Bài giảng môn Quản trị kinh doanh - Chapter 14: Capacity: matching productive resource to demand

Chapter 14Capacity: Matching Productive Resource to Demand1Learning ObjectivesDefine capacity and distinguish it from capability.Describe how capacity relates to value and profitability for B2C and B2B transactions.Describe how demand that varies from design capacity influences profitability.Describe the role individual resources and constraints play in determining system capacity.Make the calculations necessary to create demand chase and level production aggregate plansDescribe the information inputs and logic necessary for rough-cut capacity planning.Calculate required and available capacity for a rough-cut capacity plan.Describe the information inputs and logic necessary for capacity requirements planning.Calculate required and available capacity for a capacity requirements plan.Describe how yield management aids services in maximizing revenues.Perform the calculations to determine the number of customers to overbook.2CapacityThe ability to produce at a given volume in a specified amount of time. Being able to do “enough” of something to meet demand.When making products, capacity can be stored in the form of work-in-process and finished-goods inventory.For services, capacity usually can’t be stored.Introduction: Matching Resource Availability to Market Demand3Capacity is defined in terms of a level of output per unit of time. There must be enough capacity in each resource to meet demand.Matching Resource Availability to Market Demand: Capacity Defined4Capacity can be provided in various waysMixing production and storage capacityDemand of 1,000 units is to be met in ten daysMatching Resource Availability to Market Demand: Capacity Defined5Capacity affects value. What value attributes do customers seek?CostStyle/fashionQualityEthical issuesResponse timeTechnologyDependability of deliveryFlexibilityConveniencePersonalizationWhen capacity can’t meet demand, customers may choose to go elsewhere rather than wait.A capacity shortage creates waiting lines and impacts response time, dependability of delivery, and flexibility.A backlog is a queue of orders waiting to be processed (another term for a waiting line).Capacity and Value6Excess (protective) capacity can serve the same purpose as inventoryProtect against surges in demand.More flexible than buffering with finished goodsExcess capacity is often in short supplyViewed as an investment in resources that aren’t providing a financial return. Yet it provides a long-term benefit because it improves various time-related value attributesCapacity and Value7Design capacityThe capacity a facility is designed to accommodate on an ongoing basis.Best operating levelThe level of demand or “load” on a system that results in the lowest cost per unit produced or processed.Going either above or below the best operating level for long periods has a negative financial impactThe Financial Impact ofCapacity Decisions8Below best operating level (A and E):Lower revenueUnderutilized capacity drives up unit costs and/or forces layoffsExhibit 14.3 Demand and Design Capacity RelationshipsThe Financial Impact ofCapacity Decisions9Above best operating level (C):High revenue and lower unit cost (both good)Equipment could wear out as maintenance is postponedHave to pay overtime and/or hire and train tempsPossible decline in quality, increase in safety problemsThe Financial Impact ofCapacity DecisionsExhibit 14.3 Demand and Design Capacity Relationships10The overall capacity of a system is dependent on all of the resources used to create it.ConstraintAnything that inhibits a system’s progress toward its goals. In a production system, a constraint is called a bottleneck.Constraint managementAn integrative framework that attempts to maximize the system’s accomplishment of its goals by managing the system’s constraint.Individual Resource Influence onSystem Capacity11Step 3 is slower than the rest. It is the constraint in the system.Characteristics of constrained systemsResources don’t set their own utilization ratesTime lost by the constraint is lost (and can’t be made up) to the entire systemConstraints must be utilized 100% of the time to maximize outputIf a constraint breaks down, the result is the same as shutting down the entire system.Exhibit 14.4 Example of a Constrained SystemIndividual Resource Influence onSystem Capacity12Increasing output of a non-bottleneck doesn’t help the system. It just builds up inventory at the bottleneck.A system can be thought of as analogous to a chain. A chain is only as strong as its weakest link. Individual Resource Influence on System Capacity: Constraints13A business can constrain an entire supply chain. The supply chain can be thought of as a “chain of chains”.Exhibit 14.7 Weakest Link in a Supply ChainConstraints don’t have to be in production resources or machines. They can occur in transportation, distribution, or storage.A Broader View: Supply Chain Capacity14Aggregate demandThe total demand for all products and servicesOften utilizes a “pseudoproduct” or fictional “representative” productTwo Alternatives for Aggregate Planning:Demand Chase: Adjusting capacity to meet varying demand; hiring and firing workersPrimary cost is hiring and firing costsLoss of labor qualityLevel Production: Building up and using from inventory, while keeping workforce levelPrimary cost is inventory carrying costThe Demand-Capacity Match in Manufacturing15Step-by-Step: Demand Chase Aggregate PlanningConvert units required for each time period to labor hours by multiplying number of units by labor hours required per unit.Compute number of workers required per period by dividing number of labor hours by the number of hours worked by each worker (rounding up).Hires are required if the number of workers needed in a time period is greater than the number of workers needed in the previous period. The difference between the two is the number of hires.Fires or layoffs are required if the number of workers needed in a time period is less than the number needed in the previous time period. The difference between the two is the number of fires.Calculate hiring costs by multiplying number of workers hired by cost of hiring a worker. Calculate firing costs the same way.Calculate total plan costs by summing hiring and firing costs.The Demand-Capacity Match in Manufacturing16Example 14.1:Labor per unit = 1.2 hours40 hour week (160 hours per month)Hiring cost = $475Firing cost = $400Initial staffing = 11 employeesThe Demand-Capacity Match in Manufacturing: Demand Chase Example171,400 * 1.2 = 1,680 hours requiredExample 14.1:Labor per unit = 1.2 hours40 hour week (160 hours per month)Hiring cost = $475Firing cost = $400Initial staffing = 11 employeesThe Demand-Capacity Match in Manufacturing: Demand Chase Example18The Demand-Capacity Match in Manufacturing: Demand Chase Example1,680 / 160 = 10.5 workers requiredRound to 11 workers in order to meet demand19Total hiring cost = $6,650 Total layoff cost = $4,400Total plan cost = $11,050The Demand-Capacity Match in Manufacturing: Demand Chase Example20Step-by-Step: Level production aggregate planning.Divide total expected demand for the planning horizon by the number of days to get number of units to produce each dayMultiply the number of units produced each day by the number of labor hours per unit to get labor hours required per dayDivide labor hours required per day by number of hours each worker works in a day to get number of workers requiredGet average level of inventory for each month by averaging beginning and ending inventory.Get inventory carrying cost by multiplying monthly average inventory by monthly carrying cost per unitTotal cost is the sum of the monthly inventory carrying costs plus any initial hiring and firing costsThe Demand-Capacity Match in Manufacturing21Example 14.2Labor = 1.2 hours per unit40 hour week (8 hours per day)Hiring cost = $475Layoff cost = $400Initial staffing = 11 employees 253 working days per yearTotal forecast production = 21,320 unitsCarrying costs = $12 per unit per month(85 units * 1.2 hours)/8 hours per day 12.75  13 workers on staff85 units per dayThe Demand-Capacity Match in Manufacturing: Level Production Example22Hire two workers for $950 Carrying cost = $91,890Plan cost = $92,840The Demand-Capacity Match in Manufacturing: Level Production Example23It is unlikely that either the demand chase or level production aggregate plan will be totally acceptable.Best solution is some hybrid of using inventory and adjusting the level of the workforce.Adjust workforce levels periodically and level the production between adjustmentsThe Demand-Capacity Match in Manufacturing24Capacity-demand relationships must be addressed on a detailed level in the short term.Goal is to determine the load on firm resourcesCapacity planning processes are typically integrated with dependent demand inventory- with material requirements planning (MRP)Bill of capacity: A statement of the time required on each resource needed to produce a product.Rough-cut capacity planning: An approach used in manufacturing that uses the master production schedule to provide the quantity of units that must be produced.Detailed Capacity Planning in Manufacturing25Step-by-Step: Rough-Cut Capacity PlanningCalculate capacity required (in hours) for each work center for each week by multiplying the quantity of items to be produced in each week (from the master production schedule) by the time it takes on that particular work station to produce themCalculate available capacity (in standard hours) at each work center by multiplying the actual hours available in a week by the historical utilization and by the historical efficiencyOn a weekly basis, compare required capacity to available capacity, for each work stationDetailed Capacity Planning in Manufacturing26Example 14.3A manufacturer of crates wants to create a rough-cut capacity plan for one of their lines (model 2440). The utilization rate for all machines averages 93%. Efficiency is at 95%. Develop a rough-cut capacity plan using data from master production schedule and the bill of capacity.Rough-Cut Capacity Planning Example27First, multiply the number of units you will produce in each week (from the MPS) by the time one unit takes at each work center (from the bill of capacity).Exhibit 14.15 Bill of CapacityExhibit 14.14 Master Production Schedule210 * 0.08 = 16.8 Do this for all the numbers to create a tableRough-Cut Capacity Planning Example28The table below shows capacity required at each work center, each week. Exhibit 14.16 Capacity RequiredRough-Cut Capacity Planning Example29Multiply actual hours available by the historical utilization rate for the work center and also by historical efficiency to get capacity available, in “standard hours”. Exhibit 14.17 Capacity AvailableRough-Cut Capacity Planning Example30Combine the capacity required and capacity available tables for easy comparison. Exhibit 14.18 Rough-cut Capacity PlanRough-Cut Capacity Planning Example31Rough-cut capacity planning is a quick but inaccurate analysis.It is frequently used to check if the MPS is feasibleIgnores on-hand inventoryIgnores possibility of production occurring in weeks before the MPS shows a product to be dueCapacity Requirements Planning is more accurate.Uses the planned releases from MRP- timing of production is more accurateAccounts for inventoryDetailed Capacity Planning in Manufacturing32Step-by-Step: Capacity Requirements PlanningUsing MRP logic, compute planned order releases for all componentsFor each department or work station, identify the components that will utilize that work stationCompute required capacity for each work station by multiplying quantity of a component (from planned order releases) by the time required per unit on that work station. Do this for each weekCompute total capacity required on a work station for a given week by summing the time required for each of the components using itDetailed Capacity Planning in Manufacturing33Example 14.4A fly rod manufacturer wants to use planned order releases from MRP to help plan for capacity. The manufacturer has three departments: Handle assembly, wrapping department, and finishing. The product structure of a fly rod is given below:Capacity Requirements Planning ExampleExhibit 14.19 Product Structure for 9-foot 5-Weight Fly Rod34MRP logic generates the planned order releases:All the bottom-level components are purchased, so assembling these components into the butt and tip sections is what needs capacity.Exhibit 14.20 Planned Order ReleasesCapacity Requirements Planning Example35Multiply the time each section takes at each department by the planned order releases from MRP.Exhibit 14.21 Routings for Components48 * 0.08 = 3.84 Exhibit 14.20 Planned Order ReleasesCapacity Requirements Planning Example36Add butt and tip section capacities to get total required capacity per week per department.Exhibit 14.22 Capacity Requirements PlanCapacity Requirements Planning Example37Relationships between material and capacity planning within a generic production planning and control system:Exhibit 14.23 Generic Manufacturing Planning and Control SystemDetailed Capacity Planning in Manufacturing38For services, the load on capacity can’t be leveled by inventory. We must often smooth demand to smooth the load on capacity.We use appointments, reservations, or pricing strategies to level demand. Services that have high fixed costs and little marginal cost for additional customers have developed more sophisticated approaches, such as yield management.The Demand-Capacity Match in Services39Yield Management: An approach used in capital-intensive services that attempts to obtain maximum revenues through differential pricing, reservation systems, and overbooking.Used in services with high fixed costs, low variable costs.Requires segmenting the customer base, using multiple price levelsThe Demand-Capacity Match in Services: Yield Management40Overbooking: Taking more reservations than you have capacity.Minimizing costs associated with “no-shows” when reservations are usedBalance these costs with costs of not being able to serve a customer (or having to serve them differently) when too many show upCommon issue in high fixed cost service businesses and where “no-shows” are a problemAirlinesHotelsThe Demand-Capacity Match in Services: Overbooking41Step-by-Step: Determining the Low-Cost Overbooking Policy.Calculate percentage of the time each no-show condition occursDetermine the cost of walking or bumping a customer and the opportunity cost of a vacant room or seatIdentify an overbooking policy to evaluate. For each scenario under the policy, determine the cost of the no-shows or bumping. If there are empty rooms, calculate the expected cost of that condition by multiplying the number of empty rooms by the cost per empty room by the probability of this condition occurring. Similarly, multiply number of customers bumped by the cost of bumping, by the probability of it happening. The cost of the plan is the sum of all bumping and empty room costsRepeat last step for any overbooking policies being evaluated, and pick the one with the lowest costThe Demand-Capacity Match in Services: Overbooking42Example 13.5:A hotel wants to use overbooking to minimize the cost of no-shows. Over the past year it has had an average of 1.56 no-shows per day, at a cost of $89 each. It has calculated the cost of bumping a customer to be $110. No-show probabilities are given below. Find the best overbooking policy.Exhibit 14.24 No-show HistoryThe Demand-Capacity Match in Services: Overbooking Example43Overbooking by one results in a total cost of $101.38Exhibit 14.25 Expected Costs of Overbooking by OneThe Demand-Capacity Match in Services: Overbooking Example44Overbooking by two results in a total cost of $143.72Exhibit 14.26 Expected Costs of Overbooking by TwoThe Demand-Capacity Match in Services: Overbooking Example45Overbooking by one is the best policy: Expected cost is less than no overbooking, and less than overbooking by two.There is no need to try policies where you overbook by three or more, as costs will only increaseThe Demand-Capacity Match in Services: Overbooking Example46The goal is flexibilityTemporary workersContract manufacturersOutsourced componentsAll of these have negative aspects, as far as quality, reliability, and increased transportation time, but there are tradeoffs in all capacity decisions.Current Trends in Capacity Management47