Что обозначает показатель mttr
Расшифровка результатов теста на антитела к коронавирусу – таблица
Что такое антитела к коронавирусу?
Антитела (другое название – иммуноглобулины) – это специальные белки, которые вырабатываются и (или) продуцируются плазматическими клетками.
Что делают иммуноглобулины?
Иммуноглобулины образуются в ответ на попадание в организм чужеродных бактерий или вирусов. Они взаимодействуют с антигеном (специфическим участком вредителя) и обезвреживают его.
Таким образом наш иммунитет стоит на страже нашего здоровья.
Какие классы иммуноглобулинов существует?
Выделяют 5 классов иммуноглобулинов, некоторые из которых содержат подклассы.
IgA – секретируются на поверхности эпителия и присутствуют в слюне, слезе, на поверхности слизистых.
IgM – обнаруживается при первичном попадании антигена. Указывает на острый инфекционный процесс у человека.
IgG – основной класс иммуноглобулинов, защищающий от вирусов, бактерий, токсинов.
IgD – обнаруживают на поверхности развивающихся B-лимфоцитов. Функция не установлена.
IgE – секретируются при аллергической реакции немедленного типа.
Методы определения антител к коронавирусу
Существуют два метода определения иммуноглобулинов к коронавирусу в организме человека – ИФА и ИХА.
Иммуннохроматографический анализ – это качественный метод определения иммуноглобулинов классов М и G.
Качественный метод – это метод, позволяющий только определить наличие антител в организме. Иными словами, ответить на вопрос – есть они или нет.
Иммуноферментный анализ – это количественный метод определения иммуноглобулинов.
Количественный метол – не просто говорит о наличии антител, но и показывает их количество в единице объема крови.
Для анализов проводят забор венозной крови, следовательно, подготовка к процедуре стандартная:
Проводить исследование на пустой желудок (не есть за 8 часов до процедуры).
Воздержаться от питья воды за час до забора крови.
Для курильщиков – не курить за 2 часа до процедуры.
Что выбрать – качественный или полуколичественный анализ?
Для чего проводится качественный и количественный анализ?
Качественный анализ позволяет ответ на 2 вопроса:
Полуколичественный тест позволяет ответить на эти вопросы, а также определить количество иммуноглобулинов в организме.
Для чего определять количество иммуноглобулинов?
Определение количества антител позволяет определить, сформирован ли долговременный иммунитет. Именно он защищает на организм от повторного заболевания коронавирусом.
Показания к проведению исследования
Показаниями к проведению анализа является:
Наличие симптомов общего недомогания. В этом случае тестирование проводится для подтверждения диагноза.
При контакте с носителем или больным коронавирусной инфекцией.
По желанию – для лабораторной оценке иммунного статуса.
Как проводится тест
Необходимо прийти в Клинику МЕДЕЛ по предварительной записи.
Процедура проводится путем забора крови.
В Клинике МЕДЕЛ результаты изготавливаются в течение 1 дня.
Среднее время до отказа (MTTF). Когда производители дисков сообщают об этом, как следует интерпретировать их числа?
Среднее время до отказа (MTTF) обычно указывается в часах, и при выполнении некоторых вычислений кажется, что диск должен выйти из строя только после того, как прошло немало лет.
Кажется, что диски нуждаются в ремонте чаще, чем это. Кто-нибудь знает, почему это так?
Я понял, что в этом показателе есть что-то подозрительное. Здесь что-то не так?
MTTF = среднее время до отказа
MTTR = среднее время до восстановления
MTBF = среднее время между сбоями = MTTF + MTTR
MTBF часто более или менее равен MTTF, поскольку ремонт может занять час, а MTTF может составлять десятки тысяч часов. Но также MTBF часто не применяется, поскольку дефектные изделия не ремонтируются, а просто заменяются, потому что ремонт стоит дороже, чем замена.
там, где в начале много сбоев, потом долго, почти без сбоев, и ближе к концу жизни число сбоев снова возрастает. В жестких дисках также есть некоторые механические части, которые имеют более линейную кривую разрушения; это медленно нарастает с первого дня.
Например, если производитель говорит, что MTTF составляет 1000 000 часов (чаще всего это POH или часы включения ), это означает, что в среднем накопитель должен работать более 100 лет. Некоторые накопители прослужат дольше, некоторые выйдут из строя раньше. Таким образом, несмотря на 1000 000 часов, вполне возможно иметь сбой через 1000 часов. Однажды у меня не получилось в течение недели подвезти, а потом ты должен вспомнить кривую ванны. Запасной диск вращался счастливо в течение> 50 000 часов.
Если единица оборудования имеет MTBF использования 1 000 000 часов, это не означает, что любая часть оборудования может прослужить 1 000 000 часов. Скорее, это примерно означает, что если 1 000 000 единиц оборудования, которые находятся в пределах их номинального срока службы, работают каждый в течение одного часа, или 100 000 единиц работают в течение десяти часов (но все еще в пределах расчетного срока службы), или 60 000 000 в течение одной минуты и т. Д. в партии будет примерно один сбой. Обратите внимание, что расчетный срок службы является полностью ортогональным к MTBF. Рассмотрим следующие два типа виджетов:
Первый тип виджета будет иметь среднее время жизни около 1000 часов, а также MTBF около 1000 часов. Второй срок службы составляет в среднем 61 минуту, но MTBF составляет 1 000 000 000 часов в течение срока службы. Хотя может показаться странным сказать, что второе устройство имеет MTBF, который почти в миллиард раз превышает ожидаемый срок службы, MTBF вряд ли является бессмысленной цифрой.
Добавим к ответу Стивенвха: все известные производители дисков, как и производители электронных компонентов, проводят прогон новых устройств. На жестких дисках есть не только общая MTBF и MTTF, но и статистика отдельных сбоев для блоков дисков. Другими словами: некоторые части вращающегося «диска» на диске могут выйти из строя, в то время как большинство все еще читает / пишет нормально. Так называемые «плохие сектора» могут быть обнаружены и затем отображены встроенным программным обеспечением внутри привода.
Все накопители сегодня содержат в резерве дополнительные секторы, которые затем можно использовать вместо дефектных секторов. Это просто мера предосторожности производителя: если они этого не сделают, они не смогут продать диск за заявленную емкость. Если они встраивают дополнительные x% скрытых секторов в качестве резерва, они увеличивают стоимость примерно на — CFI
источник
Вы должны интерпретировать это как маркетинг. Они на самом деле не знают точного MTBF (среднее время между сбоями), поэтому они используют различные приемы для его оценки и показывают более высокие цифры для «корпоративных» дисков, чтобы оправдать их стоимость.
В действительности, производителям жестких дисков выгодно, чтобы их жесткие диски выходили из строя вскоре после окончания гарантии.
Как теория заговора, я считаю, что массовый сбой Seagate 7200.11 был ошибкой в реализации «запрограммированной смерти», приводившей к отказу дисков до истечения срока гарантии, поэтому они должны были «исправить» это путем обновления прошивки.
MTTR vs MTBF vs MTTF: A Simple Guide To Failure Metrics
Before we can get into MTTR, MTBF and MTTF, we want to be clear that maintenance metrics are not the same thing as maintenance KPIs. Maintenance metrics support the achievement of KPIs, which, in turn, support the business’s overall strategy. With so many maintenance performance metrics out there, it’s hard to know which one to choose.
In this article, we focus on the three most common failure metrics. We’ll make it simple for you to understand what they are, how they work, and when to use them. If you want to know more about the rest, we suggest visiting this piece on maintenance-related metrics and KPIs.
Introduction to failure metrics
To understand how to use MTTR, MTBF, and MTTF to your advantage, you need to understand the bigger picture of failure metrics.
What is equipment failure?
Failure exists in varying degrees (e.g., partial or total failure). In the most basic terms, equipment failure simply means that a system, component, or device can no longer produce desired results.
Even if a piece of manufacturing equipment is still running and producing items, it fails when it stops delivering the expected quantities or quality of products.
Why should I be tracking it?
Even the most efficient maintenance teams experience equipment failures. That’s why it’s critical to plan for them. Managing failure correctly means minimizing its negative impact. To help you effectively manage losses, several critical metrics should be monitored.
Tracking and understanding these metrics will eliminate guesswork and empower maintenance managers with the hard data they need to make informed decisions – helping you keep operational disruptions down to a minimum. This is your secret weapon, the source of your superpower!
What are the key failure metrics to pay attention to? We’ll discuss 3 of them:
Capturing reliable data from the get-go
Data is important. High-level failure statistics require a large amount of meaningful data. As we’ll show in the calculations below, the following inputs must be collected as part of your maintenance history.
Labor hours spent on maintenance
If you’re working with a modern CMMS like Limble, it will track maintenance hours automatically. Technicians report how much time it takes to complete a job every time they finish a WO. Over time, this data becomes invaluable. And it doesn’t take any extra time or work to obtain.
Technicians are prompted to enter “time spent” when closing a WO
The number of breakdowns and repairs
Limble gives you real-time views of all the maintenance tasks that are scheduled and completed — including ones that cause downtime. This lets you see what’s happening with all your assets easily and determine where there is room to improve efficiency.
Limble helps you track tasks that caused downtime
Operational time
You can calculate total operational time by subtracting asset downtime from the number of expected operating hours per week. (To make it easy on you, Limble lets you see how long it takes to get assets up and running again if they do fail).
An example of asset uptime report in Limble CMMS
Recording maintenance figures can be tedious. Still, it’s an essential part of improving maintenance operations – identifying items with a high failure rate and finding the root cause of those failures.
Doing this manually is painfully time-consuming. But it’s made simple with a mobile CMMS like Limble. Limble lets you quickly and easily log reliable data for labor hours and downtime on your phone while you’re performing maintenance tasks. More than that, Limble runs all the calculations of MTTR and MTBF automatically for you.
MTTR and MTBF report inside Limble CMMS
Collecting inaccurate data can cause a lot of issues. If data is missing or wrong, your failure metrics will be useless in informing decisions on improving operations. Worse still, if you don’t know that the information is unreliable, you might make operational decisions that could damage or slow production down.
Now that we got that out of the way, let’s focus on the things you came here for.
What is MTTR (Mean Time To Repair)?
Mean Time To Repair (MTTR) refers to the amount of time required to repair a system and restore it to full functionality. The MTTR clock starts ticking when the repairs start, and it goes on until operations are restored.
MTTR is a measure, but it’s not magic
MTTR is the metric you’ll use to prove operational excellence. You cannot, however, expect it to solve all your problems. It needs to be coupled with other metrics to help build a strong and valuable KPI that will speak directly in the greater company strategy.
MTTR can easily be distorted by outliers. If you have a single incident with a vastly different resolution or repair than others, your data might be skewed.
For example, let’s say the bulk of the water heaters in your building tend to suffer from broken thermostats. For most of them, this is relatively easy and inexpensive. But one is standing out from the rest. It’s making strange noises, has mineral buildup, and needs to be drained and the unit repaired before a costly leak or explosion. It takes a lot longer to fix that thermostat. As a result, your mean time to repair a thermostat will seem unusually high.
Furthermore, MTTR is not time-bound. It cannot calculate for on or off-peak usage times, meaning that it cannot accurately report back on overuse or quiet periods impacting repair times.
Because there are so many ways to interpret MTTR, success will only come when you have a clear definition of what it means within your organization. You’ll need to combine this with a well-trained team and the systems to manage the information. Find the right set of metrics that give you the complete picture you are looking for.
Why is MTTR helpful?
Assets under repair equal downtime. Regular system failures and lengthy downtime periods have a huge effect on productivity. That, in turn, has an even bigger impact on business results. This is especially the case for processes that are particularly sensitive to failure.
In a manufacturing environment, long mean time to repair leads to missed production deadlines, increased labor costs, loss of revenue, and various operational issues.
Understanding MTTR is an important tool for any organization because it tells you how well you are responding to issues with your assets. Most organizations work to shorten MTTR with an in-house maintenance team supported with the necessary resources, tools, spare parts, and CMMS software.
How to calculate MTTR?
To calculate MTTR, you need to add all the time you’ve spent on the repairs and divide it by the number of repairs you performed.
Imagine a pump that fails three times throughout a workday. The first repair lasted for 30 minutes, while the other two repairs lasted only 15 minutes. In this case:
MTTR = (30 + 15 +15) / 3
The average time for performing repairs on that pump is 20 minutes.
A special note about MTTR calculation —
Each failure will have a different severity level, so while some will require days to diagnose and repair, others could take minutes to fix. MTTR can give you an average of what to expect.
In Limble, you can get two views of MTTR. They can help draw different conclusions:
1.) MTTR for a specific asset, which is calculated based on how many tasks have caused downtime for this asset only.)
2.) Combined MTTR for all assets, which is calculated based on how many tasks have caused downtime for all assets within a certain time frame.
If you are only working with a small number of units, you may want to remove any data that stands out. This can skew your results.
For example, somebody could make a huge mistake during the repair process, like accidentally cutting through a wire or breaking a piece of the unit while fixing the original problem. This could turn a small repair into one that lasts a few days if you didn’t have the part in or know-how to fix it.
What can MTTR tell you?
The MTTR figure itself is excellent, but a lot more data analysis is required to get to a specific action. MTTR can tell you:
When to use MTTR?
Use MTTR when you want to:
Tactics to reduce MTTR
Every efficient maintenance system needs to look at how to reduce MTTR as much as possible. That can be done in a few different ways:
Mean Time to Repair vs. Mean Time to Recovery
MTTR has A LOT of different meanings. The two most relevant for our discussion are “mean time to repair” and “mean time to recovery.”
Mean Time To Recovery measures the time between when the failure is first discovered until the equipment returns to operation. So, in addition to repair time, testing period, and return to normal operating condition, it captures failure notification time.
Although these terms are often used interchangeably, they need to be more clearly defined when it comes to Service Level Agreements (SLAs) and maintenance contracts so that all parties agree on exactly what they mean and what they are measuring.
What is MTBF (Mean Time Between Failures)?
Mean Time Between Failures measures the time it takes from one equipment failure to the next time it fails. This gives you a better idea of how long equipment can stay running over a given period between unplanned breakdowns. It’s a way for you to plan around the unexpected.
So, while MTTR impacts availability, MTBF measures availability and reliability. The higher the figure of the MTBF, the longer the system will likely run before failing.
Why is MTBF helpful?
Because equipment failure can be expensive and damaging to the organization, you need to be on top of unexpected breakdowns as much as possible. MTBF is an important indicator of expected performance. If the MTBF value is low, it means you are experiencing a significant number of breakdowns, which likely means there’s a deeper issue to uncover.
Manufacturers can use the mean time between failures as a quantifiable reliability metric during many product design and production stages. It is commonly used today in mechanical and electronic systems design, safe plant operations, product procurement, etc.
MTBF does not consider planned maintenance, but it can still be used to calculate the frequency of inspections for preventive replacements.
If it is known that an asset will likely run for a certain number of hours before the next failure, introducing preventive actions like lubrication or recalibration can help prevent that failure.
Essentially, it helps save you money, reduces downtime, and makes you look good at your job (and who doesn’t want that?).
How to calculate MTBF?
The equation for MTBF is simple. It is the sum of operating time divided by the number of failures.
Building on the example of the pump we mentioned under MTTR, out of the expected runtime of ten hours, it ran for nine hours. It failed for one hour spread over three occasions. So:
MTBF = 9 hours / 3 repairs
The pump is failing every 3 hours on average.
Keep in mind this is a very simplified example. You will generally want a much bigger sample of information to work with to get a more accurate prediction. As you can see from the example above, we did not include the repair time in the calculation of MTBF.
Other common factors can influence the MTBF of systems in the field. A big one is the fact that we have humans doing the work. For example, low MTBF could either indicate poor handling of the asset by its operators or a poorly executed repair job in the past.
When calculating MTBF, you won’t take predictive or preventive maintenance into account or routine parts replacements. Although predictive and preventative maintenance can sometimes cause brief outages, they are not breakdowns. You will simply calculate the time from the end of the last breakdown as the machine was back in service to the following breakdown.
You need to come in with the expectation that failure will happen at some point.
What can MTBF tell you?
Because of where MTBF falls in the process, it is often coupled with other maintenance strategies. MTBF can help inform your decisions by telling you:
When to use MTBF?
Use it to start conquering downtime. This is by far the most important application of MTBF. Using MTBF, you will also be able to predict, prevent and prevail over the bulk of your unplanned breakdowns. You’ll be able to use it for:
Tactics to increase MTBF
There are small things you can do to increase the time between failures. Some of them are:
What is MTTF (Mean Time To Failure)?
Mean Time To Failure is a very basic measure of reliability used for non-repairable systems. It represents the length of time that an item is expected to last in operation until it needs to be replaced.
MTTF can be used to represent the lifetime of a product or device. Its value is calculated by looking at a large number of the same kind of items over an extended period and tracking how long they last.
In the manufacturing industry, MTTF is one of the many metrics commonly used to evaluate the reliability of manufactured products. However, there is still a lot of confusion in differentiating between MTTF and MTBF because they are both somewhat similar in definition. This is resolved by remembering that MTBF is used when referring to repairable items, while MTTF is used for non-repairable items.
Why is MTTF helpful?
MTTF is important because it helps estimate the lifespan of products that are not repairable. Some common examples of these products range from items like fan belts in automobiles to light bulbs in our homes and offices.
MTTF is particularly useful as a reliability metric. Engineers can use it to estimate how long a component would last as part of a larger piece of equipment. This is especially true where the entire business process is sensitive to the failure of the equipment in question. Shorter MTTF means more frequent downtime as the failing items need to be replaced.
How to calculate MTTF?
MTTF is calculated as the total time of operation, divided by the total number of units being tracked.
Let’s assume we tested 3 desktop hard drives. The first one failed after 500,000 hours, the second one failed after 600 000 hours, and the third hard drive failed after 700,000 hours in use. MTTF in this instance would be:
MTTF = (500,000 + 600,000 + 700,000) / 3 units
MTTF = 600,000 hours
We can now assume that this particular type and model of the hard drive is likely to fail after 600,000 hours of use.
What can MTTF tell you?
Mean Time to Failure can be used for:
When to use MTTF?
Suppose you are looking at investing in new equipment that will replace your current equipment. It’s important to know how long they are expected to last. This will be a core component when you are putting your budget together.
MTTF will inform you of a lot of the spending on both your capex and opex budgets. How often will you be replacing things, and at what costs?
You can sometimes find information about MTTF from the OEM. While we are always optimistic that they are correct, they can sometimes be misleading. Reach out to other maintenance managers to get their input if you can. Always run your own MTTF reporting to keep track of your asset lifespans.
Tactics to increase MTTF
Other noteworthy maintenance metrics related to failure
There are at least 10 different metrics, if not more, with overlap between many of them. This article has covered the three most popular. Still, there are a few others we’d like to introduce you to so that you can make an informed decision about the metric set that’s right for you:
Luckily, Limble allows the people responsible for assigning work to see this in real-time. They can quickly and easily reshuffle work order assignments to help alleviate overload and keep your team as productive as possible.
Tracking maintenance metrics with Limble CMMS
Tracking maintenance metrics sounds like a lot of work, and it can be if it’s not automated.
Our system manages this both on the global level for all assets and reporting on each individual asset.
As long as the customer updates each task with all the data, these maintenance metrics will be tracked automatically (example in the image below):
When it comes to maintenance metrics and your KPIs, Limble lets you build out custom dashboards for every report you need. Your team does the work; Limble does the rest.
An example of Limle’s custom dashboard
When you use Limbles Custom Dashboards, you’ll be able to:
Using Limble, your maintenance team can access all the information about an asset’s history and past repairs to quickly get to the root cause of the problem and cut down on the amount of troubleshooting it takes to find the solution.
Limble is mobile-friendly, making it easy for you to access important information on your mobile device at all times. No more running between your desktop and the job to get the information you need, making your jobs less frustrating to execute and speeding up your responsiveness.
What’s next?
At Limble, we know that it’s up to you to make sure the equipment is available, in perfect working order. You are the hero of uptime, as well as plant operations and safety.
When you have a handle on the failure metrics and calculations to get to them, you can build better asset management strategies and improve your overall maintenance processes.
By calculating failure metrics and planning maintenance based on the results, you can also reduce their organization’s dependence on reactive maintenance in favor of proactive methods that will prevent unexpected breakdowns in the first place.
Let Limble CMMS take the guesswork out of metrics measurement and automate the process for you. Reach out to us via email, and we’ll get in touch to see how we can make your life easier by placing your maintenance management in the palm of your hand.