of cars to be produced in month 4 11 Inventory at the end of month 1 I2 Inventory at the end of month 2 I3 Inventory at the end of month 3 I4 Inventory at the end of month 4 Min Z 10800X111000X211000X311300X4 7510 15011 15012 15013 7514 Subject to 103000 10X111 10000 11 X2 12 15000 12 X3 13 25000 13 X4 14 20000 X1 3 25000 X12 3000 X2 3 35000 X2 2 3000 X3 3 30000 X3 2 3000 X4 3 10000 X4 2 3000 11 3 15000 11 22000 12 3 15000 12 22000 13 3 15000 13 22000 14 3 15000 14 22000 X13 X23 X33 X43 113123 133 Z 0 Microsoft Excel 70 Answer Report Target Cell Min Cell Name Original Value Final Value K4 Total cost 0 763075000 Sensitivity Analysis 1 Objective function coef cients 0 Holding all else the same what is the range that each objective function coef cient can change without changing the optimal solution 2 Righthandside parameters 0 Holding all else the same what is the change in the value of the objective function if we add one more unit of each constrained resource In other words what is the shadow price 0 What is the range over which the righthandside can vary while its shadow price remains valid Microsoft Excel 70 Sensitivity Report Changing Cells Final Reduced Objective Allowable Allowable Constraints Final Shadow Constraint Allowable Allowable Sensitivity Analysis Aggregate Planning Problem 1 What changes in the aggregate plan would cause costs to go down 2 Why does an increase in the minimum inventory level at the end of month 4 cause costs to go up Why is this deceptive 3 According to the sensitivity report increasing the initial inventory by 1 results in costs going down by 10725 Why is this deceptive Level and Chase Strategies Example Bob Carlton s golf camp estimates the following workforce requirements for its services over the next two years Quarter 1 2 3 4 Demand 4200 6400 3000 4800 Quarter 5 6 7 8 Demand 4400 6240 3600 4800 Each certi ed instructor puts in 480 hours per quarter regular time and can work an additional 120 hours overtime Regulartime wages and bene ts cost Carlton 7200 per employee per quarter for regular time worked up to 480 hours with an overtime cost of 20 per hour Unused regular time for certi ed instructors is paid at 15 per hour There is no cost for unused overtime capacity The cost of hiring training and certifying a new employee is 10000 Layoff costs are 4000 per employee Currently eight employees work in this capacity Level Strategy Find a level workforce plan that allows for no delay in service and minimizes undertime What is the total cost of this plan Chase Strategy Use a chase strategy that varies the workforce level Without using overtime or undertime What is the total cost of this plan MD 021 Management and Operations Introduction to Operations ManagementProductivity Analysis Syllabus Operations and operations management de ned Manufacturing vs service operations Operations management decision categories Measures of productivity Operations and Operations Management De ned Operations The production of goods and services the transformation process that converts inputs to outputs Operations The direction and control of the processes that transform inputs management into nished goods and services How it s supposed to work Boeing Company 1 Fuselage An NG 737 fuselage arrives by rail om Kansas and enters the assembly line 2 Wings and wheels An overhead crane lifts the fuselage to the next step where workers attach the main wings and the landing gear 3 Final assembly I The 737 rolls into a slant where a crane installs the vertical tail and workers add the horizontal stabilizer 4 Final assembly 11 Workers add the guts of the plane including the ightcontrol systems galleys and interiors 5 Engines Customized engines om Seattle are installed The 7 37 rolls out for paint pre ight and delivery And why it sometimes hasn t Boeing Company 0 Certi cation delays Added specs demanded by US and European aviation authorities can mean costly re ttings o Soaring demand Orders jumped from 124 to 754 in two years putting strains on the production line and causing a backlog 0 Work force Huge layoffs in the mid 90 s meant a loss of experienced workers Boeing then had to play catchup 0 Supply network Earlier cutbacks drove many outside suppliers out of business causing serious parts shortages later 0 Customization The 1000 or more options Boeing offers its customers hinder planning and bog down the production system 0 Inef ciencies Until recently assembly was slowed by inef cient organization and labor methods and excessive paper work Strategic Choices and Processes Strategic Choices Sample Questions Competitive priorities 0 Which competitive priorities create a competitive advantage Positioning strategy 0 How can processes be aligned to support the competitive priorities Processes Sample Questions Process management 0 How should processes be con gured for optimal effectiveness Management of technology 0 Which technologies should be pursued and When Service operations design using 0 How many servers are needed waiting line models Quality and Structural Decisions Quality Total Quality Management Statistical Process Control Sample Questions How can employees be included in the quality improvement process Which control chart is appropriate for a given situation Structural Decisions Capacity Location Layout Sample Questions 0 Should we add more capacity now or later Where is a good store location What departments should be close together Operating Decisions Operating Decisions Supplychain management Forecasting Inventory management Aggregate planning Resource planning Lean systems scheduling Managing project processes Sample Questions What criteria should we use to select suppliers How do we design the best forecasting system How should we control our inventory How big should our staff be How can an MRP system be used to better manage materials When should we release new orders for production Which activity times should be shortened to meet our due date Productivity Analysis Productivity M Input Partial Measures of productivity Out ut Labor product1v1ty p 68 Employee hours Multifactor Measure Output Multifactor productivity Labor cost Materials cost Overhead cost Note 1 The Output in a productivity measure is usually measured by the quantity units of the output or by the economic value 33 of the output Note 2 Only usable output should be counted Productivity Growth Current Period Productivity Previous Period Productivity Productivity Growth X 100 Previous Period Productivity Example 1 Four workers packed 100 boxes in 8 hours What is the labor productivity Example 2 A factory produces 6000 units of car replacement component per month which can be sold at the price of 50unit The monthly labor cost is 8000 material cost is 5000 and overhead cost is 3000 The percentage of the products that meet the quality standard is 96 What is the multifactor productivity MD 021 Management and Operations Lean SystemsScheduling Outline De nition of a justintime JIT system Characteristics of JIT systems Types of scheduling Scheduling performance measures Priority sequencing dispatching rules Scheduling in services JIT System De nition Justintime JIT is a dependent demand production control system designed to produce goods or services as needed and minimize inventories Environments for Effective JIT 0 Manufacturing Firms that tend to have highly repetitive manufacturing processes welldefined material ows and reasonably high volumes use JIT systems because the pull method allows closer control of inventory and production at the work stations 0 Services Firms that tend to have repetitive operations reasonably high volumes and deal with tangible items can bene t from J IT systems 0 In general JIT works well in stable and predictable environments because there is little forward visibility Characteristics of JIT Systems Pull method Consistently high quality Small lot sizes Short setup times Uniform workstation loads Standardization of components and work methods Close supplier ties Flexible work force Product focus Automated production Preventive maintenance Enabling Customization using Standardized Operations Product or service customization has negative effects on both Predictability of demand Predictability of operations Since uncertainty in operations requires extra resources customization is inherently less ef cient than standardization However it is sometimes possible to increase operational ef ciency even with customization using standardization strategies Standardization strategies include o Part standardization Maximize component commonality across products Process standardization Delay customization as late as possible Product standardization Carry a limited number of products in inventory Types of Scheduling 0 Operations scheduling Assigns workers to tasks or jobs to machine work centers Operations schedules are shortterm plans designed to implement the master production schedule 0 Workforce scheduling Determines when human resources are available for work Common Performance Measures for Operations Schedules Job ow time The time a job spends in the shop Makespan For a group of jobs the time between the start of the rst job and the nish of the last job Past due 0 The amount of time late average job lateness o The percentage of jobs completed late Workinproeess 0r pipeline inventory expressed in units number of jobs dollar value or weeks of supply Total inventory The sum of scheduled receipts and onhand inventory Utilization The percentage of paid time spent productively Priority Sequencing Rules CR T1me Remammg to Due Date Total Shop Time Remaining s R0 2 Time Remaining to Due Date Total Shop Time Remaining Number of Operations Remaining EDD Select Job With Earliest Due Date FCFS Job That Arrives First is Processed First SPT Select Job With Shortest Processing Time Performance of Priority Sequencing Rules Earliest due date EDD Performs well with respect to minimizing percentages of jobs past due minimizing the maximum amount of time a job is late Performs poorly with respect to job ow time workinprocess inventory utilization First come first serve FCFS Perceived as being fair Performs poorly with respect to all performance measures Shortest processing time SPT Performs well with respect to average job ow time workin process inventory minimizing percentages of jobs past due utilization Performs poorly with respect to minimizing the maximum amount of time a job is late minimizing total inventory it pushes work to finished goods before it is needed adjusting schedules when due date changes due date is not used in the calculation of priority Critical ratio CR Performs well when we are concerned with global operation of a system of work centers Slack per remaining operations SRO Performs similarly to EDD with added advantages of a global view and accounting for the duration of the jobs Scheduling in Services Characteristics of services that have an impact on scheduling 0 Services can not buffer demand uncertainties with inventory 0 Demand for services is dif cult to predict 0 Scheduling systems can facilitate the capacity management of service providers Two approaches 0 Schedule customer demand capacity remains xed and demand is leveled o Appointments 0 Reservations 0 Backlogs 0 Schedule the work force to meet forecasted demand adjust capacity to demand MD 021 Management and Operations Statistical Process Control Outline De nition of statistical process control SPC Process variation Characteristics of control charts Types of control charts Choosing an SPC method De nition of Statistical Process Control Statistical process control SPC is the application of statistical techniques to determine Whether the output of a process conforms to the product or service design SPC is implemented Via control charts that are used to monitor the output of the process and indicate the presence of problems requiring further action Process Variation All processes exhibit variation For example a machine that lls cereal boxes will not put exactly the same amount in each box If we were to collect data over time on the amount of cereal in each box a plot of the data would be described as a distribution A distribution is characterized by its 0 Mean Cereal Production 700 0 Spread 0 Range 0 Standard deviation 600 500 400 300 200 No of boxes 0 Shape o Symmetric 100 o Skewed 0 l l l l l l l 97 975 98 985 99 995 10 101 101 102102103103 Average weight 02 Quality Measurements Control charts can be used to monitor processes Where output is measured as either variables or attributes Variables measures Characteristics of a product or service that can be measured on a continuous scale Examples include length Width and time Attributes measures Characteristics of a product or service that can be quickly counted for acceptable quality Examples include the number of defects in a product or service Sources of Process Variation Sources of process variation can be categorized as 0 Common causes Random or unavoidable sources of variation Within a process A process With only common causes of variation is stable ie the mean and spread do not change over time Such a process is said to be in a state of statistical control or incontrol o Assignable causes Any cause of variation that can be identi ed and eliminated originating from outside the normal process Characteristics of Control Charts A control chart is a timeordered diagram to monitor a quality characteristic consisting of o A nominal value or center line The average of several past samples 0 Two control limits used to judge Whether action is required an upper control limit UCL and a lower control limit LCL 0 Data points each consisting of the average measurement calculated from a sample taken from the process ordered over time By the Central Limit Theorem regardless of the distribution of the underlying individual measurements the distribution of the sample means will follow a normal distribution The control limits are set based on the sampling distribution of the quality measurement Purpose of Control Charts Control charts are intended to re ect only common causes of variation in order to detect assignable causes of variation Question If at the time we are constructing a control chart there are assignable causes of variation in the process how can we construct a meaningful control chart Answer By carefully choosing our sample size so that only common causes are found within a sample The control limits are set to 0 Usually detect when the process has gone out of control narrow control limits work better 0 Usually not overreact to random variation wider control limits work better The control limits are set to strike a balance between these competing priorities Control Charts for Variables Standard Deviation of the Process 039 Known Controlicharts for variables with the standard deviation of the process a known monitor the mean X of the process distribution The control limits are UCL 7 Z0 LCL X Z0 Where if center line of the chart and the average of several past sample means Z is the standard normal deviate number of standard deviations from the average a 0 xZ and is the standard deviation of the distribution of sample means and n is the sample size 2 An automatic filling machine is used to fill 1liter bottles of cola The machine s output is approximately normal with a mean of 10 liter and a standard deviation of 001 liter Output is monitored using means of samples of 25 observations a Determine upper and lower control limits that will include roughly 97 percent of the sample means when the process is in control x 10 liter 0 01 liter n 25 11 0 a Centre ll l lltS X 3 Z for 97 01 UCL ls 10217 210043 I 25 LCLisl 0 2 17 3901 9957 b Given the sample means 1005 1001 0998 1002 0995 and 0999 is the process in control 1006 7 out b39 10043 UCL 1002 1000 0 liters 998 i 39 Mean 9957 994 Control Charts for Variables Standard Deviation of the Process 039 Unknown Control charts for variables monitor the mean Ychart and variability R chart of the process distribution R chart To calculate the range of the data subtract the smallest from the largest measurement in the sample The control limits are Egszm gzgR Where R average of several past R values and is the central line of the control chart and D3D4 constants that provide three standard deviation threesigma limits for a given sample size Echart The control limits are LC RmME R Where R central line of the chart and the average of past sample means and A2 constant to provide three sigma limits for the process mean Control Chart for Vgiables Example X R Charts Webster Chemical Company produces mastics and caulking for the construction industry The product is blended in large mixers and then pumped into tubes and capped Webster is concerned whether the lling process for tubes of caulking is in statistical control The process should be centered on 8 ounces per tube Several samples of eight tubes are taken and each tube is weighed in ounces Tube number Sample 1 2 3 4 5 6 7 8 1 798 834 802 794 844 768 781 811 823 812 798 841 831 818 799 806 789 777 791 804 800 789 793 809 824 818 783 805 790 816 797 807 787 813 792 799 810 781 814 788 813 814 811 813 814 812 813 814 Othth a Assuming that taking only 6 samples is sufficientLuse the data in the table to construct threesigma Rchart and X chart control limits Is the process in statistical control b The process variability for the rst and sixth samples appear to be out of control Webster looks for assignable causes and quickly notes that the weighing scale was gummed up with caulking Apparently a tube was not properly capped The sticky scale did not correctly read the variation in weights for the sixth sample Delete that data and recalculate IT UCLITe and LCLE Is the process in statistical control Solution to Control Chart for Variables Example a Tube number Sample 1 2 3 4 5 6 7 8 Avg Range 1 798 834 802 794 844 768 781 811 8040 076 2 823 812 798 841 831 818 799 806 8160 043 3 789 777 791 804 800 789 793 809 7940 032 4 824 818 783 805 790 816 797 807 8050 041 5 787 813 792 799 810 781 814 788 7980 033 6 813 814 811 813 814 812 813 814 8130 003 8050 038 7 805017 038 n 8 From TableZ1 UCLR D4R 1864038 0708 LCLR D 0136038 0052 UCLI 7 AZE 8050 0373038 8192 LCL7 7 Az 8050 0373038 7908 b We delete the sixth observation and recalculate the control limits The ranges including the range for the first sample are now all within the revised control limits and the process average for the second sample now falls just inside of the revised control limits R i 076 043 032 041 033 X 5 8040 8160 7940 8050 7980 045 5 UCLR D4 1864045 0839 LCLR D3 0136045 0061 UCL7 7 AZE 8034 0373045 8202 LCL7 7 A28 8034 0373045 7866 8034 Control Charts for Attributes pChart A pchart is a commonly used control chart for attributes whereby the quality characteristic is counted rather than measured and the entire item or service can be declared good or defective The standard deviation of the proportion defective p is Up 130 3 n Where n sample size and Z9 average of several past p values and central line on the chart Using the normal approximation to the binomial distribution Which is the actual distribution of p i i UCLp pzap and LCLp p ZO39p Where z is the normal deviate number of standard deviations from the average Control Chart for Attributes Example pChart A sticky scale brings Webster s attention to Whether caulking tubes are being properly capped If a significant proportion of the tubes aren t being sealed Webster is placing their customers in a messy situation Tubes are packaged in large boxes of 144 Several boxes are inspected and the following number of leaking tubes are found Sample Tubes Sample Tubes Sample Tubes 1 3 8 6 15 5 2 5 9 4 16 0 3 3 10 9 17 2 4 4 11 2 18 6 5 2 12 6 19 2 6 4 13 5 20 1 7 2 14 1 Total 72 Calculate pchart threesigma control limits to assess Whether the capping process is in statistical control 72 0025 20144 1 i 0025 1 0025 a 2 p p I gt20013 1 n 144 UCLP Z zap 0025 30013 0064 LCLP Z zap 0025 30013 0014 adjusted to zero Solution 11 144 Z The highest proportion of defectives occurs in sample 10 but is still Within control limits p10 2 9 144 00625 Therefore the process is in statistical control Control Charts for Attributes cChart A cchart is another type of control chart for attributes whereby the quality characteristic is counted as the number of defects unit Using the normal approximation to the Poisson distribution Which is the actual distribution of c UCLC Ez and LCLC E z Where cis the average number of defectsunit and the center line of the cchart Control Chart for Attributes Example c Chart At Webster Chemical lumps in the caulking compound could cause difficulties in dispensing a smooth bead from the tube Testing for the presence of lumps destroys the product so Webster takes random samples The following are the results of the study Tube Lum s Tube Lum s Tube Lum s l 6 5 6 9 5 2 5 6 4 10 0 3 0 7 1 ll 9 4 4 8 6 12 2 Determine the cchart twosigma upper and lower control limits for this process Solution E650464165092 4 12 ac f 42 UCLC EZac 4228 LCLC E zac 4 220 The eleventh tube has too many lumps 9 so the process is probably out of control Process Capability Exercise Webster Chemical s nominal weight for filling tubes of caulk is 800 ounces i 060 ounces The target process capability ratio is 133 The current distribution of the filling process is centered on 8054 ounces with a standard deviation of 0192 ounces Compute the process capability indeX to assess Whether the filling process is capable and set properly Solution Process capability ratio C Upper specification Lower specification 86 74 p 60 60192 10417 Process capability index i L if i if i i C k mlmmum of ower spec1 1cat10n 3 Upper spec1 1cat10n p 30 30 8054 7400 21135 86008054 2 0948 30192 30192 Cp 0948 The process is not capable of consistently meeting specifications according to the minimum capability level set by Webster Supplementary Material 1 Calculating P pf 1 P proportion of defective products X number of the defected products 11 sample size m number of samples x1x72 xi 2x 1 p1p2 pm n n n xlx2 xm il m m 171 171 total number of defected products 7 total number of products CHAPTER 2 EXAMPLES OF PRODUCTIVITY MEASURES Productivity Analysis O t t Product1v1ty u pu Input Partial Measures of productivity Ou ut Labor productrvrty A 63 Employee hours Multifactor Measure Output Multifactor productivity Labor cost Materials cost Overhead cost Note 1 The Output in a productivity measure is usually measured by the quantity units of the output or by the economic value 33 of the output Note 2 Only usable output should be counted Productivity Growth Current Period Productivity Previous Period Productivity Productivity Growth X 100 Previous Period Productivity Example 1 Four workers packed 100 boxes in 8 hours What is the labor productivity Output Input SingleFactor Productivity Example 2 A factory produces 6000 units of car replacement component per month which can be sold at the price of 50unit The monthly labor cost is 8000 material cost is 5000 and overhead cost is 3000 The percentage of the products that meet the quality standard is 96 What is the multifactor productivity Output Input MultiFactor Productivity Example 3 A woman who runs an inhome business on average spends 4 hours performing setups prior to a sales call and 5 hours processing an individual sales transaction The average value of each sales transaction is 1200 What is the labor productivity What would the labor productivity be if setups could be reduced to 1 hour Output Input SingleFactor Productivity SingleFactor Productivity Reduced Setups Example 4 The above woman recently discovered that she usually invests 45 in materials per transaction and incurs 50 in overhead per transaction She also began to pay herself 35hour of labor assume 9 hours of work per sales call What is her multifactor productivity Output Input MultiFactor Productivity James Coleman the manager of a university dormitory system in the Midwest is trying to determine which student dorm room painting team should get a bonus for the highest productivity during the 13 weeks of summer break Information about each team is presented below Based on labor productivity what team do you recommend gets the bonus Painting Team Crew Size Total Labor Hours Worked Rooms Painted A 4 B 2 2880 61 C 3 4320 75 D 3 4756 67 E 4 6624 125 A team of 20 Boston College food service employees produces 2500 prepared meals in a 36 hour work week Each meal incorporates food and packaging that costs 5 per meal Each meal sells for 10 Typical overhead costs are 6000 per week Each employee is paid 9 per hour What is the multifactor productivity Greater than 10 but less than or equal to 15 Greater than 15 but less than or equal to 20 Greater than 20 but less than or equal to 25 Greater than 25 UOUJCD If two employees quit and are not replaced yet production stays the same what is the productivity growth MD 021 Management and Operations Operations Strategy De nitions of strategy and operations strategy Levels of strategy corporate business functions Evaluating an operations strategy Example McDonald39s De nition of Strategy Strategy is a deliberate search for a plan of action that Will develop a business39s distinctive competence and compound it De nition of Operations Strategy An operations strategy consists of a sequence of decisions that over time enables a business unit to achieve a desired operations structure infrastructure and set of speci c capabilities in support of the competitive priorities OrderQuali ers and OrderWinners Orderquali ers are those criteria that a company must meet for a customer to even consider it as a possible supplier Companies need only be as good as competitors OrderWinners are those criteria that Win the order Companies need to be better than their competitors Levels of Strategy What business 39 9 Corporate are we 1n How do we compete D1V1s10nal Busmess Role 9f each Prod functlon m Components of the Operations Strategy Structural decision Capacity categories Facilities Vertical integration Technology Infrastructural decision Workforce categories Organization Informationcontrol systems Capabilities Unique to each rm Competitive priorities Cost Quality Highperformance design Consistent quality Time Fast delivery time Ontime delivery Development speed Flexibility Customization Volume exibility Criteria for Evaluating an Operations Strategy Consistency internal and external Between the operations strategy and the overall business strategy Between the operations strategy and the other functional strategies within the business Among the decision categories that make up the operations strategy Between the operations strategy and the business environment resources available competitive behavior governmental restraints etc Contribution to competitive advantage Making tradeoffs explicit enabling operations to set priorities that enhance the competitive advantage Directing attention to opportunities that complement the business strategy Promoting clarity regarding the operations strategy throughout the business unit so its potential can be fully realized Providing the operations capabilities that will be required by the business in the future Statement of McDonald s Operations Strategy To provide unmatched consistency in operations in support of high product quality This must be accomplished with adequate speed low cost and process innovation to accommodate changes in consumer tastes From the statement of McDonald s operations strategy it is clear that both consistent and high performance quality are considered order Winners While speed cost and innovation are considered order quali ers McDonald s Operations Strategy Dimension Strategy Capacity 0 Growth as needed through additional stores but capacity added carefully o Wellutilized franchisee s wellbeing depends on it being used heavily Facilities 0 Distributed facilities each facility being very similar to the next all focused around the same menu although the uniformity is beginning to change Process 0 High degree of process understanding emphasis on Technology quotfoolproof processes 0 A leader in the technology of fastfood delivery Vertical o Partnership arrangement Integration 0 Longterm relationship with suppliers to promote innovation and quality improvement Workforce o Franchisees welltrained carefully selected entrepreneurs o Operators highturnover cheap Organization 0 Guidelines provided by corporation but franchisees push to locally optimize Control 0 Centralized buying Systems 0 Bulk contracts quotPushquot system for basic supplies quotpullquot system dayto day in the restaurants Evaluation of the operations strategy 0 Internal and external consistency Looking at the operations strategy along the seven dimensions they all support the operations mission and the business strategy from the previous page Contribution to competitive advantage Systemic strategy creates unmatched consistency in operations that has been difficult to imitate MD 021 Management and Operations Capacity Planning and Decision Theory Measures of capacity Bottlenecks Capacity strategies A systematic approach to capacity decisions Make or Buy Problem Decision Making Under Uncertainty and Risk Decision Trees Capacity Planning Capacity is the maximum rate of output for a facility Capacity planning considers questions such as Should we have one large facility or several small ones Should we expand capacity before the demand is there or wait until demand is more certain Measuring Capacity Measurement Type 0 Output measure for product focus 0 Input measure for process focus W Utilization Design Capacity Actual Output Ef ciency E ectz ve Capacity Effective Capacity Design Capacity maximum output rate Allowances eg personal time maintenance and scrap Sizing Capacity Cushion Cushion the amount of the reserved capacity that a rm maintains to handle sudden increase in demand or temporary losses of production capacity Capacity cushion l Utilization Pressures for Large Cushion Uneven demand Uncertain demand Changing product mix Capacity comes in large increments Uncertain supply Pressure for Small Cushion Capital costs Links with Other Areas Other Choice Faster delivery times Smaller yield losses Higher capital intensity Less worker exibility Lower inventories More stable schedules Cushion 0 Larger o Smaller o Smaller 0 Larger 0 Larger o Smaller A Systematic Approach to Capacity Decisions 1 Estimate capacity requirements 2 Identify gaps 3 Develop alternatives 4 Evaluate the alternatives Estimate Capacity Requirements 1 One type of product Numbers of machines required Processing hours required for year39s demand hours available from one machine per year after the desired cushion deducted M Dp N1 C Where D number of units customers forecast per year p processing time in hours per unit or customer N total number of hours per year during Which the process operates C desired capacity cushion rate 2 More than one type of product n types of products Numbers of machines required 2 Processing and setup hours required for year39s demand sumed over all products hours available from one machine per year after the desired cushion deducted M D19 DQspmdm1 D19 D Qspmdm2 D19 D Qspmdm N1 C Q number of units in each lot s setup time in hours per lot Note Always round up the fractional part for the number of machines required Capacity Planning Problem You have been asked to put together a capacity plan for a critical bottleneck operation at the Surefoot Sandal Company Your capacity measure is number of machines Three products men s women s and kid s sandals are manufactured The time standards processing and setup lot sizes and demand forecasts are given in the following table The rm operates two 8hour shifts 5 days per week 50 weeks per year Experience shows that a capacity cushion of 5 percent is suf cient Time Standards Demand Processing Setup Lot Size Forecast Product hrpair hrlot pairslot pairsyr Men s sandals 005 05 240 80000 Women s 010 22 180 60000 sandals Kid s sandals 002 38 360 120000 a How many machines are needed at the bottleneck b If the operation currently has two machines what is the capacity gap c If the operation can not buy any more machines which products can be made d If the operation currently has ve machines what is the utilization Capacity Planning Problem Solution Total time available per machine per year 2 shiftsday8 hoursshift5 daysweek50 weeksyear 4000 hoursmachineyear With a 5 capacity cushion the hoursmachineyear that are available are 40001005 3800 hoursmachineyear Total time to produce the yearly demand of each product This is equal to the processing time plus the setup time Men s 005800008000024005 4167 hrs Women s 010600006000018022 6733 hrs Kid s 00212000012000036038 3667 hrs Total time for all products 416767333667 14567 hrs a Machines needed 145673800 383 4 machines CT Capacity gap is 4 2 2 machines c With two machines we have 3 8002 7600 hours of machine capacity We can make all of the women s sandals 6733 hours and some of the men s sandals for example 9 With five machines 54000 20000 machinehoursyr are available The total number of machinehoursyr needed for production are 14567 Utilization 1456720000100 73 Thus the capacity cushion is 100 73 27 Vertical Integration Problem Make or Buy Hahn Manufacturing has been purchasing a key component of one of its products from a local supplier The current purchase price is 1500 per unit Efforts to standardize parts have succeeded to the point that this same component can now be used in ve different products Annual component usage should increase from 150 to 750 units Management wonders whether it is time to make the component inhouse rather than to continue buying it from the supplier Fixed costs would increase by about 40000 per year for the new equipment and tooling needed The cost of raw materials and variable overhead would be about 1100 per unit and labor costs would go up by another 300 per unit produced a Should Hahn make rather than buy b What is the breakeven quantity c What other considerations might be important Decision Making Under Uncertainty Decision Rules Maximin Choose the alternative that is the best of the worst Maximax Choose the alternative that is the best of the best Laplace Choose the alternative with the best weighted payoff Minimax regret Choose the alternative with the best worst regret ie opportunity losses Decision Making Under Uncertainty Pro ts Event 1 Low demand Event 2 High demand Alternative 1 Small facility 300 200 Alternative 2 Large facility 50 400 Decision rules Maximin Maximax Laplace Minimax regret Decision Making Under Risk Pro ts Event 1 Low demand Event 2 High demand Probability 03 Probability 07 Alternative 1 Small facility 300 200 Alternative 2 Large facility 50 400 Use the expected value decision rule CHAPTER 18 EXAMPLES OF WAITING LINE MODEL PROBLEMS Application 1 Sin gle Server Model Customers arrive at a checkout counter at an average 20 per hour according to a Poisson distribution They are served at an average rate of 25 per hour with exponential service times Use the singleserver model to estimate the operating characteristic of this system p LS W3 Waiting Line Models Application 2 MultipleServer Model Suppose the manager of the checkout system decides to add another counter The arrival rate is still 20 customers per hour but now each checkout counter will be designed to service customers at the rate of 125 per hour What is the waiting time in line of the new system Note that even though the average service rate is the same in the two systems the average waiting time is less in the multipleserver arrangement Waiting Line Models Application 3 FiniteSource Model DBT Bank has 5 copy machines located in various of ces throughout the building Each machine is used continuously and has an average time between failures of 50 hours Once failed it takes 4 hours for the service company to send a repair person to have it xed What is the average number of copy machines waiting to be repaired and what is this systems downtime Waiting Line Models Application 4 Hilltop Produce The Hilltop Produce store is staffed by one checkout clerk The average checkout time is exponentially distributed around an average of two minutes per customer An average of 20 customers arrive per hour a What is the average utilization rate p b What is the probability that three or more customers will be in the checkout area P1 P1 P2 P3 c What is the average number of customers in the waiting line Lq MD 021 Management and Operations Total Quality Management Outline De nitions of quality Total quality management TQM Costs of poor quality Tools for improving quality Quality awards and standards CustomerDriven De nitions of Quality 0 Conformance to speci cations 0 Value 0 Fitness for use 0 Support 0 Psychological impressions Quality as a Competitive Weapon 0 The costs of poor quality are estimated to be 20 30 of product or service costs 0 Companies can improve their bottom line through better quality in several ways 0 Lower costs through consistent quality 0 Higher prices through highperformance design 0 Greater market share through both consistent quality and high performance design 0 Consistent quality has become or is becoming an order quali er in many markets Quality at the Source Errors or defects should be caught and corrected at the source not passed along to an internal or external customer In other words Do It Right the First Time Why 1 It costs less 2 Inspection and sorting are often not effective Employee Involvement Employee involvement an important component of TQM because perceived and actual quality is assessed throughout the process involving all employees This suggests that Quality perceptions can be negatively affected at one point in the process even if the rest of the process is ne All employees can participate in improving quality Work Teams Work teams are small groups of people Who have a common purpose performance goals and accountability Types of teams 0 Problemsolving teams 0 Specialpurpose teams 0 Selfmanaging teams How can work teams help improve quality 0 Products and services are becoming more complex and interrelated Quality can not be ensured by individual efforts 0 Workers producing products or services often have the best ideas how the processes can be improved Applications of TQM Purchasing considerations Product and service design Process design Quality function deployment Benchmarking Tools for Organizing Data for Analysis Checklists Histograms Bar charts Pareto charts Scatter diagrams Causeandeffect diagrams Graphs Costs of Quality Cost categories 0 Prevention gtQuality assurance costs 0 Appraisal 0 Internal failure gtNonconforrnance costs 0 External failure There is a tradeoff between quality assurance and nonconforrnance costs As the product or service moves farther along in the process the cost to address a quality problem rises steeply Quality Awards and Standards Awards 0 Malcolm Baldrige National Quality Award 0 State quality awards 0 Vendor supplier quality awards Standards 0 ISO 900014000 CHAPTER 5 EXAMPLES OF CAPACITY PLANNING Example 1 Eagles Cash Money Bank has the following processes a A loan processing operation that processes an average of 77 loans per day The operation has a design capacity of 100 loans per day and an effective capacity of 83 loans per day b EaglesCashMoneyBankcom a website that provides online banking services The website can process an average of 15000 transactionshour The website has a design capacity of 30000 transactionshour and an effective capacity of 23000 transactions per hour Calculate the efficiency and the utilization for each of these processes Loan Processing Operation Efficiency Utilization EaglesCashMoneyBank com Efficiency Utilization Example 2 PizzaTime Restaurants is building a new pizza place and needs to determine how big to make the various parts of its facility It wants to be able to accommodate a maximum of 500 customers per hour at its peak times PizzaTime has collected the following information the average time to place and receive an order is 11 minutes the average time spent in the restroom is 04 minutes 50 of the customers are men and 50 are women 20 of the customers have cars and require parking spots and the average length of time at the restaurant is 20 minutes per customer Assuming that PizzaTime wants to maintain a 20 capacity cushion for each area determine The number of cash registers required The number of toilets sinks needed for the restrooms The number of parking spaces needed The number of seatstables needed Are any of these operations bottlenecks What do you think an appropriate capacity cushion is for each of the operations listed in ad hQQOU N M7Dp N1 C Cash Registers ToiletsSinks Parking Spaces SeatsTables Are any of these Bottlenecks Example 3 Bob s Bicycles manufactures three different types of bikes the Tiny Tike the Adult Aero and the Mountain Monger Given the production schedule below including setup and processing times and lot sizes calculate the required capacity for this year s production Note that the times are given for indiVidual production lines so capacity calculations should be in terms of the number of lines necessary Assume that Bob s operates two shifts each with 2000 hours per year and wishes to maintain a 15 capacity cushion ZDP DQSlpmm M 1 N1 C N of hours during which the process operates C capacity cushion M Example 4 Eagleman s Donuts produces two varieties of pastry which are sold to a national grocery chain Muffin Tops and Doughnuts Assuming that Doog s operates a single shift for 1800 hours per year calculate the required capacity The processing time per unit setup time per lot the annual demand and lot size are given below Assume that the times given are for a production cell of four workers each so required capacity should be in terms of the number of production cells needed Eagleman s would like to maintain a 10 capacity cushion Zle DQSpmdu tx 2 N1 C N of hours during which the process operates C capacity cushion M Example 5 Surefoot Sandal Company operates two 8hour shifts five days per week 50 weeks per year A capacity cushion of 5 percent is used for all products Management is trying to determine if they should make a new line of sandals Time standards lot sizes and demand forecasts are Time Standards Processing Setup Lot Size Demand Forecast Product hrpair hrlot pairslot pairsyr Men s sandals 005 05 240 80000 Women s sandals 010 22 180 60000 Children s sandals 002 38 360 120000 a What are the capacity requirements for the three types of sandals b One manager threw out the idea that they should buy 5 machines Assuming managers choose to use 5 machines in the factory what is their utilization What is their capacity cushion c How many machines are needed at the bottleneck assuming a 5 capacity cushion d If the operation currently has two machines what is the capacity gap e If the operation can not buy any more machines which products can be made Example 6 Vertical Integration Problem Make or Buy Hahn Manufacturing has been purchasing a key component of one of its products from a local supplier The current purchase price is 1500 per unit Efforts to standardize parts have succeeded to the point that this same component can now be used in five different products Annual component usage should increase from 150 to 750 units Management wonders whether it is time to make the component in house rather than to continue buying it from the supplier Fixed costs would increase by about 40000 per year for the new equipment and tooling needed The cost of raw materials and variable overhead would be about 1100 per unit and labor costs would go up by another 300 per unit produced a Should Hahn make rather than buy b What is the breakeven quantity c What other considerations might be important

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