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Capacity Management

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Operation management presentation on how companies help determine the factory output and inventory.

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Capacity Management

  1. 1. CAPACITY MANAGEMENT
  2. 2. Hello! Luke D’Silva (5) Yash Vardhan Lohia (9) Madhurima Paul (10)
  3. 3. “ “The world has enough for every one’s needs, but not enough for everyone’s greed.” -Mahatma Gandhi.
  4. 4. CAPACITY MANAGEMENT  Capacity is a very relative term. In operations, it is defined as the amount of resource inputs available relative to output requirement over a particular period of time.  Strategic Capacity Planning is an approach taken to determine the overall capacity level of capital-intensive resources- facilities, equipments and the labour force size- that best supports the companies strategy.
  5. 5. CAPACITY PLANNING Long Range Greater than one year. In this case, the resources take a long time to acquire and dipose. e.g., building, equipment, etc. Intermediate Range Monthly or quarterly planning. Capacity may vary due to hiring, layoff, new tools and changes, or subcontracting. Short Range Less than a month. This is tied into weekly or daily process and involves making adjustments to decrease variance between planned and actual output.
  6. 6. CAPACITY UTILIZATION  By capacity, we mean an attainable output, e.g., 4 lakh tablets per day, but it does not provide information that how long the rate can be sustained. Therefore, we do not know wether this rate is sustainable or not.  To avoid such problems, the concept of Best Operating Level is used.  It is a level of capacity at which the output level minimizes the average cost per unit.
  7. 7. CAPACITY UTILIZATION  The important measure is the capacity utilization rate. It reveals the best operating level. 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 = 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑠𝑒𝑑 𝐵𝑒𝑠𝑡 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐿𝑒𝑣𝑒𝑙  For example, if a company’s best operating level is 4.5 lakh tablets per day, and it makes 4 lakh tablets per day, the capacity utilization rate is 89%. 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 = 400000 450000 = 89%
  8. 8. Market demand is just the tip of the iceberg. The real problem lies with managing the resources and providing a correct supply to the demands in the market.
  9. 9. ECONOMIES OF SCALE  Economics of scale is the basic idea that as the plant gets larger and volume increases, the average cost of unit drops.  This happens due to lower costs of operation and capital because the equipment with twice the capacity does not cost twice as much to purchase or operate.  Plants also gain efficiency when they learn how to utilize their dedicated resources- people and equipment- for IT, material handling and administrative support.
  10. 10. DISECONOMIES OF SCALE  Sometimes, a size of a plant may become too large and cause diseconomies of scale.  Diseconomies may surface due to many reasons. Maintaining the demand required to keep the large facility busy requires significant discounting of the product.  E.g., M&M Mars has highly automated high volume equipment to make M&Ms. A sinngle equppment moves 2.6 million M&Ms a day. Even if the labour required to operate is low, the labour for maintainance is high.
  11. 11. LEARNING CURVE  A line which displays the relationship between unit production time and cumulative number units produced.  It is used to estimate the time for product design and production, as well as costs.  Integral part of planning corporate strategy such as decisions concerning pricing, capital investment and operating cost based on experience curves.  Applied to both individuals and organization.
  12. 12. TYPES OF LEARNING  Individual Learning is the improvement that the results when people repeat the process and gain efficiency from their own experience. “Practice makes Perfect”  Organizational Learning results from practice as well, but also comes from changes in administration, equipment and product design.
  13. 13. THEORY Learning curve theory is based on three assumptions:  The amount of time given to complete a given task or, the unit of a product will be less each time a task is undertaken.  The unit time will decrease at a decreasing rate.  The reduction in time will follow a predictable pattern
  14. 14. PROGRESS CURVE
  15. 15. INDUSTRIAL LEARNING
  16. 16. CAPACITY FOCUS  Focus Factory is a facility designed around a limited set of production objectives. Typically, the focus relates to a specific product or a product group.  A focused factory can be operationalized through the mechanism of Plant within a Plant.  A focus factory may have several PWPs, each of which may perform separate tasks and produce diferrentiated products.
  17. 17. PRODUCT LINE A ASSEMBLY B MACHINE SHOP PRODUCT LINE B ASSEMBLY PLANT WITHIN A PLANT Low Volume High Variety High Skill High Volume Low Variety Low Skill
  18. 18. CAPACITY FLEXIBILITY  The means of having the ability to rapidly increase or decrease production levels, or to shift production capacity quickly from one product service to another.  This is achieved through: 1. Flexible Plants 2. Flexible Processes 3. Flexible Workers
  19. 19. CAPACITY ANALYSIS  Considerations in capacity change requires: 1. Maintaining System Balance- Balance between output and input of different stages. 2. Frequency Of Capacity Additions- Frequent and Infrequent. 3. Use of External Capacity- Sharing capacity or no addition at all.
  20. 20. DETERMINING CAPACITY REQUIREMENTS  Capacity requirement is essential for every business.  The determination of the units is done by: 1. Using forecasting techniques for predicting Sales for individual product in a product line. 2. Calculate equipment and labour requirements to meet product line forecasts. 3. Project labour and equipment availabilities according to planning. Also, capacity in excess of demand is kept for precaution- Capacity Cushion.
  21. 21. DETERMINING CAPACITY REQUIREMENTS: Example. Stewart company produces two type of salad dressings. They are available in a plastic bottle with a single serving bag. The brands are:  PAUL’s  NEWMAN’s 2010 2011 2012 PAUL’s Bottles(000s) Bags (000s) 60 100 100 200 150 300 NEWMAN’s Bottles(000s) Bags (000s) 75 200 85 400 95 600
  22. 22. DETERMINING CAPACITY REQUIREMENTS: Example. Total Forecast:  If, capacity is 450000 per year, then 135,000 bottles will take 135/450= 0.9 machines.  Similarly, for bags, 1,250,000 per capacity is available, then for 300 bags it becomes 1.2 machines. 2010 2011 2012 Bottles (000s) Bags (000s) 135 300 185 600 245 900
  23. 23. DETERMINING CAPACITY REQUIREMENTS: Example.  Now, if 2 operators are required for bottle making and 3 operators for bags, the equations comes as: 0.9 bottle machine x 2 operators = 1.8 op. 1.2 bag machines x 3 operators = 3.6 op.  This is further balanced and operated in excess, which is used as the cushion capacity.
  24. 24. DECISION TREE  A decision tree is a schematic representation of the alternatives available to a decision maker and their possible consequences.  The term gets its name from the treelike appearance of the diagram.  They are particularly useful for analyzing situations that involve sequential decisions.
  25. 25.  Square nodes denote decision points, and circular nodes denote chance events.  Branches leaving square nodes represent alternatives; branches leaving circular nodes represent chance events.
  26. 26.  After the tree has been drawn, it is analyzed from right to left; that is, starting with the last decision that might be made.  For each decision, choose the alternative that will yield the greatest return (or the lowest cost).
  27. 27. DECISION TREE  EXAMPLE: A manager must decide on the size of a video arcade to construct. The manager has narrowed the choices to two: large or small. Information has been collected on payoffs, and a decision tree has been constructed.  The decision tree is analyzed to find out which initial alternative (build small or build large) should be chosen in order to maximize expected monetary value.
  28. 28. DECISION TREE
  29. 29. DECISION TREE  The dollar amounts at the branch ends indicate the estimated payoffs if the sequence of chance events and decisions that is traced back to the initial decision occurs.  For example, if the initial decision is to build a small facility and it turns out that demand is low, the payoff will be $40 (thousand).  Similarly, if a small facility is built, demand turns out high, and a later decision is made to expand, the payoff will be $55 (thousand).  The figures in parentheses on branches leaving the chance nodes indicate the probabilities of those states of nature.  Hence, the probability of low demand is .4, and the probability of high demand is .6. Payoffs in parentheses indicate losses.
  30. 30. DECISION TREE  Analyze the decisions from right to left: 1. Determine which alternative would be selected for each possible second decision. For a small facility with high demand, there are three choices: do nothing, work overtime, and expand. Because expand has the highest payoff, you would choose it. Indicate this by placing a double slash through each of the other alternatives. Similarly, for a large facility with low demand, there are two choices: do nothing and reduce prices. You would choose reduce prices because it has the higher expected value, so a double slash is placed on the other branch.
  31. 31. DECISION TREE 2. Determine the product of the chance probabilities and their respective payoffs for the remaining branches: Build small Low demand = .4 ($40) = $16 High demand = .6 ($55) = $33 Build large Low demand = .4 ($50) = $20 High demand = .6 ($70) = $42 3. Determine the expected value of each initial alternative: Build small $16 + $33 = $49 Build large $20 + $42 = $62 Hence, the choice should be to build the large facility because it has a larger expected value than the small facility.
  32. 32. SERVICE CAPACITY PLANNING  Service capacity is different to manufacturing capacity planning and facility sizing.  The variables which are critical in service are: 1. Time 2. Location 3. Volatality of Demand.
  33. 33. TIME  Unlike goods,services cannot be stored for later use.  Managers must consider time as one of their supplies.  The capacity must be available to produce a service when it is needed.
  34. 34. LOCATION  The service capacity must be located near the customer.  The capacity to deliver a service must first be distributed to the customer(either physically or through some communications medium), then the service must be delivered.
  35. 35. VOLATALITY OF DEMAND  Volatility of demand on a delivery system is much higher than on a manufacturing production system. 1. Services cannot be strored 2. Customers interact directly with the production system 3. Directly affected by consumer behavior
  36. 36. CAPACITY UTILIZATION AND SERVICE QUALITY  Planning capacity levels for services must consider day-to-day relationship between service utilization and service quality.
  37. 37. CAPACITY UTILIZATION AND QUALITY Relationship between Rate of Service Utilization (ρ) and Service Quality.
  38. 38. HOSPITAL EMERGENCY ROOMS AND FIRE DEPARTMENTS
  39. 39. COMMUTER TRAINS
  40. 40. STADIUM AND PERFORMANCE SELLOUTS
  41. 41. Thanks! Have a nice evening ahead!

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