IEOR 130 Methods of Manufacturing Improvement Practice Examination Problems Part I of Course Prof. Leachman Fall, 2017

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "IEOR 130 Methods of Manufacturing Improvement Practice Examination Problems Part I of Course Prof. Leachman Fall, 2017"

Transcription

1 IEOR 130 Methods of Manufacturing Improvement Practice Examination Problems Part I of Course Prof. Leachman Fall, The thickness of a film deposited on wafers at a particular process step is subject to statistical process control. The upper specification limit for the film thickness is 50 angstroms and the lower specification limit is 20 angstroms, i.e., wafers with film thickness more than 50 angstroms or less than 20 angstroms deposited on them are scrapped. At present, the process has considerable variability, with mean film thickness equal to 25 angstroms and standard deviation equal to 5 angstroms. (a) What kind of control chart(s) should be used to track this parameter? (b) What is the process performance index for this step? (c) Assume the only yield loss mechanism at this process step is out-of-spec film thickness. What is the yield of this process step? (d) To raise the yield of this step to 95%, what value for the process performance index must be achieved? 2. A production process is subject to defects. If the number of defects on a production unit exceeds USL, the unit is scrapped. The yield of the process averages Assume the only yield loss mechanisms are the defects. (a) What kind of control chart is most appropriate for this process? (b) Estimate the process performance index. (c) The upper control limit of the control chart is 100. Estimate USL. 3. The thickness of a film deposited on wafers at a particular process step is subject to statistical process control. The thickness is measured at five points on one wafer per lot. The upper control limit is 132 angstroms and the lower control limit is 96 angstroms. (a) What kind of control chart should be used to track this parameter? Assume in the following questions that this kind of chart is in use. 1

2 (b) What are the mean and standard deviation of the film thickness? (c) Assume the yield loss due to out-of-spec film thickness is 1 percent and assume all of this loss is from wafers whose film thickness exceeded the upper specification limit. What is the equivalent process performance index? (d) What is USL for this film thickness? 4. For a product with 300 gross die per wafer, stacked wafer maps of yield by die site have been studied. Considering only wafers believed to be free of yield excursions, the best observed yield is 90%. The average die yield for the product is 80%. (a) Determine baseline random and systemic mechanisms-limited yields for the product. (b) The die size is 0.5 square centimeters. What defect density is equivalent to the baseline random yield? (c) If the defect density in (b) were cut in half, what would be the improvement in average die yield for the product? (d) The following systematic yield-loss mechanisms have been identified: Mechanism Fraction of wafers Fraction of die loss on such wafers Edge losses Missing photo patterns (excluding edge die) Poly etch bridging (excluding edge die) Metal II particle excursions (excluding edge die) Metal I particle excursions (excluding edge die) Assume the last four mechanisms can be overlapping, i.e., the same die might experience poly etch bridging, missing photo patterns, and/or particle excursions. Edge die are excluded when figuring average losses from the other mechanisms, i.e., the above figures for the last four mechanisms express losses in addition to edge losses. How much systematic yield loss remains to be explained? 2

3 5. A simple manufacturing technology has three process steps. Each step is subjected to statistical process control procedures. The process capability and process performance indices are as follows: Step Cp Cpk (a) Assume the only yield loss mechanisms are violations of the specification limits at the three steps. What is the overall yield of the manufacturing technology? (b) Now suppose that in addition there is a yield loss mechanism of random defects. There is no inspection for such defects until testing after production is completed. Further, suppose the overall yield for a device with area equal to 0.5 sq cm fabricated using this manufacturing technology is 87.5%. What is the defect density equivalent to the random defect yield loss? 6. A simple manufacturing process consists of a sequence of four steps: Step Cpk Cp (a) Which step is in most urgent need of process improvement? If the process was well-centered at each step, which step would be in most urgent need of improvement? (b) Considering only the yield loss mechanisms underlying these process performance indices, estimate the yield of the manufacturing process. (c) The engineering department is considering several projects to reduce process variability as follows: Step 1 new / Required engineering hours

4 Rank the projects in order of decreasing return per expended engineering hour. 7. Two factories A and B make the same product in three manufacturing steps. Each step has an upper specification limit but no lower specification limit. Data on the process performance index (Cpk) for each of the steps at each factory is as follows: Step Fab A Fab B Suppose the only yield loss mechanisms are from exceeding the upper spec limits. Further, suppose yield losses at each step are independent. Assume there is 100% inspection after each step, and bad units are discarded before processing by the next step. (a) Explain why, for any of the steps above, the yield of the step may be well-estimated as Prob{Z < 3*Cpk} where Z is ~ N(0,1). (b) Estimate the overall yield at each factory. Which factory is doing better? (c) Suppose the first step involves a countable parameter of quality, and suppose USL for this step is 100. What is the upper control limit of an SPC chart for the first step in Fab A? (d) Suppose we could utilize the best step from each fab to make the product. How much better would the yield be? 8. The engineering management of a fabrication line is considering three projects to improve the process stability of certain manufacturing steps. (Stability in this case means the standard deviation of the process quality parameter for the step would be reduced.) Information about the current performance, estimated engineering effort and predicted performance of the steps after process improvement is as follows: Step Cpk new Required_engineering_man_hours (a) Estimate the percentage product cost reduction for each project and if all three projects are completed. State any assumptions you need to make. 4

5 (b) If the fab could only do one of the projects, which one should be done? If it could only do two, which ones should it do? Justify your answers. 9. The management of a factory is trying to sort out how much yield loss is coming from a stationary baseline distribution of defects vs. how much is coming from defect excursions and other systematic mechanisms of yield loss. A stacked wafer map is analyzed including only wafers believed to not be involved in any defect excursions. The best-yielding die site on the wafer map has a 65% yield. The number of 0.5 sq-cm dice printed on the wafer is 450. The average die yield over all wafers (including those involved in excursions) is 35%. (a) Calculate the baseline defect-limited yield and the underlying baseline defect density. (b) Management is considering an upgrade of the air flow system costing $1.5 million. Engineering tests have been performed that indicate that this upgrade can be expected to cut baseline particle contamination on the wafers by 20%. However, particle excursions do not seem to be abated by the improved air flow. Estimate the improvement in baseline defect-limited yield and in the overall die yield if this upgrade is undertaken. (c) Management also is considering investment in a $1.5 million inspection system enabling increased process monitoring so that excursions can be detected earlier and thereby reduce yield losses. Engineering analysis and experiments indicate that total systematic and excursion yield losses could be cut 20% by this investment. Assuming the air flow system is NOT upgraded, what overall die yield would result from implementation of this inspection system? If only $1.5 million is available to spend, which is a better expenditure for improving yield the air flow system upgrade, or the new inspection system? 10. A product with 400 die per wafer has an average die yield of 61% and a die area of 0.5 cm 2. The best die yield observed near the center of a wafer map is 82%. (This wafer map was made from wafers in lots not subject to excursions.) (a) Estimate the stationary random yield (when systematic losses are not present), and estimate the systematic mechanisms limited yield. (b) Determine the Poisson defect density equivalent to the stationary random yield. (c) The following systematic mechanisms have been identified: 5

6 Mechanism Fraction of wafers Fraction die loss Total yield loss Wafer edge losses Missing photo patterns (counting only losses not overlapping the edge losses) Particle excursions (counting all die containing fatal defects, including those die experiencing missing photo patterns and those die in the edge losses) How much systematic yield loss is occurring from mechanisms not listed above? (d) The following contributors to the baseline stationary random yield have been identified: Layer Defect density Fraction fatal (defects per cm 2 ) Metal Metal Poly What amount of fatal defect density is occurring that is not observed by the above three inspections? How much yield loss does that account for? 11. A product with 400 die per wafer has an average die yield of 62% and a die area of 0.5 cm 2. The best die yield observed near the center of the wafer map is 82%. (a) In-line inspections have been implemented at the Metal 1, Metal 2 and Poly layers, and the observed defects have been correlated with the wafer maps of die yield to estimate the fraction of observed defects that are fatal. The following results were obtained: Layer Defect density Fraction fatal (defects per cm 2 ) Metal Metal Poly What amount of fatal defect density is occurring that is not observed by the above three inspections? How much yield loss does that account for? (b) The following systematic yield loss mechanisms have been identified: Mechanism Fraction of wafers Fraction die loss Total yield loss Wafer edge loss

7 Missing photo patterns (excluding the edge loss) Particle excursions How much systematic yield loss is the result of mechanisms yet to be discovered? 12. In a large stacked wafer map of wafers printed with 1,000 die, the die site with the maximum observed yield has a yield equal to 85%. (a) Estimate the baseline defect-limited yield. (b) Suppose fatal baseline defect density is reduced by 0.05 per sq cm. Suppose the die size is 0.5 sq cm. Predict the new maximum observed yield. (c) The following systematic yield loss mechanisms have been identified: Mechanism Fraction of lots Fraction of wafers Fraction of die lost affected affected per lot affected per wafer affected Edge loss Particle excursions Poisoned vias (Note: These mechanisms are not mutually exclusive, i.e., multiple failure mechanisms may be present in the same die.) 13. A product with 400 die per wafer has an average die yield of 65% and a die area of 0.5 cm 2. The best die yield observed near the center of a wafer map is 85%. (This wafer map was made from wafers in lots not subject to excursions.) (a) Estimate the stationary random yield (when systematic losses are not present), and estimate the systematic mechanisms limited yield. (b) Determine the Poisson defect density equivalent to the stationary random yield. (c) Clustering of the random defects has been studied. It has been found that mean number of defects per die is 0.8 and the variance in the number of defects per die is 1.2. Revise the estimate of the random defect density accordingly. 7

8 (d) In-line inspections have been implemented at the Metal 1, Metal 2 and Poly layers, and the observed defects have been correlated with the wafer maps of die yield to estimate the fraction of observed defects that are fatal. The following results were obtained: Layer Defect density Fraction fatal (defects per cm 2 ) Metal Metal Poly What amount of fatal defect density is occurring that is not observed by the above three inspections? How much yield loss does that account for? 14. Rework is sometimes required at photolithography steps. Statistics on rework in recent shifts are as follows: Shift # # of wafers # of wafers processed reworked (a) During which shifts was photo rework in statistical control? (b) The photo engineer has determined that an adjustment to the photo machine can reduce rework. The adjustment requires 60 minutes to perform. The process time per lot is 30 minutes. The photo engineer has collected statistics on rework and has found that the probability of rework grows as a function of the number of lots processed since last adjustment. The probability of no rework on the n th lot processed after an adjustment is P(n) = n-1. Consider the following potential frequencies for adjustment: Once every 10 lots, once every 20 lots, once every 30 lots, once every 40 lots, or once every 50 lots. Which frequency maximizes photo capacity? Explain. 15. A wet bench consists of a series of tanks served by a robot arm. Two production lots (50 wafers total) form one batch that travels down the bench. The batch is dunked in each tank by the robot arm. One of the tanks contains sulfuric acid that strips an undesired film off the wafers. With repeated use, the acid bath contains more and more residue from previously stripped wafers, and there is increasing probability that the film on the wafers in the next batch may be inadequately stripped. An inspection step carried out after the wet bench step would detect this, in which case the batch must be re-worked. At some point the acid bath must be dumped and re- 8

9 poured with fresh acid; this involves one hour of down time to the wet bench as well as the expenses for new sulfuric acid and disposing of the old acid. The process time in the sulfuric acid tank is 30 minutes per batch, whether for a first-time batch or a re-worked batch. The wet etch engineer estimates the probability that rework is required is a linear function of bath usage: P(n) = 0.05*n, where n is the number of first-time batches processed since the acid bath was re-poured and P(n) is the probability that the n th batch must be re-worked. You may assume that with probability one a batch that is reworked will be successfully stripped of the undesired film on the second pass through the tank, and that reworking does not cause the acid bath to deteriorate. (a) Suppose our objective is maximum wet-bench capacity. What frequency of re-pour is best? (By frequency, we mean how many batches between re-pours of the sulfuric acid bath.) (b) Now suppose our objective is minimum cycle time. Assume the following data for the wet bench: m=1, ca = 1, ce = 1, the wet bench receives 250 lots per week (i.e., 125 batches per week, excluding rework), and the only down time is for re-pouring the acid bath. Now what frequency of re-pour is best? (Hint: You can calculate the availability and average rework rate as functions of the re-pour frequency. And be sure to include rework in utilization.) (c) Now suppose our objective is maximum profit. What factors should be taken into account to decide the best frequency of re-pour? What other data would you request in order to make this determination? 16. The overlay alignment of the exposure machine used in a particular manufacturing technology is difficult to control. After re-calibration of the machine, the first lot processed has zero probability of mis-alignment. The second lot processed has probability 0.02 of misalignment. The third lot has probability 0.02(2) = 0.04 of mis-alignment, the fourth lot has probability has probability 0.02(3) = 0.06, and so on. Each lot that is mis-aligned must be re-worked. Re-worked lots are manually aligned on the machine, so there is zero chance of mis-aligning a rework lot. Processing one lot through the machine takes 1 hour. It takes another 1 hour to process the lot through the machine if rework is required. To re-calibrate the machine takes 8 hours, during which time processing can not be performed. The exposure machine is the bottleneck of the manufacturing process. (a) Starting with a just-calibrated machine, assuming a continuous supply of work-in-process, and assuming no further re-calibration of the machine, provide a formula for the expected duration for the exposure machine to complete processing of n lots, including any required rework of those lots. You do not need to simplify the expression. 9

10 (b) Which frequency of re-calibration will maximize the long-run output rate of the exposure machine: re-calibrate every 5 lots, every 10 lots, every 25 lots, or every 50 lots? (Hint: use your formula from part (a) to express the output rate per calibration cycle.) (c) Assuming there is no idle time and assuming 1 hour is the theoretical time to process one lot, what is the expected OEE of the machine for the frequency of re-calibration you chose in part (b)? 17. A wet etching machine processes a batch of two 25-wafer lots. The lots are dunked in an acid batch, followed by a dunk in a rinse bath. The acid tank of a wet etching machine becomes increasingly dirty with each batch processed. As a result, there is an increasing chance of particles becoming lodged in the circuitry on the wafers within each batch that cannot be rinsed off. Starting with a fresh acid bath, the process engineer estimates that the fatal defect density increases by 0.35 per sq cm after every batch processed. That is, if the fatal defect density of a batch run in a fresh acid bath is D0 per sq cm, then the fatal defect density of the next batch will be D , and that for the next batch will be D , and so on. At some point, the acid bath should be dumped and re-poured; this takes 2 hours. Suppose the process time of a batch is one hour, and suppose the die size is 0.5 sq cm. Suppose the wet etching machine is very busy, i.e., there are almost always lots waiting to be wet-etched. (a) Suppose we re-pour the acid bath after every n batches. Provide a formula to estimate the average yield of the n batches between re-pours of the acid bath. (b) Consider three alternative frequencies for re-pouring the acid bath: after every 2 batches, after every 4 batches, or after every 6 batches. Which frequency would you recommend? Explain. (c) Suppose the fab product mix changes such that this wet etching machine now has considerable idle time. Qualitatively, how should the frequency be changed, i.e., should we dump the bath more often, less often, or no change? 18. The processing cycle for a diffusion furnace consists of three phases: load, run, and unload. During the load portion of the cycle, an operator transfers wafers from incoming lots into a boat accommodating 150 wafers. If the incoming lots include less than 150 wafers, the operator inserts dummy wafers to raise the total wafers in the boat up to 150. During the run portion of the cycle, the boat is mechanically inserted into the furnace, the wafers are cooked for a specified length of time, and then the boat is mechanically withdrawn from the furnace. During the unload portion of the cycle, the operator unloads the product wafers from the boat into lots to be sent to follow-on operations, and he/she unloads the dummy wafers for re-use in subsequent furnace runs as may be required. 10

11 For a particular furnace, the run portion of the cycle takes exactly 6 hours every cycle. The theoretical times to perform the load and unload portions of the cycle are 0.5 hours each, but sometimes the operators take longer to complete these tasks. The average load time is estimated to be 0.6 hours (and the average unload time also is 0.6 hours). Last week this furnace completed 20 process cycles and experienced 4.5 hours of down time. The average batch size was 5.7 lots (i.e., product wafers). (a) Estimate the utilization of total time, utilization of availability, and OEE of this furnace last week. Assume the factory is operated 24 hours per day, seven days per week. (b) Identify the two reasons that rate efficiency was less than 100% for this furnace. (c) The equipment vendor offers a modification to the furnace whereby the furnace would be equipped with dual boats instead of a single boat. If equipped with dual boats, the operator could load boat B while the furnace was running boat A. After the run on boat A was completed, the furnace could immediately start the run on boat B. In parallel with the run on boat B, the operator could unload boat A. When loading and unloading are conducted in parallel with processing, the furnace is said to be backloaded. If equipped with dual boats, what is the reduction in theoretical process time per cycle? (d) Assuming the same number of process cycles were run with the same average batch size, estimate the OEE and utilization of availability last week if the furnace had been equipped with dual boats and all batches could be backloaded. (e) Assuming the same number of process cycles were run with the same average batch size, estimate the reduction in cycle time last week if the furnace had been equipped with dual boats and all batches could be backloaded. Assume there are no alternative furnaces, i.e., this is the only one that can be used, and assume down time statistics and process time variability would be unchanged if dual boats are installed. Other data: c0 = 1, MTTR = 4.5, cr = 1.0, ca = 1, lot arrival rate = lots per hour. (f) Suppose the current revenue from one lot is $25,000 and is declining 25% per year. The current fab cycle time is 40 days. The remaining product lifetime is 3 years. Assuming last week s processing rate is maintained, estimate the revenue gain from installation of dual boats in the furnace. 19. A wafer fab runs a single process technology that includes three high current implant steps. Data concerning these three steps are as follows: 11

12 Parameter Theoretical Time (secs) Average Time (secs) Beam Setup Time, BSU Vent Time, VT Wafer Exchange Time, XT Pump-down time, PT Wheel Rev-up Time, RT Implant Time - step 1, IT Implant Time - step 2, IT Implant Time - step 3, IT There are two high current implant machines in the fab. For each machine, down time averages 6 hours per day and idle time averages 3 hours per day. The maximum load size per implant is 12 wafers. Assume the average load size also is 12 wafers. (a) Estimate the fab output rate. Assume line yield losses in the fab are negligible. (b) Estimate the OEE of the high current implant machines. Assume there are no quality efficiency losses for the high current implant machines. (c) The equipment vendor offers a modification to the implanters that will reduce the average beam setup time (BSU) to 60 seconds. Assuming the fab output rate is held constant, by how much will the idle time increase for each high current implanter? In this case, how will the OEE score change? (d) Now suppose high current implant is the bottleneck equipment type. Suppose the fab starts rate is raised just enough so that all of the time saved by reducing BSU is absorbed by processing more wafers per day. Now how will the OEE score change? 20. A fabrication plant includes a sophisticated etching machine purchased almost a year ago. The purchase agreement for the machine included a service contract lasting one year whereby technicians working for the machine vendor perform preventative maintenance and repairs on the machine. At present, a machine vendor s technician performs a weekly PM. The PM takes the machine down for 4 hours. When the machine breaks down, the down time averages 8 hours (including time for the technician to drive to the plant). Data on machine failures indicates that the time until failure from performance of PM is distributed as follows: Days since PM, t Fraction of breakdowns occurring on day t

13 The service contract is about to expire. The machine vendor offers to renew the service contract for one year at a fixed cost of $150,000. Alternatively, the plant could hire a local, on-call independent contractor charging $250 per hour to perform PMs or repairs. This contractor used to work for the vendor and is very knowledgeable about the machine. It is believed that the contractor could perform high-quality maintenance work just as quickly as the vendor s staff. (a) The machine vendor is currently performing weekly PMs. Estimate the availability of the machine. (b) What frequency of PMs would you recommend to maximize machine availability? (c) Estimate the availability if the frequency of PM was changed to follow your recommendation in (b). (d) Estimate the annual costs for maintenance of the machine if the plant terminates the service contract and instead utilizes the local independent contractor following the PM frequency you calculated in (b). Would you recommend renewing the service contract? Or hiring the local contractor? 21. A wet bench consists of a series of tanks served by a robot arm. Two production lots (50 wafers total) form one batch that travels down the bench. The batch is dunked in each tank by the robot arm. Batches move along the bench one after another; the minimum spacing of the batches is the longest time spent in any one tank. One of the tanks contains sulfuric acid that strips an undesired film off the wafers. With repeated use, the acid bath accumulates more and more residue from previously stripped wafers, so there is increasing probability that the film on the wafers in the next batch may be inadequately stripped. An inspection step carried out after the wet bench step would detect this, in which case the batch must be re-worked. At some point the acid bath must be dumped and re-poured with fresh acid. The minimum time between consecutive batches run on the bench is 30 minutes, regardless of whether the batches involved are first-time batches or batches being re-worked. Once it is decided to re-pour the acid bath, no 13

14 more batches can be input to the bench until the re-pour is complete. A re-pour involves one hour of down time to the whole wet bench. The wet etch engineer estimated that the probability that rework is required is a linear function of bath usage: P(n) = 0.03*n, where n is the number of first-time batches processed since the acid bath was re-poured and P(n) is the probability that the n th batch must be re-worked. You may assume that with probability one a batch that is reworked will be successfully stripped of the undesired film on the second pass through the bench, and that rework causes negligible deterioration of the acid bath. Suppose our objective is maximum wet-bench output. Consider the following alternative frequencies for re-pouring the acid bath: Once every 4 batches, once every 8 batches, once every 12 batches, or once every 16 batches. Given an unlimited supply of WIP, which frequency of repour would achieve the highest output rate? 22. A wet etching machine processes a batch of two 25-wafer lots. The lots are dunked in an acid batch, followed by a dunk in a rinse bath. The acid tank of the wet etching machine becomes increasingly dirty with each batch processed. As a result, there is an increasing chance of particles becoming lodged in the circuitry on the wafers within each batch that cannot be rinsed off. Starting with a fresh acid bath, the process engineer estimates that the fatal defect density increases by 0.01 per sq cm after every batch processed. That is, if the fatal defect density of a batch run in a fresh acid bath is D0 per sq cm, then the fatal defect density of the next batch will be D , and that for the next batch will be D , and so on. At some point, the acid bath should be dumped and re-poured; this takes 3 hours. Suppose the process time of a batch is one hour, and suppose the die size is 0.05 sq cm. Suppose the wet etching machine is very busy, i.e., there are almost always lots waiting to be wet-etched. (a) Suppose we re-pour the acid bath after every n batches. What is the average defect density across those n batches? (b) Consider three alternative frequencies for re-pouring the acid bath: after every 50 batches, after every 100 batches, or after every 150 batches. Which frequency would you recommend? Explain. (c) Suppose the fab product mix changes such that this wet etching machine now has considerable idle time. Qualitatively, how should the frequency be changed, i.e., should we dump the bath more often or less often? 23. A vacuum process machine currently equipped with a wet pump is being modified to incorporate a dry pump. The equipment maintenance department would like to set up a preventative maintenance (PM) schedule for the dry pump. The process machine currently experiences weekly PMs, monthly PMs, bi-monthly PMs, and quarterly PMs. The maintenance 14

15 department does not want to add any more frequencies of PMs because of the long requalification time. The maintenance department is wondering to which of the existing frequencies of PMs it is best to place maintenance of the dry pump. Data received from the dry pump vendor is as follows: Weeks of service Probability of failure To add the dry pump to an existing PM involves 4 hours of incremental down time. If the dry pump fails, the unscheduled down time to repair the pump and re-qualify the process machine for service takes 12 hours. (a) From the point of view of maximizing machine availability, which of the existing PM frequencies is best for the dry pump? (b) Suppose the incremental cost of a dry pump PM is $500, and if the dry pump fails, the cost of lost output and repair of the dry pump is $25,000. From the point of view of cost minimization, is the same PM frequency as in (a) best? If not, which frequency is best? 24. Three photolithography scanner machines in a particular fabrication plant experience rate efficiency losses because of substandard lamp intensity. This substandard lamp intensity also generates occasional rework. The photo engineer has determined that, with weekly cleaning of the mirrors forming the optical path inside the machine, the average lamp intensity (LI) can be raised from its current average value of 700 mw/sq cm to an estimated 770 mw/sq cm. In addition, the average photo rework rate is expected to decline from 10% to an estimated 7%. However, this cleaning effort would introduce an additional 1 hour of machine down time per week. 15

16 Data concerning theoretical process times on the scanner are as follows: AT = 50 seconds XT = 35 seconds MT = 2 seconds LI = 785 mw/sq cm There is no blading required. Two products are in production, each with one photo step: Product Exposure energy (EE) No. of exposures to cover wafer A 2800 mw-sec/sq cm 500 B 2000 mw-sec/sq cm 350 Data concerning last week s operation of the scanners is as follows: Total photo department machine hours: (3 machines)(168 hours) = 504 machine-hours Total available time: = 462 machine-hours Total wafers processed by scanner machines: Product No. of wafer operations No. of wafers completed (including rework) (excluding rework) A B (a) What was the availability (A) of the photo scanner machines last week? Estimate the utilization of total time (U). Estimate the utilization of availability (U/A). (b) Estimate the overall equipment efficiency (OEE) of the photo scanner machines last week. You may assume the actual values of AT, XT and MT were equal to their theoretical values. (c) Suppose weekly cleaning of the mirrors is implemented, and suppose the production rates of A and B are kept at 300 and 250 per week, respectively. Suppose further that last week s actual availability is a good estimate of the average availability of the photo machines before cleaning of the mirrors is implemented. Estimate the values of A, U, and U/A after the change is made. Qualitatively, what do you expect would happen to cycle times? (d) Suppose instead of keeping the same production rates for products A and B, the production rates of products A and B are scaled proportionately so that U/A would have the same value as it did in part (a). Estimate the new output rates of A and B, and estimate the new OEE in that case. Qualitatively, what do you expect would happen to cycle times? Is cleaning of the mirrors a good idea? 25. A wafer fabrication plant is manufacturing a single device whose area is 0.5 sq cm and whose fatal defect density according to the Seeds Model is 0.5 per sq cm. The device has a line yield of 100%. 16

17 It has been determined that the metalization process is a source of significant particles. It is possible to reduce this contamination if a special machine clean cycle is inserted into the process recipe. This extra clean cycle will reduce particle contamination, but it will increase the metalization process time. The Process Engineering Dept. would like to know if it is beneficial to introduce this special clean cycle. There are two metallization steps in the overall process flow for the device, each performed by the same machine type. It is estimated that, without the special clean cycle, the machine deposits 0.40 particles per sq cm per wafer pass, of which 20% are fatal. If the special clean cycle is added to the process recipe of each step, it is estimated that the particles deposited per wafer pass will drop to 0.30 per sq cm. The fab inputs 21,000 wafers of the device per 30-day month, which is just equal to the capacity of the bottleneck equipment. The average process time per wafer pass of the metalization machine is currently 0.05 hours, but if the special clean cycle is introduced, this time will rise to 0.06 hours. There are five metalization machines; they average 30% down time. The metalization machines are not the current fab bottleneck, but if they were, it is estimated that their minimum idle time would be 5%. (a) Express the die yield improvement as a multiplier on the current die yield. Estimate the die yield subsequent to implementation of the special clean cycle. (b) Estimate the fab wafer throughput subsequent to implementation of the special clean cycle. (c) Estimate the % increase (or decrease) in die output if the special clean cycle is implemented. (d) Find the lower limit on the amount of particle reduction resulting from the special clean cycle in order for implementation of the special clean cycle not to reduce die output. 17

PRACTICE PROBLEM SET Topic 1: Basic Process Analysis

PRACTICE PROBLEM SET Topic 1: Basic Process Analysis The Wharton School Quarter II The University of Pennsylvania Fall 1999 PRACTICE PROBLEM SET Topic 1: Basic Process Analysis Problem 1: Consider the following three-step production process: Raw Material

More information

DRIVING SEMICONDUCTOR MANUFACTURING BUSINESS PERFORMANCE THROUGH ANALYTICS

DRIVING SEMICONDUCTOR MANUFACTURING BUSINESS PERFORMANCE THROUGH ANALYTICS www.wipro.com DRIVING SEMICONDUCTOR MANUFACTURING BUSINESS PERFORMANCE THROUGH ANALYTICS Manoj Ramanujam Table of Contents 03... Introduction 03... Semiconductor Industry Overview 05... Data Sources and

More information

for higher reliability by lower costs

for higher reliability by lower costs Service Strategies for higher reliability by lower costs Joerg Recklies Director Engineering Infineon Dresden GmbH Content Todays Challenges Existing Strategies Reliability Centered Optimization / Review

More information

3.155J / 6.152J Micro/Nano Processing Technology TAKE-HOME QUIZ FALL TERM 2005

3.155J / 6.152J Micro/Nano Processing Technology TAKE-HOME QUIZ FALL TERM 2005 3.155J / 6.152J Micro/Nano Processing Technology TAKE-HOME QUIZ FALL TERM 2005 1) This is an open book, take-home quiz. You are not to consult with other class members or anyone else. You may discuss the

More information

IMPROVEMENT OF A MANUFACTURING PROCESS FOR SUSTAINABILITY USING MODELING AND SIMULATION Thesis

IMPROVEMENT OF A MANUFACTURING PROCESS FOR SUSTAINABILITY USING MODELING AND SIMULATION Thesis IMPROVEMENT OF A MANUFACTURING PROCESS FOR SUSTAINABILITY USING MODELING AND SIMULATION 4162 Thesis Submitted by: Pol Pérez Costa Student #: 7753145 Thesis Advisor: Qingjin Peng Date Submitted: April 3

More information

Customer Support: Leveraging Value of Ownership

Customer Support: Leveraging Value of Ownership Customer Support: Leveraging Value of Ownership Bernard Carayon SVP Customer Support WW Analyst Day, 30 September 2004 / Slide 1 Agenda! Customer Support main activities! Worldwide Organization and installed

More information

Report 1. B. Starting Wafer Specs Number: 10 Total, 6 Device and 4 Test wafers

Report 1. B. Starting Wafer Specs Number: 10 Total, 6 Device and 4 Test wafers Aaron Pederson EE 432 Lab Dr. Meng Lu netid: abp250 Lab instructor: Yunfei Zhao Report 1 A. Overview The goal of this lab is to go through the semiconductor fabrication process from start to finish. This

More information

Optimal network topology and reliability indices to be used in the design of power distribution networks in oil and gas plants *

Optimal network topology and reliability indices to be used in the design of power distribution networks in oil and gas plants * Optimal network topology and reliability indices to be used in the design of power distribution networks in oil and gas plants * R Naidoo and EJ Manning University of Pretoria, Pretoria, South Africa ABSTRACT:

More information

IEOR 130 Factory Floor Scheduling Prof. Robert C. Leachman May, 2017

IEOR 130 Factory Floor Scheduling Prof. Robert C. Leachman May, 2017 IEOR 130 Factory Floor Scheduling Prof. Robert C. Leachman May, 2017 1. Introduction The primary purpose of factory floor scheduling is to ensure the factory production plan is fulfilled. As described

More information

The Tri-Star Simulation Model

The Tri-Star Simulation Model The Tri-Star Simulation Model After Mark Redmond and his former colleague, Hal Brookings, finished a nice dinner at Mark s country club and a lengthy discussion of Hal s experiences with lean manufacturing,

More information

Getting the Best 300mm Fab Using the Right Design and Build Process. Presented on SEMI ITRS

Getting the Best 300mm Fab Using the Right Design and Build Process. Presented on SEMI ITRS Getting the Best 300mm Fab Using the Right Design and Build Process Presented on SEMI ITRS Agenda Introduction Objectives of Fab Design Design Process Overview From process flow to toolset Resource Modeling

More information

Total Productive Maintenance OVERVIEW

Total Productive Maintenance OVERVIEW Total Productive Maintenance OVERVIEW Aims and Objectives Target Audience : Senior Management Purpose of Module : To understand the need for TPM and the commitment required to achieve an effective system..

More information

2015 EE410-LOCOS 0.5µm Poly CMOS Process Run Card Lot ID:

2015 EE410-LOCOS 0.5µm Poly CMOS Process Run Card Lot ID: STEP 0.00 - PHOTOMASK #0- ZERO LEVEL MARKS Starting materials is n-type silicon (5-10 ohm-cm). Add four test wafers labeled T1-T4. T1 and T2 will travel with the device wafers and get all of the processing

More information

Increasing Your Competitiveness in PCB Assembly

Increasing Your Competitiveness in PCB Assembly Increasing Your Competitiveness in PCB Assembly This article offers a seven step model for analyzing and integrating production systems. This phased approach can reduce costs, improve on-time delivery,

More information

Notes for Production and Operations Management- I

Notes for Production and Operations Management- I Notes for Production and Operations Management- I Factors affecting Process Design Decisions Nature of product/service demand Degree of vertical integration Production Flexibility Degree of automation

More information

SPECIAL CONTROL CHARTS

SPECIAL CONTROL CHARTS INDUSTIAL ENGINEEING APPLICATIONS AND PACTICES: USES ENCYCLOPEDIA SPECIAL CONTOL CHATS A. Sermet Anagun, PhD STATEMENT OF THE POBLEM Statistical Process Control (SPC) is a powerful collection of problem-solving

More information

WHITE PAPER. spencermetrics LLC Three Giffard Way, Melville, NY p:

WHITE PAPER. spencermetrics LLC Three Giffard Way, Melville, NY p: WHITE PAPER MEASURE ANALYZE W p IMPROVE Operational Equipment Effectiveness spencermetrics CONNECT When you think of printing as the production of printed objects whether those objects are documents, labels,

More information

BA 3653: Assignment #1 (Due: Oct. 20, 2015) I. General Instructions

BA 3653: Assignment #1 (Due: Oct. 20, 2015) I. General Instructions BA 3653: Assignment #1 (Due: Oct. 20, 2015) I. General Instructions 1. Each group (or team) consists of 3~4 students (maximum 5 students) enrolled in the same section. The right table shows the deduction

More information

Online Course Manual By Craig Pence. Module 12

Online Course Manual By Craig Pence. Module 12 Online Course Manual By Craig Pence Copyright Notice. Each module of the course manual may be viewed online, saved to disk, or printed (each is composed of 10 to 15 printed pages of text) by students enrolled

More information

QUALITY ASSURANCE IN AN MDRD

QUALITY ASSURANCE IN AN MDRD QUALITY ASSURANCE IN AN MDRD MAINTENANCE AND PREVENTATIVE MAINTENANCE MDRD is a machine dependent department washers, pasteurizers, cart washer, sterilizer, ultrasonic, heat sealers, RO water systems All

More information

By: Adrian Chu, Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington November 12, 2009.

By: Adrian Chu, Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington November 12, 2009. OPT Report By: Adrian Chu, Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington 98195. November 12, 2009. The Goal Every manufacturing company has one goal to make

More information

KEMET Electronics Italia. December 7, 2011

KEMET Electronics Italia. December 7, 2011 Development of fb Battery Manufacturing Technologies Joint EC / European Green Cars Initiative Workshop 2011 Bruxelles 7 December 2011 December 7, 2011 1 Corporate Statistics Headquarters: Simpsonville,

More information

THE COMMANDER NAVY REGION, SOUTHWEST (CNRSW) HAZARDOUS MATERIALS (HAZMAT) OPERATIONS QUALITY ASSURANCE SURVEILLANCE PLAN (QASP) 20 June 2000

THE COMMANDER NAVY REGION, SOUTHWEST (CNRSW) HAZARDOUS MATERIALS (HAZMAT) OPERATIONS QUALITY ASSURANCE SURVEILLANCE PLAN (QASP) 20 June 2000 THE COMMANDER NAVY REGION, SOUTHWEST (CNRSW) HAZARDOUS MATERIALS (HAZMAT) OPERATIONS QUALITY ASSURANCE SURVEILLANCE PLAN (QASP) 20 June 2000 TABLE OF CONTENTS 1.0 INTRODUCTION 1 1.1 PURPOSE... 1 2.0 OVERVIEW.2

More information

4. Thermal Oxidation. a) Equipment Atmospheric Furnace

4. Thermal Oxidation. a) Equipment Atmospheric Furnace 4. Thermal Oxidation a) Equipment Atmospheric Furnace Oxidation requires precise control of: temperature, T ambient gas, G time spent at any given T & G, t Vito Logiudice 34 4. Thermal Oxidation b) Mechanism

More information

Measurement Systems Analysis

Measurement Systems Analysis Measurement Systems Analysis Components and Acceptance Criteria Rev: 11/06/2012 Purpose To understand key concepts of measurement systems analysis To understand potential sources of measurement error and

More information

Project Quality Management

Project Quality Management 1 Project Quality Management Unit 8 Eng.elsaka09@gmail.com Project Quality Management Includes the processes and activities of the performing organization that determine quality policies, objectives, and

More information

Proceedings of the 2012 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher, eds

Proceedings of the 2012 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher, eds Proceedings of the 0 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher, eds OPTIMAL BATCH PROCESS ADMISSION CONTROL IN TANDEM QUEUEING SYSTEMS WITH QUEUE

More information

Maintenance Contract Basics Webinar July 2010

Maintenance Contract Basics Webinar July 2010 Maintenance Contract Basics Webinar July 2010 Overview... 1 Objectives... 1 Assumptions... 1 Considerations... 2 Recommendations... 2 Processing Cycle... 2 Flowcharts... 3 Maintenance Contracts... 3 Create

More information

Plasma-Enhanced Chemical Vapor Deposition

Plasma-Enhanced Chemical Vapor Deposition Plasma-Enhanced Chemical Vapor Deposition Steven Glenn July 8, 2009 Thin Films Lab 4 ABSTRACT The objective of this lab was to explore lab and the Applied Materials P5000 from a different point of view.

More information

EE40 Lec 22. IC Fabrication Technology. Prof. Nathan Cheung 11/19/2009

EE40 Lec 22. IC Fabrication Technology. Prof. Nathan Cheung 11/19/2009 Suggested Reading EE40 Lec 22 IC Fabrication Technology Prof. Nathan Cheung 11/19/2009 300mm Fab Tour http://www-03.ibm.com/technology/manufacturing/technology_tour_300mm_foundry.html Overview of IC Technology

More information

Eclipse Production Management Software Training

Eclipse Production Management Software Training Eclipse Production Management Software Training Eclipse & Pathfinder Training Schedule Tuesday 8:30am 9:00am 10:20am - 10:30am 11:45am - 12:30pm 2:20pm - 2:30pm Introduction Training begins Break Lunch

More information

TenStep Project Management Process Summary

TenStep Project Management Process Summary TenStep Project Management Process Summary Project management refers to the definition and planning, and then the subsequent management, control, and conclusion of a project. It is important to recognize

More information

Justifying Simulation. Why use simulation? Accurate Depiction of Reality. Insightful system evaluations

Justifying Simulation. Why use simulation? Accurate Depiction of Reality. Insightful system evaluations Why use simulation? Accurate Depiction of Reality Anyone can perform a simple analysis manually. However, as the complexity of the analysis increases, so does the need to employ computer-based tools. While

More information

MTP_Final_Syllabus 2016_June 2018_Set 2

MTP_Final_Syllabus 2016_June 2018_Set 2 Paper 15 Strategic Cost Management and Decision Making DoS, The Institute of Cost Accountants of India (Statutory Body under an Act of Parliament) Page 1 Paper 15 - Strategic Cost Management and Decision

More information

SDD: Total Productive Maintenance REV1: 2014 January 31. Page 1 of 21. Step 1

SDD: Total Productive Maintenance REV1: 2014 January 31. Page 1 of 21. Step 1 Page 1 of 21 Page 2 of 21 Contents 1. Introduction... 3 2. Planned maintenance benefits... 4 3. Planned maintenance responsibilities... 5 3.1 The role of the production department... 6 3.2 The role of

More information

Total Cost of Operations TCO

Total Cost of Operations TCO Total Cost of Operations TCO Agenda Introduction Objectives Elements of TCO ABC Costing TCO in a working Fab Fab Cost Product Margin Building TCO Model Summary Introduction Total Cost of Operations is

More information

Chapter 11. Decision Making and Relevant Information Linear Programming as a Decision Facilitating Tool

Chapter 11. Decision Making and Relevant Information Linear Programming as a Decision Facilitating Tool Chapter 11 Decision Making and Relevant Information Linear Programming as a Decision Facilitating Tool 1 Introduction This chapter explores cost accounting for decision facilitating purposes It focuses

More information

Online Student Guide Types of Control Charts

Online Student Guide Types of Control Charts Online Student Guide Types of Control Charts OpusWorks 2016, All Rights Reserved 1 Table of Contents LEARNING OBJECTIVES... 4 INTRODUCTION... 4 DETECTION VS. PREVENTION... 5 CONTROL CHART UTILIZATION...

More information

Agilent Technologies

Agilent Technologies Η Supplier Performance Agilent Technologies Supplier Performance Technology Quality Responsiveness Delivery Cost Environment Agilent Restricted 2000 TABLE OF CONTENTS Introduction... 3 Technology... 4

More information

Making. MRP work. Vendors must address long-standing problems with capacity planning, lot sizes and lead-times

Making. MRP work. Vendors must address long-standing problems with capacity planning, lot sizes and lead-times Making MRP work Vendors must address long-standing problems with capacity planning, lot sizes and lead-times By Gregory W. Diehl & Aaron J. Armstrong November 2011 35 making mrp work Materials requirements

More information

How To Write A Flowchart

How To Write A Flowchart 1 Learning Objectives To learn how you transfer a device concept into a process flow to fabricate the device in the EKL labs You learn the different components that makes up a flowchart; process blocks,

More information

Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras

Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras Lecture - 37 Transportation and Distribution Models In this lecture, we

More information

Aluminium & Non-Ferrous Production Optimization Fast, Reliable, Efficient

Aluminium & Non-Ferrous Production Optimization Fast, Reliable, Efficient Optical Surface Inspection for Aluminium & Non-Ferrous Production Optimization Fast, Reliable, Efficient Leading the Way in Aluminium & Non-Ferrous Process Improvement BEYOND INSPECTION MORE Than Just

More information

HARVEST HAUL MODEL THE COST OF HARVESTING PADDOCKS OF SUGARCANE ACROSS A SUGAR MILLING REGION By G.R. SANDELL 1 and D.B.

HARVEST HAUL MODEL THE COST OF HARVESTING PADDOCKS OF SUGARCANE ACROSS A SUGAR MILLING REGION By G.R. SANDELL 1 and D.B. HARVEST HAUL MODEL THE COST OF HARVESTING PADDOCKS OF SUGARCANE ACROSS A SUGAR MILLING REGION By G.R. SANDELL 1 and D.B. PRESTWIDGE 2 1 BSES Limited, Mackay 2 CSIRO Sustainable Ecosystems, Brisbane gsandell@bses.org.au

More information

Utilization vs. Throughput: Bottleneck Detection in AGV Systems

Utilization vs. Throughput: Bottleneck Detection in AGV Systems Utilization vs. Throughput: Bottleneck Detection in AGV Systems Christoph Roser Masaru Nakano Minoru Tanaka Toyota Central Research and Development Laboratories Nagakute, Aichi 480-1192, JAPAN ABSTRACT

More information

Using Simulation in the Process Industries. Bennett Foster Sr. Consultant, DuPont Co.

Using Simulation in the Process Industries. Bennett Foster Sr. Consultant, DuPont Co. Using Simulation in the Process Industries Bennett Foster Sr. Consultant, DuPont Co. What s different about the Process Industries? Processes are often difficult (and/or expensive) to start and stop Relatively

More information

Implementing Inkless Wafer Sort. by: Mark Banke, Altera Corp. June 2006

Implementing Inkless Wafer Sort. by: Mark Banke, Altera Corp. June 2006 Implementing Inkless Wafer Sort by: Mark Banke, Altera Corp. June 2006 Implementing Inkless Wafer Sort Introduction Benefits - Why implement inkless wafer sort? Inkless process flow example Implementation

More information

Describing DSTs Analytics techniques

Describing DSTs Analytics techniques Describing DSTs Analytics techniques This document presents more detailed notes on the DST process and Analytics techniques 23/03/2015 1 SEAMS Copyright The contents of this document are subject to copyright

More information

- Rev 4 Date

- Rev 4 Date Product Safety Management Manual - Rev 4 Date 10.05.2013 - Revision Index Revision no Change description Date 0 Initial release 30.12.2008 1 Part identification guidelines for traceability 25.07.2009 included

More information

MIT Manufacturing Systems Analysis Lecture 1: Overview

MIT Manufacturing Systems Analysis Lecture 1: Overview 2.852 Manufacturing Systems Analysis 1/44 Copyright 2010 c Stanley B. Gershwin. MIT 2.852 Manufacturing Systems Analysis Lecture 1: Overview Stanley B. Gershwin http://web.mit.edu/manuf-sys Massachusetts

More information

A Hit-Rate Based Dispatching Rule For Semiconductor Manufacturing

A Hit-Rate Based Dispatching Rule For Semiconductor Manufacturing International Journal of Industrial Engineering, 15(1), 73-82, 2008. A Hit-Rate Based Dispatching Rule For Semiconductor Manufacturing Muh-Cherng Wu and Ting-Uao Hung Department of Industrial Engineering

More information

Ion Implantation Most modern devices doped using ion implanters Ionize gas sources (single +, 2+ or 3+ ionization) Accelerate dopant ions to very

Ion Implantation Most modern devices doped using ion implanters Ionize gas sources (single +, 2+ or 3+ ionization) Accelerate dopant ions to very Ion Implantation Most modern devices doped using ion implanters Ionize gas sources (single +, 2+ or 3+ ionization) Accelerate dopant ions to very high voltages (10-600 KeV) Use analyzer to selection charge/mass

More information

Lab #2 Wafer Cleaning (RCA cleaning)

Lab #2 Wafer Cleaning (RCA cleaning) Lab #2 Wafer Cleaning (RCA cleaning) RCA Cleaning System Used: Wet Bench 1, Bay1, Nanofabrication Center Chemicals Used: H 2 O : NH 4 OH : H 2 O 2 (5 : 1 : 1) H 2 O : HF (10 : 1) H 2 O : HCl : H 2 O 2

More information

PIP REEE002 Reliability Indicators for Rotating Machinery

PIP REEE002 Reliability Indicators for Rotating Machinery June 2016 Machinery PIP REEE002 Reliability Indicators for Rotating Machinery PURPOSE AND USE OF PROCESS INDUSTRY PRACTICES In an effort to minimize the cost of process industry facilities, this Practice

More information

World Class Manufacturing SMED. Single-Minute Exchange of Die

World Class Manufacturing SMED. Single-Minute Exchange of Die World Class Manufacturing Single-Minute Exchange of Die After completing this chapter you will understand Meaning and Basic of. History of Purpose of. Basic steps Implementation. Process of Benefits of

More information

Govt. Contracting, Dynamics 365 Operations Implementing Dynamics 365 Operations for Govt. Contractors PVBS

Govt. Contracting, Dynamics 365 Operations Implementing Dynamics 365 Operations for Govt. Contractors PVBS Implementing Dynamics 365 Operations for Govt. Contractors PVBS Contents Background... 4 Setups... 4 Project Management and Accounting... 4 Ledger Posting Setup... 4 Category Groups... 4 Category Group

More information

TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM QM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM

TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM QM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM TQM QM TQMAccounting TQM for TQM TQM TQM TQM TQM TQM QM TQM TQM TQM Quality TQM TQM TQM TQM TQM TQM TQM TQM TQM T T QM TQMwith TQMNonfinancial TQM TQM TQM TQM Measures: A Simple No-Cost Program for the QM

More information

Deep Silicon Etching An Enabling Technology for Wireless Systems Segment By Carson Ogilvie and Joel Goodrich Commercial Product Solutions

Deep Silicon Etching An Enabling Technology for Wireless Systems Segment By Carson Ogilvie and Joel Goodrich Commercial Product Solutions Deep Silicon Etching An Enabling Technology for Wireless Systems Segment By Carson Ogilvie and Joel Goodrich Commercial Product Solutions Abstract The recent installation of a new etch tool, the Surface

More information

Design Guide: Impact of Quality on Cost Economics for In-circuit and Functional Test.

Design Guide: Impact of Quality on Cost Economics for In-circuit and Functional Test. Design Guide: Impact of Quality on Cost Economics for In-circuit and Functional Test USA, CANADA, MEXICO, MALAYSIA, CHINA, UNITED KINGDOM Contact locations: www.circuitcheck.com Copyright Circuit Check,

More information

DEVELOPMENT OF TPM IMPLEMENTATION PLAN IN SWITCHGEAR & ENGINEERING COMPANY

DEVELOPMENT OF TPM IMPLEMENTATION PLAN IN SWITCHGEAR & ENGINEERING COMPANY Proceedings of the International Conference on Mechanical Engineering 2003 (ICME2003) 26-28 December 2003, Dhaka, Bangladesh ICME03-AM-32 DEVELOPMENT OF TPM IMPLEMENTATION PLAN IN SWITCHGEAR & ENGINEERING

More information

Cpk. X _ LSL 3s 3s USL _ X. Cpk = Min [ Specification Width Process Spread LSL USL

Cpk. X _ LSL 3s 3s USL _ X. Cpk = Min [ Specification Width Process Spread LSL USL Cpk A Guide to Using a Process Capability Index Cpk = Min [ USL _ X, X _ LSL ] 3s 3s Specification Width Process Spread LSL X USL The following information is provided by the Technology Issues Committee

More information

Continuous Improvement Toolkit

Continuous Improvement Toolkit Continuous Improvement Toolkit Lean Measures Managing Risk PDPC Pros and Cons Importance-Urgency Mapping RACI Matrix Stakeholders Analysis FMEA RAID Logs Break-even Analysis Cost -Benefit Analysis PEST

More information

SUPPLIER QUALITY MANUAL Customer Specific Requirements

SUPPLIER QUALITY MANUAL Customer Specific Requirements Quality Management System Even though it is preferred by AMC that all suppliers become registered to ISO/TS 16949, suppliers at a minimum will be expected to be third party registered to ISO 9001 by an

More information

Asphalt Plant Level 1. Module 3 - Sampling Bituminous Paving Mixtures. Release 10 4/19/

Asphalt Plant Level 1. Module 3 - Sampling Bituminous Paving Mixtures. Release 10 4/19/ Release 10 4/19/2016 3-1 This module covers FM 1-T 168 Sampling Bituminous Paving Mixtures. Loose mix samples are obtained from the haul truck at the asphalt plant. These samples are used to prepare gyratory

More information

CHAPTER 1 INTRODUCTION

CHAPTER 1 INTRODUCTION 1 CHAPTER 1 INTRODUCTION 1.1 MANUFACTURING SYSTEM Manufacturing, a branch of industry, is the application of tools and processes for the transformation of raw materials into finished products. The manufacturing

More information

TOTAL PRODUCTIVE MAINTENANCE, THE SIX BIG LOSSES, AND OVERALL EQUIPMENT EFFECTIVENESS AND THE TPM VISION

TOTAL PRODUCTIVE MAINTENANCE, THE SIX BIG LOSSES, AND OVERALL EQUIPMENT EFFECTIVENESS AND THE TPM VISION TOTAL PRODUCTIVE MAINTENANCE, THE SIX BIG LOSSES, AND OVERALL EQUIPMENT EFFECTIVENESS AND THE TPM VISION TOTAL PRODUCTIVE MAINTENANCE Total productive maintenance (TPM) was first defined in 1971 by the

More information

The Impact of Agile. Quantified.

The Impact of Agile. Quantified. The Impact of Agile. Quantified. Agile and lean are built on a foundation of continuous improvement: You need to inspect, learn from and adapt your performance to keep improving. Enhancing performance

More information

Accounting Information Systems, 12e (Romney/Steinbart) Chapter 14 The Production Cycle

Accounting Information Systems, 12e (Romney/Steinbart) Chapter 14 The Production Cycle Accounting Information Systems, 12e (Romney/Steinbart) Chapter 14 The Production Cycle 1) The AIS compiles and feeds information among the business cycles. What is the relationship between the revenue

More information

Welcome to the course, Evaluating the Measurement System. The Measurement System is all the elements that make up the use of a particular gage.

Welcome to the course, Evaluating the Measurement System. The Measurement System is all the elements that make up the use of a particular gage. Welcome to the course, Evaluating the Measurement System. The Measurement System is all the elements that make up the use of a particular gage. Parts, people, the environment, and the gage itself are all

More information

Are you in control of process safety? Basis of safety assurance can provide the answer

Are you in control of process safety? Basis of safety assurance can provide the answer Loss Prevention Bulletin 231 June 2013 23 Safety practice Are you in control of process safety? Basis of safety assurance can provide the answer Phil Eames Eur Ing BSc CEng FIChemE Eames Risk Consulting

More information

Portable Appliance Testing

Portable Appliance Testing Portable Appliance Testing 1. PURPOSE 1.1 The purpose of this procedure is to provide a standardised system for the inspection and testing of portable electrical appliances throughout the University, to

More information

Lean for Service. Presented by: Dennis Sowards, Quality Support Services, Inc

Lean for Service. Presented by: Dennis Sowards, Quality Support Services, Inc Lean for Service Presented by: Dennis Sowards, Quality Support Services, Inc. 480 835-1185 dennis@yourqss.com DENNIS SOWARDS 15 years experience in mechanical contracting 35 years helping companies improve

More information

Process Mapping. You cannot improve a process until everyone agrees on what the process is.

Process Mapping. You cannot improve a process until everyone agrees on what the process is. Process Mapping You cannot improve a process until everyone agrees on what the process is. 1 Topics I. What is a Process Map? II. III. IV. Types of Process Maps A. Process Flow Chart B. SIPOC Diagram C.

More information

450mm Metrology and Inspection: The Current State and the Road Ahead. Rand Cottle (CNSE), Nithin Yathapu (GF), Katherine Sieg (Intel)

450mm Metrology and Inspection: The Current State and the Road Ahead. Rand Cottle (CNSE), Nithin Yathapu (GF), Katherine Sieg (Intel) 450mm Metrology and Inspection: The Current State and the Road Ahead Rand Cottle (CNSE), Nithin Yathapu (GF), Katherine Sieg (Intel) Outline Program Update Demonstration Testing Method (DTM) Equipment

More information

Chapter 14. Waiting Lines and Queuing Theory Models

Chapter 14. Waiting Lines and Queuing Theory Models Chapter 4 Waiting Lines and Queuing Theory Models To accompany Quantitative Analysis for Management, Tenth Edition, by Render, Stair, and Hanna Power Point slides created by Jeff Heyl 2008 Prentice-Hall,

More information

Assignment 10 (Solution) Six Sigma in Supply Chain, Taguchi Method and Robust Design

Assignment 10 (Solution) Six Sigma in Supply Chain, Taguchi Method and Robust Design Assignment 10 (Solution) Six Sigma in Supply Chain, Taguchi Method and Robust Design Dr. Jitesh J. Thakkar Department of Industrial and Systems Engineering Indian Institute of Technology Kharagpur Instruction

More information

Technical Memorandum #4 Analysis of the Performance Guarantee Component of the Siemens Contract

Technical Memorandum #4 Analysis of the Performance Guarantee Component of the Siemens Contract Technical Memorandum #4 Analysis of the Performance Guarantee Component of the Siemens Contract Raftelis Financial Consultants, Inc. (RFC) was engaged by the City of Jackson (City) to review and analyze

More information

COPYRIGHTED MATERIAL OVERVIEW OF THE THEORY OF CONSTRAINTS DEFINITIONS FOR THE OPERATIONAL ASPECTS OF THE THEORY OF CONSTRAINTS

COPYRIGHTED MATERIAL OVERVIEW OF THE THEORY OF CONSTRAINTS DEFINITIONS FOR THE OPERATIONAL ASPECTS OF THE THEORY OF CONSTRAINTS 1 OVERVIEW OF THE THEORY OF CONSTRAINTS Every now and then, a completely new idea comes along that can be described as either refreshing, disturbing, or both. Within the accounting profession, the theory

More information

PLANNING AND CONTROL FOR A WARRANTY SERVICE FACILITY

PLANNING AND CONTROL FOR A WARRANTY SERVICE FACILITY Proceedings of the 2 Winter Simulation Conference M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds. PLANNING AND CONTROL FOR A WARRANTY SERVICE FACILITY Amir Messih Eaton Corporation Power

More information

Process Capability Studies

Process Capability Studies Definition The quality of a production process is subject to certain fluctuations. What are known as capability indexes are calculated so that these processes can be assessed, with a broad distinction

More information

Portable Appliance Testing

Portable Appliance Testing OHSS: Guidance 111.1 Portable Appliance Testing Portable Appliance Testing Contents Scope... 3 Legislation and Best Practice Guidance... 3 Fixed Electrical Installation... 4 Types and Classifications of

More information

Performance audit report. New Zealand Transport Agency: Information and planning for maintaining and renewing the state highway network

Performance audit report. New Zealand Transport Agency: Information and planning for maintaining and renewing the state highway network Performance audit report New Zealand Transport Agency: Information and planning for maintaining and renewing the state highway network Office of the Auditor-General PO Box 3928, Wellington 6140 Telephone:

More information

Proficy * Plant Applications. GE Intelligent Platforms. Plant Performance Analysis and Execution Software

Proficy * Plant Applications. GE Intelligent Platforms. Plant Performance Analysis and Execution Software GE Intelligent Platforms Proficy * Plant Applications Plant Performance Analysis and Execution Software As a production manager, the key to unlocking the full performance potential of your manufacturing

More information

Turn-key Production System for Solar Cells

Turn-key Production System for Solar Cells SOLARE Turn-key Production System for Solar Cells 02 Innovations for New Technologies provides technology solutions for both crystalline and thin-film highperformance solar cell platforms. Our production

More information

INDUSTRIAL ENGINEERING

INDUSTRIAL ENGINEERING 1 P a g e AND OPERATION RESEARCH 1 BREAK EVEN ANALYSIS Introduction 5 Costs involved in production 5 Assumptions 5 Break- Even Point 6 Plotting Break even chart 7 Margin of safety 9 Effect of parameters

More information

LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS

LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS Advances in Production Engineering & Management 4 (2009) 3, 127-138 ISSN 1854-6250 Scientific paper LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS Ahmad, I. * & Al-aney, K.I.M. ** *Department

More information

Ramping up at warp speed

Ramping up at warp speed Echo/Cultura/Getty Images F E B R UA RY 2016 Semiconductors Ramping up at warp speed Fabs can reduce expansion costs and streamline ramps through a new approach that emphasizes datadriven decision making

More information

Surface Preparation Challenges in Crystalline Silicon Photovoltaic Manufacturing

Surface Preparation Challenges in Crystalline Silicon Photovoltaic Manufacturing Surface Preparation Challenges in Crystalline Silicon Photovoltaic Manufacturing Kristopher Davis 1,3, Andrew C. Rudack 2,3, Winston Schoenfeld 1,3 Hubert Seigneur 1,3, Joe Walters 1,3, Linda Wilson 2,3

More information

Call Center Benchmark

Call Center Benchmark Call Center Benchmark United States In-house/Insourced Call Centers Report Contents Benchmarking Overview Page 2 KPI Statistics and Quartiles Page 8 Benchmarking Scorecard and Rankings Page 15 Detailed

More information

Defect report-step ABC. Figure 1: YieldManager s enhanced automation framework embeds decision making processes through data analysis

Defect report-step ABC. Figure 1: YieldManager s enhanced automation framework embeds decision making processes through data analysis DATASHEET YieldManager Customizable yield management for IC manufacturers Overview For semiconductor foundries and IDMs that must maintain high yield for their products and real-time identification of

More information

PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen. PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant

PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen. PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen

More information

Productivity Improvement Techniques in Apparel Manufacturing Industry

Productivity Improvement Techniques in Apparel Manufacturing Industry Productivity Improvement Techniques in Apparel Manufacturing Industry Introduction In this article, a study was conducted in the sewing section under a garment manufacturing company. We have mentioned

More information

Lecture 22: Integrated circuit fabrication

Lecture 22: Integrated circuit fabrication Lecture 22: Integrated circuit fabrication Contents 1 Introduction 1 2 Layering 4 3 Patterning 7 4 Doping 8 4.1 Thermal diffusion......................... 10 4.2 Ion implantation.........................

More information

Deeper. Deeper. Deeper. Deeper. Deeper. Deeper. What is the advantage of breaking a project down into tasks and sub-tasks?

Deeper. Deeper. Deeper. Deeper. Deeper. Deeper. What is the advantage of breaking a project down into tasks and sub-tasks? A 1 A 2 What is the advantage of breaking a project down into tasks and sub-tasks? Tasks are natural units of work, estimation, and assignment. What is the advantage of breaking down goals, over breaking

More information

Process Flow in Cross Sections

Process Flow in Cross Sections Process Flow in Cross Sections Process (simplified) 0. Clean wafer in nasty acids (HF, HNO 3, H 2 SO 4,...) --> wear gloves! 1. Grow 500 nm of SiO 2 (by putting the wafer in a furnace with O 2 2. Coat

More information

For Questions 1 to 6, refer to the following information

For Questions 1 to 6, refer to the following information For Questions 1 to 6, refer to the following information The Box-and-Whisker plots show the results of the quiz and test for QMS102 in Fall2010 Question 1. Calculate the mode for the quiz result of QMS102

More information

DuPont MX5000 Series

DuPont MX5000 Series DuPont MX5000 Series DATA SHEET & PROCESSING INFORMATION High Performance Multi-Purpose Polymer Film for MEMS Applications PRODUCT FEATURES/ APPLICATIONS Negative working, aqueous processable dry film

More information

Supplier Quality Manual

Supplier Quality Manual Supplier Quality Manual 1 1. Introduction Scope Purpose Application Implementation 2. Purchasing Expectations Terms and Conditions Engineering / Technical Support Customer Support Resources Pricing Consistent

More information

MODULE 2A GENERAL MANAGEMENT SYSTEM REQUIREMENTS

MODULE 2A GENERAL MANAGEMENT SYSTEM REQUIREMENTS MODULE 2A GENERAL MANAGEMENT SYSTEM REQUIREMENTS 2A.1 SCOPE (See ISO/IEC 17025:2005, Section 1) Laboratories shall meet all requirements of the ISO/IEC 17025:2005 International Standard and other AIHA-LAP,

More information

INTRODUCTION. Professional Accounting Supplementary School (PASS) Page 1

INTRODUCTION. Professional Accounting Supplementary School (PASS) Page 1 INTRODUCTION Under the new CPA certification program, management accounting has become very important on the CFE and it will therefore be critical for students to have a strong grounding in this area.

More information