text:
What do you retweet?
For those of you who don't use Twitter, let me briefly explain. Sometimes we who tweet will read a post and feel like sharing it, so we will "retweet" by copying it to our own followers. You might think that someone like Justin Bieber, who has some 23 million followers on Twitter, would have the most retweets, but he doesn't. People follow him on Twitter, but they're not particularly moved to share what he says.
Do you know the content of the tweets that people share or "retweet" the most? I read about it right here in the Deseret News. The most retweeted tweets are about God's love.
God's love.
"That's awesome," author Anita Stansfield said on "A Woman's View." "As messed up as our world is, to recognize that that is still there, the craving to know that God is still there. Wars, politics, crime, violence — but God is still there, and he loves you. That is amazing."
Some of the most retweeted tweets come from a woman named Joyce Meyer. I had never heard of her before, but I follow her now. Here are some of her most retweeted tweets of late:
"You don't need to know what tomorrow holds; all you need to know is the One who holds tomorrow."
"Every time you look in the mirror remember that God created you and that everything He creates is beautiful and good!"
"I'm not in charge of my reputation, God is."
"Part of trusting God is having unanswered questions. Get used to not knowing."
"Love can melt the hardest heart, heal the wounds of the broken heart and quiet the fears of the anxious heart."
"That tells me there's hope," Sen. Luz Robles shared on my radio program. "We get so caught up in the negative stuff. I made this new friend recently. Every morning I get a text from her, and they're religious in nature. They're all about God loving you as a woman. I'm not big into Twitter. It's hard when you're in politics. But I really look forward to those messages from this woman every morning saying, 'I love you. Continue serving the state so well. God bless you.' It's just wonderful."
Another one of the most retweeted evangelical leaders is Max Lucado. Here are some of his more popular tweets:
"Love is risky. The fear-filled cannot dream wildly. ... The worship of safety emasculates greatness."
"Before you serve, before you teach, before you encourage, you should pray."
"Look for ways to be a source of kindness."
"Feed your fears and your faith will starve. Feed your faith, and your fears will."
"Each one of us should lead a life stirring enough to start a movement."
"I just got a chill," Angel Shannon said. Angel is the life enrichment coordinator at Olympus Ranch Retirement Community in Murray. "That should be on the front page of the paper. It's uplifting and balancing. There are so many more important things than the things we read about in the news, like this. This is wonderful."
To the Deseret News' credit, I did read about this in the Deseret News. And here we are — talking about it. And I can't stop thinking about Max Lucado's comment. I should be leading a life stirring enough to start a movement. (I have to retweet that.)
What would that movement be? How could I help people to feel better about themselves, to see themselves for the beautiful beings they are, to focus on their strengths and not their weaknesses? How could I help them to set down the weapons they've been using to wound themselves and feel kindness and love toward themselves instead, just for a moment, or a lifetime? Can't we play jump rope and pay a mortgage in the same day, admire a round belly instead of just a flat one, say "I love you" with reckless abandon?
The tweets I will never retweet are the intellectually bullying tweets. Why would I want to spread that around? I feel sorry for those people. They need a few more tweets from Max Lucado, like this one:
"A man who wants to lead the orchestra must turn his back on the crowd."
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text:
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subset: commoncrawl


text:
Think these Red Sox games are meaningless? Think again. The team's offseason -- and its road map to reload -- could well depend on the outcome of the remaining 11 games in a season in which the Sox have long since been eliminated.
The Red Sox' recent "hot streak" has come with an unexpected consequence. After they seemingly cemented themselves in position to pick as high as sixth in the next draft, a few wins in Toronto and Tampa Bay have them at a bizarre crossroads.
Thursday night's dramatic 7-4 walkoff meltdown against the Rays represented a somewhat bitter pill for players and other members of the organization to swallow, of course, but it could be of considerable benefit to the team in the long term. After all, entering play on Thursday, the Sox had the 10th worst record in baseball. At 68-82 (.4533), they were almost indiscernibly "ahead" of the 67-81 (.4527) Royals.
The consequence of that difference of six-hundredths of a percentage point? Because the Pirates are locked in to pick No. 9 overall in next year's draft due to their failure to sign Stanford right-hander Mark Appel*, the Sox entered the day with the 10th-worst record in the majors -- an achievement that would leave them in line for the No. 11 overall pick in the draft.
However, Kansas City beat the White Sox on Thursday while the Sox blew apart at the seams in the ninth inning in Tampa Bay. That, in turn, improved the Royals' record to one game "better" than the Sox -- which, in turn, pushed the Sox back into the 10th pick in the draft.
Sound trivial? It's not. The implications, in fact, are potentially monumental. Most members of the Sox braintrust are monitoring vigilantly whether or not the team will have a top-10 pick in the draft.
Red Sox general manager Ben Cherington (in a conversation for "Down on the Farm" that will air on WEEI 93.7 FM and WEEI.com on Saturday at 8:30 am**) said that he's monitoring regularly where the Sox stand in the 2013 draft, but "not quite every day. Maybe others in the office check it every day. I do check it from time to time because it is a factor, it will be a factor in exactly where we end up [in the offseason]."
Suffice it to say that the significance of a top-10 pick extends beyond just the draft order.
The top 10 picks in the draft are "protected," meaning that a team need not forfeit such a pick if signing a free agent who receives a one-year qualifying offer (roughly $13 million) from the team with whom he spent all of 2012. Picks outside of the top 10 are not protected.
Say the Red Sox wanted to sign Josh Hamilton, a player who is certain to receive a one-year qualifying offer from the Rangers. If the Sox had the No. 10 pick in the first round of the 2013 draft, the selection would be protected. And so, the Sox only would give up their second-round selection -- a spot that likely would fall somewhere around the No. 45 overall selection in the draft -- for signing Hamilton.
But, if the Sox are sitting at the No. 11 spot in the draft, the pick is unprotected. Signing a free agent like Hamilton would cost the Sox the No. 11 overall pick.
The talent drop-off of picking No. 10 compared to, say, No. 45, would be considerable. The 48 players taken at the No. 10 overall spot have combined for 43 All-Star seasons. The next player who was taken at the No. 45 spot in the draft and earns an All-Star berth will be the first.
But the impact wouldn't necessary be felt just in the absence of a first-round pick.
Further complicating matters, the value of the top draft picks is potentially far more vast than just the pick. After all, each pick in the draft comes with a recommended slot figure that is used to define how much a team can spend on its overall draft without incurring penalties.
In 2012, for instance, the No. 10 overall pick came with a recommended slot bonus of $2.7 million. If a player taken at that spot is willing to sign for, say, $2 million, then the remaining $700,000 can be conferred without penalty upon a pick (or picks) in the later rounds as a means of scooping up players who sign in the draft for signability reasons. The Sox, for instance, were able to reallocate money from some of their draft picks to sign fourth-rounder Ty Buttrey for $1.3 million.
Put another way: The Sox are going to be in a position where there's no way that they will want to part with their first-round pick. In all likelihood, they will end up with their lowest pick in the draft since either 1994 (when they used the No. 12 overall pick on Nomar Garciaparra) or 1993 (when they tabbed Trot Nixon with the No. 7 pick). It is almost impossible to imagine the team passing on an opportunity for such a player in order to sign anyone in this year's free agent class.
"I think we've always been a little bit allergic to that," Cherington said of signing a free agent who would require sacrificing a first-round pick. "We have done it on occasion. We tended to do it in years when we had additional compensation picks coming back the other way, where we could kind of even it out to some extent.
"There's only so many lottery tickets you get. Each pick in the draft, every part of the spending pool you have is in some ways a lottery ticket. In order to hit big and bring impact talent into the organization, you've got to hit on some of those lottery tickets. The more you have, the better chance you have to hit on them.
"We want to increase our chances in any way possible to get the most we can out of the draft. That extends to the international market also. And so, we're certainly going to be calculated and cautious in giving up any advantage there. There very well may be times when it's justified to do that, to sign a free agent and give up a pick. It just depends on the circumstance, the player involved and where we are as a team."
Multiple major league sources have suggested that the Sox are unlikely to get involved in the Hamilton sweepstakes. The team just shed players (in Adrian Gonzalez and Carl Crawford) who are going to be paid handsomely in their post-prime years. Hamilton is on the wrong side of the 30 line, with a lengthy injury history, for a long-term commitment.
Still, there are other players in whom the Sox might have interest as free agents but who might receive qualifying offers from their current teams. Among them:
OF Michael Bourn (Braves)
RHP Edwin Jackson (Nationals)
RHP Hiroki Kuroda (Yankees)
1B Adam LaRoche (Nationals)
RHP Kyle Lohse (Cardinals)
C/1B Mike Napoli (Rangers)
1B/OF Nick Swisher (Yankees)
OF B.J. Upton (Rays)
If those players get qualifying offers, the Sox' willingness to pursue them literally could hinge on whether or not the Sox finish the year with one of the worst nine records -- and hence one of the top-10 picks -- in baseball.
"What we do know is that we're going to be picking up higher than we have in a while and we've got to take advantage of that in next year's draft," Cherington said. "Certainly, there's a difference between having a protected pick and not having one in terms of the level of how aggressive you are in going after certain free agents. That's certainly part of the calculus in terms of who to go after -- what you're giving up. If it's just money, it's one thing. If it's money plus a pick, it's another thing.
"There's no doubt that that will be factored in. It won't be the only factor, but it will be factored in," he continued. "The last thing we want to do is be picking that high, because obviously it's a reflection of what our major league team has done, but it is what it is this year and we've got to take full advantage of it."
The best way for the Sox to take the fullest advantage of their first losing season in 15 years? A spiral that would continue to push them up in the draft pecking order, something that would not only offer the shot at elite prospects but also maximize the team's flexibility in the free agent market.
It's not exactly the slogan that will fill up the stands during the final Fenway homestand ("Root, root, root against the home team!"), but nonetheless, the circumstances facing the Red Sox highlight an easily overlooked reality: These games matter -- just not, perhaps, for more customary reasons in September.
* The fact that the Pirates will have one of just 10 protected picks due to their failure to sign Appel is problematic. That is not to say that the Pirates' pick should not be protected, but instead points to the fact that a team with the 10th-worst record in the majors will be badly -- and perhaps unfairly -- punished by another team's failure to sign its pick. It would take only a slight modification of the CBA to protect the picks of the teams that finish the previous season with the 10 worst records in baseball, rather than providing protection just to the teams picking in the top 10.
** Cherington's discussion of the state of the Red Sox farm system, and the challenges created by the new collective bargaining agreement to the maintenance of a productive farm system, will air in "Down on the Farm" on Saturday from 8:30-9 a.m. on WEEI 93.7 FM and WEEI.com.
Dale, Michael and Jerry dig into the details of this draft for the Patriots with ESPN's Mike Reiss.
Giardi and Price discuss the Tom Brady appeal getting overturned and Roger Goodell's victory tour. The guys can't believe the victory lap and some of his behavior. The more you listen to him, the more frustrating his behavior becomes.
Giardi and Price break down how the teams in the AFC East altered their futures after the NFL Draft weekend.
Danny Ainge joins Glenn and Christian to explain the Celtics draft process; and he also discusses the trade rumors that permeated the night.
Mut is flying solo the last hour, but he's giving reaction and analysis as the Celtics draft a power forward out of France by the name of Guerschon Yabusele and getting some early grades for the Celtics
Mut and Kirk are talking more about the Celtics pick of Jaylen Brown and can't seem to find anyone who thinks it's a good pick or can make a case for why the Celtics took him third overall.
Christian recaps the Red Sox 6-2 loss to the Rangers.
Joe, Tim, and Lou talk with Red Sox shortstop Xander Bogaerts after his walk-off RBI single propelled the Red Sox past the White Sox 8-7.
Mut recaps the Red Sox 8-6 loss to the White Sox.
DJ and Pete continue to assess the season that was for the Bruins and look toward the future for the franchise and how they can improve.
DJ and Pete are together for the final Sunday Skate of the season. They get into their overall thoughts on the season, the Bruins keeping Claude Julien on as head coach and the end-of-season press conferences last week. They discuss the rebuild process, what the Bruins need and how they can obtain it. Plenty of callers have their own theories and opinions on all of these topics as well.
Butch is joined by two-thirds of the Sunday Skate show in DJ and Pete. The guys discuss the problems with Bruins including leadership and grit, who should stay and who should go and if Claude is to blame.
John, Gerry and Kirk open the show Monday discussing the Red Sox slide, as well as WEEI.com beat writer Rob Bradford electing to go to a Texas waterpark by himself.
A conversation about OJ Simpson still being in the Hall of Fame and Peter King's desire to keep character concerns out of HOF voting spurns a discussion about Darren Sharper and others who Minihane wants banned for life from the Hall.
It's quite the Sporty R. McKenzie 8am hour as the guys muscle through Red Sox trade possibilities.
OMF looks at the possibilities for Free Agency, specifically reports out of Canada about the possibility of Steven Stamkos and the Bruins.
We should be closing in on a Deflategate ruling soon, James Harrison will talk PED's on his terms, and $10,000 bongs?
Glenn has an Exclusive BBQ, and Lou whines about Friday's whines
We discuss the reports that Boston is on the short list of cities for both Kevin Durant in the NBA and Steven Stamkos in the NHL to potentially end up in. The chances aren't great but we discuss them and dream about it.
What was meant to be just a small portion of our show exploded in to a huge topic as we comment on and take your reaction to Ray Bourque's DUI arrest this past weekend, and the news that his BAC was 3 times the legal limit.
Boston has had enough of Clay Buchholz, but who else ran out of excuses here through the years?
Former Celtics General Manager Jan Volk joins Kirk Minihane for a discussion that any Celtics fan will love. Kirk and Jan talk about the legendary 85/86 Celtics and how the team was constructed and of course the decision to draft Len Bias and his tragic death.
Kirk Minihane sits down with John Tomase to talk about the current political landscape, John's desire to write about social issues, and of course Spygate is discussed.
Kirk Minihane is joined by one of his radio heroes, Artie Lange. They discuss everything from Artie's comedy career, his time with Howard Stern, his issues with drugs and prostitutes, and the comedy show to benefit slain Officer Ronald Tarentino Jr.
Ben, Russ & Alex recap the 4-0 loss the USMNT suffered to Argentina in the COPA America Centenario semifinal. Then they catch up with the EURO's, and recap if their predicted winners are still in the tournament.
Former Celtics General Manager Jan Volk joins Kirk Minihane for a discussion that any Celtics fan will love. Kirk and Jan talk about the legendary 85/86 Celtics and how the team was constructed and of course the decision to draft Len Bias and his tragic death.
This week we look back at the US Open.
It's quite the Sporty R. McKenzie 8am hour as the guys muscle through Red Sox trade possibilities.More from this show
Gerry Callahan has been invited to Donald Trump's upcoming Wednesday fundraiser. Should he go? Is Trump in trouble per the latest polls?More from this show
Kirk Minihane's Monday 'Headlines' including Bill Clinton's jogging list, Pope Francis apologizing in Italian, and Ray Bourque's DWI apologyMore from this show
Arcand talks about the Sox and their recent struggles on the mound while previewing the Sox/Rangers rubber match today. He also gets into the Celtics and their future.More from this show
The moody and opinionated Kirk Minihane stops by the station with Bradford and MLB.com's Ian Browne live in Arlington. Kirk, Rob and Ian discuss anything and everything.More from this show


text:
|Publication number
|Publication type
|Application number
|Publication date
|Oct 24, 2006
|Filing date
|May 18, 2005
|Priority date
|May 18, 2005
|Fee status
|Publication number
|Christopher Gould, Abeer Singhal
|Original Assignee
|Infineon Technologies Richmond, Lp
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (5), Non-Patent Citations (1), Referenced by (41), Classifications (12), Legal Events (6)
|External Links: USPTO, USPTO Assignment, Espacenet
The following co-pending and commonly assigned U.S. patent application has been filed on the same date as the present application. This application relates to and further describes other aspects of the embodiments disclosed in the present application and is herein incorporated by reference:
The fabrication of integrated circuits is a complex and expensive process which requires extremely tight tolerances and has little margin for error. A particular integrated circuit, such as a microprocessor, is fabricated according to a set of recipes which specifies the materials and processing steps which are necessary to result in a finished working product in accordance with the design specification. Typically, integrated circuits are fabricated in batch on wafers, wherein multiple copies of the particular integrated circuit are fabricated on a single wafer and later separated. Multiple wafers may be processed in parallel to achieve a desired manufacturing volume.
Each of the recipes further details the parameters of a particular process step, e.g. what processing machine as well as what control parameters for the particular processing machine should be used. Processing machines include chemical vapor deposition ("CVP") devices, chemical-mechanical-planarization ("CMP") devices, etching devices, such as wet etching or plasma etching devices, optical or electron beam, a.k.a., e-beam, imaging devices, such as scanning electron microscopes, etc. These processing machines perform their particular process on one or more wafers subject to a myriad to control parameters. Often, the same process/processing machine is repeatedly used using different recipes so as to fabricate the different parts/layers of the integrated circuits, all according to the overall design specification. For example, a typical integrated circuit will be processed through several different CVP, CMP, lithography and etch processes, each according to a particular recipe, to build up the many layers of transistors and interconnections which make up the integrated circuit. Control parameters, as provided in the recipe, for these processing machines, which may vary among different products, different processing machines and/or different processing stages, include, but are not limited to, duration of processing, processing rate, temperature, pressure, composition of processing materials/chemicals, and other variables.
In a manufacturing environment, a particular recipe will be performed over and over on batches of wafers, referred to as lots, with each processing machine being used to repeatedly perform the same process with the same or different control parameters, depending on the particular stage of production or, as will be described below, on the results of quality control inspections/measurements. In addition, the manufacturing facility may provide multiples of particular processing machines so as to allow the parallel processing of batches of wafers and boost production capacity. Further, the particular manufacturing facility may be used to produce many different types of integrated circuits, according to different recipes, i.e. using the same processing machines with the same or different control parameters. In actual production, some production runs of a given integrated circuit may require using more of the available manufacturing capacity than other runs, i.e. using more of the available processing machines to run processes in parallel if necessary. The amount of the available capacity which may be used may be dependent upon the production goals for the particular product during a particular time period and may vary from day to day. Further, production may be affected by the unavailability of processing machines, such as unavailability due to required maintenance or repair, expected or unexpected, the return of processing machines back into service, or other manufacturing events.
The control of workflow through the manufacturing process is referred to as process control. Process control refers to the overall concept of controlling the manufacturing processes, i.e. the implementation of a given set of recipes, to end up with functional products within the specified tolerances, i.e. functioning integrated circuits. The wafer fabrication process requires a high degree of precision, where one error can compromise an entire production, necessitating a high degree of process control.
Essentially, the object of process control is to repeatedly produce a product that falls within its design and operational specifications at a profitable rate. Factors which may affect the results of a given process include: environmental factors, such as the ambient temperature or humidity; process machine factors, such as calibration, operating temperature and wear; and materials factors, such as the composition of the product undergoing processing or the composition of process consumables. These factors may vary over time as well as between similar processing machines and similar recipes, necessitating continued evaluation and refinement of the control parameters of the process, i.e. refinement of the recipe, to compensate.
Process control is accomplished by enacting quality control methodologies in the production process to monitor the quality of production and detect problems quickly so that they may be resolved quickly. In cases where in situ measurements are not possible, it is necessary to evaluate the finished product to determine if the specified tolerances are met. For example, after each processing step, measurements or testing may be performed on a sample wafer, either an actual production wafer or a test wafer included in the production run, to determine if the processed product is within the specified tolerances. Alternatively, the particular process may be tested on a test wafer/batch before being used in actual production. Where the resultant product is not within the specified tolerances or the product is within the specified tolerances but testing indicates that the process is drifting toward being out of tolerance, measures can be taken to correct the situation, such as by adjusting the control parameters of the particular processing machine, i.e. modifying the recipe. This is also referred to as Run-to-Run control, wherein the production results of a particular processing machine are continuously measured/evaluated. These measurements/evaluations are then utilized to adjust the recipe, i.e. the processing parameters of the processing machine, prior to the next run through that processing machine to compensate for any detected errors. This process is iteratively repeated such that the processing parameters of a given recipe on a given processing machine are continuously evaluated, adjusted and refined, effectively evolving with each successive generation of product, ultimately to a relatively stable state. Given the variability in the factors that can affect the results of a given process, it is likely to have two similar processing machines performing the same process but with different recipes to achieve results according to the design specification.
Statistical process control refers to the use of sampling and statistical computations to analyze the measured quality control data. This analysis can then be used to more accurately modify the recipe. Further this analysis may be used to predict and correct trends in the process results, such as a trend that the process is tending to deviate outside of the specified tolerances, though it has not yet done so.
General process control techniques, including statistical process control techniques, work well for high volume production runs, or production runs having a relatively stable throughput, because the large number of production runs provide many opportunities to test and refine the various process control stages and the consistent use of the various processing machines acts to keep those processing machines properly calibrated and their control parameters in a consistent/relatively stable state of refinement. Further, the time/resource cost of running test production runs to ensure accurate processing is minimal compared to the time/resource costs devoted to actual production. However, such techniques do not work well for low volume production runs or production runs where the production volume may vary from day to day. In such situations, there may not be enough actual production runs to generate statistically significant quality control data so as to be able to refine the various process control stages and further, the use of test production runs, which likely result in unusable products, may not be justifiable based on the cost/resources consumed as compared to the volume of actual production. In addition, for varying production volumes, excess production capacity on any one day may result in idle process machines for that day, while on a day with more significant demand, those idle process machines will be put into operation, necessitating re-calibration and testing of recipes to ensure production tolerances are met on the formerly idle processing machines being pressed into service. Similarly, processing machines may be idled by the need for maintenance, repair or due to some other event, again necessitating re-calibration and testing of recipes to ensure production tolerances are met before they are put into production.
Accordingly, there is a need for a method and system of process control which can be used efficiently in low volume production, variable volume production, as well as in situations where an unanticipated manufacturing event occurs.
At each level of the process control hierarchy 106, the process controllers 108, 110, 112 may utilize the described run-to-run and statistical process control iterative "process-evaluate-adapt" feedback loop to constantly evaluate the resultant products and adjust the recipe/control parameters of the various process controllers 108, 110, 112 to maintain the production within the specified tolerances. It will be appreciated that the disclosed embodiments may be used with any suitable semiconductor manufacturing facility and the number, type and logical/physical arrangement of processing tools 102 and process control systems 106 is implementation dependent, and all such implementations are contemplated herein.
To clarify the use in the pending claims and to hereby provide notice to the public, the phrases "at least one of <A>, <B>, . . . and <N>" or "at least one of <A>, <B>, . . . <N>, or combinations thereof" are defined by the Applicant in the broadest sense, superseding any other implied definitions here before or hereinafter unless expressly asserted by the Applicant to the contrary, to mean one or more elements selected from the group comprising A, B, . . . and N, that is to say, any combination of one or more of the elements A, B, . . . or N including any one element alone or in combination with one or more of the other elements which may also include, in combination, additional elements not listed.
As described above, the iterative "process-evaluate-adapt" procedure results in continually evolving control parameters for a given recipe for a given processing tool(s) 102 whereby the processing tool 102 essentially learns and maintains the optimal parameters, accounting for variability in environmental, materials and process tool factors, to consistently produce a product/perform a process within the specified tolerances with each successive run/lot, whether actual production runs or test runs. This is also referred to as "run to run" or "R2R" control. At any given moment, the present state of these control parameters is referred to as a controller state or controller set-point and may be expressed as a set of values, such as a numeric or alphanumeric string. The time/resources iteratively consumed to arrive at a given controller state is referred to as a "learning curve." As used herein, the term "process" refers to the performance of a particular recipe on a particular part. A "recipe" refers to the specification of individual process steps, a control model as will be discussed below, and the attendant control parameter values, either the initial values or the present values, thereof, that are to be performed by a particular semiconductor processing tool. Accordingly, a process which operates on one type of part may be a different from a process which operates on another type of part, even though both processes use the same recipe.
The disclosed system and method relates to the prediction of the present state of the processing tool control parameter values, i.e. controller state, for a particular processing tool 102, which has little or no utilization history, i.e. is data starved or has not gone through the learning curve, for a given process, or has undergone an event for which the current controller state has been reset or is otherwise now sub-optimal. It will be appreciated that the disclosed embodiments may be applicable to any tool which utilizes a statistical process control along side an integrated engineering process control system, as will be described.
The prediction is based on the processing tool control parameter values of a substantially similar processing tool, being used in a substantially similar fashion to the given situation, which has significant utilization history. The processing tool having significant utilization history may be the same processing tool as the processing tool with little or no processing history where a manufacturing event disrupts the operations thereof. In this case, the pre-event control parameter values and utilization history may be used, according to the disclosed embodiments, to predict the post-event controller state. Effectively, the disclosed embodiments provide for the processing tool with little or no utilization history to inherit the controller state, i.e. the evolved control parameter values, of the processing tool with significant utilization history. Thereby, the processing tool with little or no utilization history is spared having to go through the learning curve, and the associated costs in delay and resources, to arrive at a particular controller state, i.e. the processing tool 102 does not have to go through the iterative process-evaluate-adapt procedure to refine its control parameter values to achieve results within the desired specifications. It will be appreciated that the semiconductor processing tools do not necessarily have to be the same type of semiconductor processing tools in order to be substantially similar and that substantial similarity may exist when any one or more operating parameters of the two semiconductor processing tools can be correlated, such as by utilizing regression or time series models, and data from both tools is available to validate the correlation. For example, correlation of the Pad Pressure of a CMP processing tool with the Alignment Translation parameter of a lithography processing tool would allow the disclosed embodiments to predict controller state as described herein.
Run-to-run (R2R) control is a form of discrete process and machine control in which the product recipe with respect to a particular machine process is modified ex-situ, i.e., between machine runs, so as to minimize process drift, shift, and variability. This type of control is a critical component of the hierarchical scheme that is widely suggested for facility control in the semiconductor manufacturing arena. Run-to-run control is a generic methodology in control of semiconductor manufacturing processes. For example, in semiconductor manufacturing, if the perturbations are small enough, they can be compensated successfully using the exponential weighted moving average (EWMA) method. But, unfortunately, this is not always the case. For example, many plasma processes have been shown to exhibit small to large non-linearity in behavior. Furthermore, the photoresist process requires dynamic process models too. Thus it is necessary to develop nonlinear algorithms to solve this type of problems.
The process of continuously evaluating production and refining control parameters is necessary due to the multitude of variables which affect the process result and which may fluctuate over time, and the fine tolerances which are required. Exemplary variables which effect the result of processing include environmental variables, such as temperature, humidity, contaminants, etc., which may vary among each run of a given process and/or among similar semiconductor processing tools running the same process. Other variables include processing machine 102 variables, such as operational tolerances, wear and calibration, as well as variations in materials, such as variations in the compositions of the parts/work pieces undergoing processes or variations in the component/processing materials used/consumed in the processing of the parts, such as the purity or concentration of process gasses, all of which may vary among each run of a given process and/or among similar semiconductor processing tools running the same process. Accordingly, these variables may be different between process runs on the same tool 102, or between the different processing tools 102 within a given processing cell 104 or among the entire factory 100, and, therefore, the controller state for one processing tool 102 may vary from run to run or vary from that used by another processing tool 102 of same type performing the same process on the same type of part. Typically, each processing tool 102 must be brought up its own learning curve to establish and maintain a controller state which results in products within the acceptable tolerances and which accounts for the nuances of the particular tool 102.
In general, a R2R based control system may include:
(1) A metrology interface component: As R2R control is a form of feedback control, it requires measured output data. The metrology interface component could be automated (e.g., obtaining data from a metrology unit via a Semiconductor Equipment Communication Standard ("SECS") interface and communicating it to the R2R controller via a TCP/IP link), manual (e.g., prompting a user to type in metrology data obtained manually), or a combination thereof;
(2) One or more R2R optimization and/or control algorithms or process models: This component utilizes metrology information and some form of knowledge of the process to make recommendations on how to modify equipment and/or process inputs so as to optimize or control the process. Generally the algorithm(s) utilizes the history of the process in some form and a process model, in conjunction with a set point or state. The methods utilized by these algorithms vary widely, from simple SPC alarm reporting to heuristically-based optimal solution searching. More than one algorithm may be required in the R2R controller so that the system may provide optimization/control over a required domain; these algorithms must be utilized in a complementary fashion;
(3) A recipe download component: This component facilitates the communication of recipe advice information from the R2R control system 110 to the equipment controller, such as the process controller 112. This can be accomplished for example through an automated communication network link or via a graphical user interface (GUI) presenting the recipe advice to a user;
(4) A process monitoring component: Once a recipe is downloaded to a process, processing may begin. Metrology may be conducted for this run only after processing has completed. Thus some form of synchronization is required between the process and the R2R controller. This duty is performed by a process monitoring component. In its simplest form, this component could just be a trigger to the R2R controller indicating that the metrology data for the next run is now available (e.g., a key stroke). In a more complex form, the component could monitor the process in-situ, and generate events to the R2R controller as necessary so as to address warnings, alarms, etc., in addition to normal processing; and
(5) A central control navigation component: the controller must contain a core component that coordinates the information of the other four components to effect R2R control. In the simplest form, this navigation component could be developed as a software program that provides non-robust and inflexible R2R control. In most applications it is required that this navigation component provide a dynamic and flexible control environment.
As discussed above, one quality that sequential controllers should possess in the semiconductor manufacturing environment is the ability to adapt to multiple and varying control schemes. Many semiconductor processes are not well understood and process response surfaces are constantly shifting, drifting, and changing shape. The control schemes for these processes likewise must vary with time. Further, many processes and their process controllers are expected to exist in a flexible manufacturing environment. Thus controllers must be able to adapt to their changing environment by navigating through a robust and necessary complex control paradigm during operation. This navigation must include obtaining, during runtime, information from outside sources where necessary so as to adapt to new and unforeseen control situations. As an example, the controller may be able to query an expert user or a neural network as necessary during runtime to formulate responses to unforeseen control events and learn how to service these events in the future.
For example, Chemical-Mechanical Planarization (or polishing) has become a widely accepted technology for multilevel interconnects. In addition to providing planarization, CMP has also been shown to reduce defect density and define vertical and horizontal wiring. CMP is basically a surface planarization method in which a wafer is affixed to a carrier and pressed face-down on a rotating platen holding a polishing pad. A silica-based alkaline slurry is applied during polishing thus providing a chemical and mechanical component to the polishing process. The general process goal is the preferential removal of high material across the wafer. Typical process metrics include removal rate (or amount removed) and within-wafer uniformity. Equipment and process parameters that are typically utilized to control the process include polish time, pressure, rotation speed, and parameters that impact the conditioning of the polishing pad such as conditioning profile.
There are a number of characteristics of CMP that make it an ideal candidate for R2R control. First, the process is not well understood. This combined with factors such as inconsistency and degradation of consumables, and lack of sensors and actuators makes CMP a challenging candidate for control. Second, as there is a lack of in-situ sensors for CMP, in-situ control is not yet feasible; thus R2R control appears to be the tightest form of control that can be applied to CMP at this time.
The controller 202 features a controller state, also referred to as a set-point, which is the particular values of all of the variables/parameters/inputs which provide for specific control the controller 202 and allow fine tuning of its operation. As described above, the controller state may be expressed as a set of values, such as a numeric or alphanumeric string. In one embodiment, the controller state is expressed as a binary value. The recipe initially specifies an initial state, also referred to as a seed value, for the controller state which sets up the controller 202 to run the process the first time. Once the process has been run, the results are evaluated and the controller state is adjusted to optimize the results, as was described in detail above.
Referring back to
As was discussed, it may take several iterations of executing the process, evaluating the results and adjusting the controller state to ultimately obtain and maintain substantially optimal results from the process. Should some form of manufacturing event occur, this learning curve may be lost and the process of fine tuning the controller state would have to be performed again, incurring a significant waste of resources.
Manufacturing events include scheduled or unscheduled situations or occurrences which may affect the tolerances of the particular semiconductor process tool 102 or otherwise require a reset and re-fine tuning of the controller state to account for a substantial change in the operation of the tool 102, and which cannot be accounted for efficiently via the R2R control logic. Such events include replacement of parts or other maintenance, tool 102 down-time, such as where the tool 102 is allowed to cool down, tool 102 re-calibration, use of the tool 102 for a new process that has never been run before on the tool 102, or where the given process has not been run on the tool 102 for a significant amount of time, e.g. the R2R logic 210 is data starved, i.e. lacks sufficient historical data to adequately adjust the controller state. In each case, such an event may require multiple iterations of the process-evaluate-adapt methodology to bring the process within the specified margins, which may represent an unacceptable resource cost.
In a R2R controlled manufacturing environment, a manufacturing event, such an event requiring a new processing tool 102 to be used or a processing tool 102 to be switched from one process to another, such as a switch from processing one part type another part type, typically is handled by processing one or more pre-cursor/Send Ahead lots ("SAHD"), so that the run-to-run controller can re-learn the optimal process settings, as was described above. Larger high-volume facilities may use mathematical models alongside run-to-run (R2R) control to minimize the effects of the Run to Run controller to bring the controller back to up-to speed.
The disclosed embodiments provide a system and method which allows a processing tool 102 to inherit the controller state of another processing tool 102, thereby avoiding the learning curve required by R2R control, while accounting for the variances which distinguish the tools 102 and/or processes from each other. The disclosed embodiments may be used in any situation where a processing tool 102 is to be pressed into service for a particular task for which it has little historical utilization data and where the other similar processing tools 102 are available with significant utilization data relating to the particular task. For example, the disclosed embodiments may be used in a manufacturing environment where varying production results in some processing tools 102 being idled on one day and being pressed into service on another day. In this situation, the particular processing tool 102 which is being pressed into service on a given day may inherit the control parameters of another similar processing tool 102 that has been continuously used. In a situation where the idle machine 102 was idle due to maintenance or some other manufacturing event, the prior utilization history of that tool 102 may serve as the reference rather than another tool 102.
In another example, the disclosed embodiments may be used in a mixed manufacturing environment where more than one type of product is manufactured, each product utilizing the various processing tools 102 according to their own recipe. In this situation, a processing tool 102 may have historical utilization data regarding one of the products but little or no historical utilization data for the other product. In this situation, the processing tool 102 may inherit the control parameters for another processing tool 102 having historical utilization data for both products.
With the Semiconductor industry today turning into a highly competitive market and with new technologies emerging at the present pace, it is imperative for manufacturing facilities to be flexible enough to accommodate these new products into there manufacturing portfolios. The disclosed embodiments focus on a mechanism to predict process control settings for controllers by applying the concept of inheritance. As described above, the control systems available today rely on the Run to Run control system along with statistical process control methods to adjust the control settings to approach the specified target. In most cases due to low production volumes based on market demands, it is costly and time consuming to wait for the Run-to-Run system to tune the product process controller to hit target.
The present run-to-run system, applies statistical process control to monitor and statistical algorithms to control a manufacturing process. Therefore, if a low volume product is to be introduced for manufacturing the system has to relearn the process to determine optimal process settings.
The mechanism of the disclosed embodiments does not require any additional setup as the information required for predicting settings is already used by Statistical Process Control in the run-to-run control system.
The prediction mechanism uses algorithms which search for a processing machine 102 bearing similar attributes to the processing machine where the product is to be processed. Once the prediction mechanism locates this processing machine 102, the prediction mechanism searches for a product-controller 202 which is available on both the tools. Then using a mathematical algorithm, it builds a relation between the product-controllers 202 and processing machines 102. This relation is used by the mechanism to inherit settings to predict the most optimal controller setting on the processing machine 102 in question. The mechanism relies on data which is collected and recorded as run to run control history and is available in almost all run-to-run control systems. This data is also updated regularly in order for SPC to monitor the control system. The main goal of the disclosed embodiments is to minimize the time required to introduce a low volume product into production, henceforth reducing the necessity to process SAHD/Pre-cursors which in turn minimize possible rework and Out of Control Events. The core benefit is that it provides the manufacturing facility the much needed flexibility to introduce and manufacture products in-tune with the present market demand and still maximize on throughput.
Further, the mechanism of the disclosed embodiments may continuously predict process control settings for controllers in real time mode. This permits, for example, the process control mechanism to adapt as process response surfaces shift, drift or change shape, as was described. As described above, in the case of manufacturing events, which may be scheduled or unscheduled, all controllers connected with the event may need to be reset so they may relearn the process settings. This may be a very costly and taxing process. The disclosed embodiments are capable of predicting the controller settings, continuously and real time, thereby reducing the impact for systems to relearn processes.
The operation of the disclosed embodiments may be exemplified by at least one of the following scenarios. In a first scenario, a target tool has been running both a target process and an exemplar process when an event occurs that affects the controller state. In order to get the target tool back up and running as quickly as possible, the prediction logic 212 looks at the pre-event history of controller states of a given controller 202 of running both the target and exemplar processes and computes a delta value, i.e. the pvp delta, between the historical controller states of each process. In one embodiment, the delta is computed for each parameter value of the controller state. At least one post-event test lot is then run for the exemplar process and the controller state is determined. As the target tool/controller is acting as a point of reference for the prediction logic 212 to determine if a significant process shift has occurred, one metrology point may suffice but additional points will improve the computation of the optimal target controller state. The computed process delta, i.e. pvp delta which in this case is also the controller state delta, is then applied to the controller state determined from running the exemplar process to obtain a predicted substantially optimal target controller state for running the target process. In this way, the target process does not have to be iteratively executed to optimize the controller state. Note that since the same tool was used as the basis for the prediction, the tool v. tool delta will be zero, unless the event caused significant changes to the tool 102 and therefore need not be computed.
In a second scenario, a target tool has a history of running an exemplar process, i.e. has many gone through many iterations of the exemplar process and the controller state is substantially optimal and relatively stable. However, the target tool has little or no history running a target process. Accordingly, the prediction logic 212 will utilize the history databases 208 to determine a similar exemplar tool and an exemplar controller 202 that has history running both the exemplar and target processes. This determination may be made mathematically, from a list of candidate process tools which include the target controller 202 in its portfolio, such as by a clustered grouping. For example, where the operating parameters of a particular tool are pre-defined, such as the process layers which can be operated upon or the wavelength of light utilized, these characteristics can be listed in the history database 208 such that tools of similar characteristics can be clustered, e.g. sorted, together to create a pool of candidates to choose from. While the same control model/algorithm should be used, different proportional/integral/derivative ("PID") control loops may be used. The longer the history that the exemplar tool and controller have at running both the exemplar and target processes may yield a higher confidence in the computed correlation, though, as the exemplar tool/controller acts as a point of reference, a single metrology point will be sufficient. In one embodiment, approximately 30 observations results in an acceptable statistical approximation. The prediction logic 212 will then compute a pvp delta between the historical controller states of the exemplar and target processes on the exemplar tool. The prediction logic 212 will also compute a tvt delta between the historical controller states of the exemplar processes run on the exemplar and target tools. Using the pvp and tvt deltas, a controller state delta for the target tool is computed. The controller state delta is then used by the prediction logic 212, in conjunction with the controller state of the exemplar process on the target tool, to compute the predicted controller state for the target process on the target tool. This is a similar analysis as used in the first scenario, however in that case, the tvt delta was likely zero because the exemplar and target tools were the same tool, pre and post event.
In yet another scenario, a flexible manufacturing environment is provided which permits tools 102 to be flexibly brought on-line to run different processes, such as for short production runs of a given part or to handle dynamic production capacity requirements. In this scenario, the prediction logic 212 monitors all tools 102 and the various processes being run on them. For each tool which is running an exemplar process but which is not running a target process, the prediction logic 212, continuously in real time, operates as described above to identify similar exemplar tools/controllers running both the exemplar and target processes and computes the pvp and tvt deltas to obtain the controller state delta for the target tool. In one embodiment, the controller state delta for the target tool, the actual controller state of the target tool and an Errors-to-Tolerance ("T/E") value are computed. This controller state delta is then stored in a database associated with the particular target tool. In this way, the target tool is always ready to be switched over to the target process if necessary by applying the controller state delta to the controller state of the exemplar process to obtain the target controller state for running the target process. In addition, statistical processing of the various delta values may be performed to compute a confidence value representative of the likelihood that the controller state delta, when applied to the exemplar controller state from the target tool, will achieve a controller state for the target process that obtains substantially optimal results. This confidence value may then be presented to the manufacturing personnel to advise them whether or not switching the target tool to the target process will be cost/resource effective.
Referring back to
The similarity processor 402, once having identified a similar exemplar tool 102 and exemplar controller 202, accesses the controller state history databases 208 of the exemplar and target tools 102 to retrieve the historical controller state data for the exemplar and target processes. The logic 404 then computes the pvp controller state delta between the controller states of the exemplar process running on the exemplar tool 102 and the controller states of the target process running on the exemplar tool 102. The logic 406 computes the tvt controller state delta between the controller states of the exemplar process running on the exemplar tool 102 and the controller states of the exemplar process running on the target tool 102. Obtaining the controller state of the exemplar process on the target tool 102 may require the processing of a pre-cursor/SAHD lot. The tvt and pvp deltas are then passed to the controller state generator 408 which computes the controller state delta between the controller state of the exemplar process running on the target tool and the predicted controller state for the target process running on the target tool 102. The controller state generator 408 may then further compute the predicted controller state for the target process running on the target tool 102. This state is then passed to the process controller 110 to be used as the initial controller state 204 for running the target process. In the real-time embodiment described above, the controller state delta and/or predicted controller state may be stored in an offset matrix/database 412 for later use and/or processed via a confidence processor 410 to determine the statistical probability that the predicted controller state will achieve substantially optimal results.
Referring to
Referring to
For each of the plurality of target semiconductor processing tools and each of the associated target process control models (block 600), an exemplar semiconductor processing tool having an exemplar process control system and an exemplar process control model is identified, the exemplar process control model and exemplar semiconductor processing tool being substantially similar to the particular target process control model and the particular target semiconductor processing tool, the exemplar process control model and exemplar semiconductor processing tool having been used previously to execute both the target process and an exemplar process (block 602). It will be appreciated that the semiconductor processing tools do not necessarily have to be the same type of semiconductor processing tools in order to be substantially similar and that substantial similarity may occur any one or more operating parameters of the two semiconductor processing tools can be correlated. For example, correlation of the Pad Pressure of a CMP processing tool with the Alignment Translation parameter of a lithography processing tool would allow the disclosed embodiments to predict controller state as described herein. A first controller state of the identified exemplar process control system is determined as a result of at least one execution of the target process on the identified exemplar semiconductor processing tool (block 604). A second controller state of the identified exemplar process control system is determined as a result of at least one execution of the exemplar process on the identified exemplar semiconductor processing tool (block 606). A process delta between the first and second controller states is computed (block 608). A third controller state of the particular target process control system is determined as a result of at least one execution of the exemplar process on the particular target semiconductor processing tool (block 610). A tool delta between the second and third controller states is computed (block 612). The substantially optimal target controller state is computed based on the third controller state and the process delta and the tool delta (block 614). The substantially optimal target controller state is then stored in a database, the substantially optimal target controller state being stored in association with the particular target semiconductor processing tool and particular target process control model (block 616). The process is repeated for all of the tools 102, either in the entire facility or within a particular tool group 104 (block 618).
The prediction mechanism uses statistics, modeled algorithms and matrix based calculations to predict optimal settings for every controller available in the production cell. By performing these calculations in real time, there is never a point during production that a particular process controller is starved for an optimal controller state, which reduces the requirement for the system to relearn process settings. The mechanism relies on data which is collected and recorded as run to run control history and is available in almost all run-to-run control systems. This data is also updated regularly in order for SPC to monitor the control system.
Accordingly, the time required to reduce the impact of manufacturing events, both scheduled and unscheduled, is minimized. By introducing an apparatus that follows the prediction mechanics, a manufacturing facility is provided with the much needed flexibility to introduce and manufacture products in-tune with the present market demand and still maximize on throughput.
The present run-to-run system, applies SPC to monitor and statistical algorithms to control a manufacturing process. Therefore, if a manufacturing event (scheduled/unscheduled) occurs the prediction system will learn the process through a single SAHD/pre-cursor lot and then predict optimal settings for all other controllers to hit specified target, thereby reducing the need for other controllers to relearn. Additional setup is not required as the information required for predicting controller state is already used by Statistical Process Control in the run-to-run control system. With the aid of a rapid software development package, such as Visual Basic, published by Microsoft Corporation, located in Redmond, Wash., or MATLAB� published by The Mathworks, Corp. Natick, Mass., the data can be extracted and operated on by using algorithms brought forward by this invention.
In one exemplary embodiment, the disclosed system and method is used in the prediction of lithography process control settings in a semiconductor manufacturing environment via a model for inheritance which is based upon the concept of controller state in a mixed part semiconductor manufacturing factory. The concept of controller state analysis is expanded to develop a predictive model, by virtue of which control settings can be inherited within or across contexts/controllers. It will be appreciated that the mathematical computations necessary to implement the disclosed functionality may vary depending upon the implementation.
The following statistical equations may be used for the controller state prediction:
Sigma Test: It is a test used to analyze, if the difference in controller state-I and controller state-II is statistically significant.
({overscore (X)} CSI−(α*S CSI))≦(X CSII)≦({overscore (X)} CSI+(α*S CSI)) (5)
Where, XCSI is the Controller State-I mean; SCSI is Standard deviation of the controller state-I;
XCSII is the controller state-II; α is the sigma multiplication factor which is always less than 3 and can be use as a tuning parameter for tighter control of the process. Deadband Test: A test used to analyze if the delta in Controller state I and II is significant enough to have an effect on product.
|ΔControllerstate|≦(deadband) (6)
Where, Δcontroller-state is the delta between the pre-event controller state (CS-I) and post-event controller state (CS-II); Deadband is the limit beyond which there is noticeable effect on product.
Error Approximation (nm): It is the approximate error in nanometers for each of the overlay parameters.
ErrorOVL-parameter(nm)≈(ΔOVL-parameter*α) (7)
Where, ErrorOVL-parameter is the error in units of nanometer; ΔOVL-parameter is difference in controller state-I and controller state-II; α is the conversion factor specific to that overlay parameter.
MAD=median|x i −{overscore (x)} (11)
Percent Weighted Average: It is percent weighted average of the data points.
where wi is the weight value, xi is the data points, n is the total no of data points. Note: wi for the controller state calculation is calculated based on equation [13].
w i=(l.c.*(lookbackdays−differenceindaysfromevent)) (13)
Where, l.c. represents the smallest percent weight that can be assigned and is calculated using formula [14]
Where, 'lookbackdays' are the number of days to go back in time to collect process data.
According to the disclosed embodiments, the controller setting for a part on a tool may be predicted by inheriting the settings from another part that has been running on the tool. The inheritance model first calculates the deltas for a controller between a high runner part (part with recent data on required tool) and the low runner part (part with no recent run history). These deltas are calculated per day between the parts on another similar tool, where both the parts have recent run history. Then a weighted average [Equation 15] of the deltas is taken and is applied to the controller state for the high runner part on the data starved tool [Equation 12]. This calculated setting is the predicted setting to process the low runner part on the tool in question.
XDelta-CState: Represents the weighted average of the deltas in controller state for each day between parts on a tool, as shown in figure a.
where wi is the weight value, xi is the delta in controller state each day between two parts on a tool, and n is the no of days for which data is collected with respect to day of tool event.
Note: wi is calculated based on equation [11].
where α is the multiplication factor to control the weight of the deltas.
Controller State (predicted): It represents the predicted controller state of the part/layer on a tool, which is data starved, i.e. has no data available on the required exposure tool.
ControllerStatepredicted=({overscore (X)} Delta-CState+Opt.Setting controller-reference) (15)
In one embodiment of the disclosed system and method, in order to simplify the approach for design of a prediction model, a rule system maybe required to be developed, based on the behavior and characteristics of the process controller. This rule system is used to develop groups of the various control-loops for the process controller. The benefits of this are that the prediction of control settings is only made for those contexts (technology/layer/part) which are within a specific group. The rule setup for the overlay controller is based on product technology node, exposure tool wavelength, exposure tool make, tool exposure mechanism (scanner or stepper), and exposure tool and wafer alignment method. The rule system for the Critical Dimension ("CD") controller is based on exposure tool wavelength, exposure tool make, tool exposure mechanism (scanner or stepper) and product exposure layer. The division of controllers based on the rule system specific to the process controller, provides the ability to inherit overlay settings either across Design/Part or across exposure tools which bare similar attributes, for the CD controller the rule system will allow for settings to be inherited across layer/reticle and across exposure tool.
Based on the rule system developed above for the process controller a matrix/database is created. The matrix is used to predict settings through the concept of inheritance, for example to allow the overlay and Critical Dimension controller inherit settings across tool and across Design in the case of overlay and across Reticle in the case of Critical Dimension.
History data for the controllers is collected for x-days in the past. The number of days to look back depends on the rule for data validity.
In one embodiment, the data is collected by extracting all of the optimized (applied) process settings from the feedback control system. The data then goes through filters and is then validated. The data filter algorithms look for all measured lots which were not reworked. The collected data is then separated by day and is validated to check for outliers before an average is taken. This is performed for each of the overlay control parameters.
Once the data has been collected, filtered and validated, an accurate prediction for the state of the controller with respect to the exposure tool, for example, is made.
The number of days over which to collect the data depends upon the time-horizon for the data and may be different for different feedback controllers. Once the data is collected the data is split into chunks based on the day they were collected. The data points are then filtered to remove outlier points and then an average of the remaining points is taken, depending on the availability of data for each day. To obtain a prediction which is most recent and accurate a percent weighted average ("PWA") of the day averages is calculated. The percent weighted average helps to nullify the effect of process shifts per day that might be present and will distort the mean. The final average represents the current state of the tool and is also called Feedback Controller State.
Once the prediction model, discussed above, is created and the data has been collected and sanitized, the process settings are calculated. This model may be applicable to predict process settings in the following situations: The most common scenario would be a scheduled preventive maintenance event, which could entail laser change, stage correction, chuck clean/replacement etc. Once such an event takes place it is imperative to ascertain the pre and post event state of the controller. A pre-cursor or send-ahead lot is run and the metrology results obtained are compared with the pre-tool event controller state, to adjudge if the change is significant based on control limits. In many cases it is not possible to make such an analysis as the data for the controller is limited and not recent enough. It is here that the prediction model allows the process engineer to obtain a recent predicted state of the controller by calculating the offsets across columns (tool-to-tool) and across rows (controller to controller) of the matrix. It must be understood that the offsets are taken from those controllers which are not data-starved.
The procedure explained above can be realized by developing a software program to perform the above calculations for the multiplicity of parameters. This would reduce the delay associated with data collection, filtering, matrix build-up and final calculation of offsets for the prediction.
In today's highly modernized semiconductor manufacturing plants, where processing every wafer the most optimal settings is imperative, the prediction model is a powerful tool for the engineer who would like to process his wafers, with minimal rework and out of control issues. Another case where the prediction model sees its utility is the ability for it to predict the process settings of a newly introduced controller, without having to process a pre-cursors or a send-ahead. The controller for which settings are required, is inserted into matrix and by finding offsets from other controllers that have been recently running on the exposure tool, as explained above, the optimal process settings can be predicted. This greatly reduces the need to run multiple send-ahead lots, which may have been potential out of control cases.
It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention.
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|Methods and apparatus for improving operation of an electronic device manufacturing system
|Dec 13, 2011
|Tokyo Electron Limited
|Autonomous adaptive system and method for improving semiconductor manufacturing quality
|Mar 8, 2008
|May 29, 2012
|Tokyo Electron Limited
|Autonomous biologically based learning tool
|Jan 29, 2010
|Mar 12, 2013
|Tokyo Electron Limited
|Method and apparatus for self-learning and self-improving a semiconductor manufacturing tool
|Jan 20, 2010
|Sep 10, 2013
|International Business Machines Corporation
|Rule-based root cause and alias analysis for semiconductor manufacturing
|Sep 29, 2008
|Dec 10, 2013
|Fisher-Rosemount Systems, Inc.
|Method of generating a product recipe for execution in batch processing
|Jan 12, 2010
|Apr 22, 2014
|Ford Global Technologies, Llc
|Weldability prediction and recommendation systems and methods
|Mar 31, 2009
|May 13, 2014
|Tokyo Electron Limited
|Method and system for detection of tool performance degradation and mismatch
|Feb 11, 2013
|Jun 3, 2014
|Tokyo Electron Limited
|Method and apparatus for self-learning and self-improving a semiconductor manufacturing tool
|Sep 22, 2011
|Jun 17, 2014
|Inotera Memories, Inc.
|Fault detection method of semiconductor manufacturing processes and system architecture thereof
|Apr 27, 2012
|Mar 1, 2016
|Tokyo Electron Limited
|Autonomous biologically based learning tool
|May 29, 2003
|Dec 16, 2004
|Sherriff Godfrey R.
|Batch execution engine with independent batch execution processes
|May 8, 2006
|Jan 4, 2007
|Hans-Juergen Malig
|Method and system for advanced process control using measurement uncertainty as control input
|May 26, 2006
|Apr 5, 2007
|Stirton James B
|Method and system for advanced process control using a combination of weighted relative bias values
|Mar 14, 2007
|Nov 8, 2007
|Sebastien Raoux
|Methods and apparatus for improving operation of an electronic device manufacturing system
|Jun 14, 2006
|Dec 20, 2007
|Taiwan Semiconductor Manufacturing Co., Ltd.
|Automatic methods and systems for manufacturing recipe feedback control
|Oct 9, 2006
|Jun 19, 2008
|James Broc Stirton
|Method and Apparatus for Compensating Metrology Data for Site Bias Prior to Filtering
|Jun 14, 2007
|Dec 18, 2008
|Baseman Robert J
|System and method for rule-based data mining and problem detection for semiconductor fabrication
|Dec 12, 2008
|Apr 9, 2009
|Baseman Robert J
|System and Method for Rule-Based Data Mining and Problem Detection for Semiconductor Fabrication
|Mar 8, 2008
|Sep 10, 2009
|Tokyo Electron Limited
|Autonomous adaptive semiconductor manufacturing
|Mar 31, 2009
|Sep 24, 2009
|Tokyo Electron Limited
|Method and system for detection of tool performance degradation and mismatch
|Sep 29, 2008
|Apr 1, 2010
|Fisher-Rosemount Systems, Inc.
|Recipe Command Steps and Recipe Inputs from External Logic
|Jan 29, 2010
|Jun 3, 2010
|Tokyo Electron Limited
|Method and apparatus for self-learning and self-improving a semiconductor manufacturing tool
|Dec 27, 2010
|Apr 21, 2011
|Inotera Memories, Inc.
|Fault detection and classification method for wafer acceptance test parameters
|Jun 2, 2011
|Tokyo Electron Limited
|Autonomous biologically based learning tool
|Jul 14, 2011
|Ford Global Technologies, Llc
|Weldability prediction and recommendation systems and methods
|Jan 20, 2010
|Jul 21, 2011
|International Business Machines Corporation
|Rule-based root cause and alias analysis for semiconductor manufacturing
|Dec 27, 2012
|Inotera Memories, Inc.
|Fault detection method of semiconductor manufacturing processes and system architecture thereof
|Aug 29, 2012
|Mar 7, 2013
|Kla-Tencor Corporation
|Method and system for detecting and correcting problematic advanced process control parameters
|Aug 30, 2013
|Mar 5, 2015
|Taiwan Semiconductor Manufacturing Company, Ltd.
|Method of making semiconductor devices and a control system for performing the same
|May 26, 2011
|Nov 28, 2012
|Method and system for avoiding misoperation during debugging of semiconductor process menu
|May 26, 2011
|Apr 8, 2015
|Method and system for avoiding misoperation during debugging of semiconductor process menu
|Aug 30, 2012
|Jun 4, 2014
|Method and system for detecting and correcting problematic advanced process control parameters
|Feb 3, 2010
|Oct 7, 2010
|Tokyo Electron Limited
|Method and system for detection of tool performance degradation and mismatch
|U.S. Classification
|700/20, 700/121
|International Classification
|Cooperative Classification
|European Classification
|May 18, 2005
Owner name: INFINEON TECHNOLOGIES RICHMOND, LP, VIRGINIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GOULD, CHRISTOPHER;SINGHAL, ABEER;REEL/FRAME:016587/0069;SIGNING DATES FROM 20050513 TO 20050515
|Jan 13, 2010
Owner name: QIMONDA AG, GERMANY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INFINEON TECHNOLOGIES RICHMOND, LP;REEL/FRAME:023792/0001
Effective date: 20060425
|Apr 16, 2010
|Fee payment
Year of fee payment: 4
|Apr 17, 2014
|Fee payment
Year of fee payment: 8
|May 8, 2015
Owner name: INFINEON TECHNOLOGIES AG, GERMANY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:QIMONDA AG;REEL/FRAME:035623/0001
Effective date: 20141009
|Oct 21, 2015
Owner name: POLARIS INNOVATIONS LIMITED, IRELAND
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INFINEON TECHNOLOGIES AG;REEL/FRAME:036908/0923
Effective date: 20150708


text:
Alright so i finished my purple run on Blue last night. Here's some screens.
Vaginaa, the Cloyster. Lv. 54 134/134/221/103/122
Casper, the Haunter. Lv. 66 163/109/88/168/181 MVP
Nido, the Nidoking. Lv. 67 231/168/155/161/132
Next time i will be adding more updates with screens. I would've added sprites but i could only attach 5 images and it would've looked weird with only 2 sprites.
New Challenge; Yellow on Silver version since no one has done Yellow or played through on Silver yet


text:
- Missing Jackson woman found dead in Bollinger County pond (06/23/16)2
- Many Jackson students may face random drug-testing (06/26/16)27
- Village of Zalma must disincorporate, law says (06/23/16)5
- Jackson man accused of felony assault after attack at Cape bar (06/26/16)8
- I want an angry president (06/21/16)17
- Man allegedly kicks woman, punches man after denied a sexual favor (06/23/16)
- Witness says he saw suspect kill his best friend (06/24/16)
- Officials: Ash borer less of a problem here than in St. Louis (06/27/16)
- Advance graduate will become superintendent of its schools (06/21/16)1
- Odd court hearing ends with judge declaring probable cause in abuse case (06/22/16)4
Pakistan chief says outside help is key to end Kashmir rift
WASHINGTON -- Pakistani President Pervez Musharraf said Tuesday that India and Pakistan need outside mediation to help them break their dangerous deadlock over the disputed region of Kashmir.
A day before he meets President Bush at the White House, Musharraf outlined an ambitious agenda to turn his country -- which has provided key help in the U.S.-led fight against terrorism -- into a modern, progressive Islamic state rejecting religious extremism.
Debt relief is key, Musharraf said in a speech sponsored by two Washington think tanks, because Pakistan now spends 50 percent of its budget to service its outside debt. Bush is expected to go at least partway toward meeting Musharraf's request for debt relief, administration officials have said.
Most Pakistanis are moderate, not religious extremists, Musharraf told the friendly audience, and they embrace the reforms he has begun to lower the influence of religious extremists and develop the economy.
At the same time, the disputed Himalayan province of Kashmir is an issue for "each one of them," and must be resolved, the president said.
"Bilateralism has failed," Musharraf said of Pakistan's bitter standoff with rival India. Both nuclear-armed countries have their armies on high alert at their joint frontier. "There is a requirement for mediation."
While he did not specifically call on the United States to act as mediator, Pakistan has long sought such a role for America.
India has just as vociferously rejected outside mediation. The United States would act as mediator only if both countries requested it, a senior Bush administration official said Tuesday.
$3 billion debt relief
Musharraf, making his first White House visit on today, wants the $3 billion in debt relief and other economic aid.
Bush, in turn, is looking for continued Pakistani action against Islamic extremists.
Both leaders badly want the freedom of abducted Wall Street Journal reporter Daniel Pearl, whose kidnapping has embarrassed Musharraf as he tries to convince the world that Pakistan is no center of Islamic extremism.
The United States has praised Pakistan's efforts to find Pearl. Officials there announced Tuesday -- before the Musharraf-Bush meeting -- that the chief suspect in the kidnapping had been arrested in Lahore. But the American reporter's whereabouts remain unknown.


text:
Twitter Link Facebook link
For most of the world`s badgers, humans are the only other animals that pose any real threat to their wellbeing. The practices of digging badgers from their setts and baiting them for hours on end with dogs; these activities were common practices in Britain until relatively recent times. Adopt a badger and help change a badgers life forever!
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Ottawa Electronics Disposal
Microsoft Store
On All Windows Devices!
1. Bob Thrush Sanitation Service
2010 Airport RdOttawa, IL 61350
From Business: Bob Thrush Sanitation offers garbage and rubbish removal in Ottawa and Marseilles, Illinois. We also offer portable toilet rental to all communities in LaSalle, Bur…
2. Town & Country Disposal
400 W Marquette StOttawa, IL 61350
3. Allied Waste Industries
2840 E 13th RdOttawa, IL 61350
4. Waste Management
3066 N State Route 71Ottawa, IL 61350
5. Illinois Vly Disposal Systems
3066 N State Route 71Ottawa, IL 61350
6. RentADumpster.com
Arwood Waste has worked with them for years and they always deliver on time.................................
7. 123 Disposal
Just thought i would share this clip that a customer sent us after renting a few portable toilets............
8. Waste Management
From Business: Waste Management provides residential, commercial and industrial trash collection, as well as recycling and dumpster services. We support a number of local communit…
9. Dumpster Direct
I wanted a local dumpster provider and was able to find it through DumpsterDirect. The toll free number enabled me to enter my zipcode and connected…
10. Easy Dumpster Rental
Keeping You and the Environment Safe The new National Garbage Man Day slogan "Keeping You and the Environment Safe" captures the true mission of th…
11. MedPro Waste Disposal
We first heard of MedPro Disposal a little over four years ago when my boss asked me search for a new medical waste disposal company because the pro…
12. Cobblestone Container Service
Serving the Ottawa Area.
From Business: Family owned and operated dumpster rental business with over 25 years of experience in the waste management industry. We pride ourselves on getting the job done rig…
13. Cheap Dumpsters
Serving the Ottawa Area.
From Business: Our customer base includes individual residential contracts to city contracts and includes industrial and commercial real estate operators, homeowner associations, …
14. MedPro Waste Disposal LLC
Serving the Ottawa Area.
15. Cheap Dumpsters
Serving the Ottawa Area.
From Business: Cheap Dumpsters is one of the largest solid waste management companies in USA that provides solid waste collection, transfer, disposal and recycling services for bo…
16. MedPro Waste Disposal
Serving the Ottawa Area.
17. Larose Disposal Service
213 N MainLa Rose, IL 61541
18. Able Disposal
Peru, IL 61354
19. R/D Computer Sales & Services, Ltd. DBA Connecting Point Computer Center
1622 4th StPeru, IL 61354
From Business: Connecting Point Computer Centers are the places to go for computer sales, hardware repair & service, manufactures and extended warranties. We serve both residentia…
20. GM Recycling and Disposal Inc
1212 E 12th StStreator, IL 61364
21. United Sanitation Services Inc
I am a very pleased customer. These portable toilets and sinks are in execellant condition and very clean. The service was very dependable and fri…
Showing1-21 of 21results


text:
STARmeterSEE RANK
Down 299,043 this week
Mario Vazquez (I)
Mario Vazquez was born on June 15, 1977 in Bronx, New York, USA as Mario Adrian Vazquez. He is an actor, known for Los 50 más bellos de People en Español (2005), Fashion Rocks (2006) and American Idol (2002). See full bio »
Born:in Bronx, New York, USA


text:
Reading mode: Light Dark
Best inexpensive D5300 lens for birds in flight?
Started Mar 4, 2014 | Discussions thread
Shop cameras & lenses ▾
larrewl • Forum Member • Posts: 78
Best inexpensive D5300 lens for birds in flight?
Mar 4, 2014
I'm buying a telephoto/zoom this month for my birthday and the Sigma 150-500mm f/5-6.3 AF APO DG OS HSM is currently at the top of my list due to its max 500mm zoom and range. Is there a better fixed focal length lens for D5300 for under $1000 USD for taking photos of birds in flight? Autofocus speed, f-stop, and optical quality matter to me. I've read that Sigma 150-500 images above 400mm are soft. I'd like more than 300mm sometimes. I also know that $1000 is not enough to get a really good telephoto. Any opinion info is sincerely appreciated.
larrewl's gear list:larrewl's gear list
Panasonic Lumix DMC-TS4 Panasonic Lumix DMC-FZ200 Nikon D5300 Nikon AF-S Teleconverter TC-14E II Sigma 18-250mm F3.5-6.3 DC Macro OS HSM +1 more
Nikon D5300
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text:
Lyrics Depot is your source of lyrics to Change by Incognito. Please check back for more Incognito lyrics.
Change Lyrics
Artist: Incognito
Album: Tribes, Vibes and Scribes
(J.P. Maunick/R. Bull)
What we got here
Is not a fool's dream
We really feel the need
We've come to ground
Like prisoners on the run
Just minutes away from freedom
Ain't no use in fooling ourselves
We really feel the need
Whatever it takes
Nothing will be too much
We both long for better days
Baby, we're different as the seasons
Never ever giving reasons
Left with the tears
And the paralysing fear
That brings us to our knees
Bring on the changes
Bring on the changes
It's no pretending, no denying
When you really feel the neeed
Going to hang on and be strong
Turn the tables, make the change
The two of us, different as the seasons
Never ever giving reasons
Left with the tears
And the paralysing fear
That brings us to our knees
Chorus x 2
There's gotta be some give and take
If we ever gonna make a change
Chorus x 2
Incognito Lyrics
Incognito Tribes, Vibes and Scribes Lyrics
More Incognito Music Lyrics:
Incognito - Cada Dia (Day By Day) Lyrics
Incognito - Cut It Loose Lyrics
Incognito - Do right Lyrics
Incognito - I hear your name Lyrics
Incognito - Incognito Lyrics
Incognito - It Ain't Easy Lyrics
Incognito - More Of Myself Lyrics
Incognito - Release yourself Lyrics


text:
- Accueil
- Bibliographie
- Informations
- Séminaires
- Flux d'actualités
- Colloques internationaux
- Usine du futur
- Members
English Press / Presse anglaise
Why the new era of auto industry collaboration creates risks
Automotive Business Review - 27 juin 2016 - 19:23
Without proper management, automotive technology collaborations have the potential to result not only in fundamental structural changes to the traditional auto industry, but further diminution of its leadership and clout.
Ford Escape stars in new series on Verizon video platform
Automotive Business Review - 27 juin 2016 - 19:13
The 2017 Ford Escape will help people avoid 'capture' in a new series airing on Verizon's recently-launched video platform.
Honda says Takata airbag ruptured in fatal crash in Malaysia
Automotive Business Review - 27 juin 2016 - 16:17
Honda said the driver-side airbag inflator ruptured during a fatal crash in Malaysia, possibly the third death this year in the Southeast Asian country linked to airbags from supplier Takata.
Aston Martin losses double to £128m
Financial Times - 27 juin 2016 - 15:49
UK carmaker steps up spending on new model line-up
Brexit: Japan carmakers weigh UK options
Financial Times - 27 juin 2016 - 12:10
Non-EU levy could prompt exodus of automakers, analysts warn
Japan: swimming against the currency
Financial Times - 27 juin 2016 - 10:53
Yen strength is a key outcome of Brexit
Penske, Group 1 assess the damage
Penske Automotive and Group 1 Automotive took an immediate stock-price hit in the wake of Britain's vote to exit the European Union. Earnings will suffer from a collapsing British pound. But the longer-term impact remains unclear.
Service adviser overtime case ain't over
The Supreme Court stopped short of settling once and for all the broader question of whether exemptions in overtime rules should apply to dealership service advisers, leaving open the possibility that the dispute could surface again.
What do Mustang and Camaro have in common?
Despite partisan loyalties on each side, starting next year the Chevrolet Camaro will share a transmission with the Ford Mustang.
Mercedes execs to sample retail experience
About 40 Mercedes-Benz USA managers will each spend a week this summer working at a Mercedes-Benz dealership.
Goodbye to the Europe I knew
I am deeply shocked and disappointed by the decision of British voters to leave the European Union. A place I loved called Britain may no longer be so great any more.
Supplier planning hits the brakes
The U.K. vote to exit the European Union leaves suppliers in the dark on future investment until new EU trade deals can be adopted.
Fixing Cadillac's problem child
Cadillac is trying to breathe new life into the ATS compact sedan through a series of price and trim-package adjustments for the 2017 model year.
Fine-tuning the dealership TV set
Zamora Automotive Group's Honda of Superstition Springs uses customized programming delivered to 24 screens throughout the dealership to get its marketing messages to customers in the store.
IIHS signals impatience on passenger protection
The Insurance Institute for Highway Safety is using its powerful megaphone to send a message to automakers: Don't slack off on passenger-side safety.
Are shifters getting too complicated?
The death of 27-year-old Star Trek actor who was pinned to his death by his own Jeep Grand Cherokee has brought scrutiny to a driving function that has changed with the advance of electronic controls.
ZEV mandates get harder to ignore
California's air-quality regulations are slated to tighten in 2018 in a way that limits the impact of partial credits from sales of plug-in hybrids and low-emissions conventional vehicles, requiring more actual ZEV sales.
These guys want your used-vehicle sales, profits
Beepi. Shift. Carvana. Vroom. Don't let the clever names fool you. These tech start-ups aim to take a bite out of the used-vehicle retail industry's lunch.
Applications open for '17 PACE Awards
The application process has opened for the 2017 Automotive News PACE Awards, which identify and honor game-changing and commercialized supplier innovations in technology and processes.
Overseas groups weigh Brexit challenges
Financial Times - 26 juin 2016 - 14:12
Many companies put investment and hiring plans on hold while others scent opportunity
Financial Times
Automotive Business Review
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French press / Presse française
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Commentaires récents
Il y a 27 semaines 2 jours
Il y a 27 semaines 2 jours
Il y a 3 an 30 semaines
Il n'y a pas d'événements prévus.


text:
Posted: 11/7/2008
This hotels stole money from my son after we decided not to stay. They tried to say "No refunds." I stayed here twice. It is a high prostitute area, known drug area and there was proof of drug usage on site. The rooms are filthy, roach infested, and if you walk on the carpet your feet are instantly BLACK. The rate go up on the weekend and the staff is nasty. Absolutely the worst hotel that I have ever stayed in.


text:
Senior man
Credit: Fotoyang - Take your shot.
Creative #: 148237274
License type: Royalty-freeRoyalty-free pricing is based solely on the size of the product you need, not the specific use. You don't have to pay any additional royalties on a use-by-use basis. Once you license a royalty-free product, you may use it multiple times for multiple projects without paying additional fees. (Pornographic, defamatory, libelous or otherwise unlawful use of any image is, of course, prohibited.)
Collection: Moment Open
Release info: Model released
- 65-69 Years,
- Active Seniors,
- Adult,
- Adults Only,
- Aging Process,
- Beijing,
- Black Background,
- China - East Asia,
- Chinese Ethnicity,
- Close-up,
- Color Image,
- Confidence,
- Front View,
- Gray Hair,
- Happiness,
- Individuality,
- Looking At Camera,
- One Man Only,
- One Person,
- One Senior Man Only,
- Only Men,
- People,
- Photography,
- Portrait,
- Senior Adult,
- Smiling,
- Studio Shot,
- Tank Top,
- Vertical,
- Vignette,
- Waist Up,
- Wrinkled,
Similar imagesSearch ResultsSame series
Senior Man Stock Photo65-69 Years,Active Seniors,Adult,Adults Only,Aging Process,Beijing,Black Background,China - East Asia,Chinese Ethnicity,Close-up,Color Image,Confidence,Front View,Gray Hair,Happiness,Individuality,Looking At Camera,One Man Only,One Person,One Senior Man Only,Only Men,People,Photography,Portrait,Senior Adult,Smiling,Studio Shot,Tank Top,Vertical,Vignette,Waist Up,WrinkledPhotographer Fotoyang - Take your shot.Collection: Moment Open © 2012 Zhang YangPortrait of senior man against black background.