Capacity Management free essay sample

Customer Demands DEMAND MANAGEMENT Costs: †¢ building plants †¢ operating plants Tactics Technological Change: †¢ rate (including breakthroughs) †¢ direction Control 2  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 5 http://factory -physics. com  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com Capacity Management Issues Volume: †¢ relative to demand †¢ safety capacity Predictions and Assumptions (cont. ) Competition: †¢ likely behavior †¢ anticipated reactions Timing: †¢ lead or follow demand †¢ relative to process technology changes Suppliers: †¢ costs †¢ availability †¢ partnering/contracts Configuration: †¢ spatial distribution †¢ vendoring †¢ layout Flexibility: †¢ volume (scalability) †¢ mix (flexibility)  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 3 http://factory -physics. com  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 6 http://factory -physics. com 1 Strategic Capacity Planning Market Share: †¢ how much of total market to aim for? †¢ effect on competitors Market Share Calculation (cont. ) Example: Suppose capacity costs $1/yr for each unit of productive capacity and lost sales result in $3 per unit. Then Timing: †¢ lead †¢ match †¢ follow cs ? c o 3 ? 1 = = 0. 67 cs 3 So we should choose capacity slightly above the mean forecast (which would correspond to the ratio 0. We will write a custom essay sample on Capacity Management or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page 5) Increments: †¢ †¢ †¢ †¢ process considerations economies of scale exposure to risk defensive value 7  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 Note: This is very rough, since cs and co may change based on how much capacity is installed (e. g. , economies of scale) and may be influenced by the future (e. g. , failure to meet demand now may affect future sales). But it gives a rough idea of whether we should aim for a large or small capacity cushion. 10  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com http://factory -physics. com Strategic Capacity Planning (cont. ) Type: †¢ matching technology to market †¢ flexibility Market Share Example Situation: In 1966 Zenith faced †¢ Industry sales for color TV’s had doubled each year for 3 years. †¢ Total demand greater than 5 million annually by 1966. †¢ †¢ †¢ †¢ †¢ Zenith had maintained a 20% market share. Capacity of 1 million/year (4,000/day) was stretched to limit. Industry demand expected to increase to 7 -10 million in next 2 years. Selling price of $370/unit. After tax profit rate of 7% of sales. Location: †¢ make or buy? †¢ expansion or new facility? †¢ global strategy Proposal: expand 2 existing plants and add new plant to bring capacity to 7,300 per day. New plant would cost $6 million and would have capacity of 2,100 per day. 8  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 11  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com http://factory -physics. com Market Share Calculation Notation: †¢ cs = cost per unit short (e. g. , lost sales) †¢ co = cost per unit over (e. g. , wasted capacity) Market Share Example (cont. ) Analysis: cs = 2,100 ? $370 ? 250 ? 0. 07 = $13,597,500 per year annual profit from new plant annual cost of new plant co = $6,000,000 ? Capacity should be added to have roughly 90% probability of being able to meet 1968 demand. This means capacity of something over 9,000 sets per day. So, proposed increase and then some would ap pear to make sense. Problem: implicitly assumes uniform distribution of demand. Fails to consider competition. 9  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 12  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. Capacity Timing Lead Demand: †¢ create â€Å"capacity cushion† planned underutilization †¢ accommodate surges in demand †¢ attract new business take market share from competitors †¢ likelihood of falling short roughly equal to likelihood of having too much capacity †¢ could require OT, extra shifts, scrambling, etc. to make up difference †¢ †¢ †¢ †¢ negative capacity cushion conservative with regard to forecast assures high utilization, higher return on investment But, can lead to erosion of market share http://factory -physics. com capacity capacity capacity Developing a Capacity Strategy Caveat: modeling/analysis can help, but can only be part of the picture, since we cannot forecast the future. time Basic Strategies: 1. Peak: don’t build until need develops. †¢ â€Å"safe† strategy †¢ but can cause synchronization with competition and high costs/risks 2. Countercyclical: add at lower point in business cycle when firm and competitors have excess capacity. †¢ riskier? †¢ reduced costs but can backfire Meet Demand: time Lag Demand: time 13  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 16 http://factory -physics. com  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 Economies of Scale Short-Term: In short-term, almost everything (labor, equipment, insurance, etc. ) is fixed: Developing a Capacity Strategy (cont. ) 3. Long Haul: match or lag demand, but on average not for short-term. †¢ easier to be right over long haul than in near term †¢ better planning 4. Follow the Leader:build when they build. †¢ prevents competition from gaining an advantage †¢ can backfire (e. g. , oil tanker purchases in 1970’s, 1973 war ? price increases ? conservation, falling demand). fixed cost + variable cost Unit cost = throughput fixed cost = + variable unit cost throughput so, short-term unit costs decrease with throughput. Intermediate-Term: In the intermediate-term, utilization of a resource depends on run lengths, so given changeover cost and run length of a particular product, unit cost can be expressed as: Unit cost = changeovercost + runningcost per unit units per run which is increasing in setup cost and decreasing in run length. 14  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 17  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com http://factory -physics. com Economies of Scale (cont. ) Long -Term: are functions of plant equipment. Equipment cost as a function o f the capacity can be approximated by Causes of Overbuilding Manufacturing Capacity Technological Factors: †¢ †¢ †¢ †¢ †¢ adding capacity in large increments economies of scale long lead times in adding capacity min efficient scale increasing over time changes in production technology Competitive Factors: †¢ †¢ †¢ †¢ large number of firms lack of credible market leaders entry of new competitors advantages of being an early mover K (C) = aC b where b is typically between 0. 6 and 1. Thus, cost per unit is: K( C) = aC b? 1 C Since b is usually less than one, this implies that unit cost tends to decrease with capacity. That is, larger plants are more efficien t than small ones. However, there are diseconomies of scale, such as material handling, communication, risk. Unit cost = Information Flow Factors: †¢ †¢ †¢ †¢ †¢ inflation of future expectations divergent assumptions or perceptions breakdown of market signaling structural change financial community pressures Structural Factors: †¢ †¢ †¢ †¢ †¢ †¢ significant exit barriers motivation from suppliers building credibility with customers integrated competitors effect of capacity share on market share effect of age/type of capacity on demand Governmental Factors: †¢ perverse tax incentives †¢ desire for indigenous industry †¢ pressures to increase/maintain employment Managerial Factors: 15  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 †¢ mgmt background and industry exp †¢ attitude toward different types of risk  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 18 http://factory -physics. com http://factory -physics. com 3 Integrating with Business Strategy Capacity as Strategic Weapon: †¢ supply can create demand (â€Å"invest and grow†) †¢ preemptive weapon (prevent smaller competitors from adding capacity) Traditional Approach Formulation: min cost capacity feasible solution min Total Equipment Cost subject to: r e(i) ? TH, for all stations i Location Decisions: †¢ move into geographic market †¢ transportation costs †¢ attractive locales to recruit talent Details: re (i) = m(i) ? TH te (i) m( i) ? TH ? t e( i) Leadtime Dimension: †¢ competing on quality/responsiveness requires capacity cushion 19  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 22  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com http://factory -physics. com Traditional vs. Modern View of Capacity 100 % Traditional Approach (cont. Provide basis for better optimization approach. Add machine at i* . 3. If CT feasible, stop. Else go to (2). 25  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 28  © Wallace J. Hopp, Mark L. Spearman, 1996, 2000 http://factory -physics. com http://factory -physics. com Other Capacity Dimensions Law (Buffering): Any manufacturing system with variability will have buffers in some combination of the following forms: 1. Inventory (and CT) 2. Capacity (low utilization, lost sales) 3. Time (long lead times) Implications: There are other ways to improve CT performance of a system.