As the rail industry increasingly relies on non-proprietary solutions, what does this mean for suppliers in terms of RAMS?

The railway industry’s safety standards place stringent demands on railway products in these areas. The trend towards implementing COTS at various system levels, rather than sticking to proprietary solutions, is therefore also evident in the rail industry’s development departments.

Reliability, Availability, Maintainability and Safety (RAMS) data is an essential part of these standards. Suppliers of COTS or electronic subsystems who are not yet familiar with railway industry standards are being asked to provide data that they do not normally have. Other suppliers, such as manufacturers of industrial safety controllers, are promoting the capabilities of their products in order to place them in the railway industry. In both cases, it is important for suppliers to understand the RAMS performance of their products and to provide RAMS data to their customers.

In the following interview with Niklas Franzke, safety expert at INVENSITY, we want to find out why customers in the railway industry request RAMS data, what this data contains and how it is created and provided by suppliers.

INVENSITY: Why is RAMS data of interest in railway applications?

Niklas Franzke: We can answer this by looking at the motivation of the rail-related manufacturers. The intrinsic motivation is to deliver a reliable, available, and safe product, which is also easily maintainable and as a result is predictable in terms of cost and operation. This should be easily understandable when you consider the typically required availability of railway systems. The extrinsic motivation for applying the RAMS process is based on ISO 22163. This international railway industry standard (IRIS) obliges manufacturers in the railway industry to apply the RAMS process, which itself is standardized in EN 50126. When railway manufacturers apply the RAMS process, they set up a RAMS management and coordinate all related activities and analyses. This RAMS management is necessary to avoid follow-up costs during development and operation. It also provides the evidence required by customers, legislators and approval authorities.

RAMS data is important for manufacturers so that they can analyze their development and is therefore requested from suppliers. Applying the RAMS process is binding, and the assurance of the related metrics is significant for railway manufacturers to be able to offer their products on international markets.

INVENSITY: What does RAMS-data exactly include and how is it created?

Niklas Franzke: Each letter of RAMS can be assigned to a few certain values. There are qualitative and quantitative methods used to determine those. To name a few: failure mode effect analysis (FMEA), failure mode, effect, and criticality analysis (FMECA), failure mode, effect, and diagnostic analysis (FMEDA), Reliability Block Diagrams, Maintainability Analysis, Risk Assessment and Hazard Analysis are most likely part of every RAMS data determination. Together all the necessary methods can be summarized in the RAMS-Analysis.

To take one more step into the matter, let me follow the abbreviation RAMS and explain the data that is used to quantify reliability.

Reliability Data includes Mean Time Between Failure (MTBF) or Mean Time To Failure (MTTF), which both describe the expected time it takes the product to fail before it is either repaired or replaced. Just to be clear on that, MTTF or MTBF do not resemble lifetimes but are statistical values that only account for certain assumptions and under specified conditions. Failure rates or so-called FIT-values are indirectly proportional to MTBF/MTTF and usually measured in failure per billion hours.

Both types of values offer insights into system reliability and the capability of interruption-free operation of railway systems. They can be statistically derived from field data or determined via a reliability prediction. Methods like different derivates of the FMEA, FMEDA, or the FMECA, and reliability block diagrams are used in combination with appropriate error models to determine this reliability data during RAMS-analysis.

Availability Data comprises system uptime, downtime, and Mean Time To Repair (MTTR). Availability ensures operational continuity and minimizes disruptions. Here again, field data can be essential to apply statistical methods, or the availability can be calculated from the reliability data in combination with a planned product lifetime.

The Maintainability Data includes maintenance intervals and costs, planned product lifetime and the determination of MTTR, which is also considered for Availability. The aspect of maintainability focuses on quantifying maintenance efforts by the maintainability analysis. The required high availability of railway systems induces the need for short maintenance time. Replacing a defective train door and repairing it onsite instead of repairing it offsite is an example of shortening the MTTR. This data helps focus on the ease of maintenance, shorten maintenance time efforts, and increase operational efficiency.

The generation of Safety Data usually requires the most effort. FMEA or its derivatives combined with Hazard Analysis and Risk Assessment (HARA) are the methods that lead to the safety data. When a system is designed according to EN 50126, the system integrator must consider the required Safety Integrity Level, the SIL, and with it certain budgets for associated metrics. These metrics are failure rates or probability of failure on demand (PFD). The system integrator will request this data from any supplier of medium to high complexity non-standard components. The effort to determine safety data is highly dependent on the complexity of the product and its functionality. The more complex the product, the more communication is required with the railway manufacturer. For COTS, this part is usually the most challenging, and well-formulated safety related application conditions (SRACs) help to provide common data in this area.

INVENSITY: What are some common challenges suppliers face when addressing RAMS considerations for their products?

Niklas Franzke: What I experienced is that the methodology often poses a challenge for suppliers of COTS-subsystems. Additionally, they cannot pay respect to all the different industry standards out there.

Predicting the reliability of a system, for example, can be enormously time-consuming if the needed data is not available or the method is not well mastered. Also, when working with a standard for the first time, it is never easy to make sure to comply with the required processes and documentation. Uncertainty in those two aspects leads to delays or failures in the supply of RAMS data. It is difficult to prevent both when trying to answer requests from customers who usually wish to have the data present on time.

INVENSITY: What advice would you give to manufacturers who are aiming to provide their products’ RAMS data to a customer?

Niklas Franzke: Firstly, the available data should be checked, and the customer’s requirements should be recorded properly. This is because in the beginning of each RAMS analysis it must be defined which data can be used for the reliability prediction of the system. From that, it is decided which method, calculation, or prediction, is applicable. High-level methodical expertise and precise initial data collections ensure an effective RAMS-analysis.

In most cases, the development of COTS is completed quite a time before customers request safety- or RAMS-data. Therefore, the analysis to conduct has to be chosen according to the availability of internal product knowledge. As an example, conducting a more costly FMEDA, rather than the required FMEA, can provide greater assurance regarding the system’s behavior under the influence of random faults. On the other hand, if sufficient field data is available a statistical approach could be easier to apply and could deliver more reliable data in a shorter period.

So, choosing the right starting point and the right method has a significant impact on the efforts of the manufacturer and the reliability of the results. The best case is, of course, when safety and reliability data is created during the development and maintained during operation.

INVENSITY: You already gave a hint in the previous answer that the reliability of the determined RAMS-data can vary. But how important is the actual RAMS performance of COTS Products? How do I know whether a product is performing successfully in terms of reliability, availability, maintainability, and safety?

Niklas Franzke: Let us define successful at first. A good performance in this context means that the product can fulfill the requirements that it inherits from the SIL-classified system in which it is integrated, or that a system integrator can choose that exact product to carry out the function he needs to implement. Besides the RAMS-data of the integrated components, the architecture also plays a significant role in the overall RAMS performance of a railway system.

For COTS, this means that their RAMS performance is measured with their RAMS-data. Since the applications are not precisely known to the COTS-suppliers, it is important to report the data and the functionality transparently. Reported in a way that the system integrator at the customer side can ensure SIL-related requirements and the overall RAMS requirements are met for the developed railway system.

INVENSITY: You spoke about the motivation of manufacturers to build reliable systems in the beginning. So, what value does the measurement of RAMS data add internally?

Niklas Franzke: When the reliability of a product is predicted during development and measured during testing and operation, it is available as a characteristic value. Obviously, this makes it possible to control it and to optimize the product. This logically also applies to the other RAMS data. Having it available makes it easy to react to customer requests. Additionally, it benefits sales in multiple industries, because the rail industry is not the only one that has safety standards.

If RAMS data is created for an already existing product, it often turns out that products are achieving adequate levels of performance. If a product does not perform well, the analysis delivers pointers to necessary changes that can be considered for technical product updates or formulated into application conditions. So, when you are conscious of a product’s RAMS data this adds value for sales and development.