Iec 61508 3 pdf free download

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These sections identify methods designed to contribute to the achievement of software safety. Although module testing can be performed by writing custom code for the purpose, the use of a certified, proven test tool like the TBrun component of the LDRA tool suite is likely to be much more cost effective unless the code base is very small. The integrated software is to be proven on the target programmable electronic hardware to ensure compatibility and to meet the requirements of the intended safety integrity level.

Structural code coverage analysis can be supported by unit test, system test, or a combination of the two, operating in tandem. For instance, a preferred approach might be to use dynamic system test to generate coverage of most of the source code, and to supplement it using unit tests to exercise code constructs which are inaccessible during normal operation. To complete the structural coverage analysis, boundary values could be provided manually or generated automatically to check the permissible and inadmissible ranges.

This section details how it is to be confirmed that the integrated system complies with the software safety requirements specification at the required safety integrity level. During development, the TBrun component of the LDRA tool suite is used to confirm that the functions of a system or program behave as the specification dictates.

The stored test data is reused for regression analysis to confirm ongoing adherence to the specified requirements. Automated requirements tracing complements this approach by providing forward and backward traceability between the software safety requirements specification and software safety validation plan.

Section 7. It is a technique used to determine whether a change or an enhancement to a software system has affected, or has the potential to affect, the existing system. When a change is made and impact analysis is complete, the extent of the re-verification required will be influenced by the number of software modules affected, the criticality of the affected software modules and the nature of the change. Possible decisions are. The TBrun component of the LDRA tool suite makes re-verification easy to achieve by storing test data for subsequent automated regression test.

Like many other safety critical standards including ISO , IEC , and EN , IEC references the need for due consideration of response timing for time-critical applications, and memory constraints. The WCET of a computational task is the maximum length of time that the task could take to execute in a specific environment. Hard real-time systems need to satisfy stringent timing constraints imposed by the nature of the functions they fulfil. Unfortunately, it is not possible in general to calculate definitive upper bounds on execution times for programs.

There are further complications in the case of multicore processors. The use of additional cores results in resources being shared between them. Time-related delays occur as users wait for access. These interference channels cause the execution-time distribution to spread. Instead of a tight peak, the distribution of execution times becomes wide with a long tail. This page presents a practical, compliant approach to addressing this problem.

It involves the optimisation of system configuration by means of interference research through measured execution times using the TBrun component of the LDRA tool suite supported by the optional TBwcet module. Where proof of fitness-for-purpose within a specified tool chain is required, the LDRA Tool Qualification Support Packs TQSPs contain the test cases to demonstrate both the structural coverage analysis and programming rules checking capabilities of the tool suite itself.

In addition, associated documentation for the development and verification of the product is provided, including plans, procedures, and expected results. Functional safety with legacy software � case study. Clarifying and fulfilling test tool qualification requirements. The safety integrity levels of IEC and a revised proposal. Email: info ldra. Gomathi Gunasekaran. Cira Rojas.

Juan Diego Toledo Valera. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Download Free PDF.

Functional safety and IEC A basic guide. Velibor Stokic. Read Now Download. Related Papers. Assessment of hardware safety integrity requirements. Cross domain comparison of System Assurance. Addressing the safety of programmable electronic mining systems: lessons learned. This material may be freely reproduced, except for advertising, endorsement or commercial purposes. All rights reserved. IEC has no responsibility for the placement and context in which the extracts and contents are reproduced; nor is IEC in any way responsible for the other content or accuracy thereof.

Section 2 of this document gives an informal definition of functional safety, describes the relationship between safety functions, safety integrity and safety-related systems, gives an example of how functional safety requirements are derived, and lists some of the challenges in achieving functional safety in electrical, electronic or programmable electronic systems.

Section 3 gives details of IEC , which provides an approach for achieving functional safety. It explains that IEC can be applied as is to a large range of industrial applications and yet also provides a basis for many other standards. We begin with a definition of safety.

This is freedom from unacceptable risk of physical injury or of damage to the health of people, either directly or indirectly as a result of damage to property or to the environment. Functional safety is part of the overall safety that depends on a system or equipment operating correctly in response to its inputs. For example, an overtemperature protection device, using a thermal sensor in the windings of an electric motor to de-energise the motor before they can overheat, is an instance of functional safety.

But providing specialised insulation to withstand high temperatures is not an instance of functional safety although it is still an instance of safety and could protect against exactly the same hazard. Neither safety nor functional safety can be determined without considering the systems as a whole and the environment with which they interact.

If so, then it has to be taken into account in an appropriate manner in the design. Functional safety is just one method of dealing with hazards, and other means for their elimination or reduction, such as inherent safety through design, are of primary importance.

The term safety-related is used to describe systems that are required to perform a specific function or functions to ensure risks are kept at an accepted level.

Such functions are, by definition, safety functions. The safety function requirements are derived from the hazard analysis and the safety integrity requirements are derived from a risk assessment. The higher the level of safety integrity, the lower the likelihood of dangerous failure.

Any system, implemented in any technology, which carries out safety functions is a safety- related system. A safety-related system may be separate from any equipment control system or the equipment control system may itself carry out safety functions. In the latter case the equipment control system will be a safety-related system.

Higher levels of safety integrity necessitate greater rigour in the engineering of the safety-related system. The blade is accessed for routine cleaning by lifting the cover. The cover is interlocked so that whenever it is lifted an electrical circuit de-energises the motor and applies a brake. In this way the blade is stopped before it could injure the operator.

In order to ensure that safety is achieved, both hazard analysis and risk assessment are necessary.

For this machine it might show that it should not be possible to lift the hinged cover more than 5 mm without the brake activating and stopping the blade. Further analysis could reveal that the time for the blade to stop must be one second or less. Together, these describe the safety function. The aim is to ensure that the safety integrity of the safety function is sufficient to ensure that no one is exposed to an unacceptable risk associated with this hazardous event.

The risk also depends on how frequently the cover has to be lifted, which might be many times during daily operation or might be less than once a month. The level of safety integrity required increases with the severity of injury and the frequency of exposure to the hazard.

Both the safety function and its safety integrity specify the required behaviour for the systems as a whole within a particular environment.

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The principles of reducing risk to as low as reasonably practicable are discussed in Annex C. In deciding risk criteria to be applied for a specific hazard, the risk profile over the life of the asset may need to be considered. Residual risk will vary from low just after a proof test or a repair has been performed to a maximum just prior to proof testing. This may need to be taken into consideration by organisations that specify the risk criteria to be applied. If proof test intervals are significant, then it may be appropriate to specify the maximum hazard.

NOTE 1 The first part of the definition specifies that the safety-related system must perform the safety functions which would be specified in the safety functions requirements specification. For example, the safety functions requirements specification may state that when the temperature reaches x, valve y shall open to allow water to enter the vessel. NOTE 2 The second part of the definition specifies that the safety functions must be performed by the safetyrelated systems with the degree of confidence appropriate to the application, in order that the tolerable risk will be achieved.

For example, a person could receive information, on the state of the EUC, from a display screen and perform a safety action based on this information. Safety integrity is defined as the probability of a safety-related system satisfactorily performing the required safety functions under all the stated conditions within a stated period of time 3. Safety integrity relates to the performance of the safety-related systems in carrying out the safety functions the safety functions to be performed will be specified in the safety functions requirements specification.

Safety integrity is considered to be composed of the following two elements. Hardware safety integrity; that part of safety integrity relating to random hardware failures in a dangerous mode of failure see 3.

The achievement of the specified level of safety-related hardware safety integrity can be estimated to a reasonable level of accuracy, and the requirements can therefore be apportioned between subsystems using the normal rules for the combination of probabilities. It may be necessary to use redundant architectures to achieve adequate hardware safety integrity. Systematic safety integrity; that part of safety integrity relating to systematic failures in a dangerous mode of failure see 3.

Although the mean failure rate due to systematic failures may be capable of estimation, the failure data obtained from design faults and common cause failures means that the distribution of failures can be hard to predict.

This has the effect of increasing the uncertainty in the failure probability calculations for a specific situation for example the probability of failure of a safetyrelated protection system. Therefore a judgement has to be made on the selection of the best techniques to minimise this uncertainty.

Note that it is not the case that measures to reduce the probability of random hardware failure will have a corresponding effect on the probability of systematic failure. Techniques such as redundant channels of identical hardware, which are very effective at controlling random hardware failures, are of little use in reducing systematic failures such as software errors.

The mode of operation relates to the way in which a safety function is intended to be used with respect to the frequency of demands made upon it which may be either: low demand mode: where frequency of demands for operation made on the safety function is no greater than one per year; or high demand mode: where frequency of demands for operation made on the safety function is greater than one per year; or continuous mode: where demand for operation of the safety function is continuous.

Tables 2 and 3 of IEC detail the target failure measures associated with the four safety integrity levels for each of the modes of operation.

The modes of operation are explained further in the following paragraphs. Figure A. The resulting risk model may therefore differ from that shown in Figure A.

The various risks indicated in Figure A. To prevent unreasonable claims for the safety integrity of the EUC control system, this standard places constraints on the claims that can be made see 7. The necessary risk reduction is achieved by a combination of all the safety protective features.

The necessary risk reduction to achieve the specified tolerable risk, from a starting. The general model assumes that: there is a EUC and a control system;. It can be lower if other risk reduction measures reduce the probability of harm. During the determination of the safety integrity levels it is important to take account of common cause and dependency failures.

The models shown above in Figures A. There are many applications where this is not the case. Examples include the following: 1 Where a dangerous failure of an element within the EUC control system can cause a demand on a safety-related system and the safety-related system uses an element subject to failure from the same cause. An example of this could be where the control and protection system sensors are separate but common cause could lead to failure of both see Figure A. An example would be where the same type of sensor is used in two separate protection systems both providing risk reduction for the same hazard see Figure A.

In such cases the actual PFD avg achieved by the combination of multiple systems will be significantly higher than the PFD avg suggested by the multiplication of the PFD avg of the individual systems. Consideration should be given as to whether the final arrangement is capable of meeting the necessary systematic capability and the necessary probability of dangerous random hardware failure rates relating to the overall risk reduction required.

The effect of common cause failures is difficult to determine and often requires the construction of special purpose models e. The effect of common cause is likely to be more significant in applications involving high safety integrity levels.

In some applications it may be necessary to incorporate diversity so that common cause effects are minimised. It should however be noted that incorporation of diversity can lead to problems during design, maintenance and modification. Introducing diversity can lead to errors due to the unfamiliarity and lack of operation experience with the diverse devices. When multiple layers of protection are used to achieve a tolerable risk there may be interactions between systems themselves and also between systems and causes of demand.

As discussed above in A. Evaluation of the interactions between safety layers and between safety layers and causes of demand can be complex and may need the development of a holistic model e. The model may include all safety layers for calculating the actual risk reduction and all causes of demand for calculating the actual frequency of accident.

This allows the identification of minimal cut sets i. It is important that the distinction between risk and safety integrity be fully appreciated. Risk is a measure of the probability and consequence of a specified hazardous event occurring. This can be evaluated for different situations EUC risk, risk reduction required to meet the tolerable risk, actual risk see Figure A. The tolerable risk is determined by consideration of the issues described in A. Once the tolerable risk has been set, and the necessary risk reduction estimated, the safety integrity requirements for the safety-related systems can be allocated see 7.

NOTE The allocation is necessarily iterative in order to optimize the design to meet the various requirements. To cater for the wide range of necessary risk reductions that the safety-related systems have to achieve, it is useful to have available a number of safety integrity levels as a means of satisfying the safety integrity requirements of the safety functions allocated to the safetyrelated systems.

Software systematic capability is used as the basis of specifying the safety integrity requirements of the safety functions implemented in part by safety-related software. In this standard, four safety integrity levels are specified, with safety integrity level 4 being the highest level and safety integrity level 1 being the lowest.

The safety integrity level target failure measures for the four safety integrity levels are specified in Tables 2 and 3 of IEC Two parameters are specified, one for safetyrelated systems operating in a low demand mode of operation and one for safety-related systems operating in a high demand or continuous mode of operation.

NOTE For safety-related systems operating in a low demand mode of operation, the safety integrity measure of interest is the probability of failure to perform its design function on demand. For safety-related systems operating in a high demand or continuous mode of operation, the safety integrity measure of interest is the average probability of a dangerous failure per hour see 3.

The requirements for the safety requirements allocation phase are given in 7. Safety integrity requirements are associated with each safety function before allocation see 7. A safety function may be allocated across more than one safety-related system. The objective is to reduce the consequences associated with a hazardous event rather than its frequency.

When determining the safety integrity requirements it should be recognised that when making judgments on the severity of the consequence, only the incremental consequences should be considered. That is, determine the increase in the severity of the consequence if the function did not operate over that when it does operate as intended.

This can be done by first considering the consequences if the system fails to operate and then considering what difference will be made if the mitigation function operates correctly. In considering the consequences if the system fails to operate there will normally be a number of outcomes all with different probabilities. Event tree analysis ETA may be a useful tool for this. This annex lists a number of techniques that can be used for determination of safety integrity levels.

None of the methods are suitable for all applications and users will need to select the most suitable. In selecting the most appropriate method consideration should be given to the following factors: 1 the risk acceptance criteria that need to be met. Some of the techniques will not be suitable if it is required to demonstrate that risk has been reduced to as low as reasonably practicable; 2 the mode of operation of the safety function. Some methods are only suitable for low demand mode; 3 the knowledge and experience of the persons undertaking the SIL determination and what has been the traditional approach in the sector; 4 the confidence needed that the resulting residual risk meets the criteria specified by the user organisation.

Some of the methods can be linked back to quantified targets but some approaches are qualitative only; 5 more than one method may be used. One method may be used for screening purposes followed by another more rigorous approach if the screening method shows the need for high safety integrity levels; 6 the severity of the consequences. Whatever method is used all assumptions should be recorded for future safety management.

All decisions should be recorded so that the SIL assessment can be verified and be subject to independent functional safety assessment. It can be used in a qualitative or quantitative way. When used in a qualitative way the SIL requirements for a specified safety function are increased until the frequency of occurance is reduced such that the conditions associated with Class II or Class III risk class are satisfied.

When used in a quantitative way frequencies and consequences are specified numerically and the SIL requirements increased until it can be shown that the additional capital and operating cost associated with implementing a higher SIL would meet the condition associated with Class II or Class III risk class see Figure C. The quantitative method is described in Annex D. The quantitative method can be used for both simple and complex applications.

With complex applications, fault trees can be constructed to represent the hazard model. Software tools are available to allow modeling of common cause if the same type of equipment is used for control and protection functions.

In some complex applications, a single failure event may occur in more than one place in the fault tree and this will require a boolean reduction to be carried out. The tools also facilitate sensitivity analysis that shows the dominant factors that influence the frequency of the top event. SIL can be established by determining the required risk reduction to achieve the tolerable risk criteria. The method normally results in low SILs because the risk model is specifically designed for each application and numeric values are used to represent each risk factor rather than the numeric ranges used in calibrated risk graphs.

Quantitative methods however require the construction of a specific model for each hazardous event. Modeling requires skill, tools and knowledge of the application and can take considerable time to develop and verify. The method facilitates demonstration that risk has been reduced to as low as reasonably practicable.

This can be done by considering options for further risk reduction, integrating the additional facilities in the fault tree model and then determining the reduction in risk and comparing this with the cost of the option. The risk graph qualitative method is described in Annex E. The method enables the safety integrity level to be determined from knowledge of the risk factors associated with the EUC and the EUC control system.

A number of parameters are introduced which together describe the nature of the hazardous situation when safety related systems fail or are not available. One parameter is chosen from each of four sets, and the selected parameters are then combined to decide the safety integrity level allocated to the safety functions.

The method can be qualitative in which case the selection of the parameters is subjective and requires considerable judgment. The residual risk cannot be calculated from knowledge of the parameter values.

It will not be suitable if an organisation requires confidence that residual risk is reduced to a specified quantitative value. The parameters descriptions can include numeric values that are derived by calibrating the risk graph against numeric tolerability risk criteria. The residual risk can be calculated from numeric values used for each of the parameters. It will be suitable if an organisation requires confidence that residual risk is reduced to a specified quantitative value. Experience has shown that use of the calibrated risk graph method can result in high safety integrity levels.

This is because calibration is usually carried out using worst case values of each parameter. Each parameter has a decade range so that for applications where all the parameters are average for the range, the SIL will be one higher than necessary for tolerable risk. The method is extensively used in the process and offshore sector. The basic method is described in a number of books and the technique can be used in a number of different forms.

The method is quantitative and the user will need to decide the tolerable frequencies for each consequence severity level. Numeric credit is given for protection layers that reduce the frequency of individual demand causes. Not all protection layers are relevant to all demand causes, so the technique can be used for more complex applications. The numeric values assigned to protection layers can be rounded up to the next significant figure or the next significant decade range.

If numeric values of protection layers are rounded to the next significant figure, then the method on average gives lower requirements for risk reduction and lower SIL values than calibrated risk graphs. Since numeric targets are assigned to specified consequence severity levels, the user can have confidence that residual risk meets corporate criteria.

The method can however be adjusted so as to be suitable for such cases. The hazard event severity method is described in Annex G. An inherent assumption is that when a protection layer is added that an order of magnitude risk reduction is achieved. A further assumption is that protection layers are independent of demand cause and independent of each other. The method as described is not suitable for functions that operate in continuous mode.

The method can be qualitative in which case the selection of the risk factors is subjective and requires considerable judgment. The residual risk cannot be calculated from knowledge of the risk factors selected. It will not be suitable if an organization requires confidence that residual risk is reduced to a specified quantitative value.

This annex considers one particular approach to the achievement of a tolerable risk. The intention is not to provide a definitive account of the method but rather an illustration of the general principles. The approach includes a process of continuous improvement where all options that would reduce risk further are considered in terms of benefits and costs.

Those intending to apply the methods indicated in this annex should consult the source material referenced see reference [7] in the Bibliography. Clause C. With respect to c , the ALARP principle requires that any risk shall be reduced so far as is reasonably practicable, or to a level which is as low as reasonably practicable these last 5 words form the abbreviation ALARP.

If a risk falls between the two extremes i. This three zone approach is shown in Figure C. Above a certain level, a risk is regarded as intolerable and cannot be justified in any ordinary circumstance. Below that level, there is the tolerability region where an activity is allowed to take place provided the associated risks have been made as low as reasonably practicable.

Tolerable here is different from acceptable: it indicates a willingness to live with a risk so as to secure certain benefits, at the same time expecting it to be kept under review and reduced as and when this can be done.

Here a cost benefit assessment is required either explicitly or implicitly to weigh the cost and the need or otherwise for additional safety measures. The higher the risk, the more proportionately would be expected to be spent to reduce it. At the limit of tolerability, expenditure in gross disproportion to the benefit would be justified. Here the risk will by definition be substantial, and equity requires that a considerable effort is justified even to achieve a marginal reduction.

Where the risks are less significant, proportionately less needs to be spent in order to reduce them and at the lower end of the tolerability region, a balance between costs and benefits will suffice.

Below the tolerability region is the broadly acceptable region where the risks are small in comparison with the everyday risks we all experience. While in the broadly acceptable region, there is no need for a detailed working to demonstrate ALARP, it is, however, necessary to remain vigilant to ensure that the risk remains at this level. Risk cannot be justified except in extraordinary circumstances Tolerable only if further risk reduction is impracticable or if its cost is grossly disproportionate to the improvement gained.

As the risk is reduced, the less, proportionately, it is necessary to spend to reduce it further to satisfy ALARP. The concept of diminishing proportion is shown by the triangle. Figure C. Subclause C.

Annex D and F outline quantitative methods and Annexes E and G outline qualitative methods for the determination of the necessary risk reduction for a specific hazard. One way in which a tolerable risk target can be obtained is for a number of consequences to be determined and tolerable frequencies allocated to them. This matching of the consequences to the tolerable frequencies would take place by discussion and agreement between the interested parties for example safety regulatory authorities, those producing the risks and those exposed to the risks.

To take into account ALARP concepts, the matching of a consequence with a tolerable frequency can be done through risk classes. Table C. That is, the descriptions for each of the four risk classes are based on Figure C. The risks within these risk class definitions are the risks that are present when risk reduction measures have been put in place.

With respect to Figure C. For each specific situation, or sector comparable industries, a table similar to Table C. Each consequence would be matched against a frequency and the table populated by the risk classes. For example, frequent in Table C. Therefore, this table should be seen as an example of how such a table could be populated, rather than as a specification for future use. This annex outlines how the safety integrity levels can be determined if a quantitative approach is adopted and illustrates how the information contained in tables such as Table C.

The integrated software is to be proven on the target programmable electronic hardware to ensure compatibility and to meet the requirements of the intended safety integrity level. Structural code coverage analysis can be supported by unit test, system test, or a combination of the two, operating in tandem. For instance, a preferred approach might be to use dynamic system test to generate coverage of most of the source code, and to supplement it using unit tests to exercise code constructs which are inaccessible during normal operation.

To complete the structural coverage analysis, boundary values could be provided manually or generated automatically to check the permissible and inadmissible ranges. This section details how it is to be confirmed that the integrated system complies with the software safety requirements specification at the required safety integrity level.

During development, the TBrun component of the LDRA tool suite is used to confirm that the functions of a system or program behave as the specification dictates. The stored test data is reused for regression analysis to confirm ongoing adherence to the specified requirements. Automated requirements tracing complements this approach by providing forward and backward traceability between the software safety requirements specification and software safety validation plan.

Section 7. It is a technique used to determine whether a change or an enhancement to a software system has affected, or has the potential to affect, the existing system. When a change is made and impact analysis is complete, the extent of the re-verification required will be influenced by the number of software modules affected, the criticality of the affected software modules and the nature of the change.

Possible decisions are. The TBrun component of the LDRA tool suite makes re-verification easy to achieve by storing test data for subsequent automated regression test. Like many other safety critical standards including ISO , IEC , and EN , IEC references the need for due consideration of response timing for time-critical applications, and memory constraints.

The WCET of a computational task is the maximum length of time that the task could take to execute in a specific environment. Hard real-time systems need to satisfy stringent timing constraints imposed by the nature of the functions they fulfil. Unfortunately, it is not possible in general to calculate definitive upper bounds on execution times for programs. There are further complications in the case of multicore processors.

The use of additional cores results in resources being shared between them. Time-related delays occur as users wait for access.

These interference channels cause the execution-time distribution to spread. Instead of a tight peak, the distribution of execution times becomes wide with a long tail.

This page presents a practical, compliant approach to addressing this problem. It involves the optimisation of system configuration by means of interference research through measured execution times using the TBrun component of the LDRA tool suite supported by the optional TBwcet module. Where proof of fitness-for-purpose within a specified tool chain is required, the LDRA Tool Qualification Support Packs TQSPs contain the test cases to demonstrate both the structural coverage analysis and programming rules checking capabilities of the tool suite itself.

In addition, associated documentation for the development and verification of the product is provided, including plans, procedures, and expected results.

Functional safety with legacy software � case study. Clarifying and fulfilling test tool qualification requirements. The safety integrity levels of IEC and a revised proposal. Email: info ldra. Careers Newsroom Contact us. Case studies White papers On-demand webinars Demo videos.