And any business faces the task of reducing non-production time. If necessary equipment or the process does not work, this reduces the planned output, followed by a reduction in the profit and margin of the business.
The key question this metric helps answer is how effectively are we managing our processes or equipment?
Simple is any production time during which a process or equipment is unavailable due to breakdowns (errors) or repairs (maintenance).
Equipment downtime is commonly associated with manufacturing industries; process downtime can occur in any industry. Take, for example, call centers, which can experience interruptions in the delivery of assistance over the phone, or hospitals, which are characterized by downtime of diagnostic equipment.
Downtime analysis gives companies the ability to evaluate the efficiency of internal production processes.
How to take measurements
Information collection method
The data for calculating a key performance indicator (KPI) comes directly from the process or equipment, or from reports.
Formula
The downtime of a process or equipment can be calculated using the relationship:
Downtime = (TAt / PPTt) × 100%
where TAt is the actual production time of the process or equipment for a given period t; PPT t is the planned production time of a process or equipment for a given period t.
KPI can be obtained in absolute terms:
Downtime = PPTt - TAt.
Downtime can be measured continuously (especially when automating a process) and serve as an indicator when a predetermined value has been reached. At the same time, information about downtime can be submitted on a monthly or quarterly basis.
The source of information may be the equipment itself, since many types production equipment track downtime automatic mode. The same applies to processes if there is an automatic monitoring system. IN in some cases manual entries required.
The cost of measuring downtime is modest and depends on the data already available. If equipment and processes generate downtime information automatically, the calculations are relatively simple. Costs increase with manual data collection.
Target values
The goal for this KPI should be a value equal to zero, subject to the exclusion or at least minimization of any unplanned interventions in manufacturing process- in particular, if the process or equipment does not operate 24 hours a day, then maintenance may be carried out during non-production hours.
Example. Consider the radiology department of a hospital, which has two CT scanners for which we will determine the downtime. At least one of the tomographs must be ready to work around the clock, and during normal business hours (from 9.00 to 17.00) both devices must be ready to work.
Downtime is considered to be the time during which at least one tomograph is not ready for operation during normal business hours. Critical downtime is considered to be the time during which both tomographs are not ready for operation.
Let's look at an example based on one day.
Tomograph No. 1 was not working from 13.00 to 15.00 due to a breakdown and from 19.00 to 22.00 due to routine maintenance.
Tomograph No. 2 did not work from 19.00 to 20.00 due to a breakdown.
(2 hours / 8) × 100% = 25%, or 2 hours.
Downtime of tomograph No. 1 Downtime of tomograph No. 2 = 0%.
Critical downtime = 1 / 24 = 4.16% or 1 hour.
Notes
When measuring equipment downtime, you need to understand the cost component, such as the direct labor costs you incur by paying wages to the equipment operator when it is idle.
Availability factor
Equipment availability factor is the ratio of failure-free operation time to the sum of failure-free operation and equipment recovery time taken over the same calendar period. This characteristic will be further denoted as K .
According to this definition
where t r is the time of non-failure operation of the equipment, t in – recovery time, i.e. time spent on equipment maintenance and repair.
The composition t does not include storage time and the time spent preparing the equipment for operation after its downtime. This is explained by the fact that downtime is not determined by reliability, and therefore cannot be its characteristic. The time spent on preparation is small compared to the recovery time, and it poorly characterizes the reliability of the equipment, since it depends on many other factors (ease of use, qualifications of maintenance personnel, the need to refill with fuel, lubricants, etc.).
From the definition of the availability factor, it is clear that it depends on the operating time of the equipment, during which K g is determined. The distribution of the operating time of the equipment and its recovery time can be represented as follows (Fig. 2.1):
;
And the availability factor can be written as:
(2.2)
Expression (2.2) is a statistical definition of the availability factor. To move to a probabilistic determination, it is advisable to use the average values of failure-free operation time and recovery time. Then
where t av is the average time between adjacent failures, t b is the average recovery time.
Expression (2.3) establishes the relationship between the availability factor and the main quantitative characteristics of reliability. Since , then
, (2.4)
Since at t ¥ the average failure rate tends to , the system availability coefficient during long-term operation tends to a constant value:
Expression (2.5) shows the probability that the system is operational at any time t. It is a probabilistic determination of the availability factor. It should be borne in mind that expression (2.4) does not show the probability of proper operation of the system at any time t during an unsteady operation process.
Recovery time and therefore significantly depend on reliability. The higher the reliability, the less often the equipment is repaired, and, consequently, the less. If we take into account that this is also a function of the average failure rate, it becomes clear that the availability factor quite fully characterizes the reliability of the equipment.
Since it depends on the recovery time, this coefficient also characterizes performance equipment (ease of use, cost of operation, etc.), quality service personnel etc. However, the dependence of the availability factor on the recovery time often makes it difficult to assess the reliability of equipment, since by its value it is impossible to judge the time of continuous operation of the equipment without failures.
The specified property of the availability factor limits its use and does not allow it to be considered universal characteristic equipment, namely reliability and ease of use.
Forced downtime factor
Forced downtime rate is called the ratio of recovery time to the sum of recovery time and failure-free operation of equipment taken over the same calendar period. This coefficient is denoted K p and, according to definition, is written as follows:
.
(2.6)
Using the average times of failure-free operation and recovery, we can write:
From a comparison of expressions (2.1) and (2.6) it is clear that the forced downtime coefficient and the availability coefficient are related by the relationship:
. (2.7)
For long-term equipment, the downtime coefficient tends to a constant value, described by the expression:
Expression (2.8) determines the probability that in a steady-state operation the system will be in a faulty state at any arbitrarily chosen point in time. From expressions (2.7) and (2.8) it is clear that the forced downtime coefficient is a derivative of the availability coefficient. Therefore, it has all the advantages and disadvantages inherent in the availability factor.
Prevention rate
Prevention rate is called the ratio of recovery time to failure-free operation time, taken over the same calendar period. It is designated K pr and is often called the prevention norm. According to definition
(2.9)
or in a probable interpretation
From expressions (2.8) and (2.10) the following relationship is obvious:
(2.11)
Thus, just like the forced downtime coefficient, the prevention coefficient is a derivative of the availability coefficient and, therefore, has the same advantages and disadvantages as K g.
Prevention frequency
Frequency of prevention is the ratio of the number of equipment inspections and repairs to the sum of uptime and recovery time taken over a certain calendar period.
The frequency of prophylaxis is further denoted by K w . According to this definition
, (2.13)
where n p – number of equipment repairs, n os – number of preventive inspections, t p – time of proper operation of the equipment for a certain calendar period, t in – recovery time.
Let's give a probabilistic interpretation to the coefficient K w. Let us divide the numerator and denominator of expression (2.13) by n p. Then we get:
(2.14)
.
The frequency of prevention, like all the coefficients considered, characterizes the reliability of the equipment and the ease of its operation. From expressions (2.13) and (2.14) it is clear that the more reliable the equipment (the larger t av) and the fewer preventive examinations (n av), the lower the frequency of prevention.
It should be noted, however, that a decrease in the number of preventive inspections (n os) can lead to a decrease in the average time between adjacent failures. This may, in turn, lead to an increase in the frequency of maintenance and a decrease in the availability of equipment. Apparently, there is an optimal number of preventive measures at which the frequency of prevention (K w) and the readiness rate (K g) are the most beneficial.
The frequency of preventive maintenance allows you to determine the required number of preventive inspections and repairs. In this regard, it complements the coefficients that take into account the forced downtime of equipment and, together with them, gives a good idea of the reliability and ease of use of the equipment.
22. Indicators of the use of machinery and equipment.
In the analysis of equipment operation, indicators of the number of equipment, its operating time and power are used. Equipment groups:
Available equipment;
Installed equipment;
Equipment actually used in production;
Equipment under repair or modernization;
Backup equipment.
The degree of use of equipment in production is characterized by the following economic indicators:
Availability equipment utilization rate;
Usage rate of installed equipment.
The difference between the amount of cash and installed equipment, multiplied by the planned average annual production per unit of equipment - this is a potential reserve for production growth due to equipment.
To characterize the degree of extensive loading of equipment, the balance of its loading time is studied, including:
Calendar time fund - the maximum possible operating time of the equipment (calculated as the product of the number calendar days, number of hours in a day (24) and number of pieces of equipment);
Regular time fund (the product of the number of pieces of equipment, the number of working days and the number of hours of daily work);
Planned fund - the time the equipment operates according to plan (includes the time the equipment is in scheduled repairs and on modernization);
Actual time spent on equipment.
To characterize the use of equipment operating time, the following coefficients are applied:
Using the calendar fund of time;
Use of the regime fund of time;
Use of the planned fund times.
To comprehensively characterize the use of equipment, an integral load coefficient is used, obtained by multiplying the intensive load coefficient by the extensive load coefficient.
The dynamics of these indicators and the reasons for their changes are also studied.
For homogeneous equipment, the change in production volume is also calculated due to:
Quantities of equipment;
The extent of its use;
Intensity of its use.
The influence of these factors can be calculated using the chain substitution method.
The influence of the average hourly output of equipment on the volume of production is established on the basis of studying the implementation of the plan of innovative activities, which includes such indicators as:
Replacement of old equipment;
Modernization of existing equipment;
Improvement of technology.
A decrease in production output can be caused by reasons such as:
Excessive all-day equipment downtime;
Excessive intra-shift equipment downtime;
Reduced shift ratio.
Due to more complete use of equipment, the enterprise can have reserves for increasing production.
When analyzing the use of machinery and equipment, it is important to identify the equipment available, installed and actually operating.
1. Usage rate of all available equipment (K1)
K1 = installed equipment / available equipment
2. Degree of use of installed equipment (K2)
K2 = operating equipment / installed equipment
If part of the equipment is inactive, then it is necessary to identify the reasons for this phenomenon. It may turn out that it is unnecessary and does not correspond to the nature of the product being manufactured. In this case, it should be included in the list of sales due to the fact that the enterprise suffers losses from idle equipment.
The next stage is an analysis of the existing equipment. The performance of existing equipment depends on the intensive and extensive factors of its use.
An indicator reflecting the action of intensive factors is equipment productivity per 1 machine-hour or product output per 1 machine-hour or machine-hour.
Equipment intensive use factor.
Kinten = Product output per 1 machine-hour according to the report / Product output per 1 machine-hour according to the plan
Indicators reflecting the influence of extensive factors are the operating time of equipment, in particular, the number of machine and machine hours worked.
To characterize the use of equipment over time, the coefficient of extensive use of equipment is calculated:
Kext = fact. work time, in machine hours / equipment operating time according to plan
The analysis examines the degree of use of calendar, routine, planned and actual equipment operating time funds. Comparison of actual and planned calendar funds of time allows us to establish the degree of implementation of the plan for putting equipment into operation in terms of quantity and timing; calendar and scheduled - opportunities for better use of equipment by increasing the shift ratio, and scheduled and scheduled - time reserves by reducing time spent on repairs.
Based on a study of the use of equipment over time, identifying a reserve for increasing production volume by eliminating all-day and intra-shift equipment downtime.
For a detailed analysis of capital productivity of machinery and equipment, information is required on the following indicators:
Product volume (N)
Average annual cost of the active part of funds in the total cost of fixed assets (Fmash)
Ud. weight of the active part of the funds in the total cost of fixed assets (UDak)
Return on assets of the active part (λak)
Number of technological (operating) equipment (K)
Equipment worked per year, machine-hour
Worked out per unit of equipment:
Equipment shift ratio
Kcm = number of operating equipment per day / number of available equipment
Kcm = number of machine-shifts worked / number of machine-days worked
Average length of shifts in hours
Product output per machine-hour, r
Most often, equipment downtime as a result of problems with the electric motor accounts for half of all malfunctions. May be considered simple form, on which losses are calculated. To do this, you need to take some downtime. Let it be 100%. As a result, it turns out that the time for dismantling and turning off the electric motor is 5%, the time for transportation to and from the service center is 5%, the time for repairing equipment is 80%, installation and testing is 5%.
Every manager knows the cost of the product and the time it takes to produce it. Based on this, you can very simply outline the costs that the enterprise will incur when emergency stop equipment.
Let a be the number of units of products that are produced in a given time. Let's say an enterprise can produce 300 alloy wheels for cars in 8 hours, it turns out that 37.5 disks are produced per hour. We introduce another variable - the cost of the disk, which is 1000 rubles.
To determine the cost of direct losses as a result of equipment downtime per hour, it is necessary to calculate C=A*B. As a result, we get C = 37,500 rubles. in 1 hour.
It turns out that if the repair period for the electric motor is 80 hours, and taking into account the costs of transportation, dismantling and installation, there will be 100 hours of downtime, we calculate: 100 * C, which will be 3,750,000 rubles. for the entire period of inactivity.
Please note that this amount only includes direct costs. In addition, there is the constant cost of rent, energy, staff salaries, securing contractual and loan obligations, and, of course, the very costs of repairing failed equipment.
Most of the time is devoted specifically to repairing electrical equipment; it can be reduced; for this purpose, there is a service for quick replacement of the electric motor.
