Electronicdesign 29973 Computermentor 03
Electronicdesign 29973 Computermentor 03
Electronicdesign 29973 Computermentor 03
Electronicdesign 29973 Computermentor 03
Electronicdesign 29973 Computermentor 03

What’s Required to Manage Complexity in a New Era of Engineering?

Dec. 6, 2019
Complexity of software-enabled assets has significant implications for the engineering lifecycle management. AI-enabled solutions can simplify this task.

The increasing complexity of software-enabled assets has a significant impact on the engineering lifecycle, engineers, and everyone involved in the product-development value chain. AI-enabled solutions can simplify the complexity, ensuring products are produced at higher quality and speed.

I talked with Erin O’Connor, Offering Manager, Engineering Lifecycle Management SaaS Solutions at IBM, about the technologies that designers and managers are using to address the challenge.

Why is electronic design becoming increasingly complex?

The short answer is because of the increasing complexity of software-enabled connected products. Today, electronic design engineers incorporate hardware, software, and connectivity into systems, but they also have to design for data. Designing connected products that are active, autonomous, and constantly sharing information—upstream and downstream—has become essential. Some examples are:

  • Upstream data from external sources like sensors can be used to predict problems.
  • Downstream data can be used to deliver software updates and new features.
  • Mid-stream data can be used to improve the active user experience.

With increasing complexity, design engineers often collaborate on complex operational models. Product features need to fit a broad set of potential customers, and they must be designed for the environmental data that can tailor the product to the individual user’s happiness. Engineers often can gain efficiency in collaboration when they’re able to visualize operational requirements, while maintaining design consistency.

The connectivity between devices also creates new risks. For example, a mobile phone can collect health data, which can be shared with healthcare providers, who can offer lifestyle guidance to patients. But what if the personal information is shared with the wrong entity, or the guidance provided back was nefarious? Design engineers must now consider the type of data they’re collecting and sharing.

With every new point of connectivity created, there’s a new intersection of potential vulnerability. Medical-device makers today need to comply with regulatory and quality standards, while providing ISO documentation and evidence of traceability.  Businesses increasingly must meet compliance requirements and find new ways to effectively manage the risk associated with complex design.

What challenges is this creating for engineers, and which parties in the value chain are bearing most of these challenges?

As software becomes the main driver of mechanical controls, it’s increasingly central in the design of connected products. A standalone product may not bear a safety-critical approach. However, once it becomes connected, new software-driven use cases and any of the components could introduce critical risks in the development processes. In parallel, industry and regulatory compliance is required of OEMs and suppliers such as APSICE, DO178, and ISO2626. The engineering process requires supply-chain collaboration, traceability, and reporting as evidence that their practices meet the standards for safety, privacy, and standardization.

Ultimately, it’s the maker of the product that shoulders the greatest challenges in the value chain. Not only do they have to be compliant and manage risks, they also must be swift to market in delivering a product that creates user delight. Engineers are faced with the daunting task of incorporating functionality that at its core is the user, and the user’s experience delivering value.

More components are being built to leverage data, sensors, and connectivity, lending to new opportunities and new business models for user value. OEMs, suppliers, and consumers contribute to the value chain: Consumers demand more pleasing solutions, manufacturers demand more features from their suppliers, and both demand increasing quality, security, stability, and insight.

What can companies do to address this new complexity?

Companies need to determine if their engineering lifecycle management tools empower them to best meet the growing the complexity and regulatory compliance demands. A complex system must be thought of holistically using techniques such as model-based system engineering (MBSE) and digital twin/thread to visualize and connect all dimensions, as well as leverage artificial intelligence (AI) to drive efficiencies in the processes.  

Certainly, manual processes and siloed products make developing competitive products increasingly challenging. Today's interconnectedness offers an opportunity to embrace digital transformation in engineering—establishing an end-to-end engineering lifecycle management process with products that share a single-source of truth and provide full traceability at scale.

Engineering lifecycle management tools need to support a systems-of-systems and enable strategic reuse to facilitate team workflows using collaboration and real-time reporting throughout the ecosystem. Companies establishing a more robust digitization of the engineering process will empower development teams to optimize and automate processes, seamlessly exchange information, and lay the foundation for analytics and AI.

What technologies are being developed to support engineers in the development and design process?

There’s a need to address development process inefficiencies, where companies are still using manual processes (spreadsheets, Word docs, email), and have siloed products amidst global workgroups. 

Further, engineers spend an inordinate amount of time mining for engineering data. Availability of the engineering data is vital, but accessing that data efficiently is still rare. Engineers must first evaluate what tools they’re using in the engineering process, and whether they can handle managing the development of more complex products.

To do this, they need to look at the development process end-to-end. Requirements Management teams must demand a definition that utilizes the upstream/downstream data. Design Management should be utilizing virtual models to meet compliance with regulations, safety, and critical design. Modeling also helps eliminate defects early and increase quality by continuously testing the design. This reduces development time by automatically generating applications and documentation.  

The engineering processes should also leverage a common workflow, where being able to share data and provide collaboration seamlessly across the enterprise globally will support engineers in this ever-changing environment. Once a company has a solid foundation, integrating AI to make better and more informed decisions will enable engineer efficiency/agility and lead to increased innovative capacity and time-to-market. 

For example, AI can be used to assess requirement quality by reading through a requirement and assessing it against INCOSE guidelines, and identifying when it may not meet standards. Ultimately, this reduces the number of potential defects that are introduced and improve adherence to compliance standards.

What will the impact be when these technologies are in place? What sort of benefits will engineers and their companies begin to see?

Some of the benefits our customers have cited after adopting an end-to-end engineering solution include:

  • Reduced software validation time 
  • Reduced bug-detection time 
  • Improved quality 
  • Improved on-time delivery
  • Faster development of new systems 

Ultimately, using an end-to-end engineering lifecycle management solution will increase productivity, improve product quality, lower costs, and help teams meet compliance and regulatory requirements. The earlier a mistake is found in the product development lifecycle, the less expensive it is to correct.

What does the future look like for the industry?

Products will continue to get more complex as they evolve. Engineering will be required to develop products faster, at lower cost, with better quality, and ensure a variety of compliance and regulatory requirements are met. As product lifecycles become shorter, competitive pressures will increase, and many companies will live or die on their next product introduction.

This means that companies will have to continuously innovate and adopt engineering management processes that facilitate speed, quality, and compliance so that their engineers can focus on developing the next market-winning product. Technologies, environments, and consumers are evolving as fast as—if not faster than—the products, requiring systems to design and comprehend this multidimensional landscape.

This sounds like a challenge, but the future is bright. Although the world will not slow down as consumers continue to demand and buy connected products, it offers a gateway to smart devices, and the ability for engineers to leverage resources on a global scale—allowing them to focus on design and produce incredible products that are yet to be imagined.

Erin O'Connor is the IBM Engineering Lifecycle Management SaaS solutions Offering Manager, since the launch of the solution in 2016. Erin and her team at IBM have worked with more than 130 clients onboarded to the Engineering Lifecycle Management SaaS solution, including two of the largest North America consumer white good manufacturers, numerous medical device and automotive electronics makers worldwide. She is the focal point for Engineering Offering Management for the Electronics Industry Solutions. Erin has been in Offering Management for IBM for eight years, and in the IBM Engineering sector for 20 years. She holds a BA from Bryant University and matriculated toward her MBA at Boston College.

References:

https://www.ibm.com/thought-leadership/institute-business-value/report/3-electronics-strategies

https://www.ibm.com/thought-leadership/institute-business-value/report/dataeconomy

Sponsored Recommendations

Highly Integrated 20A Digital Power Module for High Current Applications

March 20, 2024
Renesas latest power module delivers the highest efficiency (up to 94% peak) and fast time-to-market solution in an extremely small footprint. The RRM12120 is ideal for space...

Empowering Innovation: Your Power Partner for Tomorrow's Challenges

March 20, 2024
Discover how innovation, quality, and reliability are embedded into every aspect of Renesas' power products.

Article: Meeting the challenges of power conversion in e-bikes

March 18, 2024
Managing electrical noise in a compact and lightweight vehicle is a perpetual obstacle

Power modules provide high-efficiency conversion between 400V and 800V systems for electric vehicles

March 18, 2024
Porsche, Hyundai and GMC all are converting 400 – 800V today in very different ways. Learn more about how power modules stack up to these discrete designs.

Comments

To join the conversation, and become an exclusive member of Electronic Design, create an account today!