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Monthly Archives: April 2018

  • April 30, 2018
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Does the Future of Industrial Asset Management Belong to Predictive Maintenance?

Tags :

Category : Embedded Blog

Unexpected machine downtimes can be one of the leading causes of economic loss for an industrial business, specifically in the manufacturing domain.

According to various published reports, automotive manufacturing can suffer from downtime losses amounting to $1.3 million per hour. Also, market analysts have found that an average factory unit can have downtime costs ranging between 5 and 20 percent of its productive capacity.

The machine downtime could be due to damaged or malfunctioning equipment, a fault in the connection line or the underlying software code, or fluctuation in external factors such as pressure, temperature or power.

All this makes it both necessary and challenging for a business to be able to anticipate the future occurrence of the faults. This anticipation is very critical in order to prevent the downtime or to be better prepared to minimize the loss.


Industrial Asset Management
Future of Industrial Asset Management; Image Credit: Microsoft

Redefining Industrial Asset Management Practices with Predictive Maintenance:

Predictive maintenance will be an ideal asset maintenance strategy for any business dealing with capital-intensive assets. It is also best suited for manufacturing facilities looking for ways to reduce machine downtime costs.

Predictive Maintenance is a system and process, which when implemented, has the potential to help businesses to cut down loses by enabling them to predict the costly machinery faults, unexpected shutdowns and schedule the required maintenance operation.

Predictive maintenance, especially in the context of industrial production, is said to increase productivity by 25%, decrease events of breakdowns by 70% while also reducing maintenance costs by 25%.

Power of Predictive Maintenance

Predictive maintenance solutions offer a distinctive advantage –  it allows to perform most of the evaluation and maintenance activities while in service without having to disrupt the business operations.

Needless to say this helps in greatly reducing the factory downtime for maintenance activities.

Additionally Predictive Maintenance solutions help businesses to:

  • Improve Asset Availability
  • Improved Work-force Productivity
  • Optimize Energy consumption
  • Lower operational costs
  • Reduce occurrence of fatal accidents due to faulty or poorly-maintained equipment
  • Have a Fool-proof Industrial Asset management & maintenance system

Statistical analysis of the Predictive Maintenance Market:

As Predictive Maintenance is gaining popularity across the industrial verticals, market experts and researchers have made some interesting observations about its future course.

A report [Global Predictive Maintenance Market By Component, By Deployment Type, By End User, Competition Forecast & Opportunities, 2012 – 2022] published by TechSci Research suggests that the global predictive maintenance market is projected to grow at a CAGR of over 31% during 2017 – 2022.

The report suggests that the predictive maintenance has emerged as a popular solution for industrial asset management and is being adopted by various industry domains including manufacturing, transportation, healthcare, defense, energy and utilities – to name a few.

Rapid advances at the technology front, mainly due to IoT (internet of things), has created a strong case for investments in predictive maintenance solutions. From UPS battery monitoring in industrial/commercial facilities to continuous air fleet management to thermal power plants monitoring, the spectrum of applications that are leveraging predictive maintenance solutions seems to be ever-evolving.

The ever increasing popularity of the predictive maintenance solutions can be attributed to:

  • Advent of secure cloud computing platforms
  • Widespread availability of wireless communication technology
  • Penetration of IoT based devices and advances in analytics
  • Rapid advancement in industrial sensor technology
  • Progress in machine learning tools

These technological advances has made it possible to execute real-time evaluation of machineries and opened up newer and faster modes of M2M communication.

This in turn has made it possible to collect, analyze critical data related to the actual condition of industrial assets, enabling informed maintenance decisions to be taken. The positive market sentiment towards predictive maintenance based systems is also driven by:

  • Need to replace outdated infrastructure
  • Tightening market competition to deliver faster and better
  • Shrinking profit brackets
  • The need to meet production targets without being interrupted by unplanned machine downtimes

 

predictive maintenance

Reasons for widespread adoption of predictive maintenance. Image Credit: pwc.nl

Predictive Maintenance vs Traditional Maintenance Methods:

In order to understand why predictive maintenance is fast gaining popularity over the traditional methods of industrial maintenance, let us take a brief look at what each of the technique mean.

The Industrial Asset Maintenance Techniques are Broadly Classified into:

Reactive Maintenance: is carried out when the equipment failure has already occurred and maintenance is done in response to the failure. This type of maintenance activity is carried out when the application or the equipment relatively of low value.

Preventive/ Planned Maintenance: is carried out in pre-set intervals where the machines health is analyzed for any traces of failure. While this is cost-effective, the entire fault detection and maintenance process depends on how effectively the fault was detected at the scheduled time. And this sometimes means replacing equipment, which has been detected with a defect, even if it could have more useful lifespan.

Proactive/ Condition Based Maintenance (CBM): A data-driven approach, the condition based maintenance entails equipment monitoring based on its actual conditions. Here, the equipment is monitored for any fluctuation in performance or a wear and tear in any equipment that could lead to greater harm to the entire industrial process.  Considered a more accurate maintenance activity than preventive maintenance, CBM analyses the root cause of the equipment failure and takes into account any signal towards a slackening equipment performance.

Predictive Maintenance: is carried out with the help of efficient sensors, and intelligent control systems that send real-time data about the condition of the equipment. The main advantage of the predictive maintenance is it’s a continuous process and does not require the machinery to be stalled or shut down for monitoring purpose.

Also, since predictive maintenance makes use of insightful and real time data about the machinery, it helps in pattern learning and pin pointing the root cause that may otherwise go unnoticed.

Additionally, coupled with advanced data analytics tools and machine learning techniques, Predictive Maintenance can also help in making efficient and informed maintenance decisions and gain better insights into the equipment health.


Industrial Asset Maintenance Activities
Difference between varius Industrial Asset Maintenance Activities. Image Credit: Deloitte

The investment in future:

The need to mitigate technological risks, and reduce operational costs and improve profit margins has strongly favored businesses to adopt predictive maintenance solutions as their long term strategy.

Many of the business organizations have already witnessed drastic changes with strategic investment in predictive maintenance solutions for industrial asset management. In fact, various research findings have suggested that organizations that have adopted predictive maintenance technology have reported 25%-30% efficiency gains.

Deloitte, in a recent report on Predictive Maintenance for Industry 4.0, has observed that predictive maintenance solutions helps increase equipment uptime by 10 to 20%, while reducing the maintenance cost by 5 to 10%, along with a significant reduction in maintenance planning time by 20 to 50%.

Summarizing the Predictive Maintenance (PdM) benefits:

  • Real time information about equipment condition without any downtime
  • Bases real time data and advanced analytical tools to make maintenance related decisions
  • Offers greater transparency about equipment condition through data collected through sensors.
  • Predict equipment failures well in advance so that necessary pro-active maintenance actions can be performed.

In a nutshell, predictive maintenance with the help of advanced machine learning algorithms will change how industries view asset management as a process while helping them increasing their operational efficiencies while focusing on a sustainable growth.

  • April 19, 2018
  • 0

Rearview: The Engaging Panel Discussions at the Ecommerce Roundtable at Bangalore, India

Category : Press

 
It won’t be an understatement to say that ‘the Indian Ecommerce is banking on AI and Omnichannel retail for the next wave of growth and success’.

If you are thinking to which ‘next wave’ of growth we are talking about? Well we have some numbers that can do the talking on our behalf!

As per Morgan Stanley reports, the Indian e-commerce market is expected to grow at a CAGR of 30% in the next nine years  and will  touch the $200 Bn mark by the year 2026. Increase in internet penetration, availability of low cost data plans, rise in adoption of the digital payment services coupled with Indian government’s initiatives such as introduction of GST – unified tax system are some of the driving factors of the growth in Indian ecommerce sector.

ecommerce roundtable

And there was no better time than this to facilitate a platform to discuss and to know what the industry experts have to say about the changing tides of the Indian ecommerce sector.

On 4th April, 2018, the Leela Palace, Bangalore was the venue for Ecommerce Roundtable, one of the most enlightening roundtable discussions on the Indian Ecommerce landscape.

Embitel co-organized this roundtable event in association with Magento Commerce, PayPal India and Boxx.ai.

A close group event, Ecommerce Roundtable included two panel discussions and value-add conversations by industry veterans from prominent organizations including Spencer’s, Future Group India, Enamor, Kurlon, Adobe, CaratLane, Zapyle, KPMG, CGN Global, and many more.

AI in e-commerce

Sharad Bairathi opened the roundtable discussion and extended a warm welcome to all the guests, which was followed by a session on “AI in e-commerce” by Daniel Rebhorn, Managing Partner, Diconium GmbH.

The key highlights of the event were the two very interesting panel discussions that put light on the future ecommerce trends and Omni channel retail in India.

The first panel discussion was about personalization, localization (use of vernacular languages) in payments, Artificial Intelligence and more. The panelists pressed upon the need for the ecommerce to prepare itself for the 50 million non-English speaking users who will start to use e-commerce in coming years.

Panle Discussion 1

The panel comprised some industry veterans- Sreedhar Prasad, Rashi Gulati Menda, Ajay Kashyap, Arun Kumar, Guru Bhat, Nicholas Kontopoulos, and Shamik Sharma.

The second panel discussion was quite intense with all the panelists coming up with their views about Omni channel. Mr. Ganesh Iyer came up with some really tough questions with our panel members: Is Omni channel in e-commerce really required? What are the challenges faced by various categories of businesses & more.  At the end, he also summarized the conversation highlighting the key takeaways.

We would like to extend our thanks to these gentle for the thrilling conversation- Alagu Balaraman, Manish Kapoor, Dhananjaya P, Terence Thambi Rajah, Sridhar Narayan, and Gurukeerthi Gurunathan

ecommerce development

  • April 19, 2018
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Understanding How ISO 26262 ASIL is Determined for Automotive Applications

Tags :

Category : Embedded Blog

According to the Motor vehicle safety data, by the BTS (Bureau of Transportation Statistics), more than 6 million crashes involving motor vehicles are reported every year on an average.

As per the U.S. Transportation Department data, United States automakers had to make a record safety recall of 53.2 million vehicles in 2016. This increase in auto safety recalls was caused by the rise in road traffic deaths/road traffic fatalities in U.S.

An auto recall, according to National Highway Traffic Safety Administration (NHTSA, US), is said to be issued when a manufacturer or NHTSA determines that a vehicle, equipment, car seat, or tire can create an unreasonable safety risk or fails to meet minimum safety standards”.

These statistics clearly lead us to one common conclusion – how even after technical advancements along the breadths and depths of the industry, an automobile is still a major reason for road accidents.

Hence safety, becomes the fundamental requirement of an automotive application development. For an automotive vehicle, in specific, the functional safety is a very crucial paradigm at every stage of production and decommission.

The Functional Safety Paradigm in Automotive

Within the automobile industry, the functional safety as a process is based on the guidelines specified by ISO 26262 , an international safety standard for automotive.

ISO 26262 standard defines functional safety as the “absence of unreasonable risk due to hazards caused by malfunctioning behavior of electrical/electronic systems”.

For ISO 26262 compliance; a functional safety consultant identifies and assesses hazards (safety risks). These hazards are then categorized based on their criticality factor under the Automotive Safety Integrity Level (ASIL) under ISO 26262. Such a clear classification of hazards helps to :

  • Establish various safety requirements to mitigate the risks to acceptable levels
  • Smoothly manage and track these safety requirements
  • Ensure that standardized safety procedures have been followed in the delivered product.

Automotive Safety Integrity Level (ASIL) , specified under the ISO 26262 is a risk classification scheme for defining the safety requirements. Under the ISO 26262, ASILs are assigned by performing a risk analysis of a potential hazard by looking at various risk parameters (Severity, Exposure and Controllability) of the vehicle operating scenario.

ASIL and Safety Criticality of Automotive Components:

The safety lifecycle of any automotive component, within the ISO 26262 standard starts with the definition of the system and its safety-criticality at the vehicular level.

This is done through hazard analysis and risk assessment for the corresponding automotive component (hardware/ software), necessary for the determination of the Automotive Safety Integrity Level (ASIL) .

Hence, determination of ASIL forms the very first phase of the automotive system development.  Here, basically all potential scenarios of hazards and dangers are evaluated for a particular automotive component, the occurrence of which can be critical for vehicle safety.

For example, an unexpected inflation of airbag or failures of brakes are potential safety hazards that should be assessed and managed in advance. This step is followed by identifying the safety goals for each component, which are then classified according to either the QM or ASIL levels, under the ISO 26262 standard.


ISO 26262 Standard
Automobile Safety Issue types. Image credit: Mentor

Safety goals are basically the level of safety required by an automotive component to function normally without posing any threats to the vehicle.

For example, for a car door, the safety goal could be both the importance of having it opened or closed depending on which action is safe under a particular condition. During instances of fire inside the vehicle or a flood, the safety goal would be to have the car door opened as quickly as possible so that the passengers can escape. On the contrary, while the vehicle is moving fast, the safety goal related to the door will be to remain closed- accidental opening of door of a moving car could lead to greater risks.

Determining the ISO 26262 ASIL for an Automotive Application

There are four ASILs identified by the ISO 26262 standard: ASIL A, ASIL B, ASIL C, ASIL D.

ASIL D represents the highest degree of automotive hazard and ASIL A the lowest. There is another level called QM (for Quality Management level) that represents hazards that do not dictate any safety requirements.

The following figure demonstrates the steps involved in the determination of ASIL for an Anti-Breaking System ( ABS).


ASIL for an Anti-Breaking System ( ABS)
Image credit: Whitepaper by Cadence

For any particular failure of a defined function at the vehicle level, a hazard and risk analysis (HARA) helps to identify the intensity of risk of harm to people and property. Once this classification is completed, it helps in identifying the processes and the level of risk reduction needed to achieve a tolerable risk. Safety goal definition as per ASIL is performed for both hardware and software processes within automotive design to ensure highest levels of functional safety.

These safety levels are determined based on 3 important parameters:

Exposure ( E): This is the measure of the possibilities of the vehicle being in a hazardous or risky situation that can cause harm to people and property. Various levels of exposure such as E1: very low probability, E2: low probability, E3: medium probability, E4: high probability are assigned to the automotive component being evaluated.

Controllability (C) : Determines the extent to which the driver of the vehicle can control the vehicle if a  safety goal is breached due to  failure or malfunctioning of any automotive component  being evaluated. The order of controllability is defined as: C1<C2<C3 ( C1 for easy to control while C3 for difficult to control).

Severity ( S): Defines the seriousness or intensity of the damage or consequences to the life of people ( passengers and road users) and property due to safety goal infringement. The order of severity is : S1 for light and moderate injuries; S2 for severe and life-threatening injuries, and  S3 for life-threatening incidences.

The ISO 26262 ASIL Allocation table

The ASIL levels – ASIL A, B, C ,and D are assigned based on an allocation table defined by the ISO 26262 standard.


ASIL Levels
Evaluation safety goals of automotive components Image credit: techdesignforums

Let us try to understand the determination of ASIL values for various components based on the E,C and S parameters.

Few observations from the ASIL allocation table,

  1. A combination of S3, E4 and C3 (the extremes of the 3 parameters) refers to a highly hazardous situation. Hence the component being evaluated is identified to be ASIL D, which means it is prone to severely life-threatening events in case of a malfunction and calls for the most stringent levels of safety measures.
  2. On the contrary, a combination of S1, E1 and C1 ( the lowest levels of the 3 parameters in terms of safety-criticality) calls for QM levels, which means the component is not hazardous and does not emphasize safety requirements to be managed under the ISO 26262.
  3. Similarly, combination of the medium levels – S2, E4 and C3 or S2,E3 and C2 defines either an ASIL C or an ASIL A.

The intensity of the hazard thus depends on the ASIL levels of the components , under consideration. Allocation of ASIL helps in identifying how much threat the malfunctioning of a particular component can cause under various situations.

Under the framework of the ISO 26262 ASIL and functional safety; the safety goals are more critical than the functionality of the automotive component. Let us take the example of charging of a vehicle battery to understand this statement.

The safety goals associated with a battery is a more critical consideration to be evaluated as per ASIL, more than the battery itself as shown in the table below. The overcharging of battery at a speed below 10 km/hour is not as serious a situation as overcharging at very high speeds, where the possibilities of overheating and consequent fire could also be high. :

Vehicle Condition Cause of malfunction Possible hazard ASIL
Running Speed< 10 km/h Charging of battery pack beyond allowable energy storage Overcharging may lead to thermal event A
Running Speed> 10 – 50 km/h Charging of battery pack beyond allowable energy storage Overcharging may lead to thermal event B
Running Speed>  50 km/h Charging of battery pack beyond allowable energy storage Overcharging may lead to thermal event C

Thus, ASIL determination forms a very critical process in the development of highly reliable and functional safe automotive applications. In today’s time where the car designs have become increasingly complex with huge number of ECUs, sensors and actuators, the need to ensure functional safety at every stage of product development and commission has become even more important.

This is why modern day automotive manufacturers are very particular about meeting the highest automotive safety standards in accordance to the ISO 26262 standard and ASIL Levels.

  • April 11, 2018
  • 0

CAN Network Architecture Definition for Tractor ECU design, for an Indian OEM

Tags :

Category : Automotive control units-design and development , Product Engineering

 
Customer:

Our customer is one of the largest Indian automotive OEM, who caters to several global markets as well. The project is a breakthrough in itself as it marks the beginning of introduction of electronics in agricultural vehicles in India, especially the tractors.

 

Business Challenge:

  • Unlike passenger vehicles, the agriculture and forestry vehicles in India are not equipped with electronic control units (ECUs) and a vehicle network.

  • In order to make these vehicles more efficient, feature-rich and easy-to-diagnose, electronic components and network had to be implemented.

  • Tractors are a kind of utility vehicle that acts as a central system for several functions. When integration of electronic components like ECUs is planned, different sub-systems need to be connected to each other and any kind of incompatibility has to be identified and rectified.

  • In this project, the challenge was to introduce the electronic components in the tractors and for that, electronic network topology and guidelines of the tractors had to be defined.

  • Our customer was looking out for Automotive Domain experts who could define the CAN-based network topology for tractors. Based on the topology, the actual electronic network had to be designed.

  • In addition to the topology definition, the customer also required guidelines for components such as ECUs, communication protocol, bootloader, software and more. These guidelines would help the network design engineers to implement the network architecture without any compatibility issue.

  • As we had worked in an indirect partnership with the concerned OEM before, they were quite confident in our capability of handling the complexity of the project.

    •  


    CAN Network Architecture

 

Embitel’s Solution:

    For the first phase of the vehicle network design, our automotive engineers with in-depth domain knowledge, worked on the network topology and guidelines design.

    The solution we provided to the customer consisted of:

  • Definition of network topology: With more ECUs coming into the picture, the in-vehicle network gets quite complex. A well-defined network topology clearly depicting the nodes and the connection is indispensable. We defined all the network topologies based on the requirements of an agricultural vehicle.

  • Guidelines for ECUs (Parameters etc.): All the ECU parameters were clearly defined and the guidelines for their interconnection were documented.

  • Guidelines for communication protocols: Guidelines for the integration of communication protocols such as CAN, LIN, and ISOBUS etc. have been documented here.

  • Guidelines for diagnostics protocols: These guidelines are about all the diagnostics protocols (UDS, J1939, OBD etc.) that will be integrated into the vehicle. We have defined how these protocols will be integrated to the tractor ECU.

  • Guidelines for the flash bootloader software: Bootloader software is necessary for ECU reprogramming and all the guidelines related to it are defined.

  • Guidelines for ISOBUS network: ISOBUS is a communication protocol for agricultural and forestry vehicles and the guidelines for it need to be mentioned separately.

  • Guidelines for Gateway: The rate of data transfer in different subsystems are different and therefore, a gateway is required to optimize it. The guidelines for this gateway is mentioned here.
  • April 11, 2018
  • 0

Model-Based Software Architecture Design for Tractor ECU and Body Control Module Implementation

Tags :

Category : Automotive control units-design and development , Product Engineering

 
Customer:

Our customer is a highly reputed Indian automotive OEM with a large footprint in India as well as other global markets. We have partnered with this Indian OEM for a CAN network architecture design project and also for an UDS stack integration project.

Having developed trust in the quality-driven delivery processes and industry-proven our solutions; customer decided to partner with us for this Model Based Development (MBD) project.

 

Business Challenge:

    Our customer undertook an ambitious initiative to develop and integrate a tractor Electronic Control Unit (ECU) and a Body Control Module (BCM) with the agricultural vehicle.

    The product roadmap aimed to make the tractors future-ready and deliver an advanced farming solution.

    The challenge here was to design the software architecture based on which the tractor ECU and body control module will be implemented in the agricultural vehicles. Our customer was looking for a vendor to help them define software architecture requirements for the electronic system of the tractor. The software architecture was required to be designed with respect to MATLAB model.

    Some of the requisites of the project were:

    • A MATLAB model-based system architecture definition that would serve as the reference for designing the application software for the ECUs and how different components will work together.

    • A method for designing an information system in terms of hardware and software (building blocks) and for showing how these building blocks fit together.

    While designing the software architecture, we also had to keep this points under consideration.

    • The ECUs should be able to efficiently manage the electrical loads of the vehicle.

    • The amount of wiring harness had to be reduced.

    • Diagnosis of electric loads to be made easy.

    Also, there were different sub-networks with variable data transfer speed. Hence, a gateway also had to be included in the design to ensure smooth data transfer between subnets.
     


    BCM
    Source: Element14 Community

 

Embitel’s Solution:

    Our solution aimed to create a software architecture that could give them a clear picture of how the tractor ECU and the body control unit will work together. We also designed different subsystems and the gateway with respect to the MATLAB model.

    An overview of the software architecture design we provided:

  • The Body Control Module is connected to the differential lock, seat, brake and other such components in the tractor.

  • 3 CANS subnets are designed each for inter-ECU and ECU-cluster communication, telematics communication and ISOBUS configuration.

  • A gateway to streamline the data transfer from different subnets at different rates.

  • Connectivity of the tractor ECU and BCM to the lighting load, solenoids, and relays.

  • Diagnostic stacks like SAE J1939 and UDS are also a part of the system.

 

Tools and Technologies

  • Enterprise Architecture Tool: This tool is used to create high-level system architecture and MATLAB based application layer of an embedded system.

  • MATLAB:  MATLAB is a software development environment used for numerical computing across several industries, especially Embedded Systems.

  • April 11, 2018
  • 0

Challenges Your Automotive Team may Face in ISO 26262 Functional Safety Compliance

Tags :

Category : Embedded Blog

The need for functional safety of E/E systems has become imperative in automotive industry. This is mainly due to the inherent complexity of the electronics embedded systems.

The malfunctioning of the electronic components like the Electronic Control Units (ECUs) has serious repercussions on the safety of the driver and passengers.

For instance, if the ECU controlling the braking system of the vehicle malfunctions, a fatal accident might occur.

With the introduction of ISO 26262, a standard for functional safety of electronics and electric system in road vehicles, the Automotive OEMs and Suppliers have a framework to ensure that the automotive ECU is designed according to the defined safety criticality.

However, with hundreds of electronics and electric systems and sub-systems that are part of the modern-day vehicle; the implementation of ISO 26262 standard has become an uphill task.

We will talk about the associated ISO 26262 challenges and some recommended solutions.

But before we discuss the challenges lets understand the ISO 26262 implementation in a nutshell. You can also refer to our first blog on ISO 26262 to get a clear picture.

ISO 26262 Functional Safety
Source: National Instrument

Understanding ISO 26262 implementation

ISO 26262 standard provides a framework for the entire automotive safety lifecycle i.e. from development to decommissioning. A risk-based approach is followed by ISO 26262 to determine the safety criticality of a component.

Following are some of the critical steps your ISO 26262 consultant may choose to follow:

  • Step 1: Hazard analysis and risk assessment are carried out based on the guidelines defined in ISO 26262 functional safety standard.
  • Step 2: ASIL (Automotive Safety Integrity Level) is assigned to the components and safety goals are determined.
  • Step 3: In the development phase, the safety requirements are classified into software and hardware.

The process may sound easy but in practice, altering the current process of automotive product development and making it ISO 26262 compliant is very challenging.

The functional safety consultant needs to anticipate potential malfunction scenarios of the proposed system right at the onset and recommend solutions to address them.

ISO 26262 Compliance

Source: Research Gate

Major Challenges in achieving ISO 26262 Compliance

  1. Hazard Analysis and Assigning ASIL

    2. Determination of the safety goals along with assigning of ASIL level come across as a major challenge in the course of ISO 26262 implementation.

    Hazard analysis helps to identify and analyse the safety goals of the system, which in turn is used to derive the requirements of functional and technical safety. The hardware and software design of the electronic system of a vehicle has to be prepared in accordance with these derivations.

    The assigning of ASIL to the automotive components depends on 3 factors viz. severity, exposure, and controllability. These three factors are quite hard to determine without adequate exposure to the use cases.

    The factors of severity, exposure and controllability need to be analysed consistently for a particular driving condition in order to prevent the ASIL being reduced. This could happen if we choose the lowest categories of the 3 factors for different driving conditions.

    In addition to the determination of the risk parameter, defining them in a qualitative way is a major problem that is faced by the ISO 26262 experts.

  2. Non-uniformity of Functional Safety Activities Among the OEMs, Suppliers And After-Market Companies

    3. In this day and age of globalization, a distributed approach of development is followed in most industries and automotive is no exception. Hundreds of components in a vehicle are outsourced to tier-1 suppliers some of which they outsource to other service providers.

    In such a scenario, the safety requirement of the component derived at different levels i.e. at OEM, tier-1 suppliers and after-market suppliers need to be uniform.

    Also, the safety requirements need to be shared among them so that there is no incompatibility in the final product.

    For instance, the UDS stack for an ECU is being developed by one organisation and the BSP by the other. Now, when both software will be integrated to the ECU, there must not be any sort of incompatibility in terms of ISO 26262 guidelines.

    Ensuring this compatibility becomes a major challenge given the distributed nature of product development.

  3. Quantitative Assessment of Every Hardware component

    4. The hardware used in the electronic components needs to be tested for failure rates. Quantitative assessment of the hardware is needed for this purpose.

    Quantitative assessment refers to analysing the FIT (Failure in Time) rate. It is the number of failures that is expected to occur in 1 billion device hours of operation. Based on the FIT rate the hardware is given ASIL rating.

    With several of such hardware involved, analysing each one of them is a challenge. Moreover, the testing of the most parts is performed on ASICs or other such circuits in test environment and their readings cannot be fully relied upon.

  4. Increase in product development cost Due to ISO 26262 Implementation

    5. Following are the three reasons why ISO 26262 compliance adds overhead to the OEMs.

    Additional personnel that the OEM has to hire to manage the safety critical components in the vehicle. For every expert or consultant the OEM hires, the cost escalates.

    • Automotive OEMs also need to train the existing engineering man-power, to inculcate a “safety culture” in the development process. As ISO 26262 is a relatively new standard, many engineers are not well-versed with it and need some training to get a hands-on experience.
    • Additional tests and formal verification processes add to the time invested in the product development. The increased time-to-market and efforts manifest in the cost of the development.

    These overheads need to be in check despite taking all measures to ensure functional safety according to ISO 26262 guidelines.

  5. Increase in Time-to-market due to ISO 26262 Compliance

    6. The list of features that are being included in the automobiles is getting bigger with each passing day. In such scenario, the OEMs are under constant pressure to release the new features quite rapidly.

    Some of these features that are safety critical, need to be complaint with the ISO 26262 standards. This implies additional testing and assigning ASIL ratings etc. which add to the time-to-market. With intense competition among the OEMs, keeping the time-to-market as less as possible is imperative and comes across as a major challenge.

    The pain point here for the OEMs is that the customers do not see functional safety as a value-add. Most customers are willing to pay more for active safety features and fuel-saving systems but usually perceive functional safety as a required component of a vehicle.

Conclusion

New features like ESP (Electronic Stability Program), ABS (Anti-lock brake system), and several such advance driver assistance system are being introduced in the automobiles at a very rapid pace. As ISO 26262 is relatively new standard, the challenges are yet to be overcome completely. As the engineers and solution architects get more exposure to the ISO 26262 functional safety standard, we can expect these challenges to get easier to handle.

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