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HBK Technology Days - Overall

2024 HBK Technology Days

This 6-part series of 90-minute virtual seminars are a journey from measurement, through analysis and reporting insights, to achieve durable structures, in reliable and dependable systems.

Day 1 – Minimising Electromagnetic and Cyber Threats to Measurement Data

HBK Technology Days - Session 1

Session 1: Minimising Electromagnetic Interference to Measurements

Precise and accurate measurements require a high quality DAQ measurement chain; from transducers converting a physical phenomenon to an analogue electrical signal, through electronic circuits to amplify and filter these signals, to their analogue to digital conversion. When these initially very small low voltage signals are transmitted through their wires and cables their signal quality is susceptible to interference caused by the electromagnetic fields surrounding them. There are many sources of these electromagnetic fields, from the test article, from the surrounding environment, and from the measurement chain itself. 

Current research and development of hybrid and battery powered electric drive systems for automotive and air vehicles, increases these electromagnetic measurement challenges during electric power testing in their high voltage and high current environments.

This session introduces electromagnetic sources and presents practical methods, including cable routing, shielding, and grounding, to suppress and minimise electromagnetic interference to the desired measurement signal. To complement these practical measurement methods, electromagnetic simulation methods are presented to minimise interference and ensure electromagnetic compliance in automotive design.

Electromagnetic fields are present in all electrical measurements. This presentation introduces the basics of electromagnetic coupling, the types of coupling to expect, which protection methods work best, and demonstrates the importance of good electrical grounding.

Electrical grounding during measurement is one of the most well-known but least well-understood causes of measurement error. Good electrical grounding significantly minimizes electromagnetic interference during measurement by providing a stable reference point and reducing noise, to ensure an accurate and reliable electrical measurement signal.

Download the PDF here download

About the presenter

Patrik Ott

Trainer HBM Products and Applications, HBK Academy

Patrik Ott is a trainer in the HBK Academy, for HBM measurement products and applications. Patrik began his career as an energy electronics engineer in1995, and then studied physics. His experience in electromagnetics and measurement technology comes from working and teaching for 12 years at the particle accelerator in the Institute for Nuclear Physics in Mainz. In 2016 he joined the HBM Academy, now HBK Academy, where their trainees can benefit from his measurement and teaching experience.

The world of power electronics is transitioning from silicon to wide-bandgap semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) due to their superior performance in automotive and industrial applications. GaN and SiC enable smaller, faster, and more efficient design, but they produce high-level electromagnetic interference (EMI), which generates conducted and radiated emissions. The noise on the battery and motor cables or busbars can radiate and disturb the control units and antenna placed on the vehicle, and in addition, internal couplings can be dangerous for functional behaviour of the complete e-powertrain system.

This presentation presents a complete simulation approach, formulated to be optimal in terms of accuracy and speed for each inverter main component. The virtual simulation approach is proposed at the design stage of each component, as well as at system level in the final validation and homologation to save time for EMI testing. The common mode chokes (CMC) and EMI filter designs are helping EMC engineers achieve lower emissions.

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About the presenter

Flavio Calvano

Application Engineering Manager, EMI/EMC, ANSYS

Flavio Calvano graduated in Electronic Engineering from the University of Naples "Federico II" with summa cum laude in 2007 and went on to obtain a PhD in Computational Electromagnetism in 2010. He is the author and co-author of numerous articles on electromagnetic simulation, applied to both low and high frequencies. Since 2011 he has held the position of Application Engineer at Ansys working on issues regarding Signal / Power Integrity, Power Electronics and Electromagnetic Compatibility; for the last three years he has been managing the Ansys EMI/EMC Application Engineering team in Europe.

Learn how to mitigate Electro Magnetic Interference (EMI), map torque ripple (mechanical noise), measure harmonics (electrical noise), improve accuracy, achieve uncompromised safety and rapidly calculate and map Measurement Uncertainty (MU) for every setpoint in your Electric Powertrain Measurements using a future proof testing solution.

In Electric Powertrain Measurements, learn how to:

  • Greatly improve accuracy and safety
  • Mitigate EMI issues
  • Rapidly calculate and map Measurement Uncertainty for every set point
  • Map torque ripple (mechanical noise)
  • Measure harmonics (electrical noise)
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About the presenter

Mike Hoyer

Applications Engineer – Electric Power Testing, HBK

Mike Hoyer is an Applications Engineer with over 33 years’ experience for Nicolet / LDS-Nicolet / HBM / HBK. Mike has a Bachelor’s of Science in Electrical Engineering from New York Institute of Technology, Old Westbury, NY, and an Associate Degree in Engineering Science from Farmingdale State University of New York. Mike has over 35 years of radio broadcasting experience, and over 35 years of data acquisition and applications engineering experience in automotive, aerospace and power industries, providing solution-oriented results to customers worldwide.

Session 2: Minimising Cyber Threats to Sensors, Vehicles and Software

Cyber threats are malicious activities aimed at damaging, stealing, or disrupting data and digital systems. Minimizing cyber threats to smart sensors, software defined vehicles, and cloud storage and analysis software systems involves a multi-layered approach, including:

  • Regular Updates: Ensure all software and firmware are up-to-date to protect against known vulnerabilities.
  • Encryption: Use strong encryption methods to protect data in transit and at rest.
  • Access Control: Implement strict access controls and authentication mechanisms to limit who can access critical systems.
  • Network Security: Use firewalls, intrusion detection systems, and secure communication protocols to protect networked devices.
  • Physical Security: Protect physical access to sensors and vehicles to prevent tampering.
  • Monitoring and Logging: Continuously monitor systems for unusual activity and maintain logs for forensic analysis.
  • … and Employee Training (to mitigate social engineering), and an Incident Response Plan (to quickly address any breaches).

This session includes an overview of new regulatory and compliance requirements for software systems, and focuses on the automotive industry as software-defined vehicles (SDV) converge product IT in the vehicle with enterprise IT in the cloud and backbone infrastructure. It considers the opportunities and challenges brought by increasing use of Artificial Intelligence. For example, this description is mostly a Copilot response to the question: “In 150 words please describe how to minimise cyber threats to sensors, vehicles and software.”

HBK Technology Days - Session 2

 

Security regulations and compliance aim to minimize cyber threats to measurement sensors, to software, and to AI by introducing and enforcing minimum standards. These include robust encryption, regular security audits, and adherence to industry-specific guidelines, to ensure secure data transmission, access controls, and continuous monitoring to help protect against vulnerabilities.

In Europe, key regulations include the Cybersecurity Act, the NIS Directive, and the proposed Cyber Resilience Act. The Cybersecurity Act establishes a framework for cybersecurity certification of products, services, and processes. The NIS Directive focuses on improving the cybersecurity capabilities of critical infrastructure operators and digital service providers. The Cyber Resilience Act aims to ensure that digital products are secure throughout their lifecycle by mandating cybersecurity requirements for hardware and software. These regulations collectively enhance overall security and resilience against cyber threats, ensuring the integrity and confidentiality of sensitive information across all system components.

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About the presenter

Tamlynn Deacon

Director Cloud, Service & Cyber, HBK

Tamlynn is an experienced Director of Cyber, Cloud & Infrastructure and IT/OT Support, with a focus on leadership and digital strategy. In senior leadership for nearly a decade, ensuring Cyber is a profit driver rather than a cost centre. Working other leaders to ensure the risk profile is in line with business objectives. A background as a small business owner, virtual CISO, DPO, and consultant with a demonstrated history of working in the software, manufacturing, and finance industries. Skilled in Cyber Security Risk Management, GDPR, DPA, ISO 27001/9001, PCI DSS, TISAX, CEP, NIST series as well as other country specific cyber regulations. Tamlynn is passionate about people and their development, believes that putting health and wellbeing first is key to grow and strengthen both themselves and the business. 

The software-defined vehicle (SDV) converges product IT in the vehicle with enterprise IT in the cloud and backbone infrastructure. Cybersecurity matters for SDV. There is no functional safety without security. With software and data being manipulated, the initial qualified, verified, or homologated functionality of systems is no longer guaranteed. With the exploding challenges of cybercrime, OEMs and suppliers must achieve adequate protection against manipulations of their enterprise and product IT systems. While SDV eases the evolution of functions based on a flexible hardware platform, it has more cybersecurity risks. SDV are a primary target for hackers because systems and components have high levels of always-on, connectivity, and smart application programming interfaces (APIs) for software updates and facilitate remote attacks. Many companies have no established product cybersecurity program and dedicated R&D security team. Standardized software stacks reduce the entry barrier for malicious actors. Starter kits for all sorts of malware are available, increasingly fueled by AI tools. However, generative artificial intelligence also has the potential to make software-defined systems more robust and secure, as we show in this presentation.

This presentation shows agile cybersecurity development for SDV lifecycle risk mitigation:

  • Cybersecurity risks in SDV
  • Agile systems Engineering and test strategies for adaptive software
  • The dynamic safety case and its maintenance throughout the life cycle
  • Agile documentation of changing software for OTA and SUMS
  • Mitigating AI driven IPR risks as software productivity tools try to capture data

To practically show innovative cybersecurity engineering we have developed generative AI-based methodologies for security analysis and design. The presentation will go beyond only AI and show methods to mitigate cybersecurity risks in SDV, such as deploying novel test coverage methods for grey-box Pen-Test.  Practical examples will provide insight how to best mitigate cybersecurity risks with SDV.

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About the presenter

Christof Ebert

Managing Director, Vector Consulting Services

Christof Ebert is the managing director of Vector Consulting Services. A trusted advisor for companies and member of industry boards, he supports clients worldwide to sustainably improve product strategy and product development and to manage organizational changes. Dr. Ebert is teaching at university of Stuttgart and Sorbonne Paris. He has founded the Robo-Test incubator and holds several patents in the field of autonomous systems.

The increasingly connected world brings many benefits, but also an increasingly complex cybersecurity landscape. An increase in bad actors and increasingly stringent legislation to address these mean increased volumes of work and pressure for IT and Security teams trying to balance the need to support key engineering tools while protecting their organizations. While these legislative changes aim to enhance security and protect sensitive data, they pose considerable challenges for software, necessitating upgrades or even complete overhauls to meet current standards.

Engineering software presents a particular set of challenges: business critical, high value and specialized, but frequently built and/or managed over many years by internal teams with little security experience. In this presentation we will consider the difficulties of managing engineering software with a focus on measurement and durability solutions. We will look at how modern software engineering techniques and deployment models can be used to address technical, organizational, and compliance risks. And we will consider how taking advantage of these deployment models can add value to both data and processes.

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About the presenters

Jon Aldred

Director, Product Management, HBK

Jon is Director of Product Management for HBK, and responsibilities include the product roadmaps for nCode and ReliaSoft software brands for durability and reliability engineering. His responsibilities include assessing the impact of new market trends such as electrification, digitalization and lightweighting on future software needs. Jon joined HBK in 1996 and prior to that worked at Chrysler in Auburn Hills and Jaguar Cars in the UK, performing CAE simulations for NVH, crash and durability.

Chris Phillips

Product Manager - Aqira, HBK

Chris is a product manager at HBK responsible for the development of Aqira, an enterprise system for test data management and process democratization. His background includes developing and deploying remote asset monitoring systems for railway signalling, systems to manage the operation of rail plant, and working on ground crew training simulators for the MoD. He has an MEng in Electronic Engineering and Embedded Systems from the University of Sheffield.

Day 2 – Vehicle Network Measurements and Analytics

HBK Technology Days - Session 3

Session 3: Vehicle Network Measurements

Road Load Data Acquisition (RLDA) remains a critical central process during automotive vehicle development to collect and analyse measurement data for vehicle performance under real-world conditions. RLDA measurements use calibrated sensors and transducers for high-fidelity measurement of forces, motions, accelerations, and torsion experienced by the vehicle on public roads and proving grounds. These real world measurements are used to develop drive files for physical simulators and computer simulations, to improve vehicle comfort, performance, safety, durability and reliability.

Modern software-defined vehicles (SDVs) are equipped with thousands of onboard sensors that monitor and control various vehicle systems. These sensors collect data that are processed by electronic control units (ECUs) to control and manage vehicle systems for ICEV and BEV performance, suspension, braking, steering, and much more. These sensor data are continuously and freely available in messages in the vehicle network CAN, LIN, FlexRay and/or Automotive Ethernet systems.

For modern vehicle development it is necessary to combine these high fidelity measurements with these vehicle network messages to fully understand the vehicle state. This session describes the development and rationale behind new road load data measurement capabilities to meet the requirements of next generation vehicle rig testing and simulation.

ECUs in modern vehicles exchange a lot of data between themselves during runtime. Especially in a software defined vehicle the individual ECU depends on incoming communication to perform its functionality as the sensors are not necessarily linked directly with the software feature using the measurement data.

For several years it is standard that testing of such ECUs needs an environment around them to provide suitable data to get the DuT (device under test) in active mode. This is often done with a complete set of ECUs. However, using a simulation environment allows testing much earlier in a development phase and helps to minimize complexity of testing. Reducing complexity also means reducing costs.

STAR ELECTRONICS provides a solution being in use at OEMs and their suppliers worldwide and focuses on rapid prototyping of RBS, gateway and signal manipulations.

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About the presenters

Christian Huschle

General Manager, STAR ELECTRONICS GmbH & Co. KG

Christian has an engineering diploma in Automation Technology as well as an MBA in General Management and was working at further European automotive suppliers (tier1 and technology specialists) in test centres and sales organizations. Before this, he has been working at several locations for Toyota Tsusho group companies in Europe and Japan being active for searching technology and products needed at Toyota group. During that time, he was participating in several consortia locally and worldwide for automotive industry and managed customer projects in Japan. Thus, working from different viewpoint in automotive area he is experienced in topics of conformance and certification testing, car communication, bus system specifications as well as Functional Safety.

Christian Huschle is working at STAR ELECTRONICS GmbH & Co. KG in Germany, a supplier of network equipment for the automotive industry and an engineering specialist in automotive bus systems. The company focusses on rapid prototyping and cost reduction of test environments for remaining bus simulation, gateway and signal manipulation. Data security is one of most important topics within this field of operation.

 

Complex control systems manage how modern vehicles behave driving on-road and off-road. These systems make their own real time decisions to control body and suspension motion based on calculations from on-board sensors. Traditional measurements of wheel forces, displacements, and accelerations describe the vehicle response but not the internal state of these systems. Whereas previous vehicle generation control systems required a small number of internal state signals, modern vehicles have increasingly complex control systems requiring many more internal state signals to be synchronously measured.

 

This leads to an increasing requirement to capture many more vehicle bus signals together with traditional measurements and maintain their synchronicity through signal processing workflows for provision to their respective vehicle development groups. This presentation describes integration and synchronisation of HBK SomatXR and STAR Electronics FlexDevice measurements, and nCode GlyphWorks developments for post-processing workflows.

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About the presenter

Bilel Njeh

Test and Measurement - Custom Solutions, HBK

Bilel is a Project Engineer at HBK, specializing in custom key systems to meet the diverse needs of HBK clients. He earned his degree in Electro-Mechanical Engineering from Sfax, Tunisia, followed by a Master’s in Mechanics and Mechatronics from Friedberg, Hessen, Germany. With experience in implementation, delivery and project management, Bilel has made significant contributions across various industries, including medical, automotive, and aerospace. His expertise lies in developing automated production machines and test benches, where he excels in providing innovative test solutions.

 

For this work, Bilel led the initiative to find and qualify a partner with a suitable solution to log FlexRay bus messages synchronized with Precision Time Protocol (PTP).

Rob Plaskitt

Application Engineer – Durability, HBK

Rob Plaskitt is an application engineer supporting nCode durability software for HBK with a degree in Mechanical Engineering (Loughborough) and a master's in Structural Integrity (Sheffield). He has over 30 years of experience working as an engineer at HBK (formerly nCode) in areas of automotive, aerospace, defence and power generation. He has applied nCode software and technology in these industries from CAE concept design through full-scale testing, fleet monitoring, structural durability and vibration qualification.

 

Rob led the nCode GlyphWorks developments implemented to increase speed and flexibility of post processing workflows for CAN messages to support and demonstrate this synchronisation.

Over the past two years, the openDAQ Software Development Kit (SDK) has undergone substantial advancement, evolving from concept to actualization. openDAQ release 3.10.0 signifies the culmination of this development effort, with all key features fully developed and refined. This enables seamless integration of test and measurement products into a solution via the unified application programming interface for discovery, streaming and configuration. Notably, openDAQ embraces well-accepted industry standards for achieving this.

This advancement is poised to significantly streamline our professional life. How it works, who is already engaged and how you can get engaged are explained in this presentation.

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About the presenter

Nils Röttger

Chief Technical Officer, openDAQ

Current job CTO at openDAQ d.o.o since 2022. Previous jobs: Head of firmware development at HBK (2021-2022), Firmware developer at HBK (2018-2020). Education: M.Sc. in Computer Science (Technische Universität Dortmund) and Master of Business Administration (Graduate School Rhein-Neckar).

Session 4: Vehicle Network Analytics

As described in the previous session, modern software-defined vehicles (SDVs) are equipped with thousands of onboard sensors that monitor and control various vehicle systems. These sensor data and electronic control unit (ECU) commands continuously communicate in the vehicle network CAN, LIN, FlexRay and/or Automotive Ethernet systems.

Whereas the previous session described combining these vehicle network messages with one highly instrumented RLDA test vehicle, this session considers collecting and analysing these vehicle network messages from vehicle fleets to extract vehicle performance insights for the population.

With increasingly connected vehicles it becomes possible for this data logging to stream data to cloud storage, where automated workflows post-process these data to collate population results for dashboards and reports.

HBK Technology Days - Session 4

 

For many OEMs (Original Equipment Manufacturers), collecting CAN bus data from their vehicles/machinery at scale can be a challenge. In this session, CSS Electronics will cover how CAN bus data loggers with WiFi/LTE can be used to automate this data collection - from installation to post processing. This will include example data collection work flows, considerations on data sensitivity and security - and details on how data can be integrated with any software/API tool, including tools from HBK.

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About the presenter

Martin Falch

Co-owner at CSS Electronics

Martin Falch has a master's degree in quantitative economics and has worked in management consulting and strategy. In 2015 he started CSS Electronics with founder Christian Steiniche, a Danish company specializing in CAN/LIN data loggers and modules.
Martin is responsible for sales & marketing and is the author behind hundreds of articles and videos including the popular ‘simple intro’ tutorials on CAN related protocols. In addition, he collaborates with end users to ensure successful deployments of CSS hardware across 5000+ companies and 100+ countries.

DECATHLON design and develop e-Bikes for a rapidly growing and diversifying consumer market. To meet rider expectations, it is necessary to design and optimise e-Bike components and performance as close as possible for their use: mountain bike, city bike, cargo bike, etc. We use multiple sources of information to get massive data from different testers to learn their riding habits; average speed, distance trip, assistance power, etc. Use of CSS data loggers is standard practice for a fleet of e-Bike rider measurements.

This fleet allows monitoring battery and electrical motor in relation to e-Bike use events. The purpose is to understand conditions and parameters of defaults on motors, batteries, and reproduce defaults on testing bench to improve these products. These data allow development of representative field tests, simulation models and electro-mechanical tests, especially for endurance motor tests. The main objective of this test is to accelerate endurance motor testing from several weeks to a few days to reduce time to market on project and be able to test quickly and continuously improve our motors.

This presentation will give an overview of CSS dataloggers uses in DECATHLON, and use of nCode & Aqira for measurement data analyses for accelerated test development; from e-Bike riders to the test bench.

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About the presenters

Maxime Darnois

Test Engineer, Decathlon

Maxime has an engineering diploma (Master) in mechanical engineering. Since 2018, he worked as testing engineer at Decathlon company. He has an experience of structural dynamics, fatigue and testing. He worked on structural products studies (wheel, cargo bike, luggage carrier…) by using instrumentation to understand customer expectations, to develop fatigue and static reliable tests from field tests. Since 2023, he has developed skills on electrical bikes, especially in collecting data from CAN network and make it available for teams in Decathlon (R&D, conception, simulation). Before Decathlon, he was working in the automotive motor industry at Stellantis Douvrin.

Nicolas Baron

Application Engineer – Durability and Reliability, HBK

Nicolas Baron has been an Application Engineer at HBK since 2018, where he performs support, training and pre-sales activities for nCode (durability) and ReliaSoft (reliability) software products. His background is acoustic and vibrations with a thesis at the KTH university in Sweden. He has worked for the automotive industry for about 10 years, as a test engineer for acoustic and durability tests and then as an FEA engineer in the numerical simulation department for an OEM supplier. He has a master’s degree in mechanical engineering from ENSIAME.

It is increasingly easy to acquire very large quantities of vehicle network measurement data, from data within a single vehicle network, streaming from multiple vehicles in near real time, and/or previously acquired and stored in an expanding data lake.

Conversely, these increasing quantities of vehicle data make it more difficult to extract important insights of individual vehicle behaviour and performance, and how they compare with a distribution of many vehicles. This presentation will describe effective ways to:

  • search these data
  • augment these data with calculated tags, indicators and metrics
  • reduce these data to meaningful histograms
  • show trends and statistics

The objectives being to understand product usage, validate new designs, compare program iterations, identify and extract scenarios for simulation and simulators, create inputs for virtual simulation models, create warranty reliability models, create predictive maintenance models, and more. To be able to retrospectively query the data lake and run analyses on the results to study a newly identified scenario.

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About the presenters

Frédéric Kihm

Product Manager – Analytics and Signal Processing, HBK

Frédéric Kihm is Product Manager at HBK, responsible for the signal processing related software products, which includes GlyphWorks, VibeSys and nCodeDS. Frédéric previously worked as an Engineering Consultant for nCode and then HBM, involved with signal processing, durability and vibration analyses in the automotive, aerospace, and defence industries. Frédéric holds a MS in Mechanical Engineering from IFMA University in France and a PhD from the Institute of Sound & Vibration Research (ISVR) in Southampton, UK.

Day 3 – Reliability and Dependability

Explode view of electric vehicle chassis equipped with battery pack on the road. 3D rendering image.

Session 5: Reliability Engineering from Limited Failure Data

Reliability engineering life data analysis involves using statistical methods to model and predict the lifespan of products based on observed failure data. Techniques like Weibull analysis fit life data to distributions, estimating reliability, failure rates, and mean life. However during operation there is often none or very limited observed failure data, and during design and development only a limited number of critical failure modes may be tested, as it becomes uneconomical to conduct separate reliability tests for every failure mode.

This session presents three different scenarios for reliability modelling with limited or no failure data:

  1. How to estimate confidence in a specified reliability target when no failures have been observed during testing, to answer the question; “How confident can we be that the non-critical failure modes identified in a FMEA are indeed non-critical?”
  2. Life data modelling of a complex system from limited failure data, without access to detailed OEM knowledge of the system, components and its failure modes. 
  3. Reliability prediction based on established models for electronic and mechanical components, with procedures for calculating failure rates for components.

 

Complex systems are susceptible to numerous failure modes. Conveniently, their reliable lifespan is often determined by a relatively small number of ‘critical’ modes. Often it is uneconomical to conduct separate reliability tests for each failure mode, designers typically focus on evaluating the critical ones. This raises the question: how confident can we be that those deemed ‘non-critical’ are truly non-critical?

This presentation explores how one might estimate confidence in a specified reliability target when no failures have been observed during testing. This approach is valuable because zero failures are common among non-critical failure modes, given that test articles usually fail due to a critical failure mode first. The method involves using simulations of the tests (Virtual Testing) to calculate the damage ratio for each non-critical failure mode relative to the target lifespan of the component.

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About the presenter

Dr. Andrew Halfpenny

Director of Technology – nCode Products, HBK

Dr. Halfpenny has a PhD in Mechanical Engineering from University College London (UCL) and a Master’s in Civil and Structural Engineering. With over 25 years of experience in structural dynamics, vibration, fatigue and fracture, he has introduced many new technologies to the industry including: FE-based vibration fatigue analysis, crack growth simulation and accelerated vibration testing. He holds a European patent for the ‘Damage monitoring tag’ and developed the new vibration standard used for qualifying UK military helicopters.

Failure probability compliance in reliability engineering ensures systems meet specified reliability standards by assessing and managing the likelihood of failures. Ideally this process includes comprehensive testing, statistical analysis, and strict adherence to engineering protocols to minimize risks and enhance system dependability.

However, when learning how life data analysis can be used to assess the reliability and failure probability of a product or system it is useful to consider case studies with minimal available failure information. This presentation describes just such a case study for the overall probability of failure and conditional probability of failure for next flight, of a new rocket engine through development and testing to entry into service.

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About the presenter

Chris Wynn-Jones

Senior Application Engineer – Reliability, HBK

Christopher Wynn-Jones has a BEng (Hons) in Mechanical Engineering from University of Wolverhampton coupled with 25 years of engineering experience. After various manufacturing roles Chris went on to become a Safety and Reliability Engineer for civil and military products in the air, at sea and ground vehicles. He is the host of the ReliaCast podcast series and an Application Engineer for ReliaSoft reliability software. He supports customers in industry and in universities with software solutions and best practices in Engineering for Reliability.
Chris also sits on the WG1 committee of the Institute of Mechanical Engineers [IMechE] Safety and Reliability Group (SRG). The SRG group promotes the development of safety and reliability requirements for products, systems or services.

In the early stages of product design, it is often necessary to estimate the reliability of one or more design alternatives. Most reliability analysis tools require times to failure data, either at the component or at the system level, to estimate reliability. Standards based reliability prediction is a method to estimate the reliability of a product before test or field data are available.

Each reliability prediction standard (MIL-HDBK-217F (MIL-217), Bellcore/Telcordia, FIDES, NSWC Mechanical and Siemens SN 29500)  includes mathematical formulas to calculate the failure rate of several components. Typically, the failure rate for each component is the base failure rate for that type of component modified by multiplying factors based on:

  • Physical characteristics such as size or rated voltage
  • Application characteristics such as operating temperature or environment

In today's competitive electronic products market, having higher reliability than competitors is one of the key factors for success. To obtain high product reliability, consideration of reliability issues should be integrated from the very beginning of the design phase. This leads to the concept of reliability prediction. Historically, this term has been used to denote the process of applying mathematical models and component data for the purpose of estimating the field reliability of a system before failure data are available for the system.

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About the presenter

Gabriele Serpi

Senior Application Engineer – Reliability, HBK

Gabriele Serpi is a Certified Reliability Professional and holds an M.S. degree in Electronic Engineering. Gabriele works as Senior Application Engineer with HBK for 13 years. He has a broad experience in Weibull analysis, Accelerated Life Testing, RAM analysis, Standard Based Reliability Prediction, FMEA analysis and other reliability methodologies.

Session 6: The …abilities – Reliability, Availability, Maintainability (RAM) for Dependability 

Failure Reporting, Analysis, and Corrective Action Systems (FRACAS) are essential for enhancing reliability, availability, maintainability (RAM), and dependability (RAMD) of systems. FRACAS provides a structured, closed-loop process to identify, analyse, and correct failures throughout a system’s lifecycle.

  • Reliability: FRACAS helps to identify failure patterns and root causes, enabling corrective actions to improve system reliability.
  • Availability: By addressing failures promptly, FRACAS ensures systems are operational when needed, thus enhancing availability.
  • Maintainability: FRACAS supports maintainability by providing data on failure modes and repair actions, which can be used to streamline maintenance processes.
  • Dependability: Overall system dependability is improved as FRACAS ensures that failures are systematically addressed and prevented from recurring.

Key activities in FRACAS include capturing failure data, prioritizing issues, performing root cause analysis, implementing corrective actions, and tracking the effectiveness of these actions over time. This iterative process promotes continuous improvement and supports decision-making in design, development, production, and operational phases.

HBK Technology Days - Session 6

Dependability is the collective term describing ability of the product/process to function as required when required. The factors that influence the dependability performance are reliability, maintainability, availability, testability, maintenance, and safety. Several methods can be applied for dependability assessment and management during each life cycle phase starting from product concept, through design, development, manufacturing, product operation and utilization. This comprehensive approach requires collaborative effort of an interdisciplinary team and knowledge in the field of engineering, data preparation and analysis.

This presentation explores tools and methods to be applied to assess and manage dependability during system operation. The special stress should be taken on data collection to support change management process and monitor effectiveness of the implemented changes. From the other side dependability tools should be integrated into companywide collaborative environment to gain insight from various departments and groups within the organization.

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About the presenter

Bartlomiej Swiatek

Senior Application Engineer – Reliability, HBK

Bartlomiej Swiatek is an application engineer supporting ReliaSoft reliability software for HBK with a Master’s in Power Engineering (Warsaw). He is engaged on asset life optimization and reliability projects for 10+ years. While working as an engineer at HBK in areas of automotive, aerospace, defence and oil & gas he is mentoring engineers how to implement effective reliability program.

Failure Reporting, Analysis, and Corrective Action System (FRACAS) is essential for enhancing reliability, availability, maintainability (RAM), and dependability (RAMD) of systems. FRACAS provides a structured, closed-loop process to identify, analyse, and correct failures throughout a system’s lifecycle.

  • Reliability: FRACAS helps to identify failure patterns and root causes, enabling corrective actions to improve system reliability.
  • Availability: By addressing failures promptly, FRACAS ensures systems are operational when needed, thus enhancing availability.
  • Maintainability: FRACAS supports maintainability by providing data on failure modes and repair actions, which can be used to streamline maintenance processes.
  • Dependability: Overall system dependability is improved as FRACAS ensures that failures are systematically addressed and prevented from recurring.

Key activities in FRACAS include capturing failure data, prioritizing issues, performing root cause analysis, implementing corrective actions, and tracking the effectiveness of these actions over time. This iterative process promotes continuous improvement and supports decision-making in design, development, production, and operational phases.

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About the presenter

Mariusz Dabrowski

Senior Application Engineer – Reliability, HBK

Mariusz is an application engineer supporting ReliaSoft reliability software for HBK with 17-years of professional experience in reliability engineering, with previous experience at Warsaw Institute of Aviation and General Electric in aviation and energy industries. Certified Six Sigma Black Belt focused on continuous improvement. Training instructor in reliability engineering. Specializes in reliability of nonrepairable systems and RAM analysis (Reliability, Availability, Maintainability). Project manager, currently implementing the FRACAS systems (Failure Reporting, Analysis and Corrective Action System).

The Naval Air Warfare Center Aircraft Division (NAWCAD) has developed a common FRACAS (C-FRACAS+) tool to enhance operational readiness and to develop more effective prognostic health monitoring. C-FRACAS+ is being applied across most aircraft platforms, support systems and on-wing equipment at all stages of system lifecycle from early development to sustainment.

This presentation describes the techniques used in NAWCAD to implement R&M and PHM programs and how C-FRACAS+ integral to process improvement. Particular attention is directed to how maintenance and diagnostic data are coupled to improve insights into failures and to drive better diagnostics.

Lessons learned during implementation and operation are covered to identify successes, ongoing challenges and future developments

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About the presenter

Dr. Kevin Knill

Head of Software Solutions, HBK Engineering Solutions, HBK

Dr Knill has a PhD in Mechanical Engineering for Delft University. With over 8 years of experience in chemical processing and power generation and 35 years of experience in engineering software, he has designed and developed a wide range of industrial solutions. 

He spent his early years studying how to turn coal into oil and industrial burner pollutant emission reduction. What followed was a switch to software. He developed advanced computational fluid dynamic models and lead the CFX (now Ansys) customer-directed development program. 

When CFX joined with nCode in 2000, he moved to nCode and directed GlyphWorks, DesignLife and Automation development. After a few years away in the Insurance industry, he rejoined what was now HBK and is working in the Solutions team. He is currently developing and implementing fleet maintenance and prognostic health monitoring solutions in large scale installations. 

An introduction to ReliaSoft Cloud, a fully web-based Software-as-a-Service platform (SaaS). For secure global deployment with database and web servers managed by HBK, requiring no hardware requirements or local IT support, and user access via web browser. A scalable solution for many users over a geographically dispersed workforce.

Initial release is focused on FMEA, with multiple FMEA types per major published standards with flexibility to customize for customer specific needs. Dashboards to drive decisions and track progress on design improvements and risk reduction.

With AI Assist to help with FMEA creation and consistency, to assist brainstorming and/or re-use of FMEA elements with the power of AI. AI Assist is designed to prioritise re-use, to first check to see if there are similar records in your ReliaSoft Cloud database.  If similar records are found, these results will always be displayed first.

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About the presenter

 
Jon Aldred

Director, Product Management, HBK

Jon is Director of Product Management for HBK, and responsibilities include the product roadmaps for nCode and ReliaSoft software brands for durability and reliability engineering. His responsibilities include assessing the impact of new market trends such as electrification, digitalization and lightweighting on future software needs. Jon joined HBK in 1996 and prior to that worked at Chrysler in Auburn Hills and Jaguar Cars in the UK, performing CAE simulations for NVH, crash and durability.

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