Monthly Archives: November 2019

The 2020 Internet of Things (IoT) Trends that will Disrupt Industry 4.0

The infinite ways in which Internet of Things (IoT) can be applied to industrial processes has disrupted the status quo in this domain.

This has had a very positive impact. Industrial Automation is now able to deliver unprecedented levels of operational efficiency and asset availability.

The true potential of automation in the Industrial Revolution 4.0 era has been unlocked by IoT-enabled systems.

These cloud-connected systems facilitate consolidation of smart monitoring, production integration, predictive maintenance, supply chain management and remote diagnosis into a single data model.

International Data Corporation (IDC) forecasts that the global technology spend on IoT will hit USD 1.2 trillion by the year 2022.

So, let us try to catch up with the 2020 trends of this IoT Universe, which are moving at the speed of light (figuratively).

The Industrial IoT Trends of 2020 that You Should Take Note Of

1. Convergence of Industrial IoT and Artificial Intelligence (AI) – Industrial IoT and AI are coming together to further empower the digitisation of production processes.

   This has resulted in the increase in efficiency and reduction in overall downtime of production activities, to the levels that were never imagined before.

   Challenges faced in the manufacturing sector such as minimising production waste, reducing unexpected downtime and improving the stability of processes have been streamlined through AI-driven Machine Learning (ML) algorithms.

   A technology concept named AIoT (Artificial Intelligence of Things) has been conceived to enable connected and intelligent systems that self-correct and heal automatically.

   The first generation of this technology is a cloud based IoT framework, which functions in the following manner:

   • Collect – A central location logs the telemetry data collected from various sensors and devices.
   • Store – The storage of this telemetry data is in scalable systems such as data lakes.
   • Process – The telemetry datasets are processed through Big Data platforms.
   • Analyse – The information provided by the Big Data systems are used to deliver actionable insights via visualisations.
   • Control – The Big Data systems are capable of offering recommendations to field engineers and device operators for controlling the devices.

   When industrial IoT was combined with AI in the subsequent generation of this model, the process doesn’t stop at outputs such as visualisations. The ability to act on patterns and correlations from telemetry data can also be developed.

   Fundamentally, the facts are not just presented to humans for them to act on. Instead, AI goes a step ahead and takes an intelligent action, mimicking the brain of the connected systems.

   AI can also be utilised to analyse the stream of telemetry data in batch or real-time modes. It essentially spreads out from the start to the end of the IoT spectrum.

   These AIoT systems will be able to proactively sense events and failures. This can save a huge amount of money on predictive maintenance.

2. Introduction of Cobots – Collaborative robots or Cobots, as they are commonly referred to, can improve business growth and ROI tremendously.

   Improvement in vision and sensor technology has resulted in Cobots ceasing to be a threat to humans on the shop-floor, due to their quick movements.

   The price tag on Cobots has also improved to the extent that these are now viable options for small and medium businesses as well.

   Some of the key advantages of using collaborative robots in Manufacturing 4.0 are as follows:

   • Effortless Programming – Cobots can be programmed easily, as they are essentially plug and play. Some models can be programmed through a tablet or via adjustments to the arms.
   • Quick Setup – Cobots can be setup in a few hours, unlike the industrial robots used previously.
   • Flexibility – Collaborative robots do not require too much space and can be redeployed to suit varied applications.

   Cobots can be used in the following ways:

   • Hand Guiding – A Cobot with hand guiding functionality has a pressure-sensitive device at the end of its arm. Thus, the Cobot can be programmed to grasp an object or move something at a specific speed.
   • Safety Monitored Stop – This type of Cobot can work independently as long as there is no human intervention. In case a human must take over, the Cobot automatically senses the presence of the human and freezes its movement until the ground is clear.
   • Power and Force Limiting – A Cobot with power and force limiting capabilities can sense objects in its path and stop/reverse movement to prevent a collision. Such Cobots can collaborate and work with humans on a regular basis.
   • Speed and Separation Monitoring – This is similar to the safety monitored stop functionality. Instead of stopping when a human enters the safety zone, the Cobot slows down and tracks the motions of the object (human). In case the human is very close to the Cobot, it stops completely.
3. Leveraging Augmented Reality (AR) – Augmented reality is one of the emerging trends in IoT in 2020. The believers of Industry 4.0 have been exploring the endless possibilities offered by incorporating AR in an industrial environment.

   The software and hardware for AR has consistently seen improvement over the years. Here are some of the possibilities of using AR in manufacturing:

   1. Assembly – In manufacturing units, it is required to put together thousands of components quickly, with precision. Since work instructions are usually in static documents such as PDFs, it may be hard to work through these. The risk of static documents not being updated in a timely manner is also high.
      • AR devices project the instructions in the field of view of the machinist in a voice-controlled and hands-free manner.
      • The work instructions are broken down as per the experience of the previous machinist who performed the assembly.
      • This information is then uploaded into the AR glasses.
      • This helps the machinist in performing the assembly at a faster rate, as he/she does not have to walk over to the station to check static instruction manuals.
      • This is particularly useful for complex assembly in industries such as aerospace manufacturing.
   2. Maintenance – AR can also be utilised for the maintenance of equipment used in the manufacturing industry.

      Mitsubishi Electric has developed a technology that uses AR for maintenance support. The user is able to confirm the inspection order on an augmented reality display. They can also enter inspection results using their voice.

      This process, as opposed to the traditional method of using a maintenance manual, is more efficient. The AR systems can also be used for maintenance applications beyond manufacturing.
      

   3. Expert Support – Machine manufacturers offer after-sales expert support wherein the experts are expected to travel to worksites when there are complications in the functioning of machines. In case of increased instances of such cases, there may not be enough experts to travel on-site.

      AR devices have been introduced to provide telepresence in these cases, i.e., the expert can see what the technician sees and point out features that may need further inspection.

      This offers experts the flexibility to inspect and support from distant places. This also implies that companies need not invest in training every technician on expert skills.

      They can leverage the existing knowledge of experts and deliver it through telepresence. Another use of this technology is the merging of execution with training of less-skilled labour.

   4. Quality Assurance – The basic idea behind using AR for quality assurance lies in the functionality wherein quality professionals can take photos of vehicle assemblies under inspection. These images can then be compared to the ones from company suppliers through augmented reality overlay.

      The features that do not fall in place will be highlighted by the overlay. This way, the issue can be quickly identified and fixed.

   5. Automation – AR applications enhance the capabilities of the machinist in a very powerful manner. This can be referred to as Augmented Intelligence.

      A person with a specific skill level can be strapped with artificial intelligence through AR and IoT. This elevates his/her skill level massively.

      More jobs are getting automated these days. By pushing machinists up the skill-chain, they will be more competitive in the market. Eventually, augmented humans and automated machines will be in a cooperative mode in the industry. Hence, AR can leverage automation in the manufacturing sector.

Summary

Convergence of industrial IoT and AI, introduction of Cobots and usage of augmented reality are some of the significant trends in IoT applications in Industry 4.0.

Statistics associated with the deployment of industrial IoT solutions indicate that early adopters will be able to generate five times more revenue than late adopters.

Companies should ideally focus on narrowing down the business value drivers they are looking to contribute to. This way, they can position their digital strategy with their business goals to utilise IoT platforms efficiently.

How Different is Functional Safety for Motorcycles as per part-12 of ISO 26262 Standard

When the concept of functional safety for automobiles was standardized in ISO 26262 standard, it was only meant for road vehicles weighing up to 3500 kg. Despite the fact that motorcycles were not explicitly excluded in the standard, the standard was essentially applicable only on cars or passenger vehicles.

“Why were motorcycles excluded from the standard?” you may ask. We do not have a specific answer to that question. However, if we look at the three major aspects safety criticality- severity, controllability, and exposure, we get the hint. All these aspects work differently in terms of motorcycle safety. The severity factor for a motorcycle borne passenger is higher in case of a hazardous fault. For instance, if there is a fault in ABS of the motorbike, the intensity of damage to the bike as well as the rider is higher compared to a car.

Also, the onus of balancing a motorcycle (when it is stationary) is on the rider. There is no such dependence in a car. Hence, controllability also works differently for a motorcycle.

Even some similar components in a car and a bike would pose different hazards and thus, a need for a separate set of functional safety guidelines was felt for motorcycles.

In 2018, with the launch of a new version of the ISO 26262 standard, motorcycles were finally brought under the purview of ISO 26262 functional safety.

The new scope of ISO 26262 took a major shift from “road vehicles up to 3500 kg” to “road vehicles excluding mopeds”. This, not only brought motorcycles under the ISO 26262 umbrella but also heavy vehicles like buses and trucks.

The scope of this blog will be restricted to the functional safety guidelines for motorcycles or two-wheelers in general.

Notable Differences in the New ISO 26262 Guidelines for Motorcycle Functional Safety

As already mentioned, the safety criticality in a motorcycle works differently. Therefore, there are some key differences in the ISO 26262 standards for two-wheelers.

Motorcycles have unique functional safety requirements. The emphasis is more on the rider’s behavior than the vehicle components. The changes in the latest version of ISO 26262 standard are visible right from the start, i.e., the concept phase. As the changes must come from within, safety culture in the organizations that are stakeholders in motorcycle development requires additional focus.

Let’s find out how ISO 26262 adapts itself to the unique safety needs of a motorcycle:

Safety culture:

• The organization must define process and work instructions for compliance to Part 12 in the QMS. It has to also ensure that the other standards are well integrated. For example: interactions between cybersecurity (ISO 21434) and Functional Safety.
• Measures for process improvement need to be put in place, to learn from successfully executed ISO 26262 projects.
• Organization must give sufficient authority to motorcycle safety team for execution and compliance.

Reclassification of confirmation reviews:

• For motorcycles, table 1 in Part 12 replaces Part 2 table on confirmation reviews. This table basically, skips ASIL D column as in earlier table. ASIL D is missing in the table as the highest MSIL maps to ASIL C.
• Confirmation measures such as confirmation reviews and functional safety audits are to be performed as per the independence mentioned in the table.
• Functional safety assessment to be done, if going for certification.

These guidelines shape up processes like HARA, safety validation and more while development of ISO 26262 compliant two-wheeler software and hardware. Let’s understand this in a little more detail.

1. Hazard Analysis and Risk Assessment (HARA)

There are a few modifications made to the process of HARA. Naturally so, because the safety in a two-wheeler ecosystem depends on multiple external factors such as helmets, protective gears, training, etc. Also, the rider has an enhanced responsibility to keep the two-wheeler safe while riding.

A hazard may also result from the motorcycle’s behavior and not necessarily from a failure. For instance, a passenger car is inherently designed to navigate safely through snow/ice on the road. However, a motorcycle is not.

So, if the rider decides tries off-roading or drives in hazardous situation (during a heavy snowfall), he/she is accepting a higher degree of risk.

Such a scenario is outside the scope of ISO 26262 Part-12. Moreover, the 3 important factors in Hazard Analysis and Risk Assessment (HARA) – controllability, severity and exposure are also affected to a great extent in such conditions.

Motorcycle specific hazard analysis and risk assessment:

• More emphasis on rider behaviour than the machine components, for mitigating risks. Controllability of motorcycle specific hazardous events place more emphasis on the rider.
• HARA leads to determination of MSIL (Motorcycle Safety Integrity Level) which is a motorcycle counterpart of ASIL.
• The worldwide established level of technology in the motorcycle industry suggests that ASIL classification is inappropriate for motorcycles. So, an alignment between MSIL and ASIL classification is established to match ISO26262 to the worldwide capability of the motorcycle industry.

Identifying operating scenarios:

• Malfunctions are considered in operational modes when the vehicle is correctly used and when it is incorrectly used in a reasonably foreseeable way. For example: road race, Motocross or trial events are not considered normal motorcycle use conditions.
• HAZOP can be used to identify hazards and operational scenarios. Annex B lists severity scale based on AIS standard including the exposure (duration/frequency) probability examples. For controllability, the assumption is that the driver is trained, experienced and in good condition.
• The scenarios should not be too many (which makes analysis vague and exposure rare) or too few (insufficient safety measures might get considered). The best way is to aggregate similar scenarios to the list ‘as relevant as possible’ to usage. Eg: A normal motorcycle is not expected to travel on bad roads at high speed.
1. Introduction to Motorcycle Safety Integrity Level (MSIL)

The output of HARA for a motorcycle is MSIL, the motorcycle counterpart of the ASIL.The method and the approach used to perform HARA for motorcycles is similar to that for the passenger vehicles. However, the ASIL-MSIL alignment/mapping is the key difference.

For example, ASIL C for a passenger car is equivalent to MSIL D, which is the maximum value for MSIL.

Reasons for Mapping MSIL to ASIL:

• This mapping of MSIL to ASIL helps the motorcycle industry to develop the software/hardware components in accordance with the mapped ASIL grade.
• Before the safety goals are derived from the MSIL, it needs to be mapped to the corresponding ASIL value. This is because, the product development phase (Part-4) is still relevant and so are its applicable requirements.

Similar to ASIL, MSIL is also derived based on the three factors – Severity (S), Exposure (E) and Controllability (C).  The table below will help you understand how these factors contribute to the process.

We have already discussed why it is important to map the MSIL value to ASIL. But for those interested in working on the Functional Safety of two-wheelers, ‘how’ assumes more importance.

ISO 26262 Part-12 document provides Table-6 as the reference for mapping MSIL to ASIL. MSIL QM remains QM for ASIL, however, MSIL D is mapped to ASIL C.

As per the standard, the ASIL levels mapped from the MSIL represent the minimum requirement. It implies that if the HARA determines the MSIL to be B, the component will be developed according to the requirements mentioned for ASIL A.

However, to meet the requirements of any safety goal, the requirements mentioned in Part-12 will supersede the requirements in the other parts.

1. Re-classification of Confirmation Measures

Confirmation measures are major requirements for certain work products in the functional safety lifecycle. These measures include confirmation reviews, assessments and audits.

The purpose of these reviews is to ensure that the activities such as HARA, FMEA, FMEDA, etc. are on the intended track.

Some of these reviews need to be done by a different person (I1) while few confirmation measures are supposed to be performed by a person from a different department or organization (I3). The classification depends on the safety goals and the ASIL values.

*I0 to I3 is the degree of independency

In Part-12 of the latest ISO 26262 standard, the confirmation measure has been re-classified for the motorcycle industry. I2 has been set as the highest level of independence as compared to I3 in the automotive functional safety. It implies that the confirmation measure will be performed by a person from a different team who does not report to the same direct superior.

1. Modified Methods for Vehicle Integration Testing and Safety Validation

The changes in the ISO 26262 standard are not only confined to HARA and ASIL but also permeate to the testing activities.

Major modifications have been made in Part-4 of the ISO 26262 standard (Product development at system level) with respect to motorcycles.

For instance, there is a Table-7 for correct implementation of the functional safety requirements at the vehicle level. The test methods mentioned in the table will always get preference over the test methods defined in Part-4, Part-6 or Part-8 of the ISO 26262 standard (Only Motorcycle Functional Safety).

Similarly, Table-8 gives the methods to ensure the correct functional performance, accuracy and timing of safety mechanisms at the vehicle level. These methods are recommended to fulfill the motorcycle-specific safety goals.

Modifications in the Vehicle Integration testing

• If concerns over rider safety exist, it is appropriate to select alternative test methods or move some of the vehicle integration test activities to other sub-phases.
• User tests and long-term tests with normal users as testers are not feasible for motorcycles.
• Real-life condition can be conducted using simulated condition.

Modified scope of Safety Validation

Safety validation covers:

• the controllability (including intended use and foreseeable misuse)
• the effectiveness of the external measures
• the effectiveness of the elements of other technologies (For example, a mechanical component that prevents a malfunction can be validated on the final vehicle at a later stage)
• assumptions that influence the ASIL mapped from MSIL in the hazard analysis and risk assessment
• aspects that can be checked only in the final vehicle

How is the New ISO 26262 Version Going to Impact the Motorcycle Safety?

The answer is, ‘Exactly how it impacted the automotive safety’. The response to the ISO 26262 standard and functional safety in general has been very welcoming.

While bigger OEMs were already concerned about motorcycle safety, the smaller players are now getting serious about it.

Now that the infotainment system, ABS, Battery Management System, etc. have made their way inside a two-wheeler, it is only natural that functional safety will assume far more importance.

Industry insiders report that a few two-wheeler OEMs were inculcating a safety culture even before the 2018 version of ISO 26262 was released.

They were mapping ASIL for motorcycles based on their expertise and domain knowledge.

However, with a formal ISO 26262 standard now out for motorcycles, a clearer path for ensuring motorcycle functional safety is available. Hopefully, the future holds safer motorcycles for us.

[Vlog] Demo of Our Motor Control System for BLDC/PMSM Motors in Electric Two-Wheelers, E-Autos or Electric Cars

The success of your Electric Vehicle Project depends on how efficiently the integrated control systems are able to operate various Electric Motors. Hence, investing in or developing a robust Motor Control System (for BLDC Motors/PMSMs) is akin to ‘half the battle won’, in the universe of Electric Vehicle (EV) production programs.

As an Automotive OEM/Supplier, you must have been confronted with issues related to Electric Motor operations while working with different segments of EVs such as Electric Cars, Electric Two-Wheelers, E-Rickshaws/E-Autos, etc. Each segment of EV requires motors with different power ratings.

This issue can be overcome with the help of the Motor Control Solutions designed by the Electric Vehicle Consultants at Embitel Technologies.

Our solution is a motor control system that can drive Permanent Magnet Synchronous Motors (PMSMs) and Brushless DC (BLDC) Motors of power ratings ranging from 1kW to 5kW.

It is integrated with the Field-Oriented Control (FOC) Algorithm that ensures accurate and precise operations (by overcoming the speed error).

Check out this Motor Controller Demo, to watch the FOC Algorithm in action.

(Video)

Summary of Learnings from this Demo Video of Our Motor Control System for BLDC Motors and PMSMs

Our consultants explain the hardware & software components and the system I/O.

The following are the main components of this motor controller solution for EVs:

We also have a YouTube channel with a collection of videos that may be of interest to you. Don’t forget to subscribe to our channel so that you get notified of our new videos.

[Vlog] How Embitel is Leveraging Machine Learning to Track Driver Behaviour and Anticipate Road Conditions

An application that monitors the driving pattern of individuals can be put to many uses. It can monitor drivers in school vans, help insurance companies to pass/reject claims, and aid in fine-tuning of driving skills.

But what if the same app can also warn you about road conditions and idling time?

Wait, do such applications really exist?

Yes, they do! Thanks to a team of highly motivated engineers headed by our Chief Innovation Officer, one such application has been incubated in our innovation lab. After months of brainstorming, vehicle data collection and development of a robust Machine Learning model, our R&D team was able to create a user-friendly app.

This App monitors your rides and provides important analysis to all the stakeholders.

In this demo, our Chief Innovation Officer introduces this app along with its features and possible use cases.

Additionally, you can see the Driver Behavior Tracking app in action, both in a simulated environment and on the road (real-time demo).

What will you Learn from this Driver Behavior Tracking App Demo?

• Different features of the application
• Possible use cases of the app
• Demonstration of how the App works in a simulated environment
• Demonstration of the functionalities of the App on a road trip

Our R&D and Innovation team is burning the midnight oil to make this App even more futuristic and feature-rich.

Encourage us by liking the demo video and do share it with your peers. Curious for more such videos? Check out our YouTube channel and Subscribe to it.

A Hands-on Demo Video: How to perform Functional Testing of HVAC, Mirror Control and Seat Control ECU

Automotive systems are built around very specific requirements, in order to perform some specific tasks/functions.

Thus, the number one priority of the product development and testing teams is to  ensure that the product achieves what is expected.

Functional Testing is the process that help the developers and test engineers to nail this task.

In our latest demo video, we bring you up and close with the end-to-end process of functional testing of an automotive control unit.

Our engineers demonstrate a seat control ECU, which is responsible for controlling the side-view mirrors, automatic adjustment of seats and seat heating pads.

From the test setup and testing tools to executing a ‘test case’, this demo is  a complete overview of how functional testing is performed.

So, without much ado, lets take you straight to our design lab.

Video Link goes here on live

Functional Testing of an automotive control unit is performed against the requirements. Hence, in addition to testing tools like vTest Studio, CANalyzer,  a requirement management software is also an integral part of the process.

Our Project Manager, Shajahan gives a detailed insight on the process and sums it up by executing a test case derived from the requirements.

If you think your colleagues can find this video helpful, do share it with them. Also, like the video and subscribe to our YouTube Channel.